A method for the extraction of nucleic acids from a wide range of environmental samples was developed. This method consists of several modules, which can be individually modified to maximize yields in extractions of DNA and RNA or separations of DNA pools. Modules were designed based on elaborate tests, in which permutations of all nucleic acid extraction steps were compared. The final modular protocol is suitable for extractions from igneous rock, air, water, and sediments. Sediments range from high-biomass, organic rich coastal samples to samples from the most oligotrophic region of the world's oceans and the deepest borehole ever studied by scientific ocean drilling. Extraction yields of DNA and RNA are higher than with widely used commercial kits, indicating an advantage to optimizing extraction procedures to match specific sample characteristics. The ability to separate soluble extracellular DNA pools without cell lysis from intracellular and particle-complexed DNA pools may enable new insights into the cycling and preservation of DNA in environmental samples in the future. A general protocol is outlined, along with recommendations for optimizing this general protocol for specific sample types and research goals.

Storm clouds frequently form in the summer period in temperate climate zones. Studies on these inaccessible and short-lived atmospheric habitats have been scarce. We report here on the first comprehensive biogeochemical investigation of a storm cloud using hailstones as a natural stochastic sampling tool. A detailed molecular analysis of the dissolved organic matter in individual hailstones via ultra-high resolution mass spectrometry revealed the molecular formulae of almost 3000 different compounds. Only a small fraction of these compounds were rapidly biodegradable carbohydrates and lipids, suitable for microbial consumption during the lifetime of cloud droplets. However, as the cloud environment was characterized by a low bacterial density (Me = 1973 cells/ml) as well as high concentrations of both dissolved organic carbon (Me = 179 µM) and total dissolved nitrogen (Me = 30 µM), already trace amounts of easily degradable organic compounds suffice to support bacterial growth. The molecular fingerprints revealed a mainly soil origin of dissolved organic matter and a minor contribution of plant-surface compounds. In contrast, both the total and the cultivable bacterial community were skewed by bacterial groups (γ-Proteobacteria, Sphingobacteriales and Methylobacterium) that indicated the dominance of plant-surface bacteria. The enrichment of plant-associated bacterial groups points at a selection process of microbial genera in the course of cloud formation, which could affect the long-distance transport and spatial distribution of bacteria on Earth. Based on our results we hypothesize that plant-associated bacteria were more likely than soil bacteria (i) to survive the airborne state due to adaptations to life in the phyllosphere, which in many respects matches the demands encountered in the atmosphere and (ii) to grow on the suitable fraction of dissolved organic matter in clouds due to their ecological strategy. We conclude that storm clouds are among the most extreme habitats on Earth, where microbial life exists.

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 Pseudomonas 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.

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.

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 P. syringae 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 P. syringae, 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.

The results obtained in this study allow a different perspective on the quantification of the immersi...

Airborne dispersal of microalgae has largely been a blind spot in environmental biological studies because of their low concentration in the atmosphere and the technical limitations in investigating microalgae from air samples. Recent studies show that airborne microalgae can survive air transportation and interact with the environment, possibly influencing their deposition rates. This minireview presents a summary of these studies and traces the possible route, step by step, from established ecosystems to new habitats through air transportation over a variety of geographic scales. Emission, transportation, deposition, and adaptation to atmospheric stress are discussed, as well as the consequences of their dispersal on health and the environment and state-of-the-art techniques to detect and model airborne microalga dispersal. More-detailed studies on the microalga atmospheric cycle, including, for instance, ice nucleation activity and transport simulations, are crucial for improving our understanding of microalga ecology, identifying microalga interactions with the environment, and preventing unwanted contamination events or invasions.