Utilizing a Metagenome Assembled Genome Approach Revealed Further Insights into Microbially Mediated Heavy-Metal Resistance in Soils from a Former Nuclear Materials Production Facility

Round 1

Reviewer 1 Report

This works mainly utilized metagenome method to decipher the microbial community in the soils which suffers co-contamination with radionuclides and heavy metals. Although manuscript is well written, further improvement is necessary. Specific comments are shown as follows.

1. Line 23, “annotatated” should be “annotated”.

2. Table 1 should be arranged in supplementary information.

3. The correlation between species should be discussed in this paper, the microbial community may cooperate in microbially mediated remediation process, this following paper may be helpful (DOI: 10.1016/j.jes.2023.08.008)

4. The soil parameters (such as heavy metal concentration, radiation level etc.) should be mentioned in this study, the authors just classified general ranks (high, medium, and low).

Author Response

Reviewer #1:

This works mainly utilized metagenome method to decipher the microbial community in the soils which suffers co-contamination with radionuclides and heavy metals. Although manuscript is well written, further improvement is necessary. Specific comments are shown as follows.

Line 23, “annotatated” should be “annotated”.

Author’s Response: This mistake has been corrected in the manuscript.

Table 1 should be arranged in supplementary information.

Author’s Response: The correlation between species should be discussed in this paper, the microbial community may cooperate in microbially mediated remediation process, this following paper may be helpful (DOI: 10.1016/j.jes.2023.08.008)

Author’s Response:

In our previous report on samples from the SRS (12: Pathak et al., 2020), we conducted a Canonical Correlation Analysis (CCA) to evaluate the correlation among the effects of various environmental, biogeochemical, and microbial diversity. The result of the CCA analysis showed some correlation among the bacterial and fungal species.

The soil parameters (such as heavy metal concentration, radiation level etc.) should be mentioned in this study, the authors just classified general ranks (high, medium, and low).

Author’s Response: We have previously reported the heavy metal concentrations in the studied soils (refs). These studies focused on the SRS Steeds Pond- Tims Branch riparian stream system- the same site from where metagenomes were obtained for this study. In our original submission, we referred to our previous study (12; Pathak, A.; Jaswal, R.; Xu, X.; White, J.R.; Edwards, B.; Hunt, J.; Brooks, S.; Rathore, R.S.; Agarwal, M.; Chauhan, A. Charac-terization of Bacterial and Fungal Assemblages from Historically Contaminated Metalliferous Soils Using Metagenomics Coupled with Diffusion Chambers and Microbial Traps. Front Microbiol. 2020, 11,1024. https://doi.org/10.3389/fmicb.2020.01024). But for brevity, an additional reference from our previous study has now been included (https://www.mdpi.com/2076-2607/7/9/324), indicating that the soil biogeochemical and metal analyses resulted in the binning of locations under the following levels of contamination: high (B), medium (S1), and low (S3, H-02), respectively.

Reviewer 2 Report

The manuscript entitled Metagenome Assembled Genomes (MAG) Facilitate a better Understanding of Microbially-mediated Heavy Metal Resistance in Soils from a Former Nuclear Materials Production Facility is well written and compiled article that has dealt with investigation of bacterial diversity in Savannah River Site soils with a history of uranium and heavy metal contamination. The authors have used Shotgun metagenomes to produce MAGs and several robust genomes, predominantly from Proteobacteria and Bacteroidetes involved in crucial element metabolism and resistance to various heavy metals, providing insights into metal resistance in uranium-contaminated soils.

There are a few queries should be addressed by the author and specific attributes must be considered in method section:

·         Why were both SPAdes and MEGAHIT used for assembly? Was there a specific reason for choosing these assemblers, and were their outputs systematically compared and evaluated?

·         What parameters were used for assembly, and were they optimized for soil metagenomic data?

·         What specific metrics from QUAST were used to evaluate the assembled sequences, and what thresholds were considered acceptable for further analysis?

·         Did you encounter any instances where the quality assessment conflicted with the binning results?

·         Conclusion is missing.

Minor editing of English language required

Author Response

Reviewer #2:

Comments and Suggestions for Authors

The manuscript entitled Metagenome Assembled Genomes (MAG) Facilitate a better Understanding of Microbially-mediated Heavy Metal Resistance in Soils from a Former Nuclear Materials Production Facility is well written and compiled article that has dealt with investigation of bacterial diversity in Savannah River Site soils with a history of uranium and heavy metal contamination. The authors have used Shotgun metagenomes to produce MAGs and several robust genomes, predominantly from Proteobacteria and Bacteroidetes involved in crucial element metabolism and resistance to various heavy metals, providing insights into metal resistance in uranium-contaminated soils.

There are a few queries should be addressed by the author and specific attributes must be considered in method section:

Why were both SPAdes and MEGAHIT used for assembly? Was there a specific reason for choosing these assemblers, and were their outputs systematically compared and evaluated?

Author’s Response:

We apologize for the confusion, although the nf-core/mag pipeline does support both SPAdes and MEGAHIT, we only used MEGAHIT for the soil metagenome data. We have updated the methods section to reflect this. We chose MEGAHIT because it is faster and uses less memory than SPAdes. Thus we did not systematically compare the outputs of the two assemblers. A previous study has shown that MEGAHIT produces assemblies comparable to SPAdes but using a fraction of the computation resources (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5502489/).

What parameters were used for assembly, and were they optimized for soil metagenomic data?

Author’s Response:

We used the default assembly settings for MEGAHIT version 1.2.9. We did not evaluate different MEGAHIT settings.

MEGAHIT was run via version 2.3.2 of the nf-core/mag pipeline. A custom configuration file was used to specify that 12 cpus, 200 GB of memory, and 300 hours of time should be used for the assembly step.

We also used the `--coassemble_group` to assemble all reads from a given sample type (e.g. soild from summer with low U contamination), to handle cases where the same sample type was characterized by multiple read sets.

What specific metrics from QUAST were used to evaluate the assembled sequences, and what thresholds were considered acceptable for further analysis?

Author’s Response: QUAST metrics were used to determine contig number and size for each assembly, and total assembly size. We did not use any thresholds for further analysis but instead used dRep to provide metrics for completion and contamination. Specifically, a minimum completeness of 75% and a maximum contamination of 25% were used to select the dereplicated genomes for further analysis.

Did you encounter any instances where the quality assessment conflicted with the binning results?

Author’s Response: Yes, from the quality metrics from dRep we do see several cases where the binning likely led to the creation of bins with high levels of contamination. For this reason, we applied a minimum completeness of 75% and a maximum contamination of 25% to select the dereplicated genomes for further analysis.

Conclusion is missing.

Author’s Response: The conclusion section has been added in the manuscript.