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ATMOSPHERIC SCIENCE LETTERS
Atmos. Sci. Let. 10: 215–219 (2009)
Published online 16 October 2009 in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/asl.241
Terrestrial and airborne non-bacterial ice nuclei
S. K. Henderson-Begg,1 * T. Hill,2 R. Thyrhaug,3 M. Khan1 and B. F. Moffett1
1 School of Health and Bioscience, University of East London, Romford Road, Stratford,
2 School of Land and Environment, University of Melbourne, Parkville, 3010, Australia
3 Department of Biology, University of Bergen, Jahnebakken 5, PO Box 7800, N-5020
*Correspondence to:
S. K. Henderson-Begg, School of
Health and Bioscience, University
of East London, Romford Road,
Stratford, London E15 4LZ.
E-mail:
[email protected]
Received: 8 May 2009
Revised: 16 July 2009
Accepted: 27 August 2009
London E15 4LZ
Bergen, Norway
Abstract
To freeze above −36.5 ◦ C, water requires the presence of an ice nucleus (IN). These can be
inert particles or living or dead biological material. As they are the most efficient, inducing
freezing at up to −1.8 ◦ C, bacteria are the most widely studied biological IN. Here, we show
that there is a huge repository of IN in lichens which comprise a large biomass and are
able to become airborne. The lichen IN are similar to those we have detected in urban air,
exhibiting heat sensitivity but resistance to lysozyme. This suggests many airborne IN are
non-bacterial and that eukaryotic IN may be more important to atmospheric processes than
previously thought. Copyright  2009 Royal Meteorological Society
Keywords:
ice nucleation; lichen; fungi; bacteria
1. Introduction
Ice does not form in pure water droplets until temperatures fall below −36.5 ◦ C but can occur at much
higher temperatures in the presence of ice nuclei (IN).
Many inert minerals (Mason, 1975), inorganic and
organic molecules (Fukuta, 1966) and bacteria, fungi
and lichens are able to act as ice forming nuclei,
catalysing the production of ice at relatively high
temperatures (Maki et al., 1974; Kieft, 1988; Pouleur
et al., 1992). The most efficient and well-characterised
IN are those produced by bacteria (Lee et al., 1995).
In bacteria, ice nucleation appears to be limited to a
small number of plant pathogens which induce freezing in order to damage plants and so gain nutrients
(Lindow et al., 1982; Hirano and Upper, 2000). These
include Pseudomonas syringae and Pantoea agglomerans (formerly Erwinia herbicola) which can nucleate water to ice at temperatures as high as −1.8 ◦ C
(Maki et al., 1974; Lindow et al., 1989; Morris et al.,
2005). Based on the gene sequence, the ice-nucleating
proteins in these bacteria contain repeating runs of the
same amino acids (Kajava, 1995). These are thought
to fold in switchback fashion upon themselves and
act as a template to align the water molecules into
hexagons (Warren et al., 1986). The nucleation temperature appears to depend on the number of protein molecules that are aggregated together on the
surface of the bacterium. The ice-nucleating phenotype appears to be dependent on environmental conditions, occurs infrequently and is often lost upon
sub-culturing and storage (Fall and Wolber, 1995).
Although some species of fungi and lichens also
nucleate water at high temperatures, the extent and
basis of their ice-nucleating abilities have been much
less studied. Of 15 lichens tested for IN activity, 13
were found to nucleate ice at temperatures >−8 ◦ C
Copyright  2009 Royal Meteorological Society
(Kieft, 1988), and of 20 fungal species tested only
2, both Fusarium species, were found to nucleate
ice at temperatures >−5 ◦ C (Pouleur et al., 1992).
Ice-nucleating activity in these eukaryotes exhibits
similarities to, but also distinct differences from, those
seen in bacteria. The sensitivity of lichen IN to proteindegrading treatments and heating to >70 ◦ C suggests
they may also be proteinaceous (Kieft and Ruscetti,
1990). Fungal IN are also sensitive to heat treatment
(Pouleur et al., 1992). However, both can withstand
higher temperatures than bacterial IN, which begin
to lose high temperature activity after heating to just
30 ◦ C, thought to be as a result of fragmentation of
aggregates (Pouleur et al., 1992).
Recent studies have linked ice-nucleating bacteria
with the water cycle, suggesting that the proteins could
contribute to the initiation of precipitation (Mohler
et al., 2007; Morris et al., 2008). Genetically related
IN-positive strains of P. syringae have been isolated
from snow, connected streams, irrigation water and
crop plants, suggesting they travel in the meltwater
from mountains (Morris et al., 2008). Furthermore, IN
were ubiquitous in snow from America, Antarctica and
France, and their heat instability suggests the majority
are biogenic (Christner et al., 2008). Recently, we
have observed UK snow to contain heat-sensitive IN
active at −4.2 ◦ C (Moffett, unpublished data). Further
support of the link between bacteria and the water
cycle came from Ahern et al. (2007), who found
Pseudomonas species to be the abundant bacterial
genus in Hebridean cloud water samples, although
they were unable to detect ice-nucleating genes in
cloud water samples or ice-nucleating activity in over
100 Pseudomonas isolates.
Several studies have found fungal and lichen species
to be present in the atmosphere (Marshall, 1996;
Tormo et al., 2001; Bauer et al., 2002), but the role
216
of these organisms in the water cycle is yet to be
fully explored. Here, we analyse and compare the ice
nucleation activity of lichens and urban air samples
and discuss their potential role in cloud formation and
precipitation.
2. Methods
Lichens were collected from a variety of coastal, forest and mountain sites in six geographical locations.
Ice-nucleating activity was measured using differential scanning calorimetry (DSC). A small fragment
(<0.1 mg) was sealed in an aluminium crucible along
with 10 µL of molecular biology grade water. The
temperature was then lowered at 1 ◦ C min−1 and freezing was detected by the output of latent heat.
Air samples were collected with the Karcher
DS5500 with an air flow rate of 55 L s−1 . Air is
drawn from the inlet through a sampling liquid which
makes the samples accessible for flow cytometry analysis (Marie et al., 1999). Air outlet is through a
0.3 µm pore filter which prevents bacterial-sized particles from escaping the liquid-sampling chamber. The
liquid container and inflow of the vacuum was sterilised with 70% ethanol and filled with 2 L of sterile
phosphate buffer solution (PBS) for collections. The
vacuum was placed on the roof of a six storey building in East London with the inlet facing skywards and
left running for 6 h during the day (7-4-09) or 17 h
overnight (all other samples). Following collection,
2 mL was sampled and fixed in 0.5% glutaraldehyde
for flow cytometry analysis. The remaining PBS solution was filtered (0.4 µm) and the residue resuspended
in 5 or 10 mL of molecular grade water. Part of the
suspension was then transferred to nutrient agar plates
and incubated at 37 ◦ C for 24 h to culture resident
microorganisms. The remainder was examined for IN
as a bulk sample.
The consensus amino acid sequence for the known
bacterial IN proteins was used to search the online
fungi and cyanobacteria genome databases using
the NCBI BLASTp tool (http://blast.ncbi.nlm.nih.gov/
Blast.cgi). All hits with significant e-values (<0.001)
were examined for the repeating amino acid unit structure by dot plot analysis (programme written by Shawn
Doonan, formerly of UEL) compared with that for the
known bacterial ice-nucleating protein.
Total bacterial counts were determined using FacsCalibur flow cytometer (Becton Dickinson, Franklin
Lakes, NJ) equipped with an air-cooled laser providing 15 mW at 488 nm and with standard filter set-up.
The samples were diluted in 0.2 µm filtered PBS and
stained with SYBRGreen I (Molecular Probes Inc.,
Eugene, OR) for 15 min in the dark and at room
temperature (Marie et al., 1999). The final concentration of SYBRGreen I in the samples was 2 × 10−4
of the commercial stock solution. Four different dilutions were analysed. Results presented are averages
and standard deviations of these dilutions. Fluorescent
Copyright  2009 Royal Meteorological Society
S. K. Henderson-Begg et al.
microspheres (Molecular Probes Inc.) with a diameter
of 0.95 µm were added to PBS and MilliQ water, and
analysed as a standard. The beads were not added to
the samples, but run separately to avoid bias in the
analysis of the diluted samples. The discriminator was
set on green fluorescence and the samples were analysed for 5 min, resulting in analysed particle numbers
between 5000 and 50 000. Blank samples were fixed
and stained in the same way as the samples.
3. Results and discussion
Our initial investigation focussed on expanding the IN
data available for temperate lichen species. Fifty-seven
lichen samples representing forty-six species from six
countries were tested for IN activity by DSC. Water
controls froze at temperatures between −24 ◦ C and
−30 ◦ C which is higher than the −36.5 ◦ C expected
for homogeneous freezing. This is likely to be due to
impurities in the water, but it is also possible that the
metal crucibles which contain the sample alter freezing properties. As can be seen from the distribution in
Figure 1, the ice-nucleating temperature of the lichens
ranged from −5.1 ◦ C to −20 ◦ C. However, 74% ice
nucleated at temperatures above −10 ◦ C, and this is
reflected by the median, −7.2 ◦ C. By initiating freezing at the temperatures at which the vapour pressure
difference between water and ice is close to or at its
maximum, lichen IN could drive the Bergeron Findeisen process. Therefore, lichen-derived IN, if they
become airborne, have the potential to induce precipitation. In an aerobiological monitoring programme
carried out on Signy Island in the Maritime Antarctic, lichen soredia were the most abundant airborne
propagules with a size range of 30–100 µm (Marshal,
1996). Tormo et al. (2001) found lichen propagules in
urban air in Spain. Estimates of lichen biomass are
notoriously difficult but Margulis (1998) has stated
that there is 1014 tonnes on rock surfaces alone. Coworkers state that canopy lichen biomass in temperate
forests is similar to leaf biomass (David Schwartzman,
personal communication). Although there is variability in the estimates, there is undoubtedly a great deal
of lichen biomass. It therefore seems plausible that
if lichen particles become airborne, it could have an
effect on cloud glaciation.
Lichens are formed from a symbiosis of a mycobiont
(fungus) with a photobiont which can either be an
algae or cyanobacteria. Fungal and cyanobacterial
genome sequences were searched for structures similar
to those seen in the bacterial ice-nucleating proteins.
Putative ice-nucleating proteins were identified in
two cyanobacteria and nine fungal species, including
members of the Fusarium fungal genus, which is the
only group of fungi demonstrated to be IN active
to date (Pouleur et al., 1992). However, the two
species identified as containing putative ice-nucleating
proteins here (F. oxysporum and F. graminearum,
39% and 37% identity, respectively) were not found
Atmos. Sci. Let. 10: 215–219 (2009)
DOI: 10.1002/asl
No. of samples
Terrestrial and airborne non-bacterial ice nuclei
217
25.0
Norway
20.0
Faroe Is.
Ethiopia
UK
Australia
15.0
Antartica
10.0
5.0
-19.1 – -21°C
-17.1 – -19°C
-15.1 – -17°C
-13.1 – -15°C
-11.1 – -13°C
-9.1 – -11°C
-7.1 – -9°C
-5.1 – -7°C
0.0
Freezing temperature
Figure 1. The distribution of ice nucleation temperatures of lichen by geographical region.
Temperature of Freezing in centigrade
-5
Sample 8-4-09
-6
Sample 16-3-09
-7
Sample 7-4-09
-8
-9
-10
-11
-12
-13
-14
-15
°C
90
°C
60
°C
37
Ly
s
oz
ym
e
-16
Figure 2. Biparametric flow cytometry plot showing characteristic of particles sampled by the Kärcher DS5500. Side scatter
(SSC) versus green fluorescence is presented. SSC is a non-linear
function of particle size. All particles with an inferred size range
of ∼0.5–10 µm are assumed to be bacterial and coloured red
in this image. All other DNA-containing particles which fell
outside of this range are shown in black.
to be ice-nucleating active by Pouleur et al. (1992).
Although the remaining fungal and cyanobacteria
homologues identified only displayed <26% identity
to the known bacterial consensus sequence, crucially
all contained 8- or 16-mer repeating amino acid motifs.
These help fold the protein into the correct threedimensional structure to act as an IN (Warren et al.,
1986).
It is known that a huge array of biological aerosols
are present in atmospheric samples (Jaenicke, 2005;
Sun and Ariya, 2006; Georgakopoulos et al., 2008);
therefore, atmospheric samples were examined for
evidence of biological IN. The bacterial concentration
(Figure 2) in one atmospheric sample was estimated to
Copyright  2009 Royal Meteorological Society
Treatment
Figure 3. The freezing temperatures of three atmospheric
samples following lysozyme, 37 ◦ C, 60 ◦ C and 90 ◦ C incubations.
be 5 × 104 mL−1 ± 7.7%. The total concentration of
analysed particles assumed to mainly consist of DNAcontaining particles in the size range ∼0.5–10 µm
was around ten times higher, 4 × 105 mL−1 ± 13.1%.
Assuming an air flow rate of 3.3 m3 min−1 given by
the manufacturer of the Kärcher DS5500, minimum
airborne concentration of bacterial and other DNAcontaining particles may thus be estimated to be
around 4 × 104 and 3 × 105 m−3 , respectively. The
other larger DNA-containing particles are likely to
contain a proportion of fungi and lichen components
as they have been previously reported to become
airborne (Marshall, 1996; Tormo et al., 2001; Bauer
et al., 2002).
The ability of atmospheric samples to catalyse freezing was examined. Of the five samples collected
Atmos. Sci. Let. 10: 215–219 (2009)
DOI: 10.1002/asl
218
S. K. Henderson-Begg et al.
Table I. The freezing temperatures of atmospheric samples before and after lysozyme and heat treatments.
Freezing temperature in centigrade
Treatment
Sample 1
Sample 2
Sample 16-3-09
Sample 7-4-09
Sample 8-4-09
Lysozyme
Replica 1
Replica 2
Replica 3
Average
SD
−14
−14
−12.80
−11.80
−8.90
−11.17
2.03
ND
−8.40
−8.60
−8.50
0.14
−7.30
−6.50
−7.00
−6.93
0.40
37 ◦ C
Replica 1
Replica 2
Replica 3
Average
SD
−9
−8
−8.50
−7.50
−9.00
−8.33
0.76
−7.90
−9.00
−9.30
−8.73
0.74
−8.50
−7.60
−8.70
−8.27
0.59
60 ◦ C
Replica 1
Replica 2
Replica 3
Average
SD
−8
−9
−10.40
−9.20
−8.80
−9.47
0.83
ND
−8.70
−9.10
−8.90
0.28
−9.20
−8.80
−9.70
−9.23
0.45
90 ◦ C
Replica 1
Replica 2
Replica 3
Average
SD
−8.00
−12.30
−12.00
−10.77
2.40
−9.50
−10.00
−11.20
−10.23
0.87
−10.80
−11.30
−13.50
−11.87
1.44
on different days, all ice nucleated at temperatures
<−9 ◦ C (Table I). The effect of heating the air samples to 60 ◦ C, 90 ◦ C and lysozyme treatment which
involves incubation at 37 ◦ C was investigated using a
37 ◦ C treatment in the absence of lysozyme as the control for baseline freezing temperature. As can be seen
in Figure 3, the tendancy was for the freezing temperature of each sample to decrease with each treatment.
One-way ANOVA was conducted on the data for samples collected on 16-3-09, 7-4-09, 8-4-09 and for the
combined dataset. This showed there to be a significant
difference in the ice-nucleating temperatures produced
by the 8-4-09 sample and for the combined dataset
with P values of 0.0006 and 0.0056, respectively. Further unpaired t-tests showed there to be a significant
difference in ice nucleation temperature between the
37 ◦ C and 90 ◦ C treatments for the 8-4-09 and combined data samples (P = 0.0159 and 0.0006, respectively) but not between the 37 ◦ C and 60 ◦ C treatments
(P > 0.05). Interestingly, there was also a significant
difference between the 37 ◦ C treatment and lysozyme
treatment for the 8-4-09 sample, but the mean values shown in Table I indicate this to be a reduction
in ice-nucleating temperature in the lysozyme-treated
sample. Although the freezing temperature appears to
be reduced following lysozyme treatment for samples
1, 2 and that collected on 16-3-09, this difference was
not significant.
The reduction in ice-nucleating activity following
heat treatment to 90 ◦ C suggests the most efficient IN
present (those that produce ice at the warmest temperatures) were of biological origin, although the maintenance of ice-nucleating activity following lysozyme
treatment and heating to 60 ◦ C suggests that those
components that nucleated at the highest temperatures
Copyright  2009 Royal Meteorological Society
were not a known bacterial source (Lindow et al.,
1989). As bacterial IN begin to degrade at temperatures exceeding 30 ◦ C (but are often still functional
following 37 ◦ C incubation), it is possible that these
particles were present in the air samples but destroyed
prior to testing leaving the more heat stable fungal and
lichen IN which do not begin to break down until temperatures exceeding 70 ◦ C (Kieft and Ruscetti, 1990;
Pouleur et al., 1992). A similar analysis of IN in international snow samples by Christner et al. (2008) also
found the IN in these samples to be heat sensitive
but largely tolerant of lysozyme treatment, and to ice
nucleate at similar temperatures to the atmospheric
samples analysed in this study. This suggests that the
biological IN in snow and air samples could be of the
same origin, and the majority may not be bacterial. It
is possible that the source of the biological IN contained within these samples are from lichen or fungi,
as these groups are known to nucleate ice and have
been found previously in atmospheric samples (Marshall, 1996; Tormo et al., 2001; Bauer et al., 2002;
Despres et al., 2007).
To date, most research on biological ice nucleation has focussed on bacterial systems. The evidence
presented here suggests that much greater emphasis
should be placed on eukaryotic ice nucleation. IN in
these organisms may be much more significant for
atmospheric processes due to them operating at temperatures which maximise ice crystal growth at the
expense of the available water.
Acknowledgements
This work was supported by grants from the EU PASR 2006
programme (project Aerobactics, contract SEC6-PR-214400)
and the Research Council of Norway (project MicrobAir,
Atmos. Sci. Let. 10: 215–219 (2009)
DOI: 10.1002/asl
Terrestrial and airborne non-bacterial ice nuclei
contract no. 177802). Thanks to Shawn Doonan for help with
dot plot analysis.
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DOI: 10.1002/asl
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