Comments to the authors:x000Dx000D The manuscript describes a study assaying a mock bacterial community or a single isolate using 16S rRNA genes and the Oxford Nanopore MinION. The authors employ a complicated library preparation method generating concatamers of the 16S amplicons (1400 bp) and a novel data analysis pipeline to build a consensus. The method involves amplification with universal primers, circularization by ligating amplicon concatemers, removal of linear molecules, rolling circle amplification, debranching, shearing with g-tubes, library preparation, and data analysis. The NanoAmpli-Seq pipeline involved primer identification using INC-Seq, re-orientation and removal of repeats using chopSeq, and OTU binning and consensus building using nanoClust. The authors report 99.5% sequence accuracy with 50X coverage using 1D2 chemistry with very low numbers of high quality reads (line 200; Fig. 7). The older 2D chemistry provided more high quality reads but the accuracy ranged from 98.8-99.4% identity. The authors conclude that "30X coverage [10 reads with 3 concatamers] allowed for sequence accuracy consistently greater that 99%" (line 347-348). However, they also state, "data loss [using the 1D2 chemistry] is significant and could deter the widespread use of the nano pore platform" (line 364-365). They also assert the Nano-AmpliSeq workflow is a great improvement over INC-Seq and can provide consensus sequence data with ~99% accuracy. x000Dx000D Unfortunately, the authors do not really present a case that all the convoluted manipulation of PCR product and data analysis is necessary. It would be helpful for them to just analyze their pool of amplicons (Fig 1A). Oxford now produces a sequencing kit for characterizing 16S amplicons directly. Many others have directly sequenced 16S amplicons or rRNA operons. Some, such as Benitez-Paez 2017 (doi: 10.1093/gigascience/gix043) and Kerkhof (DOI 10.1186/s40168-017-0336-9) have used the MinION reads to build a consensus with the older R7 chemistry. Finally, the authors also could put their findings into context with other papers in the literature using MinION and rRNA genes. For example, Jain et al 2016 (DOI 10.1186/s13059-016-1103-0) has an overview of improvements using the R9 chemistries, Shin et al 2016 (DOI: 10.1038/srep29681) used MinION to analyze the mouse gut microbiome, and Mitsuhashi et al 2017 (DOI:10.1038/s41598-017-05772-5) analyzed mock communities and clinical samples. It is also worth noting that Shin, Mitsuhashi, and Kerkhof have gone beyond simple mock communities of 1-20 bacteria and analyzed complex samples from the gut, the lung, soils, and bioreactors using MinION. To conclude, it would be very beneficial for the authors to show that their concatamer/RCA scheme was not the source of the sequence problems they encountered. i.e. incorrect primer orientation, tandem repeats, etc.x000Dx000D Other Specific Comments:x000Dx000D Much of the language in the methods section can be truncated. For example, Lines 407-419, the magnetic bead purification purification procedure could probably be truncated to "according to the manufacturer's instructions" unless the authors have made significant changes.

Are the methods appropriate to the aims of the study, are they well described, and are necessary controls included? If not, please specify what is required in your comments to the authors.
No

Are the conclusions adequately supported by the data shown? If not, please explain in your comments to the authors. No

Does the manuscript adhere to the journal’s guidelines on minimum standards of reporting? If not, please specify what is required in your comments to the author
Yes

Are you able to assess all statistics in the manuscript, including the appropriateness of statistical tests used? (If an additional statistical review is recommended, please specify what aspects require further assessment in your comments to the editors.)
No, I do not feel adequately qualified to assess the statistics.

Quality of written English Please indicate the quality of language in the manuscript: Acceptable

Declaration of competing interests Please complete a declaration of competing interests, considering the following questions: Have you in the past five years received reimbursements, fees, funding, or salary from an organisation that may in any way gain or lose financially from the publication of this manuscript, either now or in the future? Do you hold any stocks or shares in an organisation that may in any way gain or lose financially from the publication of this manuscript, either now or in the future? Do you hold or are you currently applying for any patents relating to the content of the manuscript? Have you received reimbursements, fees, funding, or salary from an organization that holds or has applied for patents relating to the content of the manuscript? Do you have any other financial competing interests? Do you have any non-financial competing interests in relation to this paper? If you can answer no to all of the above, write 'I declare that I have no competing interests' below. If your reply is yes to any, please give details below.
I declare that I have no competing interests

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I agree to the open peer review policy of the journal.

Authors' response to reviews: (https://drive.google.com/open?id=1qbRLqjg7MD2C6N9GwfQU64fM4JPxEuMN)

The revised manuscript has incorporated many of the suggested editorial comments by the reviewers and is greatly improved. However, there is one fundamental question in their data presentation that would be helpful to address if their methods are to be used for natural samples. Specifically, the NanoAmpli-Seq data analysis pipeline removes self-ligated circles containing different copies of the 16S rRNA genes (<97% similarity; line 176-177). It is unclear how many such "chimeric" circular molecules would be created using a natural sample containing thousands of different microbes or more. There is some sense of sequencing template loss that can be gleaned from Table 1. It would seem these chimeric circles can account for up to 25-58% of the raw reads. But, other factors during analysis (unmappable anchors or short reads) can also account for this loss. It would be good for the authors to provide a sense of the abundance of these "chimeric" circles. For a natural sample, the "chimeric" molecules may account for a much higher percentage of the self-ligated molecules compared with a 10-member system. If the self ligation step for a natural sample yields a significantly large percentages of circular molecules with more than one 16S rRNA gene, then the utility of a NanoAmpli-Seq approach to characterize natural samples (line 139) is brought into question.

Perhaps the authors could also investigate a subset of the "discarded chimeric" reads to see if they may be ultimately brought back into their NanoAmpli-Seq analysis pipeline to alleviate this data loss. This may improve accuracy by providing additional reads for consensus building and make the method more useful for natural samples.

Ultimately, I agree that a method to develop highly accurate sequences de nova from amplicons (such as 16S rRNA genes) without the need for screening against a database would be desirable. However, just because a microorganism's 16S rRNA gene is not well represented in a database does not mean the read is completely ignored (line 101). Virtually all microbiome studies continue to find sequences not well represented in our databases. These novel sequences ultimately become included in databases when enough highly similar reads are discovered and annotated.

Other Specific Comments:

Line 101. It would be more accurate to state that reads not well represented are difficult to unambiguously assign to a single OTU and could lead to clustering errors when widely different 16S rRNA genes hit the same entry in the database at roughly the same similarity.

2). Line 359. Shouldn't that read "As the number of partitions decreased"? As written, the sentence seems to contradict lines 354-356.

3). Line 380-382. The connection from deletions/insertions to the results in Figure 8 are not clear.

4). Line 502. 30x coverage is also consistent with rRNA operon sequencing [ref 20].

Declaration of competing interests Please complete a declaration of competing interests, considering the following questions: Have you in the past five years received reimbursements, fees, funding, or salary from an organisation that may in any way gain or lose financially from the publication of this manuscript, either now or in the future? Do you hold any stocks or shares in an organisation that may in any way gain or lose financially from the publication of this manuscript, either now or in the future? Do you hold or are you currently applying for any patents relating to the content of the manuscript? Have you received reimbursements, fees, funding, or salary from an organization that holds or has applied for patents relating to the content of the manuscript? Do you have any other financial competing interests? Do you have any non-financial competing interests in relation to this paper? If you can answer no to all of the above, write 'I declare that I have no competing interests' below. If your reply is yes to any, please give details below.
I declare that I have no competing interests

I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. I agree for my report to be made available under an Open Access Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.
I agree to the open peer review policy of the journal.

Authors' response to reviews: (https://drive.google.com/open?id=1cyOyQUNCYIJqEF0EHkfZFYKwVukZ4JXB)