Supplementary Table 2

Table 6

Table 7

Table 8

Table 9

Author response:
<blockquote>
Reviewer #1 (Public review):
The microbiota of Dactylorhiza traunsteineri, an endangered marsh orchid, forms complex root associations that support plant health. Using 16S rRNA sequencing, we identified dominant bacterial phyla in its rhizosphere, including Proteobacteria, Actinobacteria, and Bacteroidota. Deep shotgun metagenomics revealed high-quality MAGs with rich metabolic and biosynthetic potential. This study provides key insights into root-associated bacteria and highlights the rhizosphere as a promising source of bioactive compounds, supporting both microbial ecology research and orchid conservation.
The manuscript presents an investigation of the bacterial communities in the rhizosphere of D. traunsteineri using advanced metagenomic approaches. The topic is relevant, and the techniques are up-to-date; however, the study has several critical weaknesses.
</blockquote>
We thank the reviewer for their careful reading of our manuscript and for the constructive comments. We will revise the manuscript substantially. Our responses to the specific points are below:
<blockquote>
(1) Title: The current title is misleading. Given that fungi are the primary symbionts in orchids and were not analyzed in this study (nor were they included among other microbial groups), the use of the term "microbiome" is not appropriate. I recommend replacing it with "bacteriome" to better reflect the scope of the work.
</blockquote>
In the revised manuscript, we will expand the Results (shotgun sequencing) and Discussion to also include fungal taxa. With these additions, the use of the term microbiome will accurately reflect the inclusion of both bacterial and fungal components.
<blockquote>
(2) Line 124: The phrase "D. traunsteineri individuals were isolated" seems misleading. A more accurate description would be "individuals were collected", as also mentioned in line 128.
</blockquote>
This ambiguity will be corrected in the revised manuscript.
<blockquote>
(3) Experimental design: The major limitation of this study lies in its experimental design. The number of plant individuals and soil samples analyzed is unclear, making it difficult to assess the statistical robustness of the findings. It is also not well explained why the orchids were collected two years before the rhizosphere soil samples. Was the rhizosphere soil collected from the same site and from remnants of the previously sampled individuals in 2018? This temporal gap raises serious concerns about the validity of the biological associations being inferred.
</blockquote>
In the revised manuscript, we will explicitly state the number of individuals and soil samples included in the study, and we will more clearly describe the sequence of sampling events. We will also add a dedicated statement in the Discussion addressing the temporal gap between plant sampling and rhizosphere soil collection, acknowledging that this is a limitation of the study.
<blockquote>
(4) Low sample size: In lines 249-251 (Results section), the authors mention that only one plant individual was used for identifying rhizosphere bacteria. This is insufficient to produce scientifically robust or generalizable conclusions.
</blockquote>
In the revised manuscript, we will clearly state that only one rhizosphere sample was available and will frame the study as exploratory in nature. We will explicitly acknowledge this limitation in both the Methods and Discussion, and we will temper our conclusions accordingly.
<blockquote>
(5) Contextual limitations: Numerous studies have shown that plant-microbe interactions are influenced by external biotic and abiotic factors, as well as by plant age and population structure. These elements are not discussed or controlled for in the manuscript. Furthermore, the ecological and environmental conditions of the site where the plants and soil were collected are poorly described. The number of biological and technical replicates is also not clearly stated.
</blockquote>
In the revised manuscript, we will expand the description of the collection site and environmental conditions to the extent supported by our records. We will also clearly state the number of biological and technical replicates used for each analysis. In the Discussion, we will explicitly acknowledge that plant age, environmental variables, and other biotic/abiotic factors may influence plant–microbe interactions and were not directly assessed in this study.
<blockquote>
(6) Terminology: Throughout the manuscript, the authors refer to the "microbiome," though only bacterial communities were analyzed. This terminology is inaccurate and should be corrected consistently.
</blockquote>
As noted in our response to point (1), we will revise terminology throughout the manuscript to ensure consistency and to accurately reflect the expanded bacterial and fungal coverage in the revised version.
<blockquote>
Reviewer #2 (Public review):
The authors aim to provide an overview of the D. traunsteineri rhizosphere microbiome on a taxonomic and functional level, through 16S rRNA amplicon analysis and shotgun metagenome analysis. The amplicon sequencing shows that the major phyla present in the microbiome belong to phyla with members previously found to be enriched in rhizospheres and bulk soils. Their shotgun metagenome analysis focused on producing metagenome assembled genomes (MAGs), of which one satisfies the MIMAG quality criteria for high-quality MAGs and three those for medium-quality MAGs. These MAGs were subjected to functional annotations focusing on metabolic pathway enrichment and secondary metabolic pathway biosynthetic gene cluster analysis. They find 1741 BGCs of various categories in the MAGs that were analyzed, with the high-quality MAG being claimed to contain 181 SM BGCs. The authors provide a useful, albeit superficial, overview of the taxonomic composition of the microbiome, and their dataset can be used for further analysis.
The conclusions of this paper are not well-supported by the data, as the paper only superficially discusses the results, and the functional interpretation based on taxonomic evidence or generic functional annotations does not allow drawing any conclusions on the functional roles of the orchid microbiota.
</blockquote>
We thank the reviewer for their thoughtful and constructive assessment of our manuscript. The comments have been very helpful in identifying areas where the clarity, structure, and interpretation of our work can be improved. Our responses to the specific points are below:
<blockquote>
(1) The authors only used one individual plant to take samples. This makes it hard to generalize about the natural orchid microbiome.
</blockquote>
We agree with the reviewer that the limited number of plant individuals restricts the generality of the conclusions. In the revised manuscript, we will clearly state that only one rhizosphere sample was available for analysis and will frame the study as exploratory. We will also explicitly acknowledge this limitation in the Discussion and ensure that our interpretations and conclusions remain appropriately cautious.
<blockquote>
(2) The authors use both 16S amplicon sequencing and shotgun metagenomics to analyse the microbiome. However, the authors barely discuss the similarities and differences between the results of these two methods, even though comparing these results may be able to provide further insights into the conclusions of the authors. For example, the relative abundance of the ASVs from the amplicon analysis is not linked to the relative abundances of the MAGs.
</blockquote>
In the revised manuscript, we will expand the Results and Discussion to include a clearer comparison between the taxonomic profiles derived from 16S amplicon sequencing and those obtained from shotgun metagenomic binning.
<blockquote>
(3) Furthermore, the authors discuss that phyla present in the orchid microbiome are also found in other microbiomes and are linked to important ecological functions. However, their results reach further than the phylum level, and a discussion of genera or even species is lacking. The phyla that were found have very large within-phylum functional variability, and reliable functional conclusions cannot be drawn based on taxonomic assignment at this level, or even the genus level (Yan et al. 2017).
</blockquote>
In the revised manuscript, we will incorporate taxonomic discussion at finer resolution where reliable assignments are available. We will also revise the Discussion to avoid overinterpreting phylum-level taxonomy in terms of ecological function.
<blockquote>
(4) Additionally, although the authors mention their techniques used, their method section is sometimes not clear about how samples or replicates were defined. There are also inconsistencies between the methods and the results section, for example, regarding the prediction of secondary metabolite biosynthetic gene clusters (BGCs).
</blockquote>
In the revised Methods section, we will clearly define the number and type of samples included in each analysis, specify the number of replicates and how they were handled, and provide a clearer description of the biosynthetic gene cluster (BGC) prediction workflow, including the tools used and how results were interpreted.
<blockquote>
(5) The BGC prediction was done with several tools, and the unusually high number of found BGCs (181 in their high-quality MAG) is likely due to false positives or fragmented BGCs. The numbers are much higher than any numbers ever reported in literature supported by functional evidence (Amos et al, 2017), even in a prolific genus like Streptomyces (Belknap et al., 2020). This caveat is not discussed by the authors.
</blockquote>
We thank the reviewer for this important point. Our original intention was to present the BGC predictions as a resource for future exploration, which is why multiple tools were used. However, we understand how this approach may lead to confusion, particularly regarding the confidence level of the predicted clusters and the potential inflation of counts due to assembly fragmentation or tool sensitivity. In the revised manuscript, we will thoroughly revise this section to clearly distinguish highconfidence predictions from more exploratory findings. We will focus on results supported by stronger evidence, explicitly qualify lower-confidence predictions as putative, and temper any functional interpretations accordingly.
<blockquote>
(6) The authors have generated one high-quality MAG and three medium-quality MAGs. In the discussion, they present all four of these as high-quality, which could be misleading. The authors discuss what was found in the literature about the role of the bacterial genera/phyla linked to these MAGs in plant rhizospheres, but they do not sufficiently link their own analysis results (metabolic pathway enrichment and biosynthetic gene cluster prediction) to this discussion. The results of these analyses are only presented in tables without further explanation in either the results section or the discussion, even though there may be interesting findings. For example, the authors only discuss the class of the BGCs that were found, but don't search for experimentally verified homologs in databases, which could shed more light on the possible functional roles of BGCs in this microbiome.
</blockquote>
In the revised manuscript, we will ensure that MAG quality is described accurately and consistently throughout, distinguishing clearly between high-quality and medium-quality bins according to accepted standards.
<blockquote>
(7) In the conclusions, the authors state: "These analyses uncovered potential metabolic capabilities and biosynthetic potentials that are integral to the rhizosphere's ecological dynamics." I don't see any support for this. Mentioning that certain classes of BGCs are present is not enough to make this claim, in my opinion. Any BGC is likely important for the ecological niche the bacteria live in. The fact that rhizosphere bacteria harbour BGCs is not surprising, and it doesn't tell us more than is already known.
</blockquote>
In the revised manuscript, we will rewrite the conclusion to reflect a more cautious interpretation, focusing on the potential metabolic and biosynthetic capabilities suggested by the data without asserting ecological roles that cannot be directly supported. These capabilities will be presented as hypotheses for future investigation rather than established ecological features.

Bavesh Kana

eLife Assessment
This study presents a useful overview of the taxonomic composition of the microbiome associated with Dactylorhiza traunsteineri, a widely distributed orchid species in Central Europe. The evidence supporting the claims of the authors is incomplete, especially when it comes to the (secondary) metabolic pathways found in the metagenome assembled genomes, and requires more substantial analysis to be able to claim that these pathways play a key role in microbiome-orchid symbiosis.

anonymous

Reviewer #1 (Public review):
Summary:
The microbiota of Dactylorhiza traunsteineri, an endangered marsh orchid, forms complex root associations that support plant health. Using 16S rRNA sequencing, we identified dominant bacterial phyla in its rhizosphere, including Proteobacteria, Actinobacteria, and Bacteroidota. Deep shotgun metagenomics revealed high-quality MAGs with rich metabolic and biosynthetic potential. This study provides key insights into root-associated bacteria and highlights the rhizosphere as a promising source of bioactive compounds, supporting both microbial ecology research and orchid conservation.
Strengths:
The manuscript presents an investigation of the bacterial communities in the rhizosphere of D. traunsteineri using advanced metagenomic approaches. The topic is relevant, and the techniques are up-to-date; however, the study has several critical weaknesses.
Weaknesses:
(1) Title: The current title is misleading. Given that fungi are the primary symbionts in orchids and were not analyzed in this study (nor were they included among other microbial groups), the use of the term "microbiome" is not appropriate. I recommend replacing it with "bacteriome" to better reflect the scope of the work.
(2) Line 124: The phrase "D. traunsteineri individuals were isolated" seems misleading. A more accurate description would be "individuals were collected", as also mentioned in line 128.
(3) Experimental design: The major limitation of this study lies in its experimental design. The number of plant individuals and soil samples analyzed is unclear, making it difficult to assess the statistical robustness of the findings. It is also not well explained why the orchids were collected two years before the rhizosphere soil samples. Was the rhizosphere soil collected from the same site and from remnants of the previously sampled individuals in 2018? This temporal gap raises serious concerns about the validity of the biological associations being inferred.
(4) Low sample size: In lines 249-251 (Results section), the authors mention that only one plant individual was used for identifying rhizosphere bacteria. This is insufficient to produce scientifically robust or generalizable conclusions.
(5) Contextual limitations: Numerous studies have shown that plant-microbe interactions are influenced by external biotic and abiotic factors, as well as by plant age and population structure. These elements are not discussed or controlled for in the manuscript. Furthermore, the ecological and environmental conditions of the site where the plants and soil were collected are poorly described. The number of biological and technical replicates is also not clearly stated.
(6) Terminology: Throughout the manuscript, the authors refer to the "microbiome," though only bacterial communities were analyzed. This terminology is inaccurate and should be corrected consistently.
Considering the issues addressed, particularly regarding experimental design and data interpretation, significant improvements to the study are needed.

Reviewer #2 (Public review):
Summary:
The authors aim to provide an overview of the D. traunsteineri rhizosphere microbiome on a taxonomic and functional level, through 16S rRNA amplicon analysis and shotgun metagenome analysis. The amplicon sequencing shows that the major phyla present in the microbiome belong to phyla with members previously found to be enriched in rhizospheres and bulk soils. Their shotgun metagenome analysis focused on producing metagenome assembled genomes (MAGs), of which one satisfies the MIMAG quality criteria for high-quality MAGs and three those for medium-quality MAGs. These MAGs were subjected to functional annotations focusing on metabolic pathway enrichment and secondary metabolic pathway biosynthetic gene cluster analysis. They find 1741 BGCs of various categories in the MAGs that were analyzed, with the high-quality MAG being claimed to contain 181 SM BGCs. The authors provide a useful, albeit superficial, overview of the taxonomic composition of the microbiome, and their dataset can be used for further analysis.
The conclusions of this paper are not well-supported by the data, as the paper only superficially discusses the results, and the functional interpretation based on taxonomic evidence or generic functional annotations does not allow drawing any conclusions on the functional roles of the orchid microbiota.
Weaknesses:
The authors only used one individual plant to take samples. This makes it hard to generalize about the natural orchid microbiome.
The authors use both 16S amplicon sequencing and shotgun metagenomics to analyse the microbiome. However, the authors barely discuss the similarities and differences between the results of these two methods, even though comparing these results may be able to provide further insights into the conclusions of the authors. For example, the relative abundance of the ASVs from the amplicon analysis is not linked to the relative abundances of the MAGs.
Furthermore, the authors discuss that phyla present in the orchid microbiome are also found in other microbiomes and are linked to important ecological functions. However, their results reach further than the phylum level, and a discussion of genera or even species is lacking. The phyla that were found have very large within-phylum functional variability, and reliable functional conclusions cannot be drawn based on taxonomic assignment at this level, or even the genus level (Yan et al. 2017).
Additionally, although the authors mention their techniques used, their method section is sometimes not clear about how samples or replicates were defined. There are also inconsistencies between the methods and the results section, for example, regarding the prediction of secondary metabolite biosynthetic gene clusters (BGCs).
The BGC prediction was done with several tools, and the unusually high number of found BGCs (181 in their high-quality MAG) is likely due to false positives or fragmented BGCs. The numbers are much higher than any numbers ever reported in literature supported by functional evidence (Amos et al, 2017), even in a prolific genus like Streptomyces (Belknap et al., 2020). This caveat is not discussed by the authors.
The authors have generated one high-quality MAG and three medium-quality MAGs. In the discussion, they present all four of these as high-quality, which could be misleading. The authors discuss what was found in the literature about the role of the bacterial genera/phyla linked to these MAGs in plant rhizospheres, but they do not sufficiently link their own analysis results (metabolic pathway enrichment and biosynthetic gene cluster prediction) to this discussion. The results of these analyses are only presented in tables without further explanation in either the results section or the discussion, even though there may be interesting findings. For example, the authors only discuss the class of the BGCs that were found, but don't search for experimentally verified homologs in databases, which could shed more light on the possible functional roles of BGCs in this microbiome.
In the conclusions, the authors state: "These analyses uncovered potential metabolic capabilities and biosynthetic potentials that are integral to the rhizosphere's ecological dynamics." I don't see any support for this. Mentioning that certain classes of BGCs are present is not enough to make this claim, in my opinion. Any BGC is likely important for the ecological niche the bacteria live in. The fact that rhizosphere bacteria harbour BGCs is not surprising, and it doesn't tell us more than is already known.
References:
Belknap, Kaitlyn C., et al. "Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria." Scientific reports 10.1 (2020): 2003
Amos GCA, Awakawa T, Tuttle RN, Letzel AC, Kim MC, Kudo Y, Fenical W, Moore BS, Jensen PR. Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci U S A. 2017 Dec 26;114(52):E11121-E11130.
References:
Belknap, Kaitlyn C., et al. "Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria." Scientific reports 10.1 (2020): 2003
Amos GCA, Awakawa T, Tuttle RN, Letzel AC, Kim MC, Kudo Y, Fenical W, Moore BS, Jensen PR. Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci U S A. 2017 Dec 26;114(52):E11121-E11130.
Yan Yan, Eiko E Kuramae, Mattias de Hollander, Peter G L Klinkhamer, Johannes A van Veen, Functional traits dominate the diversity-related selection of bacterial communities in the rhizosphere, The ISME Journal, Volume 11, Issue 1, January 2017, Pages 56-66

Dark matter of an orchid: metagenome of the microbiome associated with the rhizosphere of Dactylorhiza traunsteineri

Figures and data

Sequencing statistics (16S profiling)

Dactylorhiza traunsteineri sampling.

Bacterial Community Composition Analysis based on 16S rDNA sequencing.

ASVs abundance (by Phylum) (%)

Sequencing statistics (Shotgun sequencing)

Metagenomic assembly statistics

Barnes-Hut t-SNE representation of MAG contigs.

Metagenomic binning statistics

Overview of number of predicted SM BGCs per MAG and their product classes.

ANI of MAGs and reference organisms.

Genomes used for comparative analysis

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