The effect of storage conditions on microbial communities in stool.

Microbiome research has experienced a surge of interest in recent years due to the advances and reduced cost of next-generation sequencing technology. The production of high quality and comparable data is dependent on proper sample collection and storage and should be standardized as far as possible. However, this becomes challenging when samples are collected in the field, especially in resource-limited settings. We investigated the impact of different stool storage methods common to the TB-CHAMP clinical trial on the microbial communities in stool. Ten stool samples were subjected to DNA extraction after 48-hour storage at -80°C, room temperature and in a cooler-box, as well as immediate DNA extraction. Three stool DNA extraction kits were evaluated based on DNA yield and quality. Quantitative PCR was performed to determine the relative abundance of the two major gut phyla Bacteroidetes and Firmicutes, and other representative microbial groups. The bacterial populations in the frozen group closely resembled the immediate extraction group, supporting previous findings that storage at -80°C is equivalent to the gold standard of immediate DNA extraction. More variation was seen in the room temperature and cooler-box groups, which may be due to the growth temperature preferences of certain bacterial populations. However, for most bacterial populations, no significant differences were found between the storage groups. As seen in other microbiome studies, the variation between participant samples was greater than that related to differences in storage. We determined that the risk of introducing bias to microbial community profiling through differences in storage will likely be minimal in our setting.

Introduction

The collection, transport and storage of stool samples are major challenges faced by gut microbiome researchers in resource-limited settings. Immediate freezing of stool samples at -80°C preserves the microbiome composition when compared to the true gold standard of immediate DNA extraction [1-4]. However, cold-chain storage and the addition of DNA-stabilizing agents are not always feasible when samples are collected in the field. Furthermore, thawing of samples during transport may significantly reduce DNA integrity thereby influencing the accuracy of downstream microbiome analysis [2,5].

In our study setting, stool samples collected as part of the TB-CHAMP clinical trial (https://doi.org/10.1186/ISRCTN92634082) will be used for both microbiome analysis and culture-based analysis. Given the limited resources, it is not feasible to split the stool samples for the two approaches. This makes the addition of most DNA stabilizing agents impossible, due to their bactericidal effect. The samples should ideally be collected and delivered to the laboratory within 24 hours; however, some samples may also be collected from participants’ homes, where there may not be access to a freezer. Therefore, the samples may be subjected to longer periods in a cooler box on ice or even at room temperature. Several studies have aimed to assess the effect of temperature and time on microbial communities in stool; however, the methods were variable and the results (unsurprisingly) were conflicting [1,3,5-9]. The uniqueness of microbiota composition and influencing factors in different settings, along with lack of standardization of study procedures emphasize the need to determine the possible biases introduced by storage and transport methods in all microbiome studies.

For these reasons, we investigated how different storage methods common to this study may affect the microbial communities in stool. Immediate DNA extraction (the gold standard technique) was compared to 48-hour storage with no additives at -80°C, room temperature (between 20°C and 30°C) and on an ice brick in a cooler box to simulate real-life field collection scenarios common to the trial.

While next-generation sequencing-based assays remain the gold standard for microbiome analysis, they are relatively expensive and time-consuming. We performed quantitative PCR (qPCR) as an alternative to sequencing [10-12], to provide a rapid broad overview of the microbiome, which is ideal for a pilot study such as this one. By targeting specific bacterial groups with qPCR and comparing them to the total number of bacteria present in a sample (as determined by Universal Eubacteria primers) their abundance could be determined, and changes could be observed quickly. The phyla Bacteroidetes and Firmicutes, which comprise about 90% of the healthy human gut microbiota, and several other representative groups, namely Enterobacteriaceae, Lactobacillus spp. and Bifidobacterium spp., were targeted [12]. We also investigated the change in abundance of fungi compared to total bacteria as a marker of the effect of storage conditions on the fungal microbiota.

Materials and methods

Sample population and collection

Ten stool samples collected from children (<5 years) as part of the TB-CHAMP clinical trial were randomly selected for this study. The samples were collected in a standard specimen container without preservative and delivered to the laboratory for processing on the day of collection. Stool samples were homogenized to prevent intra-sample variability caused by subsampling different microenvironments of the stool [12]. Homogenization was performed by mixing with the sterile spoon attached to the inside of the collection tube lid. Aliquots from each sample were subjected to either immediate DNA extraction, 48-hour storage with no additives at -80°C, 48-hour storage at room temperature (between 20°C and 30°C), or 48-hour storage on an ice brick in a cooler box. Temperature fluctuations were monitored by recording the ambient temperatures at room temperature and in the cooler box over a 48-hour period. Written consent was obtained from the parents/guardians of the participants as part of the clinical trial and ethical approval granted by the Stellenbosch University Human Research Ethics Committee (SU-HREC) (M16/02/009 and S18/02/031) and the Medicines Control Council of South Africa (20160128).

DNA extraction and quality analysis

Prior to DNA extraction, the aliquots were homogenised a second time, to avoid variability caused by changes in the microenvironments after 48 hours of storage. For the first five samples, three different commercially available stool DNA extraction kits were compared: PSP® Spin Stool DNA Kit (Stratec Biomedical, Germany), ZymoBIOMICS DNA Miniprep Kit (Zymo Research, USA) and QIAamp PowerFecal DNA Isolation Kit (Qiagen, formerly moBio, Germany). The workflow is shown in Fig 1. Briefly, for each kit, DNA was extracted from 200 mg aliquots of stool from each of the four storage conditions, according to the manufacturer’s instructions. Aliquots frozen at -80°C were not thawed prior to extraction. DNA purity (A260/A280 and A260/A230), and yield (ng/μL) were determined using the BioDrop μLite spectrophotometer (BioDrop, UK) and by Qubit Fluorometric Quantitation (Invitrogen, USA) at the Central Analytical Facility (CAF) of Stellenbosch University. We used the Kruskal-Wallis test [13] for non-normally distributed data to determine whether the different extraction kits or storage methods influenced the DNA yield significantly (p < 0.05). DNA degradation was assessed by gel electrophoresis. The remaining five samples were subjected to the same storage condition comparisons as described above and DNA was extracted with the kit that showed the best performance.

Fig 1

Workflow for aliquoting and extraction of stool samples.

RT = Room temperature.

Relative quantitation of microbial subpopulations

We adapted a previously described qPCR protocol [12] to determine the abundance of various microbial subpopulations, namely Bacteroidetes, Firmicutes, Enterobacteriaceae, Bifidobacterium spp. and Lactobacillus spp., relative to Eubacterial 16S rRNA gene amplification. The Lactobacillus primers were replaced with a pair that amplified a smaller product [14] more suitable for use with SYBR Green dye. We also amplified fungal species using ITS1 primers [15]. Amplification was performed on the Rotor-Gene Q thermocycler (Qiagen) as singleplex reactions using 1X KAPA 2G SYBR Fast Uni Kit (KAPA Biosystems), 0.2 μM of each primer (Table 1) and nuclease free water (Qiagen) in 20 μL reactions. DNA input was standardized to 30 ng per reaction and all reactions were performed in triplicate. The adapted cycling conditions for all bacterial populations were as follows: denaturation at 95°C for 3 minutes, followed by 40 cycles of denaturation (95°C for 5 seconds) and annealing/extension (60°C for 30 seconds). The cycling conditions for fungal amplification were denaturation at 95°C for 3 minutes, followed by denaturation (95°C for 5 seconds) and annealing/extension at 64, 62 and 60°C for 30 seconds for 10, 10 and 20 cycles respectively. Fluorescence was acquired to the green channel during the annealing step. The Rotor-Gene software was used to calculate the efficiency and detection threshold for each primer set using individual standard curves. The efficiencies ranged between 0.91 and 1.04 with R2 values > 0.99.

Table 1

Primers used for qPCR.

All primers were synthesized by Integrated DNA technologies (USA).

Group targeted	Primer Sequence 5' to 3'	Amplicon size	Reference
Bacteria(16S rRNA)	F: ACTCCTACGGGAGGCAGCAGT	174–199	[16] Walter et al., 2000
	R: GTATTACCGCGGCTGCTGGCAC
Bacteroidetes	F: CGATGGATAGGGGTTCTGAGAGGA	238	[17] Guo et al., 2008
	R: GCTGGCACGGAGTTAGCCGA
Firmicutes	F: GGAGYATGTGGTTTAATTCGAAGCA	126	[17] Guo et al., 2008
	R: AGCTGACGACAACCATGCAC
Enterobacteriaceae	F: CATTGACGTTACCCGCAGAAGAAGC	195	[18] Bartosch et al., 2004
	R: CTCTACGAGACTCAAGCTTGC
Bifidobacterium spp.	F: CGCGTCYGGTGTGAAAG	244	[19] Delroisse et al., 2008
	R: CCCCACATCCAGCATCCA
Lactobacillus spp.	F: TGGAAACAGRTGCTAATACCG	231–233	[14] Byun et al., 2004
	R: GTCCATTGTGGAAGATTCCC
Fungi (ITS1)	F: CTTGGTCATTTAGAGGAAGTAA	260	[15] Bellemain et al., 2010
	R: GCTGCGTTCTTCATCGATGC

Microbial community analysis

Differences in abundance related to storage conditions were analysed using RStudio (Version 1.1.463, R version 3.6.1) and the packages tidyverse, car and lme4. Spaghetti and distribution plots were generated to show trends in abundance in the different microbial populations and samples. The data were normalised for the distribution plots by subtracting the average Universal Ct value from the target population Ct for each sample. These data were analysed using Kruskal-Wallis multiple group comparisons to investigate the differences in abundance related to storage and subject for each of the six subpopulations targeted. Bonferroni correction was performed on the basis that multiple hypotheses were tested on data from the same subjects. The raw data were also fitted to a linear mixed effect model to show the overall relationship between abundance (shown by Cycle threshold values (Ct)), storage and population, taking into account random effects introduced by the subjects.

Correlations were deemed statistically significant at p < 0.05. We also investigated whether storage condition can influence the Firmicutes/Bacteroidetes ratio (F/B).

Results

DNA Extraction and Quality analysis

Based on samples from the first five subjects the PSP kit had the highest average yield, but the lowest DNA purity across all samples and storage methods (Table 2). The QIAamp kit also performed well with yields of > 20 ng/μL in all but one sample. The ZymoBIOMICS kit had substantially reduced yield and quality with samples containing more fibrous materials. The QIAamp extractions had the highest overall quality, with a mean yield that was slightly lower than the other kits, but still sufficient for downstream molecular experiments such as sequencing. No significant differences in DNA yield were detected for either the kit (p = 0.5142) or storage method (p = 0.1814) using the Kruskal-Wallis test. The average DNA purity (A260/280) of the QIAamp kit was 1.85, with all but one sample within the ideal range (1.8–2.0).

Table 2

Extraction kit dependent DNA quality and quantity results.

The results represent stool samples from the first five subjects extracted after storage in four different conditions. The best value in each category is indicated in bold.

	QIAamp PowerFecal	ZymoBIOMICS	PSP Spin Stool
	(n = 20)	(n = 20)	(n = 20)
Mean yield (ng/μL) (min–max)	73.04 (5.84–158.0)	97.82 (2.62–215.2)	135.63 (9.48–400.0)
Yield < 30 ng/μL (n)	2 (10%)	5 (25%)	4 (20%)
Mean A260/A280 value (min–max)	1.85 (1.8–2.21)	1.88 (1.6–2.6)	1.99 (1.89–2.1)
Mean A260/A230 value (min–max)	1.68 (1.04–2.11)	1.68 (0.3–2.2)	1.57 (0.97–2.1)
Out of range A260/A280* (n)	1 (5%)	3 (15%)	2 (10%)
Out of range A260/A230** (n)	4 (20%)	5 (25%)	8 (40%)

* Acceptable A260/A280 range defined as 1.8–2.0.

** Acceptable A260/A230 range defined as 1.4–2.2. This is wider that the traditional range of 2.0–2.2; in our setting Illumina sequencing has been successful within this range.

No significant signs of DNA degradation were detected by gel electrophoresis for any kit and all samples had large genomic weight DNA, with minimal smearing. Of the extraction kits, the PSP kit had the most samples with some evidence of smearing. For these reasons, extractions from the QIAamp PowerFecal DNA Isolation Kit were selected for further analyses. The quality ranges above were defined to show the suitability of each kit to extract DNA for use in next-generation sequencing; however, due to the robustness of PCR, we included all extractions from this kit for further analysis in this study.

Comparison of storage conditions

There was little fluctuation in room temperature over the 48 hours, in contrast to in the cooler box (Fig 2), where a rapid decline in temperature to just above 0°C was observed within the first 2 hours, followed by a gradual increase of 1 degree per hour until reaching 7°C where it remained stable until 8 hours. Over the following 24 hours, the temperature in the cooler box slowly increased until stabilizing just under room temperature until 48 hours.

Fig 2

Temperature fluctuations at room temperature and in the cooler box.

Each of the six microbial subpopulations we targeted were detected in all but one extracted sample. The extracted DNA from the cooler box group for subject 3 (3C) was not within the detection limit for the fungal qPCR and was therefore excluded from the fungal qPCR analysis. The bacterial populations in the frozen (-80°C) group most closely resembled the immediate extraction group; more variation was seen in the room temperature and cooler-box groups. Less abundant populations were more sensitive to differences in storage and showed more variation overall (S1 Fig). Still, with few exceptions, samples from the same subject tended to cluster together within a population group, regardless of storage method. This is demonstrated in the Enterobacteriaceae and Bifidobacteria groups, where clusters of colour (representing the subject) are seen (Fig 3).

Fig 3

Subject specific characteristics are associated with more variation in the abundance of microbial populations than storage conditions.

A lower Ct value represents a higher abundance. Kruskal-Wallis group comparison p-values are shown below the figure. The corrected p-value for significance = 0.004, according to the Bonferroni method. Ct = Cycle threshold; I = Immediate; F = Frozen; R = Room temperature; C = Cooler box. Samples 2C and 3C had a DNA input concentration < 30ng.

No significant differences were detected between storage groups for any of the microbial subpopulations targeted, but subject related differences were statistically significant for each population group (Fig 3). The linear-mixed effect model showed no significant differences between the storage conditions (p = 0.1655), confirming that variation was accounted for by population- (p = < 0.00001) and random effects introduced by subject specific characteristics. The population with the least amount of variation was the Firmicutes, followed by Bacteroidetes. The Enterobacteriaceae and Fungi showed the most variation across all samples, followed by the Bifidobacteria. In these populations, it is clear that subject specific characteristics are associated with more variation in abundance than the storage conditions are. Populations that were less abundant overall, such as Fungi and Enterobacteriaceae, appeared to be more sensitive to changes in storage. In concordance with our other results, the Firmicutes/Bacteroidetes (F/B) ratio also varied more between subjects than between storage methods (Fig 4). In samples where the F/B ratio was altered, it was more often than not driven by an increase in Firmicutes, rather than a decline in Bacteroidetes, especially in the room temperature and cooler box storage groups.

Fig 4

The Firmicutes/Bacteroidetes ratio shows more variation between samples than between storage conditions.

This value was calculated using the normalised Ct values, which are inversely related to abundance. Therefore, the higher the F/B ratio, the more Bacteroidetes relative to Firmicutes. I = Immediate; F = Frozen; R = Room temperature; C = Cooler box.

Discussion

We compared three commercially available stool DNA extraction kits and found that they generally produced sufficient yields for sequencing purposes. This is likely due to the fact that they all include a bead-beating step, which has been shown to significantly improve DNA yield from stool [20]. The QIAamp kit performed the best, although not by a large margin. This is not surprising, as similar MoBio kits (now marketed through Qiagen) have been used for DNA extraction by leaders in the field, including the Human Microbiome Project [21]. The QIAamp PowerFecal DNA Isolation Kit tested in this study and other related kits, such as the QIAamp Fast Stool kit (Qiagen), have also been found to be effective at extracting fungal DNA when they are combined with a bead-beating step [22], which demonstrates that parallel mycobiome analysis will be possible from the same DNA extracts. Choosing the correct kit is dependent on the samples, aim and resources available for the study. It is vital to use only one DNA extraction method for all samples, and to be careful when comparing microbiome results when different extractions were used [23-25]. It is also advisable to work in as sterile a fashion as possible and to randomly extract samples to control for contamination and environmental biases introduced through the extraction kit [26].

The results from the microbial analysis support previous findings that storage at -80˚C is equivalent to the gold standard of immediate DNA extraction [1-4]. Stool samples that are not kept in preservatives should therefore be frozen as soon as possible, and not thawed until DNA extraction. We determined that the differences in relative abundance were greater between subjects than between storage methods; this is comparable to the findings of other published studies [2,3]. While differences in abundance for all taxa was shown to be significantly related to subjects, this study was not designed to determine the drivers of differences, such as age, antibiotic exposure and diet; however, this will be investigated in a planned larger sequencing-based study from the same population. We found no significant differences in the abundance of microbes when comparing the different storage methods to immediate extraction. Our findings are supported by other published studies that investigated room temperature storage for up to 72 hours [1,3,5,8,9,23]. However, some studies have also reported significant changes after as soon as 12 hours [6,7]. These contradictory findings may be due to differences in the initial relative abundance of certain populations in a sample. Choo and colleagues [6] stated that studies that found no significant changes due to room temperature storage reported a greater relative abundance of Bacteroidetes and Firmicutes and less than 5% Actinobacteria. The effect of room temperature storage may therefore be more severe in some study populations with higher levels of Actinobacteria; though there is not enough literature to validate this. In most cases, it is assumed that the majority of the gut microbes are mesophiles that grow best at temperatures between 20°C and 45°C. Therefore, the overall abundance may be expected to increase during room temperature storage with little effect on the relative abundance of each phylum. Regarding the cooler box storage conditions, we are not aware of any studies that are similar to the one presented here. We found that there were substantial changes in temperature in the cooler box storage set-up, which may have influenced the growth of certain microbial populations and thereby contributed to the variations in abundance in this group. The temperature was between 7 and 20°C for about 24 hours, which is ideal for psychrothropic microbes which may include, among others, members of Bacilli, Enterobacteriaceae and the genera Pseudomonas and Acinetobacter. Although not substantial, we found that changes in the ratio of the two most abundant phyla was mostly driven by an increase in Firmicutes, which is in contrast to the findings of other studies that reported a decrease in Firmicutes during room temperature storage [6,7].

Conclusion

We determined that the risk of introducing bias to microbial community profiling through differences in storage will likely be minimal in our setting. The study was limited by a small sample size and the fact that the ambient (room) temperature in the field may not be as stable as in a controlled experimental environment. Therefore, we recommend that transport time and storage conditions be recorded in similar studies in order to provide the opportunity to assess the effect of storage on the microbiome on a larger scale. While it is impractical to assess every factor that may influence the microbiota, the collection of robust and complete metadata can help researchers identify important factors that influence the specific population of interest. Further, this study has shown that qPCR can be used to rapidly and reproducibly assess the effect of certain factors on the major bacterial populations of the gut in low-resource settings, where microbiome research is still relatively expensive. As qPCR only provides information on a limited number of bacterial populations, it remains essential to follow these studies up with next-generation sequencing to establish a more complete profile of the microbiota.

The abundance of different microbial populations differ between subjects and have varying responses to different storage conditions.

This plot shows the trend in abundance for each of the subjects (the ten boxes) at the different storage conditions. A lower Ct value represents a higher abundance.

Ct = Cycle threshold; I = Immediate; F = Frozen; R = Room temperature; C = Cooler box. Samples 2C and 3C had a DNA input concentration < 30ng.

(TIF)

Click here for additional data file.

11 Nov 2019

PONE-D-19-27079

The effect of storage conditions on microbial communities in stool

PLOS ONE

Dear Nel Van Zyl,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please address each concern raised, and explain how this concern has been addressed in the manuscript.  We need to see more statistics to support the conclusions.

We would appreciate receiving your revised manuscript by Dec 26 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

David N Fredricks, MD

Academic Editor

PLOS ONE

Additional Editor Comments:

In addition, please explain how samples were homogenized, in detail.

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for including the following information in your ethics statement:

"Written consent was obtained as part of the clinical trial".

We note that you included minors (age<18) in your study. Please provide additional details regarding minors' consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified whether you obtained consent from parents or guardians.

3. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors presented findings of the stability of targeted bacteria, using qPCR, in stool samples processed and stored using different methods. The authors provide adequate rationale for conducting this study, and its findings could be important toward informing those studies that similarly desire not to use preservative agents for microbial preservation in field studies. However, there are some issues with the authors’ terminology and the statistical analyses presented that need to be addressed prior to publication in PLOS One.

Line 55-57: This sentence should be revised: 1) microbial stability should not be limited to ‘specific’ populations, and should theoretically be consistent across populations, given the same conditions/storage/extraction/processing; and 2) the data used by the authors are also ‘limited’ in both sample size (n=10) and population (children); therefore, the rationale in this sentence seems not justified.

Line 76: The authors should state if subjects were on antibiotics at the time of collection

Line 80-81: It is suggested that authors use a table or diagram to demonstrate the aliquoting of the samples and how many samples were compared within each collection method. They should also include which samples dropped out due to DNA yield/quality

Lines 125-132: Statistical analyses were insufficient to appropriately compare the stability of the microbial data between the storage methods. It is suggested that the authors use more quantitative comparisons, rather than basing their findings on the subjective figure interpretations. For example, the authors could compare the adjust mean Ct for each collected method, using linear mixed effects models, and calculate a p-value for each of the collection methods compared to the referent immediately-extracted group.

Line 133: The random effect should be stated as the subject and not the sample (since there are multiple measurements on one subject)

Line 126, 128, 143: Authors should avoid using terms as ‘cause’ and ‘effect’

Line 165-166: It is unclear what the authors are referring to

Figure 2: It is unclear what the 10 boxes represent. It also appears that many of the more abundant taxa were variable (not just the less abundant taxa)

Figure 3: This seems redundant, and it is not clear that the subject cluster together. There needs to be a statistical test to quantify variation explained by subject versus storage

Line 179: It is unclear why a single p-value is being used to compared multiple taxa abundances across the storage methods, this does not seem like the appropriate statistical test

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

17 Dec 2019

To the editor and reviewers,

Our responses have been detailed fully in the "Response to Reviewers" letter. We request that the responses be read in that document, as the layout and formatting are more pliable. We have summarized those responses below:

Response to editor’s comments:

With regards to sample homogenization and informed consent: We have expanded on both comments in the edited submission.

Response to reviewer’s comments:

Line 55-57:

Microbiota and what influences them are diverse and unique in different settings; therefore, it is important to study the possible influences of study procedures in each setting. We have revised the sentence to reflect this.

Line 76: The authors should state if subjects were on antibiotics at the time of collection

• As this paper focuses on the differences related to storage relative to immediate extraction, we do not believe that it impacts the conclusions we have drawn.

• Participants were excluded if they had received ≥14 days of isoniazid or a fluroquinolone at enrolment, or if they had been treated for TB in the 12 months before. However, information regarding other antibiotics is not currently available to the authors as the trial is currently ongoing.

• Antibiotic usage data have been captured as part of the clinical trial, and have been requested from the trial data management team, but will only be made available for a larger sequencing-based study going forward.

• We have noted in the discussion section that differences in subjects, including the influence of antibiotics, will be investigated as part of a larger study going forward.

Line 80-81: It is suggested that authors use a table or diagram to demonstrate the aliquoting of the samples and how many samples were compared within each collection method. They should also include which samples dropped out due to DNA yield/quality

We have added a workflow (Fig 1) to demonstrate the aliquoting of samples. No samples were excluded from the qPCR analysis due to quality, due to the robustness of PCR. We have included a statement in the results section to this effect.

Lines 125-132: Statistical analyses were insufficient to appropriately compare the stability of the microbial data between the storage methods.

Additional statistical measures have been described below and in the edited manuscript.

Line 133: The random effect should be stated as the subject and not the sample (since there are multiple measurements on one subject)

This has been revised in the manuscript.

Line 126, 128, 143: Authors should avoid using terms as ‘cause’ and ‘effect’

These terms have been revised in the manuscript where appropriate.

Line 165-166: It is unclear what the authors are referring to

We have revised this sentence in the edited manuscript to reflect our meaning more clearly.

Figure 2: It is unclear what the 10 boxes represent. It also appears that many of the more abundant taxa were variable (not just the less abundant taxa)

We have determined that Fig 3 represents our core findings most clearly and have kept it in the main text, but request to keep Fig 2 as a supplemental figure to show the variations for each subject (the ten boxes) across populations. The figure heading has been expanded to refer to the ten boxes as subjects.

Figure 3: This seems redundant, and it is not clear that the subject cluster together. There needs to be a statistical test to quantify variation explained by subject versus storage

We have added p-values to this figure to demonstrate that statistical tests support our findings. We have described the statistical tests that generated these values below, and in the manuscript in the methods section.

Line 179: It is unclear why a single p-value is being used to compared multiple taxa abundances across the storage methods, this does not seem like the appropriate statistical test

In consultation with the statisticians, it was felt that the population differences are inherently part of the influence and it was therefore included as a fixed effect in the linear mixed effect model. We used the entire data set, including all populations including the Universal amplification Cts (therefore, non-normalized Ct values) and indicated the p-value for differences related to storage as determined by the lme model. This model also output a p-value for population, and we have added that in the edited manuscript.

We agree with the reviewer that different taxa/populations may warrant separate statistical tests. For this reason, we decided to perform statistical testing using the normalized mean/median Ct values for each taxon. Instead of fitting linear mixed effect models for each storage group compared to the immediate as suggested by the reviewer, we performed Kruskal-Wallis multiple group comparisons. The reason for this is that linear mixed-effect models are more useful when more data is available – comparing the mean/median Ct values therefore diminishes the number of data points available.

Kind regards,

Kristien Nel Van Zyl

Division Medical Microbiology, Department of Pathology, Stellenbosch University

Submitted filename: Response to reviewers_final.doc

Click here for additional data file.

20 Dec 2019

The effect of storage conditions on microbial communities in stool

PONE-D-19-27079R1

Dear Dr. Nel Van Zyl,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

David N Fredricks, MD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

3 Jan 2020

PONE-D-19-27079R1

The effect of storage conditions on microbial communities in stool

Dear Dr. Nel Van Zyl:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. David N Fredricks

%CORR_ED_EDITOR_ROLE%

PLOS ONE