the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Clouds influence the functioning of airborne microorganisms
Abstract. Airborne micro-organisms can remain at altitude for several days exposed to multiple environmental constraints that prevent or limit microbial activity, the most important of which is probably the lack of available liquid water. Clouds, i.e. air masses containing liquid water, could offer more favorable conditions. In order to investigate the influence of clouds on the functioning of airborne microorganisms, we captured aerosols into a nucleic acid preservation buffer from a high-altitude mountain meteorological station during cloudy and clear conditions, and examined metatranscriptomes. The specificities of aeromicrobiome’s functioning in clouds compared to the clear atmosphere were then decrypted from differential functional expression analysis (DEA). The data reveal higher RNA-to-DNA content in clouds than in the clear atmosphere suggesting higher metabolic activity, and an overrepresentation of microbial transcripts related to energy metabolism, the processing of carbon and nitrogen compounds, intracellular signaling, metabolic regulations, transmembrane transports, and others. Stress response orients towards responses to osmotic shocks and starvation, rather than the defense against oxidants in clear atmosphere. Autophagy processes in eukaryotes, (macropexophagy, i.e. the recycling of peroxisomes) could help to alleviate the limited amounts of nutrients in the restricted microenvironments provided by cloud droplets. The whole phenomenon resembles the rapid resumption of microbial activity in dry soils after rewetting by rain, known as the "Birch effect", described here for the first time in the atmosphere. This work provides unprecedented information on the modulations of aeromicrobiome functioning in relation to atmospheric conditions. In addition of contributing to the processing and fate of chemical compounds in the atmosphere, cloud-induced modulations of biological processes could have ecological repercussions by shaping airborne microbial diversity and their capacity to invade surface environments.
- Preprint
(1765 KB) - Metadata XML
-
Supplement
(3350 KB) - BibTeX
- EndNote
Status: open (until 20 Nov 2024)
-
RC1: 'Comment on egusphere-2024-2338', Anonymous Referee #1, 27 Oct 2024
reply
In the manuscript "Clouds influence the functioning of airborne microorganisms", by Péguilhan, et al., the authors explore the metabolic activity of cloud-borne microbes in comparison to airborne microbes using metagenomic and metatranscriptomic approaches. A thorough analysis has been conducted to explore possible mechanisms once microbes experiencing humid conditions in clouds compared to open air, with respect to stress response, metabolism, etc. However, some theories, such as the "birch effect," lack robust support, and I find the presented data unconvincing, as I specify below.
Sample collection:
- What were the negative controls for the cloud and air samples? This should be clarified in the methodology and presented as SI data.
- As the manuscript cannot include seasonality, authors should constrain their samples to a specific season. Specifically, the cloud sample during springtime could impact diversity and abundance and introduce seasonal-related impact.
- Table 1 - What was the time of sampling? It is not specified whether samples were collected during day or night.
Discussion:
P. 15, L. 56: I'm afraid authors are overstating their findings, suggesting this is the first time demonstrating the impact of atmospheric conditions on microbial functioning in the atmosphere (See Bryan et al, 2019, and others).
Section 4.1: it is problematic to deduce from higher RNA:DNA levels that the metabolic levels in clouds are higher. Especially as the annotated genes in MT are not significantly different between the two environments, as seen in Table S1. Instead, it seems that the levels of DNA gene annotation in clouds are the factor that results in a higher RNA:DNA ratio in clouds.
Thus, the Birch effect doesn’t seem likely to explain your findings. Instead, I suggest considering an environmental switch of specific genes as related to the environmental conditions.
Moreover, if a birch effect occurs, I suspect it would be linked with spore-forming species, and the transformation from the dormant to the vegetative form would be characterized by key genes that should be presented to support the proposed theory.
Section 4.3: This section appears to rely more on generalizations than on solid data. I recommend either omitting this part or revising it for clarity and support.
Figure 1A: Change “clear situation” to “clear atmosphere/open air”. Also seen in Fig. 4 and across the manuscript.
Citation: https://doi.org/10.5194/egusphere-2024-2338-RC1 -
RC2: 'Comment on egusphere-2024-2338', Anonymous Referee #2, 19 Nov 2024
reply
This study by Péguilhan et al. investigates microbial activity in clouds, comparing it to samples from clear atmospheric conditions using metatranscriptomic and metagenomic sequencing. The results revealed a higher RNA-to-DNA ratio in cloud samples than in clear atmosphere samples, indicating elevated microbial metabolic activity. Metabolic pathways associated with various cellular processes were found to be overexpressed in cloud samples. The authors attributed this increased metabolic activity to the availability of moisture in clouds, which is absent under clear conditions. Despite the limited number of samples analyzed, the study is significant, as collecting samples for metagenomic and metatranscriptomic analyses is not trivial due to the low biomass in the atmosphere. This research provides valuable groundwork for future studies in this area.
Major comments:
1. Sections 3.2.1 to 3.2.3 are primarily descriptive, listing overexpressed functions. To enhance clarity and strengthen the data presentation, the authors should consider structuring the discussion around specific research questions or hypotheses. This would create a more cohesive narrative, allowing the data to directly address these questions or test the proposed hypotheses.
2. Related to the comment above, the Introduction could more clearly articulate the research questions the study aims to address. Rather than simply determining whether microbes are active and expressing genes in clouds, the authors should frame the study around more focused, in-depth questions.
3. Section 2.3. Please provide a more detailed explanation of how the metagenomic and metatranscriptomic data were normalized. Additionally, it appears the authors analyzed short reads for this study. Did they attempt to assemble these reads into contigs or even reconstruct genomes?
4. Given the low biomass of the samples, please describe the procedures implemented to prevent contamination during sampling. Were negative controls used, and were any decontamination procedures applied to the sequencing reads?
5. Section 3.1. Currently, there is no figure on taxonomy in the main manuscript. Including a figure in the main text, rather than keeping all of them in the supplementary information, would improve readability and benefit the readers.
6. Section 3.2.3. Several stress-related pathways are described in this section, but they are not further elaborated in the Discussion. Including a brief discussion on stress tolerance would help readers understand the challenges microbes face and how they adapt to them.
7. Section 4.3. The authors suggest that microbial growth may occur in clouds. Were any genes related to cell replication overexpressed in the cloud samples?
8. A brief discussion on the limitations of this study is necessary to put the findings into perspective.
Citation: https://doi.org/10.5194/egusphere-2024-2338-RC2
Data sets
Supplementary data to "Clouds influence the functioning of airborne microorganisms", for Biogeosciences Raphaëlle Péguilhan, Florent Rossi, Muriel Joly, Engy Nasr, Bérénice Batut, François Enault, Barbara Ervens, and Pierre Amato https://www.biorxiv.org/content/10.1101/2023.12.14.571671v2.supplementary-material
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
152 | 32 | 9 | 193 | 12 | 2 | 2 |
- HTML: 152
- PDF: 32
- XML: 9
- Total: 193
- Supplement: 12
- BibTeX: 2
- EndNote: 2
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1