Immersion freezing of ice nucleation active protein complexes

Abstract

Utilising the Leipzig Aerosol Cloud Interaction Simulator (LACIS), the immersion freezing behaviour of droplet ensembles containing monodisperse particles, generated from a Snomax™ solution/suspension, was investigated. Thereto ice fractions were measured in the temperature range between −5 °C to −38 °C. Snomax™ is an industrial product applied for artificial snow production and contains <i>Pseudomonas</i> syringae} bacteria which have long been used as model organism for atmospheric relevant ice nucleation active (INA) bacteria. The ice nucleation activity of such bacteria is controlled by INA protein complexes in their outer membrane. <br><br> In our experiments, ice fractions increased steeply in the temperature range from about −6 °C to about −10 °C and then levelled off at ice fractions smaller than one. The plateau implies that not all examined droplets contained an INA protein complex. Assuming the INA protein complexes to be Poisson distributed over the investigated droplet populations, we developed the CHESS model (stoCHastic modEl of similar and poiSSon distributed ice nuclei) which allows for the calculation of ice fractions as function of temperature and time for a given nucleation rate. Matching calculated and measured ice fractions, we determined and parameterised the nucleation rate of INA protein complexes exhibiting class III ice nucleation behaviour. Utilising the CHESS model, together with the determined nucleation rate, we compared predictions from the model to experimental data from the literature and found good agreement. <br><br> We found that (a) the heterogeneous ice nucleation rate expression quantifying the ice nucleation behaviour of the INA protein complex is capable of describing the ice nucleation behaviour observed in various experiments for both, Snomax™ and <i>P. syringae</i> bacteria, (b) the ice nucleation rate, and its temperature dependence, seem to be very similar regardless of whether the INA protein complexes inducing ice nucleation are attached to the outer membrane of intact bacteria or membrane fragments, (c) the temperature range in which heterogeneous droplet freezing occurs, and the fraction of droplets being able to freeze, both depend on the actual number of INA protein complexes present in the droplet ensemble, and (d) possible artifacts suspected to occur in connection with the drop freezing method, i.e., the method frequently used by biologist for quantifying ice nucleation behaviour, are of minor importance, at least for substances such as <i>P. syringae</i>, which induce freezing at comparably high temperatures. The last statement implies that for single ice nucleation entities such as INA protein complexes, it is the number of entities present in the droplet population, and the entities' nucleation rate, which control the freezing behaviour of the droplet population. Quantities such as ice active surface site density are not suitable in this context. <br><br> The results obtained in this study allow a different perspective on the quantification of the immersi...

Particle surface area dependence of mineral dust in immersion freezing mode: investigations with freely suspended drops in an acoustic levitator and a vertical wind tunnel

“…This confirms the findings of other recent studies, e.g., Murray et al (2011), Broadley et al (2012, and Hartmann et al (2013). In the following Fig.…”

Ice nucleation by fertile soil dusts: relative importance of mineral and biogenic components

“…Indeed, previous estimates of the numbers of live ice-nucleating bacteria in soils have been unable to account for observed ice active site densities (Conen et al, 2011). Non-viable cells, cell membrane fragments and membrane vesicles have all been shown in the laboratory to exhibit IN activity (Maki and Willoughby, 1978;Phelps et al, 1986;Hartmann et al, 2013;Augustin et al, 2013), and dead bacteria have been postulated to contribute significantly to the ice-nucleating ability associated with plant tissues (Ashworth and Kieft, 1995;Lindow, 1983a, b). While the lifetime of IN active proteins derived from bacteria and fungi in soils is unknown, there is evidence to suggest that certain proteins in soils can have extremely long residence times, on the order of centuries (Amelung et al, 2006).…”

“…However, for cases where the surface area of the nucleating particles is readily definable, the number of active sites may be expected to scale directly with surface area (Niemand et al, 2012;Murray et al, 2011;Niedermeier et al, 2010;Augustin et al, 2013;Hartmann et al, 2013). Consequently, comparison of active site densities per unit mass is contingent upon the specific surface areas across the samples being similar.…”

“…The implication of this result is that nonspecific soil organic matter is more important than bacterial cells (or other whole biogenic particles such as fungal spores or pollen grains) for atmospheric ice nucleation. While it is unclear which components of the organic fraction of soils nucleate ice, fragments from pollen grains, bacteria and fungal spores are all known to retain some of the ice-nucleating ability of their parent particles (Maki et al, 1974;Pouleur et al, 1992;Pummer et al, 2012;Augustin et al, 2013;Hartmann et al, 2013). Hence, estimates of the atmospheric IN loadings determined from biogenic particles based on intact biogenic particles (e.g.…”

Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters

“…In the case of heterogeneous ice nucleation it is found that mineral dust particles are favorable INP at temperatures below about −20 • C Murray et al, 2012;Augustin-Bauditz et al, 2014) that marine particles seem to be comparably inefficient INPs at temperatures > −25 • C, whereas continental aerosols (mixtures of anthropogenic haze, biomass burning smoke, soil and road dust, and organic and biogenic particles from soils and plants) seem to contain always a significant amount of efficient INPs, already leading to ice nucleation at temperatures as high as −5 to −15 • C (Seifert et al, 2010;Zhang et al, 2010;Kamphus et al, 2010;Ebert et al, 2011;Augustin et al, 2013;Hartmann et al, 2013;Bühl et al, 2013;Pummer et al, 2015;Umo et al, 2015).…”