Diversity of the total bacterial community
We constructed clone libraries from nine individual hailstones to assess species richness and evenness, which represent the most important measures of bacterial diversity. Owing to the combination of low bacterial density (unpublished results) and low volume (Table 1) of our samples, clone libraries had to be made using a semi-nested PCR approach. It was shown that the nested PCR is not significantly more biased than the traditional PCR and can be used to investigate microbial diversity of low bacterial density environments (Fan et al., 2009). The number of PCR cycles also does not significantly influence the community composition studies, as the largest PCR-associated bias is likely generated during the first few PCR cycles (Acinas et al., 2005).
We obtained 485 sequences, which could be clustered into 231 OTUs0.01 (OTUs based on 99% similarity = species level, Stackebrandt & Ebers, 2006), 177 OTUs0.05 (OTUs based on 95% similarity = genus level, Ludwig et al., 1998) and 67 OTU0.15 (OTUs based on 85% similarity = lineage level). Rare OTUs0.01 within the total pool of sequences accounted for 84% of all OTUs0.01, with singletons (OTUs that occur once in the pooled assembly of sequences) accounting for 159 OTUs0.01 (68.8%) and doubletons (OTUs that occur twice in the pooled assembly of sequences) for 35 OTUs0.01 (15.2%). A similar proportion of rare OTUs was reported for uncontaminated soil (Hill et al., 2003) and the atmosphere (Fahlgren et al., 2010). Most abundant bacterial taxons identified by clone libraries are presented in Supporting Information, Table S2. Sixteen main OTUs0.01, represented by at least five sequences, belonged to four different phyla, Firmicutes, Actinobacteria, Bacteroidetes and Proteobacteria. Their closest relatives were previously detected in bulk and rhizosphere soil or on leaf surfaces of plants. Plant, rhizosphere and soil origin fits very well with the analysis of dissolved organic compounds in hailstones (unpublished results). The agricultural contribution has also been indicated by the ion composition (Supporting Information, Data S1, Table S1). The total bacterial community was not represented well by individual hailstones, which is illustrated in Fig. 1. Only very few genera of the total community were present in more than two hailstones (characteristic genera). In addition, 99.6% of all OTUs0.01 were uniques (OTUs that occur in one sample) or duplicates (OTUs that occur in two samples). In fact, only one OTU0.01, which belonged to the Actinobacteria genus Cellulomonas, appeared in three hailstones and no OTU0.01 was detected in more than three.
Figure 1. Community composition showing all genera and common genera (present in at least three hailstones) for total community (TC) and cultivable community (CC).
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The capacity of a bacterial community to resist environmental stress has been related to its species evenness (Wittebolle et al., 2008, 2009). We described the evenness using Pareto–Lorenz distribution curves (Marzorati et al., 2008; Wittebolle et al., 2008, 2009; Edwards et al., 2011), which are presented in Fig. 2a. The intercept of the respective Lorenz curve with the 20% x-axis line (Fig. 2a) can be used to distinguish between communities with high evenness (25% Lorenz curve, intercept at y = 25%), communities with medium evenness (45% Lorenz curve, y = 45%) and highly specialized communities (80% Lorenz curve, y = 80%, Wittebolle et al., 2008). Based on their intercepts, the Lorenz curves of the total storm cloud community suggest a community with medium evenness (Fig. 2a). Thus, approximately 55% of the species were dominant while the remaining 45% were present in low numbers. Gini coefficients, which can take values between 0 (complete equality) and 1 (complete inequality), were used to quantify species evenness (Wittebolle et al., 2009). The mean Gini coefficient for all hailstones was 0.413, and the Gini coefficient for pooled sequences was 0.448, which also points to medium evenness. Although also characterized by medium evenness, the cultivable community was more specialized than the total community, as is evident from its Lorenz curve (Fig. 2a) as well as from the Gini coefficient, which was 0.58. Community composition with medium evenness has been shown to be most balanced (Wittebolle et al., 2009) and can preserve its functionality by efficiently dealing with environmental stress. This is highly important for a bacterial community passing through the atmosphere, if we consider the rapid change that aerosolization poses for bacteria and the diverse environmental stress they encounter in the atmosphere. However, despite the fact that the medium evenness of the airborne community may be beneficial under harsh conditions, the actual activity and the resulting functionality of cloud-borne bacterial communities remain uncertain, especially considering the short residence times of bacteria in cloud droplets.
Figure 2. (a) Lorenz curves showing total community evenness for total communities of individual hailstones (dashed lines) and the pooled hailstones (thick dashed line). The Lorenz curve showing community evenness for the cultivable community is also shown (thick solid line). The 20% x-axis line is indicated. (b) Chao 2 richness estimator of the total bacterial community as a function of number of replicate samples analysed, which shows estimated number of OTUs0.01 in two hailstones with three replicate subsamples (H24, thin black lines; H16, thin grey lines) and in the storm cloud with nine replicate hailstones (thick black lines). Mean Chao 2 richness estimator is plotted as solid lines and 95% confidence intervals as dashed lines. (c) Species accumulation curves are presented for clusters of different levels of similarity. From top to bottom: OTU 0.01, OTU 0.03, OTU 0.05, OTU 0.10, OTU 0.15. (d) Estimated richness of OTU 0.01 (black lines) and species accumulation curves (grey lines) as a function of number of samples analysed by cultivation-dependent methods. Mean values are plotted as solid lines and 95% confidence intervals as dashed lines.
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Chao 2 was employed to determine the total bacterial richness of the cloud. We estimated that the storm cloud contained approximately 1800 OTUs0.01 (Fig. 2b), 500 OTUs0.05 and 80 OTU0.15, which points to a high species richness. Despite the low bacterial densities found in the storm cloud (unpublished results), which were several orders of magnitude lower than in soils or oceans, the diversity of storm cloud bacteria was comparable to that of soil and marine environments, hosting highly diverse communities (Torsvik et al., 1996; Venter et al., 2004; Schloss & Handelsman, 2005). The observed richness of the storm cloud (231 OTU0.01 detected by clone libraries) represented 12.5% of the estimated total richness. Despite the high proportion of richness that was captured in the clone libraries, the species accumulation curves for OTU0.01 and OTU0.05 are still linearly increasing, even after analysing nine hailstones (Fig. 2c). A strikingly high species richness, which was characteristic for the storm cloud, additionally supports the high functional stability of the bacterial community that was already indicated by the medium species evenness.
For the estimation of total richness in the cloud, the analysis of several hailstones was pivotal. In Fig. 2b, the estimated richness assessed by Chao 2 is presented as a function of the number of independent samples (hailstones) analysed. Examining a single hailstone, the species richness would be underestimated by 75%. Examining more than three hailstones facilitates a more reliable richness estimate (Fig. 2b). Two hailstones were also analysed in replicates, to assess bacterial diversity in a single hailstone and to estimate how comparable it is to the total diversity of the cloud. Even though the observed diversity (the number of OTUs0.01 detected by clone libraries) was very similar for both hailstones (56 OTUs0.01, H16; 51 OTUs0.01, H24), the total bacterial richness, estimated with Chao 2, differed strikingly. Hailstone H16 contained 300 OTUs0.01 (Fig. 2b), which is 15% of total estimated cloud richness, whereas hailstone H24 contained 1250 OTUs0.01, which is almost 70% of the estimated cloud richness. In addition, the estimated richness of H16 was described well with three subsamples, while the estimated richness of H24 was still increasing and was thus still underestimated (Fig. 2b). Hailstone H24 very well represented the total diversity of the cloud, which was further implied by the shape of the curve of estimated richness as a function of number of (sub)samples. The higher representation of H24 over H16 could partially be explained by the difference in the hailstones sizes, as the volume and the total number of bacterial cells in the hailstone H24 (42.5 mL, 64 000 cells) was more than two times higher than the volume and the total number of bacterial cells in H16 (20.0 mL, 30 000 cells). The Bray–Curtis coefficient was used to evaluate the compositional similarity between individual hailstones and compare it with subsamples of hailstone H16 and H24. Generally, (with an exception of subsample H16.2) the subsamples of hailstones shared a higher similarity than observed between individual hailstones (data not presented).
Cultivable bacterial community
The cultivable community represented a high proportion (up to 10.5%, unpublished results) of all cells. We isolated 424 bacterial cultures from 9 of 12 analysed hailstones, while three hailstones yielded no CFU. The isolates were clustered into 85 OTUs0.01, 61 OTUs0.03 and 44 OTUs0.05. If we consider all isolates, only 33 OTUs0.01 (38.8%) were singletons and 13 OTUs0.01 (15.9%) were doubletons. The cultivable bacterial community was represented well by some of the hailstones (Fig. 1). The majority of genera were present in more than two hailstones (characteristic genera), and there were only 74.1% of OTUs0.01 that appeared in only one or two hailstones (uniques and duplicates). This is a very different picture from the one we obtained by the cultivation-independent study. Despite the fact that nine hailstones used for the cultivation-independent study were not identical to the nine hailstones analysed in the cultivation-dependent study, the large number of replicates should diminish any influence of using distinct samples.
We estimated, using Chao 2, that the total richness of cultivable bacteria in the storm cloud is approximately 120 OTUs0.01 (Fig. 2d), 90 OTUs0.03 or 60 OTUs0.05, which represents approximately 7–12% of the estimated richness of the total bacterial community. Species accumulation curves reached a plateau, after the analysis of nine hailstones. In addition, the richness we actually observed by analysing 12 hailstones (three hailstones with no CFU were included in this analysis) is approaching the estimated richness (Fig. 2d), as we managed to cover between 68.5% and 77.0% of estimated cultivable bacterial OTUs in the cloud.
Characteristic isolates, which were found in three or more hailstones, belonged to 21 different OTUs0.03 representing five genera, Methylobacterium, Bradyrhizobium, Bacillus, Paenibacillus and Afipia. None of these genera were detected by our clone libraries, but all five were previously identified in air samples using cultivation-independent methods (Maron et al., 2005). The largest OTU0.03 with 17.2% of all isolates found in seven hailstones as well as five other characteristic OTUs0.03 belonged to the epiphytic genus Methylobacterium, which encompasses around a third of all isolates. Methylobacterium spp. are characterized by their pink pigmentation and their facultative methylotrophic lifestyle, traits that are common in epiphytic bacteria. Like the atmosphere, the phyllosphere is an extreme environment, with high levels of UV radiation, low water potential and sudden temperature shifts (Lindow & Brandl, 2003). Thus, adaptations to diverse stressful factors on plant leaf surfaces could help Methylobacterium to remain viable or even metabolically active in the atmosphere. In fact, Methylobacterium was found to possess a general stress response system, which enhances resistance to heat shock, desiccation, UV radiation and oxidative stresses (Knief et al., 2010). On plant surfaces, Methylobacterium strains are competitive against other plant colonizing bacteria because of their capability to utilize single carbon compounds, for example, methanol, formaldehyde and formic acid (Corpe & Rheem, 1989). Being capable of utilizing volatile methanol (Corpe & Rheem, 1989), cloud-borne Methylobacterium cells may grow on atmospheric methanol, the second most abundant organic compound in the atmosphere (Fukui & Doskey, 1998; Galbally & Kristine, 2002). Apart from methanol, Methylobacterium can utilize formaldehyde and formic acid that are both abundant in the atmosphere and in cloud water. Their ability to metabolize several single carbon compounds together with their stress tolerance may enable Methylobacterium to survive and even grow in cloud water.
Different strains of Methylobacterium are negative for ice nucleation and even have some antifreeze properties (Romanovskaya et al., 2001). Acting as antifreeze, large numbers of Methylobacterium in clouds could be important for patterns of precipitation, as the formation of ice crystals is often a prerequisite for precipitation in mixed phase clouds. In addition, Methylobacterium have been shown to have an antagonistic effect against some known plant-associated ice nucleating species (e.g. Xanthomonas campestris and Pseudomonas syringae). Interestingly, cultivable γ-Proteobacteria, to which the known ice nucleating plant pathogens belong, were not detected in our hailstones, although they have been found universally in atmosphere, cloud and precipitation samples (Fuzzi et al., 1997; Maron et al., 2005; Amato et al., 2007a; Ahern et al., 2007; Bowers et al., 2009). However, formation of hail does not depend on the presence of ice nuclei, as storm clouds reach high altitudes with temperatures below −40 °C (Ahrens, 2009).
Bradyrhizobium, represented by three characteristic OTUs0.03 (7.8% of all isolates), was another genus of α-Proteobacteria that was characteristic for the storm cloud hailstones. Like Methylobacterium, some Bradyrhizobium strains can grow on methanol and metabolize other single carbon compounds (Sudtachat et al., 2009). They may therefore grow on atmospheric methanol and consequently alter atmospheric chemistry. Bacterial strains belonging to the genus Bradyrhizobium fix nitrogen, and several Bradyrhizobium strains can carry out photosynthesis (Molouba et al., 1999). Their diverse metabolic capacities could be an advantage in the atmospheric environment, where at least some bacteria may be limited with bioavailable organic compounds. The residence time could, however, be an issue in the case of Bradyrhizobium, as their rRNA operon number (1.3 on average, Klappenbach et al., 2000; Lee et al., 2009) implies an ecological strategy that is characterized by oligotrophy and consequently slow growth. In contrast, Methylobacterium strains typically carry several copies of the 16S rRNA gene (5.5 on average), supporting a fast growth response that is characteristic for copiotrophic bacteria (Shrestha et al., 2007). Although we have not analysed the rRNA operon number, these values are frequently conserved within genera (Rastogi et al., 2009).
Bacillus and Paenibacillus represented almost 16.5% of all isolates, and Bacillus also formed the second most abundant OTU0.03, representing 9.2% of all isolates found in eight hailstones. Both genera have the ability to form endospores, which might provide them with means of withstanding environmental stress faced in the atmosphere. Several Bacillus isolates were closely related to known pathogenic strains, such as Bacillus anthracis or strains of Bacillus cereus and Bacillus thuringiensis. The last common genus, Afipia (third largest OTU0.03), could also be a potential pathogen, as it exhibits amoebae resistance, which is considered a possible virulence trait (Thomas et al., 2007).
Metabolic tests with Phenotype Microarray plates
Phenotype Microarray plates were used to assess the metabolic potential and niche specialization of selected Methylobacterium and Bradyrhizobium strains. We chose to test this group of plant-associated, nonspore-forming genera, which are more likely to remain metabolically active in the atmosphere, because of their preadaptations to atmospheric stress and their ability to utilize cloud-borne organics. Airborne Bacillus and Paenibacillus were likely present as endospores, which facilitates their survival under unfavourable conditions but excludes any metabolic activity. We tested seven Methylobacterium isolates and one Bradyrhizobium isolate for utilization of 95 organic compounds as single carbon sources. They were able to utilize between 2 and 9 carboxylic acids (Table 2), which on average represent 36% of total dissolved organic carbon in cloud water (Marinoni et al., 2004). Four Methylobacterium strains as well as the Bradyrhizobium strain were also able to utilize formic acid, confirming their potential to grow on major single carbon constituents of cloud water. The ability of cloud-borne bacteria to metabolize atmospheric organic compounds has previously been indicated by studies, showing that members of natural microbial communities could grow on the bulk of organic compounds found in cloud water (Sattler et al., 2001; Amato et al., 2007b; Hill et al., 2007). Bacterial isolates from dry air, precipitation and cloud water were also able to utilize common atmospheric organics (Ariya et al., 2002; Amato et al., 2005, 2007b, Vaïtilingom et al., 2010, 2011) at rates comparable to photooxidation, which means that microbial metabolism may compete with photooxidation in clouds. In addition, we demonstrated that the Bradyrhizobium strain was more specialized and could only utilize a small number of compounds, while the Methylobacterium strains were able to utilize between 17% and 49% of organic compounds of different types (Table 3). This observation provides supporting evidence for the generalistic (opportunistic) ecological strategy of cloud-borne Methylobacterium strains.
Table 2. Utilization of major carboxylic acids in cloud water (Marinoni et al., 2004) by 7 Methylobacterium and one Bradyrhizobium strain: 1 – can utilize, 0 – cannot utilize
|Carboxylic acids||% of total carboxylic acid conc.a ||7 Methylobacterium strains|| Bradyrhizobium strain|
Table 3. Utilization of different compound types as single carbon sources by 7 Methylobacterium and one Bradyrhizobium strain
|Compound type||7 Methylobacterium strains|| Bradyrhizobium strain|
|Amines (no of compounds)||0||0||1||0||0||0||0||0|
|Amino acid derivates (no of comp.)||2||11||2||4||5||3||8||0|
|Carbohydrates (no of comp.)||3||18||10||7||7||3||4||2|
|Carboxylic acids (no of comp.)||10||13||6||15||15||9||18||2|
|Nucleotides (no of comp.)||0||5||0||0||0||0||0||0|
|Phenolic compound (no of comp.)||0||0||0||0||0||0||0||0|
|Polymer (no of comp.)||1||0||0||1||0||1||1||0|
In summary, we hypothesize that the highly diverse bacterial community remains functional under stressful conditions and that it contains bacterial groups, which remain viable and are potentially active in the atmosphere. We propose that they are important for the patterns of bacterial distribution as well as for atmospheric chemistry. We also suggest that although they account for a small fraction of the highly diverse cloud community, epiphytic bacteria encompass species with particular importance for altering atmospheric chemistry.