Sulfite preservatives effects on the mouth microbiome: Changes in viability, diversity and composition of microbiota.

OVERVIEW: Processed foods make up about 70 percent of the North American diet. Sulfites and other food preservatives are added to these foods largely to limit bacterial contamination. The mouth microbiota and its associated enzymes are the first to encounter food and therefore likely to be the most affected.
METHODS: Eight saliva samples from ten individuals were exposed to two sulfite preservatives, sodium sulfite and sodium bisulfite. One sample set was evaluated for bacteria composition utilizing 16s rRNA sequencing, and the number of viable cells in all sample sets was determined utilizing ATP assays at 10 and 40-minute exposure times. All untreated samples were analyzed for baseline lysozyme activity, and possible correlations between the number of viable cells and lysozyme activity.
RESULTS: Sequencing indicated significant increases in alpha diversity with sodium bisulfite exposure and changes in relative abundance of 3 amplicon sequence variants (ASV). Sodium sulfite treated samples showed a significant decrease in the Firmicutes/Bacteroidetes ratio, a marginally significant change in alpha diversity, and a significant change in the relative abundance for Proteobacteria, Firmicutes, Bacteroidetes, and for 6 ASVs. Beta diversity didn't show separation between groups, however, all but one sample set was observed to be moving in the same direction under sodium sulfite treatment. ATP assays indicated a significant and consistent average decrease in activity ranging from 24-46% at both exposure times with both sulfites. Average initial rates of lysozyme activity between all individuals ranged from +/- 76% compared to individual variations of +/- 10-34%. No consistent, significant correlation was found between ATP and lysozyme activity in any sample sets.
CONCLUSIONS: Sulfite preservatives, at concentrations regarded as safe by the FDA, alter the relative abundance and richness of the microbiota found in saliva, and decrease the number of viable cells, within 10 minutes of exposure.

Introduction

The human oral cavity is a complex environment hosting up to 700 different species of bacteria, found primarily in 5 phyla, residing in saliva, teeth surfaces and on the apical mucosa of the tongue and cheeks [1-3]. At birth, colonization of the mouth begins. Streptococcus salivarius, a facultative anaerobe, is one of the initial colonizers along with several aerobes within the 1st year, including Lactobacillus, Actinomyces, Neisseria and Veillonella, an anaerobe. [4]. Diversity and the number of bacteria present in different individuals’ mouths may vary as a result of environmental and genetic factors including disease and diet. However, recent studies have found most healthy individuals maintain a fairly consistent population over weeks to months of time [2,5].

Human saliva contains several enzymes and buffers that contribute to the first steps in digestion and serve as a first line of defense in immunological responses [6,7]. Lysozyme is found in saliva, as well as tears, blood serum, perspiration, and other bodily fluids. It is an antimicrobial enzyme that catalyzes cleaving of ß(1,4)-glycosidic bonds between residues of N-acetylmuramic acid (NAM) and N-acetylglucosamine (NAG) in peptidoglycan of primarily gram positive bacterial cell walls. Research has shown that lysozyme found in the mouth can lower the adherence of bacteria to surfaces and limit the number of microbes [8,9].

An imbalance in the mouth microbiome can lead to oral diseases such as dental caries, periodontitis, oral mucosal disease, and systemic diseases of the gastrointestinal, cardiovascular, and nervous systems [1,10]. A few recent studies have detected significant changes in the mouth microbiota in response to short and long-term environmental alterations [11-14]. Bescos et.al. observed the effects of chlorhexidine mouthwash resulting in a significant increase in the percent abundance of Firmicutes and Proteobacteria and a decrease in Bacteroidetes, Fusobacteria, TM7, and SR1 [11]. The effects of inorganic nitrates (found in vegetables) on the mouth microbiome of 19 omnivores and 22 vegetarians, displayed an increase in the percent abundance of Proteobacteria and a decrease in Bacteroidetes consistent with the chlorhexidine mouthwash study [12]. Another study, examining the effects of green tea on both the gut and mouth microbes showed “an irreversible increase of Firmicutes to Bacteroidetes ratio, elevated SCFA producing genera, and reduction of bacterial LPS synthesis in feces” [13]. A study examining betel nut chewing in 122 individuals, found reduced bacterial diversity, elevated levels of Streptococcus infantis, and changes in distinct taxa of Actinomyces and Streptococcus genera in current users and reduced levels of Parascardovia and Streptococcus in long-term chewers [14]. At the phyla level in both the mouth and gut, an increase in Firmicutes is often observed with obesity, and an increase in Bacteroidetes is observed with inflammatory bowel disease [10,15,16]. Proteobacteria, another key player in the oral microbiome, has been found to be the most variable phylum in dysbiosis and its increase is generally related to a decrease in Firmicutes [10,16].

Antibiotics, diet, and food additives including artificial sweeteners, emulsifiers, preservatives, colorants, and acidity regulators can result in dysbiosis in the gut leading to a variety of human health issues [17-20]. An unhealthy gut microbiome influences signaling in the gut-brain axis; a bidirectional signaling system responsible for homeostasis, function, and overall health [21]. A recent study in germ-free humanized mice found that a mixture of common antimicrobial food additives including sodium benzoate, sodium nitrite, and potassium sorbate induced a significant dysbiosis in the gut [22]. Sodium sulfite and sodium bisulfite have long been used as preservatives to prevent food spoilage and browning. They can be found in a variety of foods such as dried fruit, processed meat, beer, wine, and canned goods [23]. Many foods contain such high levels of sulfites that exposure above levels generally regarded as safe (GRAS) by the US Food and Drug Administration (FDA) is common [23]. Our previous study demonstrated that under ideal growing conditions, sodium sulfite at 3780ppm and sodium bisulfite at 1800 ppm (both lower than the 5000ppm allowable for GRAS), were bactericidal to four probiotic species in 2–6 hours of exposure [24]. Few studies have been conducted to determine the effect of preservatives on the gut microbiota and none are known to us regarding their impact on the mouth microbiome.

Most recent studies on the human mouth and gut microbiota have utilized 16s rRNA sequencing, and in some cases flow cytometry or CFUs along with OD600 spectrophotometry to quantify cell numbers [2,5]. Twenty to sixty percent of the bacterial cells in the mouth microbiome are estimated to be unculturable, making plate counts and CFUs of limited use [2]. This has made 16S rRNA sequencing a powerful tool to profile mixed communities of bacteria. However immediate or short-term changes in the microbiome cannot reliably be detected due to the complex nature of the communities and the detection of DNA sequences from both living and recently lysed cells [2]. Flow cytometry is thought to be the gold standard for cell counting but also has limitations due to the potential presence of bacterial aggregates which may artificially deflate the cell count [2].

The concentration of adenosine triphosphate (ATP) present in living cells can be quantified using a proportional luminescent signal to observe immediate changes in the numbers of viable bacterial cells in a sample. Sensitivity as low as 0.0001nM ATP, reflecting the test population, is high due to the rapid loss of ATP in non-living cells [25]. This method implements a recombinant luciferase enzyme to oxidize luciferin in the presence of ATP and oxygen to produce oxyluciferin and light. It has been used to accurately quantify changes in the number of viable cells in various antibiotic susceptibility tests ranging from in-vitro biofilm formations by Pseudomonas aeruginosa [26], multiple gram-negative bacterial species within 24 hours of treatment with antibiotics [27], and slow growing species such as Borrelia burgdorferi [28]. Limitations to this method include the detection of eukaryotic cell’s ATP present in some mixed populations, differences in amounts of ATP produced by varying cell types and inhibition of the luminescence signal due to the media used in assays. All these factors were considered in the experiments described here.

This study examines the effects of two types of sulfite preservatives on the human mouth microbiome by corresponding changes in ATP activity of saliva samples collected over a 4–5-week period from 10 individuals. Bacteria in saliva samples from one individual were examined for responses to the sulfite treatments indicated by changes in the percent abundance and/or diversity with 16s rRNA sequencing. Additionally, baseline lysozyme activity in the individuals being studied was determined and compared to the number of viable cells found in the samples.

Methods and materials

Saliva collection

Unstimulated saliva was collected from 10 individuals between 2–10 hours after consuming food or drink, other than water. Prior to donation, each individual rinsed mouth 3 times with water followed by a twenty-minute waiting period before delivering saliva via spitting into a sterile tube. Samples were placed on ice for the duration of collection and aliquoting. Time allowed for saliva collection was kept under 30 minutes. Collections took place twice a week with at least 2 days in between, over 4–5 weeks. Each participant supplied 8 samples total. Collected saliva was diluted 1:10 with sterile DI water, aliquoted and stored at -80°C. Participants contributing to saliva collections included ten individuals, 2 males (M1 and M2) and 8 females (F1-F8) from 18–60 years of age, all in overall good health. Our protocol for utilizing human saliva samples was reviewed and permitted by the Institutional Biosafety Committee (IBC) at the University of Hawaii. The Internal Review Board was also consulted and it was determined that no further review was necessary because the samples were made anonymous immediately after collecting, and they were not considered human samples due to the analysis performed being directed only on the bacterial cells. Aliquots of the same samples were used in all experiments.

Sulfite exposure to saliva samples

Saliva aliquots were exposed to freshly made, 1800 ppm (17.3 mM) sodium bisulfite (Fisher Scientific) or 3780 ppm (30 mM) anhydrous sodium sulfite (Fisher Scientific) both prepared in sterile water in independent experiments. Immediately following exposure to sulfites, aliquots of each control and matching exposed sample were centrifuged at 4,600 RCFs (7000 RPMs) for 10 minutes to pellet cells. The supernatant was discarded and the pellet brought up in an equal volume of 1X phosphate buffered saline (PBS). These samples are referred to as “time 0” (T0). The other half of each aliquot was placed in an incubator set at 36°C for 30 minutes (T30), then pelleted using the same procedure described for time zero samples, brought up in 1X PBS and stored. All samples were stored at -20°C for short term storage of 6 weeks or less, or at -80°C for longer storage. See supplemental materials for additional notes on procedure.

ATP activity in saliva samples

BacTiter-Glo™ Microbial Cell Viability Assay from Promega was used to quantify relative numbers of viable bacterial cells found in saliva samples. The Perkin Elmer Victor X3 multi-mode plate reader was used to record luminescence of all samples. Samples were assayed in triplicate using a white plate with clear bottom (View-Plate 96 TC from PerkinElmer). Lids were coated with Triton X100 as described by Brewster [29] to prevent condensation.

Blank wells were filled with sterile water to cut down on cross talk, negative controls contained 100ul of 1X PBS + 100ul BacTiter-GLO™ reagent. One hundred microliters of each treated and control (untreated) sample (3 replicates each) were tested. All samples from each individual were ATP assayed on the same day using the same Bac-titer glo reagent to limit variability between luminescence readings for more accurate comparisons of results. Samples and BacTiter-Glo™ reagent were brought to room temperature before use. Assay consisted of a 5 second orbital (0.10mm) shake, a 5-minute incubation at 25°C, followed by a 1 second read of luminescence (RLU).

Statistical analysis of ATP studies

For all statistical tests, p values < 0.05 were considered significant. Statistical errors were calculated as the standard error (SE) or standard deviation (SD). Average total RLU (relative light units) for each individual’s eight saliva samples were assessed using raw RLU data by a two-way ANOVA and paired T-Tests.

Sample preparation for DNA extraction

A total of 32 saliva samples from individual F2 was sent to Zymo Research, Irvine, CA for 16s rRNA sequencing. Sequenced samples included 8 sodium sulfite treated saliva samples at T0, and 8 untreated saliva samples serving as controls at T0. Eight sodium bisulfite treated saliva samples at T0 and the respective control samples. A 10:1 RNA/DNA shield from Zymo was added to each saliva sample to maintain samples during shipping.

DNA extraction

DNA was extracted from saliva samples using ZymoBIOMICS®-96 MagBead DNA Kit (Zymo Research, Irvine, CA). The ZymoBIOMICS® Microbial Community Standard was used as a positive control. A blank extraction control was used as the negative control.

Targeted library preparation

Bacterial 16S ribosomal RNA gene targeted sequencing was performed using the Quick-16S™ NGS Library Prep Kit (Zymo Research, Irvine, CA). Bacterial 16S primers amplify the V3-V4 region of the 16S rRNA gene. The ZymoBIOMICS® Microbial Community DNA Standard was used as a positive control. A blank library preparation was used as the negative control.

Absolute abundance quantification

Zymo Research indicates the following methods were used for absolute abundance quantification: A quantitative real-time PCR was set up with a standard curve. The standard curve was made with plasmid DNA containing one copy of the 16S gene and one copy of the fungal ITS2 region prepared in 10-fold serial dilutions. The primers used were the same as those used in Targeted Library Preparation. The equation generated by the plasmid DNA standard curve was used to calculate the number of gene copies in the reaction for each sample. The PCR input volume was used to calculate the number of gene copies per microliter in each DNA sample.

The number of genome copies per microliter DNA sample was calculated by dividing the gene copy number by an assumed number of gene copies per genome. The value used for 16S copies per genome is 4. The value used for ITS copies per genome is 200. The amount of DNA per microliter DNA sample (DNA_ng) was calculated using an assumed genome size of 4.64 x 106 bp, the genome size of Escherichia coli, for 16S samples. This calculation is shown below:

Calculated Total DNA = Calculated Total Genome Copies × Assumed Genome Size (4.64 × 106 bp) × Average Molecular Weight of a DNA bp (660 g/mole/bp) ÷ Avogadros Number (6.022 x 1023/mole). (Zymo Research, Irvine, CA).

Sequencing

The final library was sequenced on Illumina® MiSeq™ with a v3 reagent kit (600 cycles). The sequencing was performed with 10% PhiX spike-in.

Bioinformatics analysis

Unique amplicon sequence variants (ASVs) were inferred from raw reads using the DADA2 pipeline as described by Callahan et al. [30]. Chimeric sequences were also removed with the DADA2 pipeline. Taxonomy assignment was performed using Uclust from Qiime v.1.9.1 with the Zymo Research Database.

Firmicutes/Bacteroidetes ratio was calculated using the number of sequences belonging to phylum Firmicutes divided by the number of sequences belonging to Bacteroidetes. To evaluate the significance of the differences between the control and treatment groups, paired t-tests were used for statistical analysis, and the results (with p-value < 0.05) shown in the figures. Alpha diversities were estimated using four indexes using R package “Vegan” [31]: including species number (richness), Chao1, Shannon index, and Inverse Simpson index. The beta diversity can be explained by the PCA (principal component analysis) plots, which was also conducted by the R package “Vegan” using the Bray-Curtis distance matrix at the ASV level. The relative abundances of ASVs in different samples were transformed and the first two principal components were plotted to show the relationships between the groups. The percentage followed in the axis shows the portion of the total variances that can be explained by the first or the second principal component. The differentially abundant taxa (at different phylogenetic levels) were identified based on the paired t-test results.

Lysozyme activity assays

Lysozyme activity initial rates were determined for all individuals untreated samples, using a Perkin Elmer Victor X3 multimode plate reader and an EnzChek™ Lysozyme Assay Kit (E-22013) from ThermoFisher Scientific at a temperature of 37°C. Black 96 well TC ViewPlates (PerkinElmer) with lids coated with Triton X100 as described by Brewster [29] to prevent condensation. Fifty microliters of saliva samples, 100ul of ENZ Check buffer, and 50ul of substrate was added to each well in triplicate.

Graphing

Results were analyzed and graphed using Originlab software.

Results

ATP assays

Two-way ANOVA tests with replication using raw (RLU) data indicate that there is no significant interaction between specific individuals and their reactions to sulfite treatments or between individual’s reactions to sulfite treatment due to exposure time. However, there is a significant difference in ATP levels between individual’s control and treated saliva samples, with a large variation in baseline numbers of bacteria present in each person’s mouth and a significant difference in ATP levels between sulfite treated and control samples for all individuals (Table 1, Fig 1 and S2 Appendix).

Table 1

“p-value” results of two-way ANOVA tests.

	Time 0			Time 30
	Individuals	Treatment	Interaction	Individuals	Treatment	Interaction
SodiumSulfite	6.38E-37 ***	0.009 **	0.500	2.37E-31 ***	0.035 *	0.997
SodiumBisulfite	1.06E-28 ***	0.002 **	0.121	2.41E-28 ***	1.35E-05 ***	0.065

Results show comparison of individual’s reactions to sulfite treatments, sulfite treatments compared to exposure time, and treated vs control samples for all saliva samples.

(* p<0.05

** p<0.01

*** p<0.001).

Fig 1

Average change in ATP activity after sulfite treatment.

Raw data (RLU) of all saliva samples (F1-F8 and M1-M2) treated with Na2SO3 or NaHSO3 compared to controls was used to determine the average % decrease of viable cells (based on ATP activity) in each at time 0 (T0) and time 30 (T30). The standard error of each test group was calculated, and evidence of observed difference was confirmed by both the paired t-test and the two-way ANOVA (Table 1).

Baseline lysozyme and comparison to number of viable cells (ATP)

A baseline of lysozyme activity in the collected saliva samples was established over a five-week period. Activity was determined as a function of initial rates of ten individuals (Figs 2 and 3). A one-way ANOVA indicated an overall significant difference between individuals of p = 5.5 E-15. Tukey comparisons indicated in Fig 2 show each sample’s range and similarity among samples. A large variation in the average initial rates over the five weeks of collection time between all individuals was observed, ranging from +/- 76% compared to individual initial rate variations of +/- 34%. No consistent correlation between viable cells (ATP) and Lysozyme activity was observed (Fig 3).

Fig 2

Lysozyme activity in untreated saliva samples.

Untreated saliva samples from all individuals (n = 10) were assayed for initial rates of lysozyme activity. The average initial rate from replicates of 3 from each sample set/individual (n = 8) were used to determine the standard deviation and median scores.

Fig 3

Viable cells and lysozyme activity in control samples.

‘Comparison of averaged ATP activity and lysozyme initial rates in all 10 individual’s control saliva samples. Standard deviation of averaged sample sets indicated for both RLU and AFU.

Comparison of individual F2 ATP, lysozyme activity and 16s rRNA sequencing

A significant decrease in viable cells based on ATP activity (RLU) in F2’s samples treated with Na2SO3 and NaHSO3 was observed, with a 40% and 30% decrease (respectively) illustrated in Fig 4A and 4B.

Fig 4

Cell viability and relative abundance of phyla in F2 samples before and after sulfite treatment.

F2 saliva samples (n = 32) were sequenced (16S rRNA) and the average percent abundance of the most predominant 5 phyla is displayed for untreated controls and sodium sulfite (A) or sodium bisulfite (B) treated samples at time 0. “p-values” were calculated using paired t-tests.

16s rRNA sequencing results

Individual “F2’s” samples indicated that Bacteroidetes, Proteobacteria and Firmicutes phyla significantly varied in relative abundance with Na2SO3 exposure (Figs 4A, 5A and 6A). However, no significant difference in the relative abundance of the top 5 phyla were observed with NaHSO3 (Figs 4B and 5B).

Fig 5

Ratio of firmicutes/bacteroidetes changes in F2 samples with sulfite treatments at time 0.

16S rRNA sequencing was used to determine the ratio (based on % abundance) for control and treated samples with Na2SO3 (A) or with NaHSO₃ (B) of individual F2.

Fig 6

Differentially abundant bacteria at different taxonomic levels in F2 sample, after sodium sulfite treatment at time 0.

16S rRNA sequencing was used to determine the % relative abundance of phyla (A), genus (B), and ASV (C) for control and treated samples with Na2SO3. P values were calculated using paired t-tests.

At a more detailed level, significant changes to 3 genus and 6 ASV’s (Fig 6A–6C) were also observed in the Na2SO3 treated samples and 3 ASV’s in the NaHSO3 assays also showed a significant change in relative abundance (Fig 7).

Fig 7

Differentially abundant ASVs in F2 sample after NaHSO3 treatment at time 0.

ASV43 shows a significant decrease while ASV116 and ASV161 increased significantly after the treatment.

A summary of the bacterial types at the genus and ASV level is presented in Table 2. Nine different anaerobic ASV’s exhibited significant changes in relative abundance with sulfite treatments. Four out of the five that showed an increase in abundance were Gram negative and three out of those five were sulfite reducing bacteria (SRB) or have the ability to avoid oxidative stress. Four ASV’s decreased in relative abundance with sulfite treatments. Three out of the four were Gram positive and one out of the 4 was a SRB.

Table 2

A: Bacteria species/ASVs exhibiting a significant change in relative abundance after exposure to sodium sulfite.

B: Bacteria species/ASVs exhibiting a significant change in relative abundance after exposure to sodium bisulfite.

Species/ASV#	Haemophilus parainfluenzae ASV5	Solobacterium moorei ASV35	Alloprevotella rava ASV126	Actinomyces naeslundii ASV141 ASV144	Leptotrichia wadei ASV30
Gram Stain	Negative	Positive	Negative	Positive	Negative
Cellular Respiration	Facultatively Anaerobic	Obligate Anaerobe	Obligate Anaerobic	Anaerobic or Microaerophilic	Anaerobe
Descriptive	This type of bacteria is known for its infectious abilities. [32]	Association with Halitosis [33]	Found in mouth in plaque	A is a common bacteria found in plaque. [1]	Normal oral flora
Relative Abundance	Increased	Decreased	Increased	ASV144 IncreasedASV141 Decreased	Increased
Sulfate reducing Bacteria	No but possess pathways to protect from oxidative stress [32]	No [33]	No [34]	No [1]	Yes [35]

Alpha diversity measured by species richness and Chao 1 showed the same significant increase after exposure to NaHSO3 and a marginally significant increase upon exposure to Na2SO3. (Fig 8). However, no significant differences were identified with the Shannon or Inverse Simpson index.

Fig 8

Alpha diversity in F2 samples with sulfite treatment at time 0.

16S rRNA sequencing was used to determine species richness (based on relative abundance) for control and treated samples with Na2SO3 (A) and NaHSO₃ (B). A paired t-test showed that species richness increased significantly after treatment with NaHSO3 and was marginally significant after treatment with Na2SO3.

Baseline lysozyme activity for F2 samples compared to the respective number of viable cells (based on ATP activity) did not indicate a correlation of any type between these two parameters (S1 Fig).

Beta diversity

The PCA plot shows consistent changes in the oral microbial communities when comparing the control samples to the Na2SO3 treated samples of F2. As shown in Fig 9, the dissimilarity (beta-diversity) within the samples was large due to the possible micro-environment changes affected by many factors such as diet, hormonal status, etc. However, when treated with Na2SO3, the changes in the microbial community composition were towards almost the same direction, which indicates that the treatment of Na2SO3 caused consistent changes to the oral microbial community, even though their original structures were not similar.

Fig 9

Beta diversity of F2 Na₂SO₃ treated samples.

The PCA of all the ASVs from the control and Na2SO3 treated F2 samples, show consistent directions of changes in the microbial communities under the treatment of Na2SO3.

Discussion

Preservatives in food interact with the human microbiome first through the mouth and then the rest of the digestive tract. Sulfites are a common preservative added to a variety of foods and occur naturally in some fermented foods. Since being regulated as GRAS for use in food in 1958 by the US FDA, allowable amounts and applications have changed several times as it became clear that sulfites were causing moderate to severe (even fatal) health effects in some individuals [20,23,37,38] Mammals oxidize sulfite to sulfate with sulfite oxidase and some SRB use sulfate as an energy source, which may result in the production of H2S [39,40]. Both insufficient production of sulfite oxidase leading to an increase in several forms of sulfite reactive compounds, and oxidative stress from H2S on eukaryotic cells, may occur as the result of ingestion of sulfites. A recent study in rats showed that Na2SO3 (≧ 100ppm) causes death of gastric mucosal cells through oxidative stress [41]. This same study also looked at the effects of sodium sulfite (1mM) on lysozyme activity. They determined that Na2SO3 decreased the bacteriolytic activity of lysozyme in a time and dose dependent manner [41]. Other studies have shown a connection between certain types of SRB found in the colon and ulcerative colitis [42]. These studies provide evidence of mechanisms by which Na2SO3 may lead to both eukaryotic and prokaryotic cell death.

Our previous work indicated that sodium sulfite was bactericidal to three probiotic species of Lactobacillus and bacteriostatic to Streptococcus thermophilus, within 2–6 hours of exposure [24]. Sodium bisulfite was found to be bactericidal to all 4 probiotic bacteria also within 2–6 hours of exposure [24]. These studies established both the potency of these preservatives and the varying susceptibility of different types of bacteria when exposed under ideal culture conditions. The current study was conducted to evaluate the effects of these same sulfites on the mouth microbiome found in saliva to better simulate the effects of ingesting foods containing these preservatives.

ATP activity

Comparison of each individual’s control samples indicated that the viable number of cells were relatively consistent over the 5-week sampling time, which supports findings from other recent studies [2,5,10]. The most striking observations were the differences found in ATP activity (indicating viable cell counts), between controls and sulfite treated samples at both exposure times. Based on these results we can conclude that both sodium sulfite and sodium bisulfite, consistently and immediately (regardless of preservative type or sample origin) significantly reduced the number of viable bacterial cells in saliva samples. We are assuming this is a drop in the number of viable cells, but it could be partially due to sulfites interfering with ATP production, or ATP being utilized by SRB to metabolize the sulfites.

These results were also supported by our preliminary experiments on the mouth microbiome which examined the effects of sulfites on 12 saliva samples from 5 individuals over a three-month period. Very similar results of reduced ATP activity as described here were observed, with an average decrease in viable cells of 27% and 28% at time 0 for Na2SO3 and NaHSO3 respectively. Additional experiments observed changes in the microbial population in these saliva samples by recording OD600 readings over a 6.5-hour period. We observed an initial decrease in cell numbers in the treated which remained lower than controls throughout study, and an increase in cell numbers in the controls.

Lysozyme

Lysozyme activity did not vary significantly over the 5 weeks of sample collection/individual and there did not appear to be any correlation between the number of viable cells and lysozyme activity (Fig 3). If the population could be measured accurately to show the number of gram-negative vs. gram-positive bacteria present, a relationship might be found due to the greater impact of lysozyme on gram-positive cells. Significant differences in lysozyme activity were observed between individuals (Fig 2). Previous studies have corroborated our results of inter versus intra-individual lysozyme variability [43] and others have shown that lysozyme varies between individuals with respect to circadian rhythm [44].

Preliminary studies on the effects of Na2SO3 on lysozyme activity in saliva (S-lys) and on human recombinant lysozyme (HR-Lys) indicated a decreased initial rate profile of HR-Lys and to a lesser degree S-lys with sodium sulfite incubation. We hypothesize that this difference may be attributed to the rich mixture of biological components that compose salivary fluid, where sulfite may act on bacteria as well as nucleophiles and nonspecific inhibitors [45]. These early studies suggest that sodium sulfite would affect lysozyme function in human saliva and subsequently alter the mouth microbiome. However, we have yet to determine conclusively that sulfite inhibits salivary lysozyme activity and further studies are in progress. More studies are needed to look at the relationship between lysozyme activity, sulfites, and the makeup of the mouth microbiome.

16s rRNA sequencing

This study identified five major bacterial phyla (Fig 4) as the most abundant in all control and treated samples. These five phyla, Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria, are considered the “core microbiome” in the human mouth since they have been consistently reported as the main bacteria found in both healthy and diseased conditions [1,3,16,46]. However, significant changes in the saliva microbiomes were observed, dependent on the type of sulfite exposure. Alterations of the Firmicutes/Bacteroidetes ratio, which is widely accepted to have an important influence in maintaining normal intestinal and mouth homeostasis [1,3,16], was observed with Na2SO3 but not with NaHSO3 (Fig 5). A more shifted microbial community structure (relative abundance), but only a slight increase in the species richness (p< 0.10) was observed in the Na2SO3 treated samples. However, NaHSO3 samples showed a much higher alpha-diversity (p<0.05) despite showing far fewer changes in relative abundance (Figs 6–8). These results contrast with the similar results found with both sulfites in the combined ATP assays from all individuals (Fig 1). As for beta diversity, the PCA plot (Fig 9) shows consistent changes in the oral microbial communities when comparing the control samples to the Na2SO3 treated samples, while no similar pattern was found in the NaHSO3 treated samples. These findings, along with our previous studies [24] seem to indicate a difference in the selective potency of these two types of sulfites. One possible explanation for the increase in alpha diversity with both sulfites might be due to the toxic effect on certain predominant bacterial species (thereby lowering their relative abundance) that may have then revealed the presence of other species normally present in populations too low to detect [47].

A comparison of the sequencing data to the ATP assays (Fig 4A and 4B) from individual “F2” samples, indicates a significant decrease in cell numbers with both sulfite treatments. However, a greater change was observed with Na2SO3 vs. NaHSO3. It is interesting to note that a decrease in [DNA] of treated samples from individual “F2” was observed, with an average decrease of 18% (p = 0.34) in sodium bisulfite and 56% (p = 0.05) in the sodium sulfite treated samples (S3 Appendix). While there are many factors that may lead to an observed difference in [DNA], this data supports our observation of a 30% and 40% average decrease in viable cells in respective samples.

It is well established that DNA from both, recently lysed, as well as living cells may be counted in 16S rRNA gene targeted sequencing [2]. The difference in observed changes (dependent on sulfite type), between our observed sequencing and ATP activity may indicate the quantitative change threshold of viable cells needed in order to detect significance, in this method of sequencing, effectively [47].

Conclusions

Our results show that sulfites have a clear and significant impact on some bacterium types found in the mouth. We hypothesize that sulfite susceptibility/metabolism differences allow some bacteria found in saliva to increase in numbers while others decrease. Bacteria that produce sulfur nucleotide reductase enzymes (SRB) or have other mechanisms to avoid oxidative stress, are better able to survive, while those that don’t will be more susceptible to sulfites toxic effects. The connections of H2S production from some SRB and its impact on both oral and intestinal inflammation and disease has been previously reported [39,40,42]. Susceptibility of different types of bacteria to lysozyme and the effects of sulfites on lysozyme activity may also be a factor.

To summarize, sulfite food preservatives appear to be affecting the makeup of the mouth microbiome by more than one mechanism including death by oxidative stress to non-SRB bacterial types and an energy source for SRB bacterial types.

Studies on the microbiomes found in or on the human body are complex and in constant flux due to the environment. The use of more than one cell detection method to measure changes in mixed populations of bacteria existing in the mouth is recommended for more accurate and sensitive assessments. ATP tests used to detect changes in the number of viable cells in saliva samples after exposure to either sulfite revealed a significant decrease in cells in all samples, whereas changes identified through 16s rRNA sequencing were less consistent between the samples depending on the type of sulfite tested. Future studies are indicated to include more individual’s samples for 16s rRNA sequencing to compare to ATP assays, to examine connections between diseases of the digestive process and the intake of sulfite preservatives.

Baseline lysozyme vs.

ATP activity in F2 control samples.

(TIF)

Click here for additional data file.

Supplementary information on methods of treatment.

(DOCX)

Click here for additional data file.

Data corresponding to Figs 1–8.

(XLSX)

Click here for additional data file.

Raw data for statistical applications supporting Fig 1 and Table 1.

(XLSX)

Click here for additional data file.

[DNA] data from 16s sequencing.

(XLSX)

Click here for additional data file.

9 Dec 2021

Please address all concerns below raised by the reviewers, with particular importance to viability measurements.

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Reviewer #2: Partly

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: This study examines the effects of sulfite preservatives on saliva samples obtained from a limited number of volunteers (10 individuals) using the following endpoints: microbiota diversity and composition, microbiota viability, and lysosyme activity. The results are original and interesting. Several points are unclear and/or not sufficiently discussed.

1. Although the limitation in using the "ATP activity" test is discussed, I still do not really understand this term and what it exactly measured. If I understand correctly, this assay measure ATP in the samples, and if ATP is decreased, it can be presumed that bacterial cells have impaired metabolic activity and/or are dead cells. If this is correct, then it is not an "ATP activity"test, but a measure of ATP in the samples, thus considered as a net balance between ATP synthesis and ATP utilization by bacterial cells. This need to be better explained in terms of what is measured, and what it means in terms of bacterial metabolic activity and viability to make the most correct interpretation.

2. What could be the consequences of the effects of sulfite preservatives on microbiota in terms of oral diseases/dysfunctions. Please discuss.

3. Sulfite preservative are useful preservatives. So please indicate the possible beneficial over deleterious effects ratio of the use of sulfite preservative. What could replace them for preservation of food if needed?

4. Are there any available data indicating conversion of sulfite preservatives into hydrogen sulfide by the oral microbiota?

Reviewer #2: Major concerns:

1. At no point is it described why two different sulfite types were used / unclear what the significance of that was to this particular study.

2. Line 496 – I do not see where this conclusion (an energy source for SRB bacterial types) is directly supported by any data from this paper. In this reviewers opinion this is an appropriate hypothesis but remains speculative and not conclusive.

3. As written this reviewer must assume that all saliva samples were first diluted and then frozen (line 159). Then all downstream experiments are performed on samples that were presumably thawed prior to sulfite exposure. This means that all downstream experiments looking at cell viability and lysozyme activity were performed on samples that underwent at least one freeze-thaw cycle. This reviewer is concerned about how much a prior freeze-thaw cycle would impact the overall viability of all cells in the initial population as well as lysozyme activity pre/post freezing. Did the authors measure viability of fresh samples prior to then after freezing? The concern is that a large decrease in viability may have happened to all samples up front and this study is only assaying the smaller population of survivors which makes one wonder as to the ultimate relevance of the data.

4. How do the sulfite concentrations used in the assays here compare to the presumed sulfite concentrations in the mouth after consuming sulfite-containing food products? Even knowing if they were in the same order of magnitude would be sufficient but this reviewer would like to know how the test conditions compare to the presumed exposure during consumption.

Minor concerns:

1. Line 36 – “American diet” – potentially “North American diet” ?

2. Abstract seems fairly heavy with specific results and data and less of a summary of the entire body of work.

3. Line 67-8 – mentions colonization of aerobes but lists Veillonella which is an anaerobe.

4. Line 159 – participant age / gender recorded but no ethnicity demographics given. Was this included / considered in the metadata for downstream analysis?

5. Line 170 – ppm used for sulfite. Was this the final concentration in the saliva sample for each? Might be nice to give the Molarity for each in the final saliva sample.

6. Line 173-4 RPM given but g values not, it is unclear if this was sufficient centrifugation to reliably pellet all cells in a saliva sample reproducibly.

7. Line 217 – any rationale for using V3-V4 for oral samples? M. Eren et al PNAS 2014 (Oligotyping analysis of the human oral microbiome) indicates that V1-V3 better discerns oral species than V3-V5.

8. Line 430-1 – This might be somewhat addressed by looking at the relative abundance of each Gram positive phyla vs lysozyme status compared to Gram negative phyla vs lysozyme amounts.

9. Line 468-470 – this could also be sequencing of reagent / aqueous contaminants that show up in amplification of low-template abundance samples. Do these samples look more similar to the reagent control samples sequenced?

**********

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22 Jan 2022

Reviewer #1: This study examines the effects of sulfite preservatives on saliva samples obtained from a limited number of volunteers (10 individuals) using the following endpoints: microbiota diversity and composition, microbiota viability, and lysosyme activity. The results are original and interesting. Several points are unclear and/or not sufficiently discussed.

1. Although the limitation in using the "ATP activity" test is discussed, I still do not really understand this term and what it exactly measured. If I understand correctly, this assay measure ATP in the samples, and if ATP is decreased, it can be presumed that bacterial cells have impaired metabolic activity and/or are dead cells. If this is correct, then it is not an "ATP activity” test, but a measure of ATP in the samples, thus considered as a net balance between ATP synthesis and ATP utilization by bacterial cells. This need to be better explained in terms of what is measured, and what it means in terms of bacterial metabolic activity and viability to make the most correct interpretation.

The amount of ATP in each saliva sample is measured based on the luminescence produced due to the chemical reaction of the luciferase enzyme and luciferin present in the BacTiter-Glo reagent. We refer to this as “ATP activity” in that it is the direct measurement of ATP driving the luciferase reaction, however it is also considered a measure of the metabolically active (viable cells) in the samples that provide the ATP (when lysed) for the reaction, and therefore the amount of ATP in the samples. Revisions for clarity can be found in line # 130-136 in the revised manuscript. The concentration of adenosine triphosphate (ATP) present in living cells can be quantified using a proportional luminescent signal to observe immediate changes in the numbers of viable bacterial cells present in a sample. Sensitivity as low as 0.0001nM ATP, reflecting the test population, is high due to the rapid loss of ATP in non-living cells [25]. This method implements a recombinant luciferase enzyme to oxidize luciferin in the presence of ATP and oxygen to produce oxyluciferin and light.

2. What could be the consequences of the effects of sulfite preservatives on microbiota in terms of oral diseases/dysfunctions. Please discuss.

Changes in the mouth microbiome and diseases related to these changes are still in the early stages of discovery. This is the first study (that we are aware of) that looks at the effects of a food preservative on the mouth microbiome. However, there have been several recent studies showing changes in the mouth microbiome associated with and contributing to diseases found in the oral cavity, gastrointestinal system, liver cirrhosis, certain cancers, endocrine system diseases like diabetes and obesity, some diseases of the nervous system, and cardiovascular disease. These studies were reviewed in a 2018 paper we cited [1] on line #’s 80-84 in the revised manuscript and similar studies which were reviewed in a 2017 paper [10] that also spoke to the possible diagnostic potential of the state of the mouth microbiota and certain diseases.

3. Sulfite preservative are useful preservatives. So please indicate the possible beneficial over deleterious effects ratio of the use of sulfite preservative. What could replace them for preservation of food if needed?

Sulfites have been utilized as a food preservative going back to the Roman days. They have been found to be very effective in their role to limit bacterial growth in many different food types. However, the effects of sulfites on human health has been noted many times over the past 60 years and have led to numerous changes in the regulations of sulfites in food. This was discussed in more detail in our first paper on sulfites effects on 4 probiotic bacteria [24] . Some studies have shown sulfites to be dangerous to humans when ingested at levels as low as 1 ppm [1,3-7]. Due to insufficient statistical data regarding individual sensitivities and consumer intake levels [8,9], it has been difficult to identify the exact level at which these preservatives become harmful. Reactions can occur between these additives and primary constituents naturally present in food, as well as during preparation and digestion, contributing to this conundrum.

Our studies did not look at alternatives to sulfites for food preservation however there are a number of preservatives that we have performed preliminary testing on (but not published) that do not show the toxicity that sulfites have on the mouth bacteria (based on ATP studies). Some herbs, hypertonic environments with high salt or sugars and lowered pH using citric acid or vinegar along with fermentation are all methods of food preservation that are less likely to disrupt the microbiome of the mouth or gut.

4. Are there any available data indicating conversion of sulfite preservatives into hydrogen sulfide by the oral microbiota?

The following two references from our manuscript describe the common presence of sulfate reducing bacteria in the mouth and the conversion of sulfates to hydrogen sulfide [39] and the reduction of sulfites to sulfates (in the gut) [40]. The presence of sulfite reducing bacteria in the mouth has not been confirmed to our knowledge.

From reference #39

“In this context, an increased incidence of sulfate-reducing bacteria (SRB) in the oral cavity has been found, which are a part of the common microbiome of the mouth.”

“The amount of SRB in the oral cavity is limited by the amount of sulfate available. Potential sources of sulfate in the subgingival region include free sulfate in the pocket fluid and glycosaminoglycans and sulfur-containing amino acids (cysteine and methionine) from periodontal tissues. SRB then metabolize the sulfate to H2S.”

From reference #40

“Another essential reaction of the process is sulfite reduction, resulting in the product of APS reduction [4,44]. Sulfite reduction is catalyzed by dissimilatory sulfite reductase (EC 1.8.99.1). This enzyme reduces sulfite to sulfate [44]. Sulfide reductase also plays an important role in the process of assimilatory sulfate reduction due to sulfide ion production. These sulfides are part of amino acids containing sulfur, such as methionine and cysteine. SRB may have several types of sulfide reductases that can be used for identification. These reductases are desulfoviridin, desulforubin, desulfofuscidine, and protein P582.”

“Sulfite reduction is the last reaction in the process of DSR. Reactive sulfite is converted into toxic sulfide, and then it is released out of the bacterial cell. This reaction is catalyzed by the enzyme sulfite reductase.”

Eukaryotes, including mammals, have sulfite oxidase in the mitochondria of all their cells. This enzyme oxidizes sulfites to sulfates [Andrei V. Astashkin, in Methods in Enzymology, 2015]. It has been established that there are individuals with deficiencies in this enzyme [Mellis, January 2021] that can lead to severe reactions to sulfites and even with normal levels of the enzyme, the ability of the enzyme to keep up with high levels of sulfites appears to be challenged. There have been studies that have observed variable levels of sulfite oxidase gene expression dependent on the specific tissues in humans and rats [Woo et al., 2003], however we have not been able to find a study that specifically looks at levels produced in the mouth.

Reviewer #2: Major concerns:

1. At no point is it described why two different sulfite types were used / unclear what the significance of that was to this particular study.

The reason we looked at the effects of both sodium sulfite and sodium bisulfite at the concentrations indicated was based on the results from our previous paper that tested the effects of these two types of preservatives on four different beneficial bacteria species. In this study [24] our results are summarized here:

“All three Lactobacillus species stopped increasing in number within 2 hrs of exposure at concentrations between 250–750 ppm NaSO3, (Fig 2), and were found to be non-viable within 4 hours of exposure, at concentrations ranging between 1000 -3780ppm, dependent on species tested (Table 3). Streptococcus thermophilus also stopped increasing in number within two hours of exposure at concentrations between 250–500ppm; however, the bacteria were still viable in all concentrations of sodium sulfite tested up to 6 hours exposure time. These results indicate a bacteriostatic effect from sodium sulfite on all bacteria within two hours of exposure and a bactericidal effect on all the Lactobacillus species by 4 hours of exposure

Sodiium bisulfite: All bacteria stopped increasing in cell number within two hours of exposure at sodium bisulfite concentrations between 250–500 ppm NaHSO3, (Fig 3). Sodium bisulfite was observed to be bactericidal at 2 hours exposure to L. casei and L. rhamnosus at 1000ppm. Lactobacillus plantarum was found to be non-viable by 4 hours exposure at ≥ 1000ppm. Sodium bisulfite was bactericidal to S. thermophilus at 6 hours exposure and ≥ 1000 ppm.”

This previous study showed us that the effects of sulfites varied depending on the bacteria genus and species and the type and concentration of the sulfite tested. This was discussed briefly in the introduction (line # 113-116 revised manuscript) and in the discussion (line # 401-406 revised manuscript). Our current study was done to observe the effects of sulfites on communities of bacteria found in saliva, to assess an environment closer to one that is “in-vivo”. We have added some additional information to those sections to make this information clearer to the reader.

2. Line 496 – I do not see where this conclusion (an energy source for SRB bacterial types) is directly supported by any data from this paper. In this reviewer's opinion this is an appropriate hypothesis but remains speculative and not conclusive.

We are in agreement that the idea that sulfites may be serving as an energy source for some SRB bacteria should still be considered a hypothesis rather than a conclusion. Our statement was based on work from others (citation #39 and see response to reviewer 1’s question #4) and our observations of changes in relative abundance of 9 ASV’s after treatment (line # 344-350 revised manuscript and Table’s 2A and 2B).

Nine different anaerobic ASV’s exhibited significant changes in relative abundance with sulfite treatments. Four out of the five that showed an increase in abundance were Gram negative and three out of those five were sulfite reducing bacteria (SRB) or have the ability to avoid oxidative stress. Four ASV’s decreased in relative abundance with sulfite treatments. Three out of the four were Gram positive and one out of the 4 was a SRB.

The common presence of SRB bacteria in the mouth has been established by others and our studies indicated a trend towards increasing abundance in SRB’s and a decrease in abundance of non-SRB’s. Line # 486-500 in the revised manuscript has been updated to make it more clear that our statement is a hypothesis rather than a conclusion.

3. As written this reviewer must assume that all saliva samples were first diluted and then frozen (line 159). Then all downstream experiments are performed on samples that were presumably thawed prior to sulfite exposure. This means that all downstream experiments looking at cell viability and lysozyme activity were performed on samples that underwent at least one freeze-thaw cycle. This reviewer is concerned about how much a prior freeze-thaw cycle would impact the overall viability of all cells in the initial population as well as lysozyme activity pre/post freezing. Did the authors measure viability of fresh samples prior to then after freezing? The concern is that a large decrease in viability may have happened to all samples up front and this study is only assaying the smaller population of survivors which makes one wonder as to the ultimate relevance of the data.

Your assumption is correct in that the samples were frozen and thawed prior to sulfite exposure. The details of this process and the possible inherent errors due to this protocol is discussed in the “Supporting information”. In preliminary studies, we tested fresh vs. frozen and thawed samples of saliva as well as pelleted and resuspended in PBS and those that were only treated and then ATP tested. The results trended towards a slight reduction in the number of cells which we attributed primarily to pipetting errors. However, we hypothesized that the loss of cells to pipetting errors or the freeze thaw cycle would be similar between controls and treated samples. This is where relatively large numbers of samples were important to statistically verify the trends we observed as a decrease in cell viability with sulfite treatments.

In addition to the study presented here, we initially assayed 5 individuals over a 3 month period (12 samples/person). In this set of experiments, some samples from the same individual were treated on different days, and ATP tested (sometimes) in different assays. Despite these variables, the results from these experiments showed almost identical results in the decrease of viable cells with treatment compared to our current study, which treated all of the samples from any one individual on the same day and included all ATP testing in the same assay. In addition to the ATP data in the preliminary study, samples were tested for growth by observing OD600 readings over a 6.5 hour period. We observed an initial decrease in cell numbers in the treated which remained lower than controls throughout study, and an increase in cell numbers in the controls. This preliminary data was discussed briefly in the discussion section in line #’s 419-427.

Lastly the [DNA] of the sequenced samples supported our ATP findings in showing a decrease in [DNA] in the treated vs. control samples (line #’s 475-478 and appendix S3 in revised manuscript).

There are also several other studies that have utilized -80℃ or - 20℃ freezing of saliva samples with later thaws and testing [5, 6, 11, 12, 43], some with more than one freeze thaw cycle. It is not ideal but we feel that it does still allow for the comparison between treated and untreated samples even with the inherent variabilities from this type of protocol.

4. How do the sulfite concentrations used in the assays here compare to the presumed sulfite concentrations in the mouth after consuming sulfite-containing food products? Even knowing if they were in the same order of magnitude would be sufficient but this reviewer would like to know how the test conditions compare to the presumed exposure during consumption.

This is the million dollar question. As a first step we can test levels that are allowable in food (which we did) and see if there are any significant effects observed. In our previous study (see answer to question 1, reviewer 2), we observed bacteriostatic and bactericidal effects at much lower concentrations of sulfites then tested here but with longer exposure times. We tested 6 other common food preservatives in preliminary experiments at GRAS levels and have not observed any to have as significant of an effect on the microbiota found in saliva. In fact, many have had no effect (i.e. Nitrites) and some have actually increased the number of cells in saliva based on ATP (i.e. Methyl Parabans).

Other studies have looked at the likelihood of people ingesting more than the allowable levels on a regular basis and have found that it is a common occurrence. In one study by Leclercq et al. “It was shown that the diets obtained from these foods would lead to an intake of 23mg/day in children and 50mg/day in adults (both slightly above the ADI for respectively a 30kg child and a 60kg adult). Among all sulphite-containing foods, the highest contributors to the intake were dried fruit and wine, both ingested without further treatment. The analysis of specific consumption data confirmed the existence of a risk of exceeding the ADI related to sulphite residue levels in wine.”

The problems faced when trying to determine the “safe” amount of a food preservative for a population is summarized by Fazio and Warner here:

“The fate of added sulfites is highly dependent on the chemical nature of the food, the type and extent of storage conditions, the permeability of the package and the level of addition. The combination with organic constituents, the equilibrium between the various inorganic forms, the volatilization of sulfur dioxide and the oxidation to sulfates are all important reactions, and their relative importance will depend mostly on the food involved.” (Fazio & Warner,1990)

Minor concerns:

1. Line 36 – “American diet” – potentially “North American diet” ?

Changed in revised manuscript.

2. Abstract seems fairly heavy with specific results and data and less of a summary of the entire body of work.

Agreed, however with the 300 word limit it was difficult to present the experiment and results in a manor generally required within this limited word count.

3. Line 67-8 – mentions colonization of aerobes but lists Veillonella which is an anaerobe.

This was not intended, it has been corrected in revised manuscript (line #68).

4. Line 159 – participant age / gender recorded but no ethnicity demographics given. Was this included / considered in the metadata for downstream analysis?

It was not included or considered for this data set.

5. Line 170 – ppm used for sulfite. Was this the final concentration in the saliva sample for each? Might be nice to give the Molarity for each in the final saliva sample.

Added in lines 169-171 in revised manuscript.

6. Line 173-4 RPM given but g values not, it is unclear if this was sufficient centrifugation to reliably pellet all cells in a saliva sample reproducibly.

This was a typo that should have said 4600 RCF’s rather than RPM’s. We corrected this in the revised manuscript and added the equivalent in RPMs which is 7000 RPMs (line # 173-174 in revised manuscript).

7. Line 217 – any rationale for using V3-V4 for oral samples? M. Eren et al PNAS 2014 (Oligotyping analysis of the human oral microbiome) indicates that V1-V3 better discerns oral species than V3-V5.

We were unaware of the research showing a higher degree of specificity using V1-V3 for the oral microbiome. We went with the V3-V4 region based on other recent papers on the microbiome (2,5) and from the advice of Zymo, the company that performed the sequencing of our samples. However, we are encouraged by the similarities in the results of both sequencing and ATP assays for individual F2.

8. Line 430-1 – This might be somewhat addressed by looking at the relative abundance of each Gram positive phyla vs lysozyme status compared to Gram negative phyla vs lysozyme amounts.

This would be interesting to look at with more sequencing data. In our sequencing data which is from one individual (32 samples) we see no change in the relative abundance of gram positive or gram negative bacterial types with sodium bisulfite treatment, however we do see a 6% decrease in gram positive and a 6% increase in gram negative bacterial types with sodium sulfite treatment (based on phylum data).

9. Line 468-470 – this could also be sequencing of reagent / aqueous contaminants that show up in amplification of low-template abundance samples. Do these samples look more similar to the reagent control samples sequenced?

We are not completely sure what is being asked/commented on here. From the manuscript “One possible explanation for the increase in alpha diversity with both sulfites might be due to the toxic effect on certain predominant bacterial species (thereby lowering their relative abundance) that may have then revealed the presence of other species normally present in populations too low to detect [47].”

Our samples did not look like the controls used by Zymo and the negative controls were very clean. In the bisulfite treated and control samples the majority (94.24%) of the sequences were classified into species level and for the sodium sulfite treated and control samples 93.84% of the sequences were classified into the species level.

From Zymo:

For projects that included DNA purification from raw samples, the ZymoBIOMICS® Microbial Community Standard was used as positive control; a blank extraction sample was used as a negative control.

Submitted filename: Response to reviewers .doc

Click here for additional data file.

28 Feb 2022

Sulfite preservatives effects on the mouth microbiome: changes in viability, diversity and composition of microbiota.

PONE-D-21-31327R1

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Reviewer #1: All comments have been addressed

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2. 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: Yes

**********

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Reviewer #1: Yes

**********

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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

**********

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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

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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: All my comments have been taken into consideration, and for some of them used in order to revise the manuscript. The responses to the questions are adequate.

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7 Mar 2022

PONE-D-21-31327R1

Sulfite preservatives effects on the mouth microbiome: changes in viability, diversity and composition of microbiota.

Dear Dr. Irwin:

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