Interannual Bacterial Diversity Variability in Antarctic Snow/Ice Samples in the Vicinity of Concordia Station

Round 1

Reviewer 1 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

The current version of the manuscript is significantly better than the previous one. Its disadvantage is the rather distant period of research, as the authors compare bacterial variability in snow between 2015–2016 and 2018–2019. They do not sufficiently explain, either in the discussion or in the conclusions, what causes the differences in bacterial communities between the compared periods. The explanations are not supported by their own experimental data. I suggest that the methodological chapter include the meteorological conditions prevailing in each period.

Although the authors replied that the References section is adapted to the Life journal, they still do not use abbreviated journal names.

I believe that, taking into account the above comments, the article can be published.

 

Author Response

Comments 1: 

The current version of the manuscript is significantly better than the previous one. Its disadvantage is the rather distant period of research, as the authors compare bacterial variability in snow between 2015–2016 and 2018–2019. They do not sufficiently explain, either in the discussion or in the conclusions, what causes the differences in bacterial communities between the compared periods. The explanations are not supported by their own experimental data. I suggest that the methodological chapter include the meteorological conditions prevailing in each period.

Although the authors replied that the References section is adapted to the Life journal, they still do not use abbreviated journal names.

I believe that, taking into account the above comments, the article can be published.

Responses 1: 

We thank the reviewer for their positive evaluation of the revised manuscript and for their constructive suggestions. In response to the comment about the time gap between the sampling periods (2015-2016 and 2018-2019), we have expanded the discussion to explain that differences in bacterial communities may be affected by environmental and meteorological variations between seasons. To provide better context, we have included a description of the main meteorological conditions prevailing during each sampling period in the 'Materials and Methods' section. This addition enables readers to better interpret potential environmental drivers of community variation, while avoiding unsupported causal interpretations. In the References section, we have revised the entire list of references to ensure that journal names are reported in the abbreviated format required by Life journal guidelines.

Reviewer 2 Report (Previous Reviewer 3)

Comments and Suggestions for Authors

After carefully reading the revised manuscript, I concluded that the changes were insufficient. The authors already have the results of the metabarcoding of the bacterial 16S rRNA. Therefore, they should not limit themselves to simple bioinformatic processing for taxonomic identification of ASVs and analysis of alpha and beta diversities.  I recommend that they add additional parameters to their work.

Author Response

Comments1: After carefully reading the revised manuscript, I concluded that the changes were insufficient. The authors already have the results of the metabarcoding of the bacterial 16S rRNA. Therefore, they should not limit themselves to simple bioinformatic processing for taxonomic identification of ASVs and analysis of alpha and beta diversities.  I recommend that they add additional parameters to their work.

Responses 1: 

We thank the reviewer for this suggestion and for recognising the potential of the metabarcoding dataset. However, the primary objective of the present study was to characterise the bacterial community composition in snow samples and compare community structure between the sampling periods investigated. For this reason, the analytical framework focused on the taxonomic characterisation of ASVs, alongside alpha- and beta-diversity analyses. These are standard and appropriate approaches for describing microbial communities in environmental metabarcoding studies. Furthermore, snow microbial assemblages are typically characterised by low biomass, high stochasticity and limited ecological structuring. In such systems, more complex ecological or functional analyses may not provide robust or biologically meaningful interpretations. Therefore, we believe that the current analytical framework is most appropriate for this type of dataset and the study's objectives, and adequately supports the conclusions presented in the manuscript.

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

The work is devoted to an interesting topic. The authors have done a considerable amount of work. Nevertheless, there are a number of comments.

The introduction needs to be expanded. Since research on the specific location studied by the authors is extremely limited, the novelty of the study would be emphasized by an analysis of how well the bacteriological community in the Antarctic region has been studied overall. When were similar studies conducted? What results were obtained? It is also necessary to formulate the purpose of the study more clearly.
Were any physicochemical analyses of the collected samples performed? For example, was the pH level or the nitrogen and phosphorus content determined?

If such analyses were carried out, it is essential to include this data in the study.

The discussion needs to be revised and expanded. The authors provide reasoning that is too general. The study notes a certain difference in the structure of the bacterial community over a mere two-year period. In the discussion, we would like to see specific reasoning about what this difference entails and which specific parameters it might be associated with (for example, temperature, etc.). We would also like to see information on how typical the obtained data are for Antarctic communities, or whether this bacterial community is unique. Does it differ from Arctic ecosystems? In what way? What abiotic or biotic factors determine this?

The conclusions need to be made more specific and focus on the particular findings obtained during this study. They should emphasize how typical or, conversely, how unique the bacterial community in this location is for the Antarctic region, note the changes that occurred between the two stages of the study, and summarize what these changes are associated with.

Author Response

Comments: 

The work is devoted to an interesting topic. The authors have done a considerable amount of work. Nevertheless, there are a number of comments.

The introduction needs to be expanded. Since research on the specific location studied by the authors is extremely limited, the novelty of the study would be emphasized by an analysis of how well the bacteriological community in the Antarctic region has been studied overall. When were similar studies conducted? What results were obtained? It is also necessary to formulate the purpose of the study more clearly.
Were any physicochemical analyses of the collected samples performed? For example, was the pH level or the nitrogen and phosphorus content determined?

If such analyses were carried out, it is essential to include this data in the study.

The discussion needs to be revised and expanded. The authors provide reasoning that is too general. The study notes a certain difference in the structure of the bacterial community over a mere two-year period. In the discussion, we would like to see specific reasoning about what this difference entails and which specific parameters it might be associated with (for example, temperature, etc.). We would also like to see information on how typical the obtained data are for Antarctic communities, or whether this bacterial community is unique. Does it differ from Arctic ecosystems? In what way? What abiotic or biotic factors determine this?

The conclusions need to be made more specific and focus on the particular findings obtained during this study. They should emphasize how typical or, conversely, how unique the bacterial community in this location is for the Antarctic region, note the changes that occurred between the two stages of the study, and summarize what these changes are associated with.

Resposes point-to-point: 

1. 

We thank the reviewer for this constructive suggestion. We have expanded the introduction to provide a broader overview of previous studies investigating bacterial communities in Antarctic environments, including snow and related cryospheric habitats. Additional references have been incorporated to provide a clearer context for current knowledge of microbial diversity in Antarctic regions, and to emphasise the limited information available for the specific study area. Furthermore, the aim of the study is now clearly stated at the end of the introduction to emphasise its novelty and objectives. Furthermore, no physicochemical analyses such as pH, nitrogen, or phosphorus measurements were performed on the collected snow samples. Since these parameters were not measured during the sampling campaigns, they could not be included in the analyses.

2. 

We thank the reviewer for this valuable feedback. In the revised manuscript, the discussion has been clarified to provide a clearer explanation of the interpretation of the differences observed between the two sampling periods. As our results show, the main factor influencing the observed bacterial diversity was the sampling year. In this environment, snow microbial assemblages are better interpreted as transient bacterial assemblages than as structured, functionally active communities. For this reason, their composition is likely to be driven more by stochastic deposition processes (e.g. atmospheric transport and annual variability) than by local environmental parameters such as temperature or pH. Furthermore, temperatures were consistently below −25 °C during the sampling periods, which is expected to result in extremely limited bacterial metabolic activity. This further supports the idea that these assemblages are not strongly structured by local environmental factors. We agree that comparing with Arctic ecosystems represents an interesting perspective. However, the main objective of the present study was to evaluate the variability of bacterial assemblages at the same sampling site over different years. A broader comparison with Arctic snow ecosystems would require a more extensive dataset, so it was considered beyond the scope of this study. However, it certainly represents an interesting direction for future research.

3. 

We thank the reviewer for this suggestion. The Conclusions section has been revised to emphasise the study's main findings more clearly. In particular, we have clarified that the bacterial assemblages detected in the snow samples are more accurately described as transient and stochastic than as structured and functionally active microbial communities. Consequently, the observed differences between the two sampling periods are most likely associated with interannual variability in atmospheric deposition rather than local environmental drivers. The revised conclusions now summarise the observed temporal variability at the same sampling site more clearly and highlight the relevance of these findings for understanding microbial assemblages in Antarctic snow environments.

Round 2

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

The authors have done a lot of work and made a number of important changes to improve the manuscript.

I recommend improving the quality of the legend in Figure 2. The text is hard to read in its present form.

It is also necessary to carefully check the references to sources in the manuscript.

Author Response

Comments 1: I recommend improving the quality of the legend in Figure 2. The text is hard to read in its present form.

Responses 1: Dear Reviewer, Thank you for your review and for the excellent suggestion. I have improved the quality and readability of Fig. 2. 

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The article presents the results of a study investigating microbial dynamics in one of the most extreme environments on Earth. The authors demonstrate that bacterial communities in the snow and ice around Concordia Station undergo significant changes from year to year, which are governed by stochastic processes rather than deterministic selection. This well-planned and methodologically sound work makes an important contribution to our understanding of microbial ecology in systems with low biomass.

Comments and recommendations:

1. Samples from 2015–2016 and 2018–2019 were distributed by year, ignoring intra-year variations. This obscures any significant seasonal patterns. While the authors briefly mention this choice (lines 73–74), they do not adequately justify it. Recommendation: discuss the potential impact of this aggregation on the conclusions.

Having only two sampling points, three years apart, limits the ability to identify long-term trends or cyclical patterns. This makes it difficult to draw definitive conclusions about 'stochastic events' being the main mechanism.

2. There were significant differences between years: Pseudomonadota dominated the community in 2015-16 (76.8%), while Bacteroidota dominated in 2018-19 (67.5%). This extreme difference requires further explanation. The authors suggest that these differences are caused by episodic atmospheric precipitation, but they provide little direct evidence for this. Recommendation: Integrate data on airflows, atmospheric events and sampling systems to confirm the atmospheric origin hypothesis. The possibility that human activity at the station (e.g. maintenance, servicing, ventilation) could be the cause of the observed differences is not discussed.
3. 3. Beta Dispersion Analysis. The results show that intra-annual heterogeneity was higher in 2015–16 (median = 0.63) and lower in 2018–19 (median = 0.50), p < 0.001. This is contrary to what would be expected by chance alone (the results should be the same in both years). One possible interpretation is that this may indicate the presence of some deterministic factors that led to a more homogeneous community in 2018–19. This requires further discussion.
4. 4. The article does not discuss the potential functional consequences of the observed shifts in composition. The possible stress resistance genes and metabolic abilities of various dominant taxa have not been studied. Recommendation: Add a discussion of functional profiles based on 16S data (e.g. using PICRUSt or similar tools).
5. 5. Figure 3A. The labels or colouring may be mixed up in Figures B and C (15–16).

Conclusion:

This is a good piece of work that contributes to our understanding of the microbial ecology of extreme environments. The main novelty lies in demonstrating that microbial communities in the oligotrophic, cold, isolated environment of Antarctica are primarily governed by stochastic processes rather than deterministic selection.

Author Response

Comments1: Samples from 2015–2016 and 2018–2019 were distributed by year, ignoring intra-year variations. This obscures any significant seasonal patterns. While the authors briefly mention this choice (lines 73–74), they do not adequately justify it. Recommendation: discuss the potential impact of this aggregation on the conclusions.

Having only two sampling points, three years apart, limits the ability to identify long-term trends or cyclical patterns. This makes it difficult to draw definitive conclusions about 'stochastic events' being the main mechanism.

Responses 1: 

We recognise this limitation and have expanded the discussion to explicitly address the potential impact of aggregating samples by year. The decision to aggregate the data was motivated by the primary objective of this study, which was to compare the composition of the bacterial community in independent sampling campaigns conducted several years apart, rather than to resolve seasonal dynamics within a single year. Furthermore, the two datasets were originally generated with distinct experimental designs, with different temporal coverage and sampling intensities, making direct seasonal comparisons statistically unbalanced and potentially misleading. We have clarified in the Discussion that aggregating samples by year may mask small-scale seasonal patterns and that our conclusions are therefore limited to interannual variability. We also emphasise that future studies specifically designed to address seasonal dynamics will be necessary to distinguish between intra-annual and interannual factors driving community variability.

Responces 2: 

We have broadened the discussion to interpret these pronounced compositional changes with greater caution. Although long-range atmospheric transport remains a plausible explanation supported by previous aerobiological studies conducted at Dome C and other locations on the Antarctic Plateau, we now explicitly acknowledge that we did not directly measure atmospheric circulation, air mass trajectories, or deposition events during the sampling periods. Furthermore, we have added a discussion dedicated to potential anthropogenic contributions, including station-related activities, maintenance operations, and ventilation systems, as episodic sources of microbial input. We clarify that such contributions are likely transient and strongly limited by extreme environmental conditions, but cannot be excluded as factors contributing to interannual variability.

Comments 3:  Beta Dispersion Analysis. The results show that intra-annual heterogeneity was higher in 2015–16 (median = 0.63) and lower in 2018–19 (median = 0.50), p < 0.001. This is contrary to what would be expected by chance alone (the results should be the same in both years). One possible interpretation is that this may indicate the presence of some deterministic factors that led to a more homogeneous community in 2018–19. This requires further discussion.

Responces 3: We thank the reviewer for this important comment. We have revised the discussion to explicitly address the beta dispersion results, emphasising that differences in heterogeneity within the year do not contradict stochastic assembly processes. Rather, they suggest that different years may exhibit varying degrees of compositional dispersion, potentially reflecting differences in the number, timing, or composition of episodic inputs.  We now clarify that greater dispersion in 2015–2016 and lesser dispersion in 2018–2019 do not imply convergence toward a deterministic endpoint, but rather differences in community variability under similar environmental conditions. The interpretation has been modified accordingly to avoid exaggeration.

Comments 4: The article does not discuss the potential functional consequences of the observed shifts in composition. The possible stress resistance genes and metabolic abilities of various dominant taxa have not been studied. Recommendation: Add a discussion of functional profiles based on 16S data (e.g. using PICRUSt or similar tools).

Responces 4: We recognise the importance of functional inference. However, given the extremely low biomass of the samples and the predominance of taxa detected near the limits of sequencing sensitivity, we believe that predictive functional profiling based on 16S rRNA data is not reliable in this specific context. We have therefore added a statement in the Discussion that acknowledges this limitation and emphasises that shotgun metagenomic or metatranscriptomic approaches would be more appropriate for studying functional potential and stress resistance traits in these systems in the future.

Comments 5:  Figure 3A. The labels or colouring may be mixed up in Figures B and C (15–16).

Responces 5: We thank the reviewer for pointing this out. The figure has been carefully checked and corrected where necessary to ensure consistency between labels, colours, and sample groups.

We appreciate the reviewer's positive assessment of the novelty and relevance of the study. Following these comments, we have substantially revised the manuscript to present a more cautious and balanced interpretation of the results, emphasising interannual variability and compatibility with stochastic and episodic assembly processes rather than stating deterministic conclusions.

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript presents the results of research on the snow and ice microbiome in snow and ice samples collected in 2018–2019 at the Italian-French Concordia station and from a comparable study conducted in 2015–2016. Bacterial amplicon sequencing datasets from snow and ice samples were obtained from the public domain. Raw sequencing data were downloaded from the NCBI Sequence Read Archive (SRA) using the SRA toolkit.

Comments

The introduction to the study should be more extensive, with a clear justification of the purpose of the study and a presentation of the research hypotheses. I cannot quite understand what is novel about this study, as differences between the microbiome studied at different times will also occur in a temperate climate.  I suggest conducting direct research on samples collected from the environment, rather than using the public domain. The references are not presented in accordance with the journal's requirements. This mainly concerns the names of journals.
In my opinion, the manuscript is not suitable for publication in its current form.

 

Author Response

Comments 1: The introduction to the study should be more extensive, with a clear justification of the purpose of the study and a presentation of the research hypotheses. I cannot quite understand what is novel about this study, as differences between the microbiome studied at different times will also occur in a temperate climate.  I suggest conducting direct research on samples collected from the environment, rather than using the public domain. The references are not presented in accordance with the journal's requirements. This mainly concerns the names of journals.
In my opinion, the manuscript is not suitable for publication in its current form.

Responces 1: We thank the reviewer for their careful evaluation of our manuscript and constructive comments. We have substantially revised the manuscript to address the issues raised and improve clarity, context, and compliance with the journal's requirements. Our detailed responses are provided below.

We agree with the reviewer that the scope and novelty of the study required clearer wording. Consequently, the introduction has been expanded to better define the objectives of the work and to explicitly state the research questions addressed. In particular, we now emphasise that the novelty of this study lies not in the simple observation of temporal variability, which is predictable in many environments, but rather in the assessment of interannual changes in microbial community composition within one of the most extreme, isolated, and low-biomass environments on Earth. Unlike temperate systems, where microbial turnover is often determined by seasonal productivity, resource availability and local growth, microbial communities in the snow and ice of the Antarctic interior are characterised by severe limitations on metabolic activity and persistence. Therefore, assessing whether interannual variability also occurs under such conditions provides insight into the mechanisms governing community assembly in environments where local selection and growth are severely limited. This comparative temporal perspective had not previously been addressed for the Concordia station.

We respectfully note that the datasets used in this study come from our previous field campaigns at Concordia Station (Napoli et al., 2022; Stoppiello et al., 2023), conducted as part of long-term research projects led by our group. The use of publicly available data in this context ensures transparency, reproducibility, and continuity between related studies and is consistent with current best practices in microbial ecology.  Furthermore, conducting new field sampling at Concordia Station involves significant logistical, environmental, and regulatory constraints. The present study was conceived as a natural extension of existing datasets to address new ecological questions, particularly interannual variability, without further environmental disturbance. We have clarified this point in the Materials and Methods section to avoid any ambiguity regarding the origin of the data.

We thank the reviewer for pointing this out. The list of references has been completely revised and reformatted to comply with the journal's guidelines, including the correct formatting and capitalisation of journal names, citation style, and order.

Reviewer 3 Report

Comments and Suggestions for Authors

Review of the manuscript of "Stochastic Events Drive the Long-Term Dynamics of Bacteria Associated to Snow/Ice Encompassing Concordia Station on the Antarctic Polar Plateau"

In their study, the authors compared the bacterial diversity sampled by two independent companies from snow and ice at Concordia Station in Antarctica in 2015–16 and 2018–19. The aim of this work was to assess the stochastic and deterministic driving forces that influence the formation of microbiomes in extreme habitats.

After a careful reading and judgment, I recommend that the manuscript be carefully revised and then resubmitted. The comments below are intended to help the authors revise their manuscript.

 Major comments

1. Although the authors indicated that the selection took place at varying distances from the station, they did not provide further detail in the description of the results and discussion. Without such a description of the results, it is incorrect to talk about the influence of the people living at the research station. The authors used annual averages for comparison, but they also need to categorise these according to the level of anthropogenic influence. In order to determine which season is more important for interannual differences in communities, it would be better to identify interannual seasonal differences. The latter relates to the publication in reference 8. The authors should also take the wind direction and speed during the sampling periods into account.
2. Several articles have already been published on the impact of different methods of extracting DNA from natural samples, including comparisons of various kits. It has been demonstrated that all of the above factors affect the outcome of microbiome analysis. Napoli et al. and Stoppiello et al. employed distinct protocols for DNA extraction. Therefore, the authors' statements that '... microbial diversity on Concordia is a result of stochastic atmospheric deposition...' and 'bacterial communities in surface snow at Concordia Station exhibit high interannual variability and lack temporal stability' are questionable.

Minor comments

1. Section 2.2. – The region of the 16S rRNA gene used for identification should be specified.
2. The tables should be numbered in the supplementary materials. In other words, each sheet should have its own number.

Author Response

Major comments: 

Comments 1:  Although the authors indicated that the selection took place at varying distances from the station, they did not provide further detail in the description of the results and discussion. Without such a description of the results, it is incorrect to talk about the influence of the people living at the research station. The authors used annual averages for comparison, but they also need to categorise these according to the level of anthropogenic influence. In order to determine which season is more important for interannual differences in communities, it would be better to identify interannual seasonal differences. The latter relates to the publication in reference 8. The authors should also take the wind direction and speed during the sampling periods into account.

Responces 1: We agree with the reviewer that the influence of distance from the station and potential anthropogenic effects require careful treatment. In the revised manuscript, we clarify that the present study was not designed to statistically resolve spatial gradients or quantify anthropogenic impacts at different distances, as this aspect has already been addressed in detail in Stoppiello et al. (2023). In the present work, samples from different distances were aggregated by year to focus specifically on interannual variability between two independent sampling campaigns. We have revised the discussion to explicitly state that any reference to anthropogenic influence is speculative and qualitative, and we no longer imply a direct or measurable human effect based on the current dataset. Instead, human presence is discussed as a potential episodic source of microbial input, without attributing a deterministic role to it in the formation of community structure.

Comments 2: Several articles have already been published on the impact of different methods of extracting DNA from natural samples, including comparisons of various kits. It has been demonstrated that all of the above factors affect the outcome of microbiome analysis. Napoli et al. and Stoppiello et al. employed distinct protocols for DNA extraction. Therefore, the authors' statements that '... microbial diversity on Concordia is a result of stochastic atmospheric deposition...' and 'bacterial communities in surface snow at Concordia Station exhibit high interannual variability and lack temporal stability' are questionable. We acknowledge this limitation and have revised the manuscript to clarify that seasonal dynamics were not explicitly addressed in this study. Although seasonal effects were examined in Stoppiello et al. (2023), the two datasets analysed here differ in temporal coverage and sampling resolution, preventing a statistically balanced seasonal comparison between years. We now explicitly state that aggregating samples by year may mask seasonal variability and that our conclusions are therefore limited to interannual differences. We emphasise that future studies specifically designed to sample identical seasons over multiple years will be necessary to distinguish seasonal from interannual factors of microbial variability at the Concordia station. We agree that atmospheric circulation data would greatly strengthen interpretations regarding microbial inputs. However, such data were not available in a form that could be directly linked to individual samples or sampling periods in either campaign. We have therefore revised the discussion to clearly acknowledge this limitation and frame atmospheric transport as a plausible but not directly demonstrated contributor to the observed interannual variability. We also emphasise that future complementary studies combining microbiological sampling with meteorological and air mass trajectory analyses will be essential to validate this hypothesis. 

Responces 2: We thank the reviewer for highlighting this important methodological point. In the revised manuscript, we explicitly acknowledge that the two datasets were generated using different DNA extraction protocols, which may contribute to differences in the observed community composition. However, both studies employed validated protocols optimised for low-biomass polar samples, and thorough contaminant screening was applied using the same bioinformatic criteria. Furthermore, sequencing data from both campaigns were rarefied to the same minimum library size prior to downstream analyses in order to minimise biases related to differences in sequencing depth and ensure comparability between datasets. Although rarefaction cannot completely compensate for methodological differences in DNA extraction, it reduces the potential influence of uneven sequencing effort on diversity estimates. We have therefore revised the text to avoid attributing interannual differences solely to ecological processes and now explicitly state that methodological differences cannot be ruled out as a contributing factor. Consequently, our conclusions have been reworded to emphasise the observed interannual variability rather than a definitive ecological cause.

Minor comments: 

Comments 1: Section 2.2. – The region of the 16S rRNA gene used for identification should be specified.

Responces 1: We thank the Reviewer for noting this omission. The targeted hypervariable region of the 16S rRNA gene has now been explicitly specified in the section.

Comments 2: The tables should be numbered in the supplementary materials. In other words, each sheet should have its own number.

Responces 2: This has been corrected.