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Homeostasis of plasma membrane viscosity in
fluctuating temperatures
Alexandre Martinière1, Maria Shvedunova1, Adrian J.W. Thomson2, Nicola H. Evans3, Steven Penfield4,
John Runions1 and Harriet G. McWatters3
1
School of Life Sciences, Oxford Brookes University, Gipsy Lane, Headington, Oxford OX3 0BP, UK; 2Institute of Molecular Plant Sciences, University of
Edinburgh, Edinburgh EH9 3JH, UK; 3Department of Plant Sciences, University of Oxford, Oxford OX1 3RB, UK; 4Centre for Novel Agricultural
Products, Department of Biology, University of York, PO BOX 373, York YO10 5YW, UK
Summary
Authors for correspondence:
John Runions
Tel: +44 1865 483 964
Email: [email protected]
Harriet G. McWatters
Tel: +44 1865 275 028
Email: [email protected]
Received: 15 April 2011
Accepted: 3 June 2011
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doi: 10.1111/j.1469-8137.2011.03821.x
Key words: Arabidopsis, circadian rhythm,
desaturation, diffusion, fatty acid, plasma
membrane, temperature sensing, viscosity.
• Temperature has a direct effect at the cellular level on an organism. For instance,
in the case of biomembranes, cooling causes lipids to lose entropy and pack closely
together. Reducing temperature should, in the absence of other factors, increase
the viscosity of a lipid membrane. We have investigated the effect of temperature
variation on plasma membrane (PM) viscosity.
• We used dispersion tracking of photoactivated green fluorescent protein (GFP)
and fluorescence recovery after photobleaching in wild-type and desaturase
mutant Arabidopsis thaliana plants along with membrane lipid saturation analysis
to monitor the effect of temperature and membrane lipid composition on PM
viscosity.
• Plasma membrane viscosity in A. thaliana is negatively correlated with ambient
temperature only under constant-temperature conditions. In the more natural
environment of temperature cycles, plants actively manage PM viscosity to counteract the direct effects of temperature.
• Plasma membrane viscosity is regulated by altering the proportion of desaturated
fatty acids. In cold conditions, cell membranes accumulate desaturated fatty acids,
which decreases membrane viscosity and vice versa. Moreover, we show that control of fatty acid desaturase 2 (FAD2)-dependent lipid desaturation is essential for
this homeostasis of membrane viscosity. Finally, a lack of FAD2 function results in
aberrant temperature responses.
Introduction
According to the fluid mosaic model of biomembranes,
molecules such as lipids and proteins are constantly in
motion and diffuse within the plane of the membrane. The
fluidity of the membrane is an intrinsic propriety of the
lipid bilayer and protein mobility is crucial for many cellular mechanisms, for example ligand–receptor interactions
(Singer & Nicolson, 1972). Two main factors strongly
influence membrane fluidity: the temperature and the relative amount of lipid saturation.
Interestingly, the lipid saturation in membranes is
adjusted by the plant depending on environmental conditions. Membranes accumulate more desaturated fatty acids
in cold than in warm growing conditions (Falcone et al.,
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2004). Desaturation of lipids makes them less able to tightly
pack and, therefore, membranes with relatively higher
amounts of fatty acid desaturation should be less viscous.
The removal of hydrogen atoms that results in desaturation
is done by members of the fatty acid desaturase (FAD) gene
family, and the activity of these enzymes is probably inhibited
in warm conditions (Burgos et al., 2011). Studies on RNA
concentrations of FAD have shown little variation in response
to either cold or warm treatment. Recently, however, O’Quin
et al. (2010) have described temperature-sensitive degradation
of FAD3 which might explain FAD-protein regulation in
response to fluctuating temperatures.
In addition to the effect of the degree of saturation of
fatty acids, temperature variation affects membrane fluidity
directly. As temperature increases, membranes become
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more fluid (less viscous) and, conversely, a decrease in temperature results in increased viscosity. Because membranes
react to temperature changes directly, they are presumed to
be involved in temperature sensing. In Bacillus subtilis, the
protein DesK is responsible for temperature sensing. DesK,
a histidine kinase, has a role in sensing plasma membrane
(PM) thickness variation induced by temperature changes.
Autophosphorylation of DesK initiates transduction
cascades which modify the gene expression profile in
response to changing temperature (Cybulski et al., 2010).
Other evidence highlights the role of lipid membranes in
temperature sensing. Manipulation of lipid composition in
yeast (Saccharomyces cerevisiae) and other organisms led to
alterations in protein expression similar to those produced
by temperature changes (reviewed in Vigh et al., 2005). In
plants, study of a variety of model systems has also suggested that lipid membranes of cells may play a role in
temperature sensing. For instance, in the plant Brassica
napus, hot- or cold-activated protein kinases were upregulated at ambient temperatures following the application
of membrane fluidifying or rigidifying agents, respectively
(Sangwan et al., 2002). These examples show that membrane fluidity could be a sensor input for cells.
The relationship between temperature, membrane composition and membrane viscosity has not been investigated
in a plant system. Here we have demonstrated that fluorescence dispersal after photoactivation of green fluorescent
protein (GFP) is an effective method for monitoring membrane viscosity in vivo. Surprisingly, we have found that
when temperature fluctuates in a manner similar to natural
conditions, PM viscosity does not decrease as temperature
increases – the membrane actually became more viscous in
warm conditions than in cold. By studying lipid saturation,
we have shown that Arabidopsis compensates for changing
temperature by adjusting the amount of fatty acid desaturation. Moreover, impairment in the fatty acid desaturation
pathway abolishes the plant’s ability to adjust membrane
viscosity and inhibits some physiological responses to
temperature changes.
Materials and Methods
Plant materials and growth conditions
All experiments were carried out using the Columbia (Col0)
accession of Arabidopsis thaliana (L.) Heynh or homozygous
fad2.2 mutants in the Col0 background (described in
Larkindale et al., 2005 and obtained from Professor M.R.
Knight, Durham University, UK). Seedlings were grown on
plates containing 1· Murashige and Skoog (MS) salts
(Sigma) with 1% agar (Duchefa biochemie, Haarlem,
Netherlands). Media was corrected to pH 5.8. Seeds were
surface-sterilized before being stratified in the dark at 4C
for 72 h before transfer to a growth chamber.
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Entrainment protocols consisted of warm : cold temperature cycles (WC, 12 h at 27C followed by 12 h at 12C)
in constant white light (50 lmol m)2 s)1) or light : dark
cycles (LD, 12 h of white light followed by 12 h of darkness) at constant 20C. Temperature cycles were provided
by a Percival E30-B chamber (< 5 min ramp time between
temperatures), and light cycles and constant light regimes
by Sanyo MLR-350 growth chambers.
Production of transformed A. thaliana lines
For photoactivation of a PM marker, photoactivatable GFP
(paGFP) was fused to the intrinsic PM protein LTI6b
(AtRCI2b, At3g05890). 35s::paGFP-LTI6b was cloned by
replacing the DNA sequence of enhanced GFP with that of
paGFP between BamH1 and EcoR1 restriction sites in the
vector pBIB 35s::EGFP-LTI6b (Kurup et al., 2005). This
was accomplished using forward primer 5¢-GCT GGA
TCC GGT ATG GTG AGC AAG GGC GAG GAG-3¢ to
add a BamH1 restriction site and reverse primer 5¢-AGC
GAA TTC TCT CAT CTT GTA CAG CTC GTC CAT
GCC-3¢ to remove the stop codon and add an EcoR1
restriction site to the paGFP PCR fragment. Lines of Col0
and fad2.2 homozygous for 35s::paGFP-LTI6b were produced by floral dipping (Zhang et al., 2006) followed by
selection on antibiotics.
For fluorescence recovery after photobleaching (FRAP)
experiments, seedlings expressing 35s::GFP-LTI6b were
used (Kurup et al., 2005).
Leaf movement
Two biological replicates of the experiment were performed
as described previously (Edwards et al., 2005), with each
replicate containing eight to 16 plants of each genotype.
Following imbibition and stratification, seedlings were
grown in LD 12 : 12 h at 22C before commencement
of imaging. Leaf movement rhythms were recorded in
constant light (50 lmol m)2 s)1) at the appropriate
temperature (12 or 27C), starting at subjective dawn on
day 11 postgermination. Circadian rhythms of leaf movement were analyzed using fast Fourier transform-nonlinear
least squares (FFT-NLLS) (Johnson & Frasier, 1985;
Straume et al., 1991; Plautz et al., 1997) via the BRASS
interface (Brown, 2004). For period estimates, the first 24 h
of data were discarded to ensure only the free-running
period was measured.
Hypocotyl measurements
Columbia and fad2.2 seeds were sown on square Petri plates
(120 cm) and placed vertically in a growth chamber
running the appropriate environmental regime for 7 d. In
every case, foil-wrapped plates were included as dark
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controls. Plates were photographed and hypocotyl lengths
measured using ImageJ software. Results are means
(± SEM) of two biological replicates, each containing 40
seedlings.
Flowering time
Flowering time experiments were conducted in walk-in
constant-environment rooms set to a long-day photoperiod
of LD 16 : 8 h or a short-day photoperiod of LD 8 : 16 h
at the appropriate temperature (22 or 27C). Light intensity
at the level of the plant was 50–60 lmol m)2 s)1.
Following germination on 1· MS plates, 2-wk-old Col0
and fad2.2 seedlings were transferred to sterilized soil.
Plants were checked daily until the floral meristem was
clearly visible. At this point, plants were dissected to count
the total number of rosette leaves. Results are means
(± SEM) of 16–20 plants.
Lipid composition
Columbia seedlings were grown for 8 d postgermination on
1· MS plates in LD 12 : 12 h or WC 27 : 12C cycles.
Samples were collected at 3 h intervals from dawn (time of
lights on (LD) or temperature up (WC); that is, zeitgeber
time (ZT) 0) on day 9 and immediately snap-frozen in
liquid nitrogen. Analysis of total lipid composition was
performed using gas chromatography, as described in
Larson & Graham (2001). Results are means (± SEM) of
five biological replicates. The degree of saturation of each
18-carbon fatty acid is indicated by the number of double
bonds it contains (0, fully saturated; 3, fully desaturated).
In order to compare effects of light and temperature, data
collected during the ‘day’ (ZT 3 h, 6 h and 9 h) were pooled
and analyzed separately from those collected at ‘night’ (ZT
15 h, 18 h and 21 h). ZT 0 and 12 time points were not
included in this analysis as we wished to avoid the transition
points between light and dark or warm and cold. The ratio
of fully desaturated : saturated fatty acid was calculated by
dividing the total amount of fully desaturated fatty acids by
the sum total amount of saturated and partially saturated
fatty acids.
Membrane viscosity
We recorded the diffusion rate of the intrinsic PM protein
LTI6b (AtRCI2b, At3g05890). For this purpose, we fused
the protein to paGFP. Quantification of the paGFPLTI6b diffusion rate was by fluorescence dispersion after
photoactivation. Experiments were carried out using a
Zeiss LSM 510 META confocal microscope system. Col0
and fad2.2 seedlings were entrained to either LD or WC
cycles as described earlier. For photoactivation experiments, sampling was done at 3 h intervals over 24 h.
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Seven-day-old seedlings expressing 35s::paGFP-LTI6b were
used.
Seedlings were immobilized to prevent focus-shift during
scanning by mounting them in 1% low-melting-point agarose at room temperature (20C) and sealing the coverslip
with VALAP (Vaseline : lanolin : paraffin wax). At each
time point, paGFP-LTI6b was photoactivated in three
hypocotyl cells per seedling in four individual seedlings
(data shown are mean ± SEM); imaging of the 12 cells at
each time point took c. 45 min. This procedure was
repeated for each genotype in each of the WC or LD conditions. ‘Day’ (ZT 3 h, 6 h and 9 h) and ‘night’ (ZT 15 h,
18 h, 21 h) time points were again analyzed separately.
Photoactivation of paGFP-LTI6b
For each cell, we focused on the cell’s outer surface so that
a circular sheet of membrane became fluorescent once
photoactivated. A 63· 1.4 numerical aperture (NA) oil
immersion objective was used at a digital zoom setting of 4.
Preactivation and postactivation imaging of paGFP was
done using a 488 nm argon-ion laser set at 50% output and
4% transmission. Three pre-scan images were made to
establish the preactivation intensity of paGFP (generally
very low to no fluorescence) and then a circular region of
interest, 25 lm2 in area (5.6 lm diameter), was activated
by 10 iterations of a 405 nm diode laser set at 100% transmission. Fluorescence dispersion was recorded during the
70 s following photoactivation with a delay of 1.5 s
between frames. Images were 256 · 256 pixels and were
made with a scan speed of 0.46 s per frame. We confirmed
that the energy of the 488 nm laser used to record postactivation data had no bleaching effect on activated paGFP by
recording control activated regions for 3 min.
Postactivation fluorescence intensity was measured within
targeted regions of interest using the ‘Measure Stack’ function of ImageJ software (http://rsb.info.nih.gov/ij/). These
data were normalized to convert values to percentage scales
for comparison (see later for specific formulae), and nonlinear regression was used to fit the data so that half-time
(t1 ⁄ 2) and curve plateau values were derivable. For photoactivation, curves start at 100% fluorescence intensity and
decay exponentially to a plateau that represents the immobile fraction of paGFP-LTI6b. Photoactivation t1 ⁄ 2 is the
amount of time required for fluorescence intensity to decay
to halfway between 100% and the plateau. For analysis of
the photoactivation of paGFP-LTI6b, we followed a previously published protocol (Runions et al., 2006). Data were
normalized with the following equation:
In = ½ðIt Imin Þ=ðImax Imin Þ 100;
Eqn 1
where In is the normalized intensity, It is the intensity at any
time t, Imin is the mean pre-photoactivation intensity and Imax
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is the brightest post-photoactivation intensity. Nonlinear
regression was used to fit normalized intensity data for the
post-photoactivation time period with GraphPad Prism 5
software using the exponentially decreasing equation:
and Imax is the mean pre-photobleaching intensity.
Nonlinear regression was used to model the normalized
FRAP data. In this case, a two-phase exponential association
equation was used:
Y ðt Þ = A expðkÞðt Þ þB;
Y ðt Þ=A þ Bð1 expðk1Þðt Þ Þ þ C ð1 expðk2Þðt Þ Þ;
Eqn 2
where Y(t) is normalized intensity, A, B, and k are parameters of the curve, and t is time.
Each data set was first fitted independently with this
equation to ensure goodness of fit (generally r2 was > 0.95)
before a single curve was fitted to all data points of a given
treatment by combining data sets and sharing curve parameter values. Half-time (t1 ⁄ 2) from this curve fitting was
calculated as t1 ⁄ 2 = 0.69 ⁄ k.
Finally, the t1 ⁄ 2 value was used for calculating the protein
diffusion rate (Axelrod et al., 1976) as D = (0.88 R2) ⁄
(4 t1 ⁄ 2), where D is the diffusion rate in lm2 s)1 and R is
the radius of the photoactivation spot.
Values of D were compared using either two-tailed t-tests
or ANOVA followed by Tukey HSD using Microsoft Excel
or SPSS software (SPSS software, IBM corporation, NY,
USA).
Fluorescence recovery after photobleaching of EGFPLTI6b and fluorescein isothiocyanate (FITC)
Fluorescence recovery after photobleaching experiments on
EGFP-LTI6b were done using the same magnification and
scan settings as described earlier for photoactivation. The
radii of photobleached regions were 2.21, 3.48, and
4.43 lm in successive experiments. Pre-bleach and postbleach scans were made using the 488 nm line of an argonion laser set to 50% output and 1% transmission. Bleaching
was done using five iterations of the 488 nm line set to
100% transmission. Ten pre-bleach scans were made and
fluorescence recovery was recorded during 143 s postbleaching. For control FRAP experiments on FITC diluted
in 100% glycerol, pre-bleach and post-bleach images were
made with the 488 nm line of the argon-ion laser set to
50% output and 0.5% transmission. Bleaching of FITC
was done within circular regions of radii 2.04, 3.49 and
5.79 lm in successive experiments using a 405 nm diode
laser set at 100% transmission for 30 iterations and fluorescence recovery was recorded for 35 s with no time delay
between scans. Image resolution was 128 · 128 pixels and
scan speed was 0.123 s per frame.
For analysis of the FRAP data for GFP-LTI6b and FITC,
the data were normalized using the equation:
In = ½ðIt Imin Þ=ðImax Imin Þ 100;
Eqn 3
where In is the normalized intensity, It is the intensity at any
time t, Imin is the minimum post-photobleaching intensity
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Eqn4
where Y(t) is normalized intensity, A, B, C, k1 and k2 are
parameters of the curve, and t is time. t1 ⁄ 2 was calculated
for each individual data set by interpolation at the intensity
change midpoint using the curve-fitting equation.
Results
Measurement of membrane viscosity
Direct measurements of membrane viscosity in living tissues
are difficult to obtain. To overcome this problem, we relied
on the propensity of membrane proteins to diffuse within
the lipid bilayer. The speed of protein diffusion within the
bilayer is inversely correlated with membrane viscosity.
LTI6b, a small intrinsic PM protein, was fused to GFP and
stably expressed in A. thaliana (GFP-LTI6b). The fusion
protein was localized to the PM as previously reported
(Cutler et al., 2000). To test the mobility of this protein in
the PM, we used FRAP to estimate the fluorescence intensity recovery half-time and the percentage of recovery.
First, we tested whether GFP-LTI6b diffuses within the
PM. In first-order diffusion kinetics (i.e. when other factors
such as protein interaction which might limit diffusion are
absent), there should exist a linear relation between the halftime of fluorescence recovery and the size of the bleached
circular region (Sprague & McNally, 2005). To test this
assertion, we did a series of FRAP experiments with different-sized bleaching spots in both a saturated solution of the
fluorescent stain FITC in 100% glycerol, a purely diffusive
system (Fig. 1a–c), and on GFP-LTI6b-expressing ‘plant
cells’ (Fig. 1d–f). In both cases, a linear relation was
observed when the half-time of fluorescence recovery was
plotted against the area of the bleached spot (Fig. 1g). This
means that GFP-LTI6b diffuses without any interactions
which might limit or increase the rate expected in first-order
diffusion and is, thus, a good candidate for monitoring
membrane viscosity.
Second, to ascertain that fluorescence recovery is the
result of laterally diffusing protein within the lipid bilayer
as opposed to insertion into the membrane within the
bleached region via exocytosis, we produced kymograms,
that is graphical representations of changing fluorescence
intensity along the line marked in Fig. 1(h) during the time
course of FRAP experiments (Fig. 1h,i). A triangular shape
is clearly formed during the recovery phase (Fig. 1i) demonstrating that recovery of GFP-LTI6b is the result of lateral
diffusion from the nonbleached area.
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(a)
(g)
(h)
(b)
(i)
(c)
(d)
(j)
(k)
(e)
(f)
Fig. 1 Photobleaching and photoactivation to record membrane viscosity. Comparison of fluorescence recovery after photobleaching (FRAP)
experiments with different bleached spot sizes confirms that fluorescence recovery is the result of lateral diffusion. Fluorescein isothiocyanate
(FITC) in 100% glycerol (a–c) and GFP-LTI6b in the Arabidopsis thaliana Columbia (Col0) plasma membrane (PM) (d–f). (a) Region of interest
(ROI), 13.07 lm2; (b) ROI, 38.43 lm2; (c) ROI, 105.54 lm2; (d) ROI, 15.47 lm2; (e) ROI, 38.22 lm2; (f) ROI, 61.68 lm2. (g) Half-times
(t1 ⁄ 2) of fluorescence recovery for FITC (crosses) and GFP-LTI6b (diamonds) experiments increase linearly as the area of bleached spots
increase, demonstrating that fluorescence recovers by lateral diffusion only (R2 = 0.97 for GFP-LTI6b and R2 = 0.99 for FITC). (h, i)
Kymogaphic analysis of the time series of GFP-LTI6b bleaching and recovery shown in (e). (h) Pixel fluorescence intensity values were
measured along the white line and are plotted vs time (i) during bleaching and recovery. The kymogram shows centripetal movement of
fluorescence within the bleached area. (j) Photoactivation of photoactivatable GFP (paGFP)-LTI6b. The sequence shows the PM before
activation, at the moment of activation and 22 s postactivation. (k) Nonlinear regression was used to fit fluorescence intensity dispersion after
photoactivation; diffusion coefficients for paGFP-LTI6b were derived from these fits.
Finally, to optimize measurement of diffusion, we compared two methods of visualizing protein movement:
photobleaching and photoactivation. For photoactivation, a
photoactivatable form of GFP (paGFP) was fused to
LTI6b. Both dispersion of paGFP-LTI6b fluorescence after
photoactivation and recovery of GFP-LTI6b fluorescence
after photobleaching were recorded (cf. Fig. 1f,j) and analyzed to extrapolate relative diffusion coefficients (Fig. 1k).
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The standard deviation of the diffusion rate obtained for
photodispersion of paGFP-LTI6b was smaller than that for
photobleaching GFP-LTI6b (Dphotodispersion = 0.20 ± 0.02,
Dphotobleaching = 0.18 ± 0.04). Consequently, we used
photoactivation measurements to estimate membrane
viscosity. Since LTI6b is free to diffuse, variation in the
diffusion rate is the result of a change in membrane viscosity. Consequently, in these experiments, a higher diffusion
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rate reflects a decrease in PM viscosity, and lower diffusion
reflects increased PM viscosity.
Membrane viscosity does not necessarily reflect the
external temperature
In nature, plants rarely experience constant conditions of
temperature or light. Thus we initially measured PM viscosity in A. thaliana (Col0 accession) seedlings grown under
warm : cold cycles in constant light (WC, 27 : 12C) or
under light : dark cycles (LD, 12 : 12 h) at a constant
20C. Averaged over 24h, the PM was more viscous (i.e.
lower paGFP-LTI6b diffusion rate) in WC cycles than in
LD cycles (P < 0.05; Fig. 2a). Therefore, we compared PM
viscosity between light and dark under LD conditions at a
constant 20C, and between warm and cold under WC
conditions at constant light. Diffusion during the warm
portion of the WC cycles differs from that during the cold
portion of the cycle, while no difference was recorded
between light and dark conditions (two-tailed t-test,
P < 0.01; Figs 2b,c, S1). Surprisingly, however, we found
the PM was more viscous during the warm portion of a
temperature cycle (Fig. 2b). As this result contradicts earlier
reports of decreased viscosity at higher temperatures (e.g.
Vaultier et al., 2006), we repeated the experiment using
plants grown under constant light and temperature conditions. In this case PM viscosity was indeed lower in plants
grown at 27C than at 12C (two-tailed t-test, P < 0.01;
Fig. 2d). Thus PM viscosity reflects ambient temperature
only under constant-temperature conditions. Taken
together, these results demonstrate that membrane viscosity
is not a direct reflection of external temperature but is subject to homeostatic regulation by an unknown mechanism.
Fig. 2 Effect of temperature on plasma
membrane (PM) viscosity (viscosity is
inversely proportional to photoactivatable
GFP (paGFP)-LTI6b diffusion rate) in wildtype (Col0) Arabidopsis thaliana plants. (a)
Mean diffusion rate over 24 h in warm : cold
(WC) and light : dark (LD) cycles. WC,
27 : 12C temperature cycles for 12 h each
in constant light; LD, 12 : 12 h light : dark
cycles at constant 20C. (b, c) Mean
diffusion rate in opposing parts of WC and
LD cycles. Diffusion rate is significantly lower
(viscosity higher) during the warm part of
WC cycles. Light or warm: ‘daytime’
zeitgeber time (ZT) 3 h, 6 h and 9 h time
points; dark or cold: ‘night-time’ ZT 15 h,
18 h and 21 h time points. (d) Diffusion rates
in constant noncycling temperature conditions
for plants grown at two temperatures. Plants
grown at 12C have significantly reduced PM
diffusion. Mean ± SEM, n ‡ 10; two-tailed
t-test, *, P < 0.05; **, P < 0.01.
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(a)
The proportion of desaturated fatty acid increases
during the cold phase of a temperature cycle
Membrane viscosity changes can be achieved by adjusting
the proportion of desaturated fatty acids – a relatively greater
amount of desaturated fatty acids equates to decreased viscosity. The degree of polydesaturation varies with growth
temperature; as a general rule, it decreases as temperature
increases (Marr & Ingraham, 1962; Falcone et al., 2004).
Previous studies have been principally concerned with
responses to constant temperature: the effects of regular temperature cycles upon lipid composition have not been
investigated. Therefore we analyzed fatty acid composition
of plants grown under cyclic conditions (Fig. S2).
There was a significant decrease in the proportion of
polydesaturated (i.e. 16 : 3 and 18 : 3) fatty acids in plants
grown in WC cycles relative to those in LD cycles
(Fig. 3a–c), consistent with the greater PM viscosity
observed in such plants (Fig. 2a). Closer examination
revealed a significant decrease in the proportion of polydesaturated fatty acids during the warm portion of WC cycles
(t-test, warm vs cold, P < 0.05; Fig. 3b). This matches the
more viscous PM observed at this time (Fig. 2b). By contrast, the overall proportions of saturated and desaturated
fatty acids did not differ over a LD cycle (t-test, light vs
dark, P = 0.06; Fig. 3c), in accordance with more stable
PM viscosity in these conditions (Fig. 2c).
Membrane viscosity homeostasis is altered in fad2.2
plants
The observation of a higher proportion of desaturated fatty
acids at the time of low PM viscosity (Figs 2b, 3b) suggests a
(b)
(c)
(d)
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(a)
(b)
(a)
(c)
(b)
Fig. 3 (a) Effect of light and temperature cycles on lipid composition
in Columbia (Col0) Arabidopsis thaliana seedlings grown in
warm : cold (WC) and light : dark (LD) cycles. Fatty acids (FA) are
categorized as fully saturated (C16 : 0 or C18 : 0), partially
desaturated (C16 : 1 or 2, or C18 : 1 or 2), or polydesaturated
(C16 : 3 or C18 : 3). Only 18 : 1 FA differed between phases of a
cycle (Mean ± SEM, n > 10). (two-tailed t-test, light vs dark, *,
P < 0.05). (b, c) Ratio of polydesaturated : saturated and partially
saturated FA in WC and LD cycles (light or warm: ‘daytime’
zeitgeber time (ZT) 3 h, 6 h and 9 h time points; dark or cold: ‘nighttime’ ZT 15 h, 18 h and 21 h time points). Means ± SEM, n = 5,
two-tailed t-test, *, P < 0.05.
causal connection between the two. To test this, we examined the effect of temperature on PM viscosity in the
linolenic acid-deficient fad2 desaturase ethyl methanesulfonate (EMS) mutant (Lemieux et al., 1990). The
endoplasmic reticulum (ER)-associated desaturase FAD2
catalyzes the desaturation of 18 : 1 fatty acids to 18 : 2
(Okuley et al., 1994), thus fad2.2 plants have a higher
proportion of saturated and partially desaturated fatty acids
than wild-type plants (Lemieux et al., 1990; Miquel et al.,
1993). We predicted this would produce a more viscous PM.
Consistent with this prediction, the rate of lateral diffusion of paGFP-LTI6b within the fad2.2 PM was equivalent
at 27 and 12C (Fig. 4a) and matched the rate of diffusion
in wild-type plants at 12C. Moreover, PM viscosity of
fad2.2 did not differ across a temperature cycle (t-test:
P = 0.65; Figs 4b, S3a), indicating it did not adjust membrane properties in response to temperature changes. Thus
high PM viscosity was associated with an increased proportion of saturated fatty acids, whether this was achieved by
manipulating temperature or genetic background. Similar
to wild-type plants, fad2.2 PM viscosity remained constant
during LD cycles (t-test, P = 0.43; Figs 4c, S3b).
Therefore, FAD2-dependent lipid desaturation is essential
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(c)
Fig. 4 Diffusion rate of photoactivatable GFP (paGFP)-LTI6b in the
Arabidopsis thaliana desaturation mutant, fad2.2. (a) Diffusion rate
in Col0 and fad2.2 at 12C (dark gray bars) and 27C (pale gray
bars); two-tailed t-test, 27 vs 12C, *, P < 0.05. (b, c) Diffusion
rates did not differ in fad2.2 in warm and cold or light and dark
(light or warm: ‘daytime’ zeitgeber time (ZT) 3 h, 6 h and 9 h time
points; dark or cold: ‘night-time’ ZT 15 h, 18 h and 21 h time
points). Mean ± SEM, n ‡ 10.
for the diurnal homeostasis of membrane viscosity under
temperature cycles.
fad2.2 plants have a partial temperature insensitivity
phenotype
fad2.2 plants are impaired in their PM ‘homeoviscosity’.
They cannot compensate for the effect of temperature on
membrane viscosity (Fig. 4b). As the PM has been
suggested to play a role in temperature sensing in different
organisms (Sangwan et al., 2002; Vigh et al., 2005;
Cybulski et al., 2010), we wondered if this mutant is correctly responding to temperature. We examined three
physiological outputs known, in wild-type plants, to
respond predictably to increased temperature.
Elevated temperature resulted in earlier flowering with a
reduced number of leaves in wild-type plants growing in
LD photoperiods (16 : 8 h at 22 vs 27C). fad2.2 flowers
earlier than Col0 at 22C under long-day photoperiods
(Fig. 5a) and short-day photoperiods (Fig. S4) but
showed no earlier flowering response when grown at 27C
under LD conditions. Hypocotyl growth is also clearly
related to temperature (Gray et al., 1998). As expected,
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sated (Pittendrigh, 1960) across the ambient range. As
expected, the FRP of wild-type plants was shorter at high
temperature (22.4 h at 27C vs 26.5 h at 12C; t-test,
P < 0.01; Figs 5b, S4a). However, the FRP of fad2.2 was
the same at both temperatures (25.8 h at 27C vs 25.9 h
at 12C; Figs 5b, S4b).
Discussion
(b)
(c)
For plants, temperature is, with light, one of the major abiotic stimuli. Indeed, seasonal fluctuation in temperature acts
as an input for key physiological processes such as seed germination and floral induction. Understanding how plants sense
and respond to temperature is crucial given current trends of
climate change and the challenges these pose to agriculture
and food security (Battisti & Naylor, 2009). In this study, we
have shown a clear correlation among temperature, membrane viscosity and fatty acid desaturation. Our conclusion is
that this represents a mechanism whereby plants stabilize
membrane viscosity during temperature variation. This
homeostasis of membrane viscosity is FAD2-dependent.
LTI6b mobility as a sensor of membrane viscosity
Fig. 5 The Arabidopsis thaliana desaturation mutant fad2.2 has
impairment in some physiological responses to temperature. (a) Leaf
number at flowering under long-day conditions (LD 16 : 8 h) at
22C (dark gray bars) and 27C (pale gray bars). fad2.2 mutants
flower early (after only six to seven leaves) irrespective of
temperature whereas Columbia (Col0) plants flower significantly
later in reduced temperatures (leaf numbers, approx. eight at 27C
vs 12 at 22C, mean ± SEM, n ‡ 16, two-tailed t-tests, high vs low
temperature, **, P < 0.01). (b) Hypocotyl length in response to
temperature increase in Col0 and fad2.2. Col0 and fad2.2 show a
strong increase in hypocotyl length at 27C (pale gray bars)
compared with 20C (dark gray bars). ** P < 0.01, Mean ± SEM,
n > 70. (c) Free-running period (FRP) of leaf movement circadian
rhythms under constant light at two temperatures, 12C (dark gray
bars) and 27C (pale gray bars). Col0 and fad2.2 mutants have a
long FRP (c. 26 h) at low temperature. This was significantly
shortened to 22.4 h in Col0 plants grown at 27C, but fad2.2 plants
did not respond to the increased temperature. Mean ± SEM, n ‡ 8,
two-tailed t-tests, high vs low temperature in Col0, **, P < 0.01.
Col0 had longer hypocotyls when grown at 27C than
when grown at 20C in constant light, but a similar result
was observed for fad2.2. In fact, the relative increase in
hypocotyl elongation was slightly more for fad2.2 than for
Col0 (1.6 times for Col0 and 2.4 times for fad2.2).
Finally, we measured the free-running circadian period
(FRP) of leaf movement rhythms, a robust measure of
clock behavior. The FRP of the plant clock shortens
slightly as ambient temperature increases (Edwards et al.,
2005), although circadian clocks are temperature-compen-
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We measured dispersion of paGFP-LTI6b within the PM
to monitor membrane viscosity. This small intrinsic protein
had high mobility (Fig. 1k) which means that the majority
of it is free to diffuse within the PM. To verify that the rate
of LTI6b diffusion was not influenced by other cellular factors, we demonstrated that the measured half-time of its
recovery after photobleaching is correlated with the size of
the bleaching spot (Fig. 1g) and showed that its recovery is
centripetal from the margins of the bleached region
(Fig. 1i). Consequently, the speed of LTI6b diffusion is
inversely related to the viscosity of the membrane
(Goodwin et al., 2005). Although this technique is an indirect measurement of viscosity, it allows us to work directly
with a living multicellular organism and abolishes artifacts
induced by membrane preparation.
Arabidopsis thaliana compensates temperature‘s
effect on PM viscosity by altering amounts of fatty
acid saturation
Although there are diurnal changes in lipid composition in
some plant species, including cotton (Rikin et al., 1993), in
Arabidopsis the proportion of fatty acids at any given saturation differs very little between light and dark or warm and
cold parts of a cycle (Fig. 3a) (Ekman et al., 2007), suggesting only a minor effect of the diurnal cycle upon lipid
composition. Our striking observation that the PM had
lower viscosity during the cooler portion of a temperature
cycle makes it clear that alterations in viscosity and lipid
composition over 24 h do not occur passively in response to
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changes in external temperature. Our data suggest that
plants counteract the direct effects of temperature cycles on
membrane viscosity by altering the relative proportion of
desaturated fatty acids within the membrane. That this phenomenon results specifically from changes in external
temperature, not from a rhythmic environment per se, is evident from the constant state of lipid composition and PM
viscosity in plants maintained in LD cycles (Figs 2b, 3b).
fad2.2 plants are not able to regulate PM viscosity in
either temperature cycles or under constant temperature
(Fig. 4a,b). Consequently, the fatty acid desaturation mechanism, and especially synthesis of highly desaturated fatty
acids (18 : 2 and 18 : 3), seems to be important for the
regulation of membrane viscosity. fad2.2 mutants are
particularly sensitive to low temperature, suffering chronic
cell damage and death when held at 6C, a temperature
wild-type plants easily withstand (Miquel et al., 1993).
fad2.2 germination is also impaired at low temperature but
is indistinguishable from wild-type plants at 20C (Miquel
& Browse, 1994). Mutations in chloroplast-localized desaturases alter thermal tolerance (Kunst et al., 1988; Kodama
et al., 1995; Zhang et al., 2005; and see Larkindale et al.,
2005) and thus the plastid may be partially responsible for
maintaining membrane fluidity (Penfield, 2008).
Interestingly, it has recently been shown that the rate of
turnover of the FAD3 protein is temperature-sensitive
(O’Quin et al., 2010). The half-life of the protein is much
longer in cold conditions, probably leading to an accumulation of polydesaturated fatty acids and consequently a less
viscous membrane to compensate for the temperature
effect. In conclusion, the fatty acid desaturation pathway
seems to be important for maintaining a homeostasis of PM
fluidity during daily temperature cycles.
Is there a link between membrane viscosity, the FAD
pathway and temperature sensing?
Fatty acid synthesis mutants of Neurospora crassa have a
long-period circadian phenotype and ⁄ or defective temperature compensation (Lakin-Thomas & Brody, 2000; Ruoff
& Slewa, 2002). In Arabidopsis, mutation of FAD2 means
that the free-running period of leaf movement does not
shorten as it does in wild-type plants when grown at 27C
(Fig. 5c). The invariant FRP of fad2.2 grown at different
temperatures suggests some impairment of the temperature
response mechanism in these plants. This result implies a
genetic link between fad2.2 and circadian rhythm.
Alternately, fad2.2 flowering time and hypocotyl growth
data do not show clear impairment of the temperature
response mechanism (Fig. 5a,b). Consequently, it is difficult to conclude a clear temperature insensitivity of fad2.2.
It is most likely that several mechanisms interact to ensure
accurate temperature sensing by plants. For instance, occupancy of the histone variant H2A.Z in nucleosomes is
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temperature-sensitive; it drives gene expression and is
involved in ambient temperature sensing (Kumar & Wigge,
2010). Further work will be required to determine whether
the change in membrane viscosity could be an input for
temperature sensing or if it is only a temperature output
via the ‘homeoviscosity’ of the PM. In any case, it seems
sensible to conclude that homeostasis of PM viscosity
is important for all of the membrane processes, such as
signaling and secretion, that require association of proteins.
Acknowledgements
We are grateful to Marc Knight for providing seed for the
fad2.2 mutants and Andrew Millar and the IMPS
(University of Edinburgh) for access to the leaf imaging
system. We would like to thank Andrew Smith, Liam Dolan
and Marc Knight for helpful discussions on the manuscript
and Pauline White for expert technical assistance. J.R. and
A.M. are funded by BBSRC grant number BB ⁄ F01407 ⁄ 1.
SP and HGM are Royal Society University Research Fellows.
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Supporting Information
Additional supporting information may be found in the
online version of this article.
Fig. S1 Lateral diffusion of paGFP-LTI6b within the
plasma membrane of Col0 seedlings over 24 h.
Fig. S2 Effect of light and temperature cycles on fatty acid
composition of Col0 seedlings over 24 h.
Fig. S3 Lateral diffusion of paGFP-LTI6b within the
plasma membrane of fad2.2 seedlings over 24 h.
Fig. S4 Leaf number at flowering in short days (LD
8 : 16 h).
Fig. S5 Plots of circadian free running period (FRP) of leaf
movement rhythms vs relative amplitude error (RAE).
Please note: Wiley-Blackwell are not responsible for the
content or functionality of any supporting information
supplied by the authors. Any queries (other than missing
material) should be directed to the New Phytologist Central
Office.
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