2 MATERIALS AND METHODS
2.1 Taxon sampling, plant material, and growth conditions
Because Cochlearia and Ionopsidium species are rare and
often endangered, our study is based upon our germplasm collections.
These collections were compiled over the last three decades
(BrassiBase [https://brassibase.cos.uni-heidelberg.de/]: Koch
et al., 2012; Kiefer et al., 2014; Koch et al., 2018) because our taxon
sampling required sufficient and high-quality seed material from wild
populations to propagate the respective material used in the freezing
experiments. Cochlearia species under study were selected from a
range of different habitats, including arctic regions (C.
groenlandica ), alpine habitats (endemic C. excelsa from Austrian
South-Eastern European Alps/endemic C. tatrae , High Tatra
Mountains), cold calcareous springs and creeks (Central EuropeanC. pyrenaica /polish C. polonica ), coastal dune areas, and
salt marshes (C. danica /C. aestuaria /C. anglica ).Cochlearia danica , which originally adapted to coastal sand dune
areas, migrated along road routes into central Europe, where it remains
today (Koch, 1996; Koch, 1997). Accessions of Ionopsidium came
from Mediterranean habitats. A total of 34 different accessions,
comprising 13 species, were used in the experiments (Fig. 1, Suppl.
Material Table 1). Plants were grown and cultivated in a growing chamber
for 34-38 weeks with a day/night cycle of 14/10 h and a 30 min
transition period, during which the light intensity was gradually
lowered. The growth conditions included a permanent temperature of 20°C
(± 2°C) and a relative humidity of 50%. Plants were watered regularly
and no light or drought stress was omitted. For each accession, 20
individuals were propagated to finally select three randomly selected
individuals each (non-flowering and healthy rosette-forming plants) for
the two acclimation treatments: (i) three individuals were acclimated at
4°C in a climate chamber for five days at a 65% relative humidity (a
slight increase in humidity, compared to 20°C growth conditions, was
implemented because of the lower temperature). (ii) Three randomly
selected individuals were not acclimated and remained in the original
growth chamber at 20°C as a control. The same day/night regime was
applied for both treatments, as was chosen for the initial cultivation.
Six week old individuals of the Arabidopsis thaliana Col-0
ecotype were used as an internal control.
The aim of this study was to performed electrolytic conductivity
measurements on leaves subjected to a freezing regime from 0°C to -10°C
at different time points and to calculate lethal experimental freezing
temperatures (LT ) for representative species from both genera.LT50 and LT100 (50% and
100% cell membrane damage) values were calculated then using logistic
functions fitted to the measured electrolytic leakage values (PEL).
2.2 Electrolytic assays
Electrolytic leakage of detached leaves is commonly used to
quantitatively assess the freezing tolerance and cold acclimation
potential of plants (Armstrong et al., 2020; Hincha & Zuther, 2014; Wos
& Willi, 2015, 2018). The cell membranes are the primary sites of
freezing damage. When cell membranes are damaged, the cell’s contents
leak out; this leakage can be detected by measuring electrical
conductivity because the ionic composition of the water in which the
leaves were immersed changes. Therefore, electrolytic leakage is
expressed in terms of relative conductivity (Lee & Zhu, 2010; Hatsugai
& Katagiri, 2018; Armstrong et al., 2020). Electrolytic leakage was
measured following cold exposure and again after boiling at 100°C to
ensure 100% leaf damage. The relative leakage, or percentage of
leakage, was calculated from the ratio of the two measurements. The
lethal temperature (LT50 ), which refers to the
temperature that causes 50% electrolytic leakage from cells (or
otherwise causes 50% leaf damage), was derived based on the relative
leakage. LT100 is the temperature at which 100%
of the electrolytes have leaked from the cells and is calculated from
the percentage of electrolytic leakage. The electrolytic leakage was
measured according to the method described by Thalhammer et al.. al
(2014), with some modifications outlined below in detail.
For the electrolyte leakage assay, six different freezing temperatures
(0°C, -2°C, -4°C, -6°C, -8°C, -10°C) were selected to follow a
respective temperature cline for further regression analyses. One leaf
per temperature treatment (0, -2, -4, -6, -8, and-10°C) and three leaves
for negative controls were harvested from acclimated (4°C) and
non-acclimated individuals (20°C). In total, nine leaves of similar size
(appr. 1 cm2) were harvested from each of the three
individuals from a single accession, which resulted in 54 leaves and
measurements for each accession. Leaves of approximately the same size
and thickness were chosen and placed into ddH2O-filled
(3 ml) 10 ml DURAN glass tubes that were closed tightly afterwards with
metal lids. The negative controls were incubated at 4°C on a shaker at
100 rpm. To control the down-cooling freezing of other samples, tubes
were placed in a cooling bath (LAUDA RP2045; LAUDA Scientific,
Lauda-Königshofen, Germany). An automatic temperature ramping program
was used to ensure a steady, standardized temperature change from 0°C to
-10°C for all samples. The temperature was lowered by 2°C during a 3 min
period between 45 min stable cooling intervals. Sample collection
commenced at the end of each cooling interval, just before the 3 min
cooling period started.
Crystallization of the remaining samples was induced using liquid
nitrogen 20 min after cooling at-2 °C. Inoculation loops (steel, 0.5 mm)
were used to initiate the crystallization. Loops were immersed in
ddH2O and subsequently in liquid nitrogen until ice
crystals formed; the loops were then placed carefully into the tubes,
carefully damaging the samples to induce immediate crystallization of
the entire sample. The samples were then removed at various freezing
temperatures (0°C to -10°C) and incubated for 48 h at 4°C and 100 rpm on
a shaker. Wires were carefully removed, and an additional 2 ml cold
ddH2O was added to the tubes. The measurements were
performed 24 h later. The electrical conductivity of the solution was
measured using a conductivity meter (METTLER TOLEDO LE703;
Mettler-Toledo, Albstadt, Germany) after the samples were brought to
room temperature. Measurements were performed before
(EL0) and after (EL1) boiling the
solution for two h at 100°C. Boiling ensured complete destruction of the
leaves, leading to 100% electrolytic leakage out of the cells. Finally,
the analysis of 34 accessions resulted in 1836 measurements.
2.3 Analysis of electrolytic leakage data
The following equations were used to calculate the percentage of
electrolytic leakage (PEL):
EL = EL0/EL1 (2.1)
ELcontrol =
EL0,control/EL1,control (2.2)
PEL = (EL–mean(ELcontrol)) x 100 (2.3)
Equations 2.1 and 2.2 calculate the ratio of electrical conductivity of
un-boiled (EL0) and boiled (EL1) samples
for frozen and control samples. Equation 2.3 calculates the percentage
of electrolytic leakage, which is corrected by subtracting the mean
ELcontrol value for each pretreatment, as leaf damage
could occur from harvesting, incubating in water, and cooling at 4°C.
Negative PEL values were corrected to a 0.00% leakage. This correction
occurred occasionally for samples cooled at 0°C or -2°C, as leaf damage
remained relatively low at these temperatures compared to the control
samples. This made it possible for control values to increase.
All calculations were performed in the R statistical environment using R
Studio (Version R.4.1.2; R Core Team, 2021). A self-starting model was
used to apply a logistic function to the measured PEL values as follows:
PEL = A/[1 + e(xmid− T/scal)] (2.4)
The inflection point (xmid) gives the LT50, and scal is a scale factor.
The asymptote (A) was set to 100%, and the input(T) was the
temperature. For this purpose, the stats package in R (Version 4.1.2; R
Core Team, 2021) implementing functions nls() and SSlogis() was used to
write an r-script (Supplementary Material File 1). Values were derived
using predict(); this process was performed for measured PEL values of
each accession for acclimated and non-acclimated samples, separately.
Using this method, the lower asymptote of the curve approached a 0%
electrolytic leakage (or zero leaf damage) and the upper asymptote
approached a 100% electrolytic leakage (or maximum leaf damage).LT50 and LT100 values for
the acclimated and non-acclimated samples were calculated using the
model data. Because some leaf damage was caused by the harvesting,
incubation in water, and cooling at 4°C, the mean
ELcontrol of each pretreatment was subtracted from
100%, and the resulting percentage was used to calculateLT100 values. To assess the variation in the
measurements, the mean PEL value and standard error were calculated from
replicates of each temperature. The difference between the acclimated LT
and non-acclimated LT values was computed to calculate the
ΔLT50 and ΔLT100 values.
Measured values and calculated values were exported, and the script
allowed the computation of a graph showing all PEL values and mean
values of the measured data, LT50 ,LT100 , and sigmoidal curves for acclimated and
non-acclimated sample accessions.
Further statistical analyses to test differences inLT50 and LT100 values,
both acclimated and non-acclimated, were performed using t-tests. To
confirm whether variation in lethal values existed among species, an
analysis of variance (ANOVA) was applied. A correlation analysis of theLT50 and LT100 values with
geographic coordinates (latitude and longitude) as well as with ploidy
level of the different species (diploid versus polyploid) was performed
using R Studio (Version R.4.1.2; R Core Team, 2021); the data were
checked for normality using the Shapiro-Wilk normality test. This was
performed using the shapiro. test() function of the stats package.
Information on chromosome number and ploidy level is provided in Suppl.
Material Table 1 (Koch et al., 1996; Koch et al., 1998; Koch et al.,
1999; Koch, 2002; Koch et al., 2003; Koch & Bernhardt, 2004; Cieslak et
al., 2007; Koch, 2012; Wolf et al., 2021).
Pearson’s correlation measures a linear dependence between two variables
that have a normal distribution: lethal values and latitude/longitude.
For visualization, scatterplots were produced using ggscatter() from the
ggpubr package (Version 0.4.0), showing lethal values of acclimated and
non-acclimated samples at different latitudes and longitudes. A simple
regression line was calculated (through add = “reg.line”).
2.4 BioClim data analyses of investigated accessions
Principal coordinate analysis was performed to identify different
species groups according to the bioclimatic characteristics of the
accession habitats. For this purpose, nineteen bioclimatic variables
were downloaded from the WorldClim climate data grid
(https://www.worldclim.org; Hijmans et al., 2005) for allCochlearia and Ionopsidium accessions. These included
temperature-related (BIO1-BIO11) as well as precipitation-related
variables (BIO12-BIO19), namely annual mean temperature (BIO1), mean
diurnal range (BIO2), isothermality (BIO3), temperature seasonality
(BIO4), maximum temperature of warmest month (BIO5), minimum temperature
of coldest month (BIO6), temperature annual range (BIO7), mean
temperature of wettest quarter (BIO8), mean temperature of driest
quarter (BIO9), mean temperature of warmest quarter (BIO10), mean
temperature of coldest quarter (BIO11), annual precipitation (BIO12),
precipitation of wettest month (BIO13), precipitation of driest month
(BIO14), precipitation seasonality (BIO15), precipitation of wettest
quarter (BIO16), precipitation of driest quarter (BIO17), precipitation
of warmest quarter (BIO18), and precipitation of coldest quarter
(BIO19). Principal coordinate analysis (PCoA) was performed using the
multivariate statistical package (MVSP 3.22; Kovach, 2007). Bioclimatic
variables and accession numbers were imported in the csv format, data
were centered and standardized, and Kaiser´s rule was used to extract
the axes that retained factors with eigenvalues greater than one.