Effect of gluten-free diet and antibiotics on murine gut microbiota and immune response to tetanus vaccination

Pernille Kihl; Lukasz Krych; Ling Deng; Lars H Hansen; Karsten Buschard; Søren Skov; Dennis S Nielsen; Axel Kornerup Hansen

doi:10.1371/journal.pone.0266719

. 2022 Apr 13;17(4):e0266719. doi: 10.1371/journal.pone.0266719

Effect of gluten-free diet and antibiotics on murine gut microbiota and immune response to tetanus vaccination

Pernille Kihl ^1,^#, Lukasz Krych ^2,^#, Ling Deng ^2,^#, Lars H Hansen ^3,^4,⁵, Karsten Buschard ⁶, Søren Skov ¹, Dennis S Nielsen ², Axel Kornerup Hansen ^1,^*

Editor: Brenda A Wilson⁷

PMCID: PMC9007335 PMID: 35417506

Abstract

The purpose of this study was to compare the effect of a gluten-free diet and/or antibiotics on tetanus vaccine induced immunoglobulin G titers and immune cell levels in BALB/c mice. The gluten-free diet was associated with a reduced anti-tetanus IgG response, and it increased the relative abundance of the anti-inflammatory Bifidobacterium significantly in some of the mice. Antibiotics also led to gut microbiota changes and lower initial vaccine titer. After a second vaccination, neither gluten-free diet nor antibiotics reduced the titers. In the spleen, the gluten-free diet significantly increased regulatory T cell (T_reg) fractions, CD4⁺ T cell activation, and tolerogenic dendritic cell fractions and activation, which extend the downregulating effect of the T_reg. Therefore, the systemic effect of the gluten-free diet seems mainly tolerogenic. Antibiotics reduced the fractions of CD4⁺ T and B cells in the mesenteric lymph nodes. These results suggest that vaccine response in mice is under influence of their diet, the gut microbiota and the interplay between them. However, a gluten-free diet seems to work through mechanisms different from those induced by antibiotics. Therefore, diet should be considered when testing vaccines in mice and developing vaccines for humans.

Introduction

Although saving millions of lives worldwide, many vaccines are not universally efficient, and varying or even lacking efficacy poses a major problem in some populations. Multiple reports on the efficacy of vaccines reveal a reduced response in humans from low-middle income countries compared to high income countries [1], which may be due to genetic background, immune status, vitamin status, age and other factors [2–4].

The gut microbiota (GM) is a complex consortium of trillions of microorganisms strongly influencing host health and disease, which has colonized the gut of all mammals [5–9]. A core GM is established in early life through contact with the mother, early life diet, and extrinsic factors [10]. Later in life, the GM composition and development of both humans and mice is to a large extent influenced by extrinsic factors with diet being among the most important ones [11–13]. Diet with reduced amounts or no gluten changes the GM composition in both humans [14] and mice [15–17]. Gut associated lymphoid tissue (GALT) is an important mediator of GM immune impacts, which is regulated via pattern recognition receptors (PRRs), such as Toll-like receptors (TLRs), and the intracellular nucleotide-binding oligomerization domain, when stimulated by gut microbial associated molecular pattern (MAMPs) [18]. GM communicates with the lungs through the gut-lung axis, which is considered of importance for the risk of developing severe disease in humans infected with respiratory viruses [19]. It has recently been proposed that the low incidence of clinical COVID-19 in some regions may be due to their intake of a mainly gluten-free diet [20].

Therefore, there are strong indications that GM composition influences host immune responses, and, thereby the vaccine activated immune response [21, 22]. Vaccine responses are initiated when naive T cells recognize the antigen associated with Major Histocompatibility Complex (MHC) class II molecules on the surface of antigen presenting cells. Dependent on the microbiota composition gut dendritic cells will secrete IL-12 to favour the development of T helper cells type 1 (Th1) [23], while the TLRs of some specialized tolerogenic dendritic cells induces the formation of regulatory T cells (T_reg), which regulate the response towards microbes by secreting IL-10 [24]. A gluten-free diet has previously been shown to increase the number of T_reg in the gut of mice [25, 26], which have consequences, such as reduced incidence of type 1 diabetes in non-obese diabetic (NOD) mice [15], and reduced risk of islet autoimmunity in humans [27], which are both Th1 dependent. Type 1 diabetes incidence in NOD mice is also reduced by the induction of tolerance to gliadin, which is accompanied by increased proportions of IL-10 positive T_reg [26]. As the GM differs essentially between global regions, vaccine response discrepancies between children from low-middle income and high-income countries may be caused by GM composition differences [28]. Children from rural Burkina Faso develop a GM distinctly different from that of Italian children, with the former being enriched in functions well suited to extract energy from the carbohydrate rich diet of rural Burkina Faso [29]. In Bangladeshi infants there is a positive correlation between vaccine responses and the relative abundance of fecal Actinobacteria, which includes Bifidobacterium spp. often associated with an anti-inflammatory response [30]. Furthermore, a lower vaccine response was associated with high relative abundances of fecal Clostridiales, Enterobacteriales, and Pseudomonadales [30].

Antibiotics, such as ampicillin, may have a strong impact on GM, which causes decreased relative abundances of T_reg and Th in both mice [31] and humans [32]. An early life germ-free period in mice induces long lasting increased activity of CD4⁺ T cells, i.e. Th1, Th2, and T_reg [11], and it is known in mice that antibiotic-driven dysregulation of the GM can modulate immune responses to vaccines in early [33] and in late life [34]. Ampicillin has been hypothesized to block humoral vaccine responses in humans, because its blocking of a specific protein the lack of may induce a transient immunodeficiency [35]. Also, bacterial flagellin stimulation of Toll-like receptor 5 (TLR5) is needed to drive antibody production after influenza vaccination [36]. Neomycin treatment of mice experimentally infected with Influenza A virus increases the disruption of the lung tissue structure and increases lung weight compared to virus infected control mice [37], but local or distal injection of Toll-like receptor (TLR) ligands rescue this neomycin induced immune impairment [38].

We hypothesized that gluten-free diet induced GM perturbations would influence vaccine response in mice. We found it most relevant to study this in relation to a vaccine based upon a bacterial product, and, therefore, we chose to study the impact on a tetanus toxoid vaccine, although this vaccine generally has high immunogenicity and protection globally [39]. Tetanus toxoid is a bacterial product, which when used as vaccine, is known to raise a strong Th reaction [40], and it has traditionally been used with aluminium oxide hydrate adjuvant, which is expected to drive a Th2 rather than a Th1 response [41]. An increase in T_reg relative abundance and subsequent IL-10 secretion, as induced by a gluten-free diet, will reduce both Th1 and Th2 and, thereby antibody producing B cell relative abundance [24, 42]. Therefore, we used the production of specific IgG as primary readout in mice fed a gluten-free or a standard gluten containing diet. To block the impact of the GM, some of the mice were treated or not treated with ampicillin.

Methods

Mouse experiments

Experiments were approved by the Animal Experiments Inspectorate, Ministry of Food, Denmark and carried out according to the EU Directive 2010/63/EU on the Protection of Vertebrate Animals used for Experimental and Other Scientific Purposes, and the Danish Animal Experimentation Act (LBK 474 from 15/05/2014). Female BALB/cBomTac mice (Taconic Europe A/S, Ejby, Denmark) health monitored at the breeders and in the experimental facilities, revealing no infections listed in the FELASA guidelines [43], were used. At arrival, they were individually ear marked, weighed, and housed in an AAALAC accredited barrier protected facility. A standard tetanus vaccine for human use (Tetanus vaccine “SSI”, D.SP.NR 8767) with 6 LF/ml tetanus toxoid dissolved in aluminium oxide, hydrate ad 1 mg Al/ml, (Statens Seruminstitut, Copenhagen, Denmark) was used. An equal dose of saline (placebo) was administered to the unvaccinated groups. Doses were 0.03 ml (Study A and B) and 0.04 ml (Study C) per mouse given in the neck region. The diets used were either a standard wheat based gluten containing Altromin 1324 diet or a modified Altromin 1334 diet (‘Altromin modified’) (‘Altromin’; Altromin, Lage, Germany), in which wheat protein was replaced with casein as previously described [44]. The mice had free access to drinking water and were all fed ad libitum diet. Food consumption was monitored by weight of food administered versus eaten. Ampicillin (Ampivet, Boehringer Ingelhem, Germany) was dosed in the drinking water as 1 gram pr. liter from arrival to euthanasia, while non-treated groups received standard tap water. Upon termination, the total blood volume was collected from the retro-orbital veins into sterile tubes (Eppendorf, Germany), under anaesthesia with fentanyl, fluanisone and midazolam (i.e. 1:1 Hypnorm/Dormicum mixture: 0.315 mg/ml fentanyl + 10 mg/ml fluanisone (VetaPharma, Leeds, UK) and 5 mg/ml midazolam (Roche, Brøndby, Denmark)). At each blood collection, the blood was stored on ice for coagulation for approximately one hour before being centrifuged (500 x g, 10 min). Serum was separated (Micronic tubes) and stored at -20°C until used for determining of anti-tetanus titers by ELISA. The overall structures of all studies are shown in Fig 1.

Fig 1 — We set up three studies in BALB/cBomTac mice, to investigate the influence of gut microbiota manipulations on the response to a tetanus vaccine. Two studies (A and B) to study the impact of either a gluten-free diet or antibiotics on the antibody production after a boosted vaccination regime, and one study (C) to study the immediate impact of one vaccination on immune cells counts in gluten-free fed or antibiotics treated mice. In study A we boosted with a second vaccination after two and a half weeks, while we in study B considered that his might be too short and did the boosting after four weeks. In study C we used only one vaccination, because the aim was to see the cell counts in relation to our observations after the first vaccination in study A and B, and, therefore, we also sampled the animals only one week later. Two diets were used, i.e. the standard wheat based Altromin diet (Altromin), and a modified Altromin diet in which wheat protein was replaced with casein (Gluten-free). ‘Antibiotics’ indicates that mice were dosed with 1 gram ampicillin per liter drinking water. Control indicates that it is a group on a standard Altromin diet (with gluten) and either vaccinated or not vaccinated. Timelines illustrate the course of the study, and analyses performed.

Study A: Impact of gluten on primary and boosting vaccination

Sixty-three mice, aged six weeks upon arrival, were randomized into three groups of each 21 animals. Two groups were fed Altromin and one group was fed Altromin modified. The Altromin and the Altromin modified group were vaccinated at eight weeks of age and again two and a half weeks after arrival, while the other Altromin group were injected at same time points with placebo (Fig 1A). Body weight of the mice, as well as food consumption was monitored throughout the experiment, and all mice were euthanized and sampled three and a half week after the boosting.

Study B: Impact of antibiotics on primary and boosting vaccination

Forty mice, aged five weeks upon arrival, were randomized into two groups of each 20 mice, which were fed Altromin. One group received ampicillin in the drinking water. All mice were vaccinated at eight weeks of age and again four weeks later (Fig 1B). Body weight of the mice was monitored upon arrival subsequently throughout the experiment. Body weight of the mice, as well as food consumption was monitored throughout the experiment, and all mice were euthanized and sampled three weeks after the boosting.

Study C: Antibiotic impact on initial immune functions after primary vaccination

Sixty mice aged five weeks at arrival were randomized into four groups of 15 mice per group. Two groups were fed Altromin and two groups were fed Altromin modified, and one Altromin and one Altromin modified group received ampicillin in the drinking water. All groups were vaccinated at nine weeks of age and euthanized and sampled one week later (Fig 1C).

Gut microbiota characterization

Fecal samples were collected weekly in sterile Eppendorf tubes from arrival until euthanasia, and stored at -80°C until DNA extraction. Immediately after euthanasia by cervical dislocation, cecum content samples were removed, kept on wet ice and stored at -80°C. DNA was isolated and extracted from the fecal and cecal samples collected using the DNeasy PowerSoil Kit (# 12888, Qiagen, Germany) following the manufacturer’s instructions, but with addition of a bead beating step to increase lysis of bacterial cells. DNA purities and concentrations were determined using a Nanodrop 1000 spectrophotometer (Thermo scientific, USA) prior to being stored at -80°C. The prokaryotic component of the mouse gut microbiota was characterised by 16S rRNA gene amplicon sequencing. 454 FLX-based 16S rRNA gene sequencing (Study A) was carried out at the National High Throughput DNA Sequencing Centre, University of Copenhagen, Denmark using tag-encoded 454/FLX Titanium (Roche) pyro-sequencing of the V3 and V4 region of the 16S rRNA gene as previously described [45]. NextSeq (Illumina) based 16S rRNA gene (V3-region) amplicon sequencing (Study B and C) was carried out as follows: Total DNA was adjusted to 10 ng/ul, and 5 ul were added to the PCR reaction setups containing 12 ul of Accuprime SuperMix II (ThermoFisher scientific, USA), 1 ul Primer Mix (10 uM nxt_338F TCGTCGGCAG CGTCAGATGT GTATAAGAGA CAGACWCCTA CGGGWGGCAGCAG and 10 uM nxt_518R GTCTCGTGGG CTCGGAGATG TGTATAAGAG ACAGATTACC GCGGCTGCTGG) and 7 ul of H₂O. The V3 region of the 16S rRNA gene was amplified by the following program; 95°C 2 min, 33 cycles of 95°C 15 sec, 55°C x 15 sec and 68°C x 30 sec, cooled down to 4°C before the final extension of 4 mins at 68°C. The amplicons were checked by agarose gel electrophoresis and 2 ul was used for the indexing PCR, if the amplification was successful, PhusionHF Mix (ThermoFisher scientific, USA) and different S5 and S7 primers (20 uM) were combined with the 1st PCR product and went through the following tagging PCR process, 95°C 2 min, 13 cycles of 95°C 15 sec, 55°C 20 sec and 68°C 20 sec, followed by 5 min final extension at 68°C. The indexed amplicons were then purified by AMpure XP beads manually or using a Biomek 4000 workstation as described by the manufactures. The final concentrations of the purified amplicons were measured by Qubit HS dsDNA reagents, each product were mixed in equal concentrations (5 ng per sample) and subjected to the Illumina Nextseq550 platform.

Sequencing data analysis

The raw dataset generated using tag-encoded 454/FLX Titanium (Roche) pyrosequencing were analysed as previously described [46]. The raw data generated by Illumina NextSeq based amplicon sequencing was processed as previously described [47]. The relative abundance tables generated by both methods were further analysed using QIIME pipeline (V 1.9.1) [48]. Details are provided below. All samples have been normalised by subsampling prior to the analysis setting the subsampling value to the 85% of reads within the most indigent sample (5,900; 10,000 and 20,000 reads/sample for study A,B and C respectively).

Tetanus specific IgG

Tetanus specific IgG in serum was tested in a pre-coated ELISA kit (XpressBio, mouse anti-tetanus toxoid IgG ELISA Assay, # IM-202, Thurmont, MD, USA). The standards, as well as all samples, were tested in duplicates on 96 wells plates. The plates were read at 405 and 450 nm on a microplate reader (Bio-Rad, model 550, Hercules, CA, USA), before being analyzed (Microplate manager, version 5.2.1, Bio-Rad). The samples were diluted 1:350 and treated according to manufacturer’s instructions including the setup of a standard curve to calculate antibody titers from OD values.

Serum cytokines

In serum diluted 1:1000 collected from the total blood collection at euthanasia from mice in study A cytokines Granulocyte Macrophage Colony-Stimulating Factor (GM-CSF), interferon gamma (IFN-γ), interleukin 1 alpha (IL-1α), IL-2, IL-4, IL-5, IL-6, IL-10, IL-17 and tumor necrosis factor (TNFα) were measured with a 10plex Th1/Th2 mouse FlowCytomix Kit (Bender MedSystems, Austria), as well as with FlowCytomix Simplex Kit for IL-18 and IL-12p70 (Bender MedSystems, Austria) on a BD FacsCanto Flow Cytometer (BD Biosciences, Denmark) in accordance with manufacturer’s instructions. Data were processed with FlowCytomix Pro 2.4 Software (BD Biosciences).

Spleen gene expression

Immediately after euthanasia the spleens of all mice from study B were harvested and frozen at -80 in RNAlater (Sigma Aldrich, St. Louis, USA). The extraction of total RNA and quality analysis, cDNA synthesis, specific primer design, pre-amplification and exonuclease treatment, and qPCR was performed as previously described [49]. Expressions of the genes in S1 Table were measured on a Fluidigm Biomark platform (Fluidigm Europe B.V., Amsterdam, Netherlands).

Fluorescence-activated cell sorting (FACS)

Immediately after euthanasia, the spleens and mesenteric lymph nodes of mice in study C were sampled and cells were prepared in PBS according to our flow preparation protocol (https://osf.io/s47np/). The cells were analysed by an Accuri C6 flow cytometer and software (Accuri Cytometers Inc., Ann Arbor, USA) for the markers shown in Table 1 as previously described [44] using AH Diagnostics antibodies (Tilst, Denmark). For FACS 1–2 million cells were labelled. At each level 10,000 cells were counted. For rationalization some antibodies were only tested on randomly selected mice, and 5, 10 or 15 mice were tested on each level (Fig 5A and 5B). In some groups some of the preparations were unsuccessful and, therefore, n was reduced accordingly.

Table 1. Markers and gates for flow cytometry.

List of cell subsets investigated with fluorescence-activated cell sorting (FACS), as well as the marker used and gate from which it is defined, on cells extracted from mesenteric lymph nodes and spleen, from female BALB/c mice euthanized one week after a single injection of a tetanus vaccine.

Cell line	Marker	Cell gate
T helper cells and regulatory T cells (Th & T_reg)	CD4⁺	All live cells
Activated CD4⁺ T-cells	CD25⁺/ CD69⁺ / CD25⁺CD69⁺	CD4⁺
Regulatory T cells (T_reg)	FoxP3⁺	CD4⁺ CD3⁺
Follicular T-cells	CXCR5⁺	CD4⁺ CD3⁺
Cytotoxic T-cells	CD8⁺	All live cells
Activated cytotoxic T-cells	CD69⁺	CD8⁺
B-cells	CD19⁺	All live cells
Macrophages	F4.80⁺	All live cells
Activated DCs	CD80⁺	CD11c⁺
Tolerogenic DCs	CD11b⁺	CD11c⁺
Major Histocompatibility complex II	MHCII⁺	CD11c⁺

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Fig 5 — Flow assisted cell sorting (FACS) data (See Table 1) from the mesenteric lymph nodes (A) and the spleens (B) of female BALB/cBomTac, which were either fed standard wheat based Altromin diet or a modified gluten-free Altromin diet (GF). Mice on both diets were either given ampicillin (AB) in the drinking water (Antibiotics; gluten-free + antibiotics) or given pure drinking water (Gluten-free; vaccinated control). All mice were vaccinated with a tetanus vaccine (Vacc) and one week later MLN were sampled. Only data being significantly different between the groups are shown. R indicates that data have been ranked before statistical tests due to the lack of equal variances and/or normal distribution. Over all p-values are the outcome of two-way ANOVA for the two factors ‘gluten-free’ and ‘antibiotics’, while the values on the comparison lines are the p-values for the post-hoc Dunnett’s test comparing the Vacc GF, Vacc AB and the Vacc GF AB with the Vacc group.

Statistics

Antibody titers were ranked and analysed in Minitab 20.4 (Coventry, UK) by a one-way ANOVA with Tukey’s post hoc comparisons (Study A and B) or a general linear model two-way ANOVA (Study C). Variances of antibody titers were compared with Levene’s test (Minitab). ELISA data were corrected for plate variation prior to statistical analysis. FACS data were ranked and tested by a two-way general linear model for the factors gluten-free and antibiotics (Minitab) and Dunnett’s post hoc test compare the gluten-free, antibiotics and combined groups with the gluten group (GraphPad Prism 9, San Diego, USA). The F test was applied to compare the variation in titers between two groups (Prism). Weight data were tested in a two-way general linear model for the factors gluten-free (Study A), antibiotics (Study B), and vaccination (Study A), and with a fixed nesting of time (Minitab). Fold change data from gene expression analysis were subjected to Kruskal–Wallis test (Minitab) and P-values were corrected with false discovery rate (FDR) with the Benjamini Krieger Yekutieli method (Prism). Growth curves were compared by a repeated measures ANOVA (Prism). Significance level was set at P < 0.05.

The compare_alpha_diversity workflow (QIIME 1.9.1) was used to test differences in alpha diversity indices between categories (nonparametric t-test with 999 Monte Carlo permutations). The compare_categories workflow (QIIME 1.9.1) was used to perform Permutational analysis of variance (PERMANOVA) on the distance matrices to test for dissimilarities between groups. Differences in the taxa relative distribution between categories were tested using analysis of composition of microbes (ANCOM) [50]. The observation_metadata_correlation workflow (QIIME 1.9.1) was used to find Pearson correlations between specific operational taxonomic units (OTUs) and tetanus vaccine specific immunoglobulin (Ig) G level with subsequent FDR correction (Q value) in Study A, B and C. Correlations were conducted using the QIIME script observation_metadata_correlation.py. The Pearson test was chosen to calculate the correlation between the IgG values and the rarefied OTU tables, 1000 permutations were applied for calculating bootstrapped p-values.

Results

Gluten-free diet as well as treatment with ampicillin had significant impact on the gut microbiota compared to mice fed standard diet

We sequenced the GM to describe the impact of a gluten-free diet or antibiotics on the GM. Mice fed the gluten-free Altromin modified diet for eight weeks in study A developed a GM distinct from the standard Altromin diet fed mice (Fig 2A and 2B, P = 0.01) with the gluten-free diet induced GM being characterized by an increased relative abundance of Parasuterella spp., Lachnospiraceae, TM7 and Bifidobacterium spp. and reduced relative abundances of Ruminococcus spp. and Prevotellaceae (Fig 2C and 2D and Table 2). Ampicillin was an effective modulator of the GM composition in study B (Fig 3A and 3B, P = 0.01). The influence on distribution of microbes was already obvious on the phylum level, as the antibiotic treatment eliminated the Bacteroidetes in many of the animals and raised the relative abundance of Proteobacteria, such as Pseudomonadaceae and Rhizobiaceae as well as Cyanobacteria (Fig 3C and 3D). Interestingly, we only observed group differences in beta-diversity but not alpha-diversity. No GM differences were found between vaccinated and unvaccinated mice on the same standard Altromin diet. Vaccine boosting did not significantly alter the GM. The effect of the gluten-free diet on the GM in study C was too small to be detected in the model due to the major effect of the antibiotics (P = 0.00) (Fig 4A–4D). Mice fed the Altromin modified gluten-free diet weighed significantly more than mice fed the standard Altromin diet in study A (S1A Fig, P = 0.000). Antibiotics in the drinking water reduced the weight significantly in study B (S1B Fig, P = 0.001), but this was mostly due to a weight decrease in the first weeks on antibiotics. We found a significant positive correlation on genus level after FDR correction of especially species within the phylum Bacteroidetes with the pooled IgG levels of both time points in the antibiotic treated mice compared to their controls (Study B), while no correlations were found after the first vaccination, in single groups or in study A (S3 Table).

Fig 2 — BALB/cBomTac mice were vaccinated or not and fed a standard Altromin wheat based diet (‘gluten’), or they were vaccinated and fed a modified Altromin diet, in which wheat protein was replaced with casein (‘gluten-free’). Unweighted (a) and weighted (b) PCoA plots with Permutational multivariate analysis of variance (PERMANOVA) results, relative abundance bar plots on phylum (c) and OTU (d) level after microbiota characterization on feces sampled three and a half week after second vaccination, and anti-tetanus IgG (median) two and a half week after first (e) and three and a half week after second (f) tetanus vaccination.

Table 2. Normalized relative abundances (Mean ± s.d.) of gut microbiota bacteria differing significantly (ANCOM) between female BALB/cBomTac, which were either fed standard wheat based Altromin diet (Gluten) or a modified gluten-free Altromin diet (Gluten-free) from the age of six to fourteen weeks.

All mice were vaccinated with a tetanus vaccine. FDR-corrected q-value was 0.010.

Taxonomy	Gluten	Gluten-free
Taxonomy	n = 21	n = 20
Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Prevotellaceae; Other; Other	23.1 ± 12.4	0.8 ± 2.6
Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Alcaligenaceae; Parasutterella; Other	1.8 ± 2.9	47.9 ± 42.4
Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Dorea; Other	13.6 ± 7.6	81.9 ± 41.6
Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Ruminococcus; Other	8.4 ± 9.7	0.2 ± 0.5
Bacteria; TM7; TM7_genera_incertae_sedis; Other; Other; Other; Other^*	12.8 ± 9.9	119.0 ± 74.0
Bacteria; Actinobacteria; Actinobacteria; Bifidobacteriales; Bifidobacteriaceae; Bifidobacterium; Other	0 ± 0	25.4 ± 39.1

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* Reclassified as Saccharibacteria_ Saccharimonadaceae.

Fig 3 — BALB/cBomTac mice were vaccinated twice with a tetanus vaccine, either in combination with antibiotics (ampicillin) in the drinking water (1g/L) or with pure drinking water. Unweighted (a) and weighted (b) PCoA plots with PERMANOVA results, relative abundance bar plots on phylum (c) and OTU (d) level after microbiota characterization on feces sampled three weeks after second vaccination, and anti-tetanus IgG (median) two weeks after first (e) and three weeks after second (f) tetanus vaccination.

Fig 4 — BALB/cBomTac mice were either fed a standard Altromin wheat based diet (‘gluten’), or they were fed a modified Altromin diet, in which wheat protein was replaced with casein (‘gluten-free’). Mice on both diets were either given ampicillin in the drinking water (Antibiotics; gluten-free + antibiotics) or given pure drinking water (Gluten-free; vaccinated control). All mice were vaccinated with a tetanus vaccine and one week later blood was sampled. Unweighted (a) and weighted (b) PCoA plots with PERMANOVA results, relative abundance bar plots on phylum (c) and OTU (d) level after microbiota characterization on feces sampled at vaccination, and anti-tetanus IgG (median) one week after tetanus vaccination.

Gluten-free diet and antibiotics lowered antibody production after the first vaccination

To describe the impact of a gluten-free diet or antibiotics we monitored serum antibodies to tetanus after the first and second vaccination. Diet had a significant impact on tetanus specific IgG titers monitored two weeks after first vaccination (study A), as mice fed the Altromin modified diet without gluten had both lower titers (P = 0.005) and higher variation (P = 0.000) (77.4 U/ml ± 30.4) compared to the vaccinated control group (100.7 U/ml ± 10.2) (Fig 2E). All titers were ten fold higher three weeks after boosting, but at this time point there no longer were significant differences between the titers or their variation (Altromin modified: 1942.0 U/ml ± 539.2; Altromin: 2110.0 U/ml ± 462.1) (Fig 2F). The non-vaccinated mice after both first and second placebo injection had titers close to zero (Fig 2E and 2F). In Study B, in which all mice were vaccinated, tetanus specific IgG titers monitored three weeks after the first vaccination were significantly lower in the ampicillin treated group (161.6 U/ml ± 40.0) (P = 0.011) compared to the untreated control mice (203.0 U/ml ± 63.5), and the ampicillin treated mice had a borderline lower variation in the titer as shown by Levene’s test (P = 0.080) (Fig 3E). This difference had vanished two weeks after boosting (Antibiotics: 2229.0 U/ml ± 1061.0; Vaccinated control: 2241.0 U/ml ± 964.8) (Fig 3F). The tetanus specific IgG titers monitored at euthanasia in the combined gluten-free and antibiotics treated mice in study C one week after vaccination also showed a lowering effect of antibiotics (P = 0.008, Fig 4E), while there at this early time point was no effect of the gluten-free diet.

The fractions of essential immune cell subsets and their activation were reduced in the mesenteric lymph nodes, while it was increased in the spleens of mice fed the gluten-free diet

To describe the impact of a gluten-free diet and/or antibiotics on the immediate immune cell activation after a single tetanus vaccination we counted immune cells one week after the vaccination (Study C). Feeding the Altromin modified gluten-free diet reduced the overall fraction of T cells (CD3⁺) (P = 0.000), and the more specific fractions of cytotoxic T cells (CD8⁺: P = 0.002), and T_reg (FoxP3⁺CD3⁺CD4⁺: P = 0.013) in the mesenteric lymph nodes (MLN) (Fig 5A). It also reduced the activation of both CD4⁺ (CD25⁺: P = 0.000; CD69⁺: P = 0.000; CD25⁺/CD69⁺: P = 0.000) (Fig 5A), and CD8⁺ (CD69⁺: P = 0.000) (Fig 5A) T cells in the MLN. In the spleen the Altromin modified gluten-free diet reduced the fraction of cytotoxic T cells (CD8⁺: P = 0.007 (Fig 5B). However, in contrast to the MLN the fraction of T_reg (FoxP3⁺CD4⁺CD3⁺: P = 0.013), as well as the fractions of activated CD4⁺ T cells (CD25⁺CD4⁺: P = 0.000; CD69⁺CD4⁺: P = 0.000; CD25⁺CD69⁺CD4⁺: P = 0.000), and activated CD8⁺ cytotoxic T cells (CD69⁺CD8⁺: P = 0.000) were increased by the gluten-free diet (Fig 5B). Furthermore, the gluten-free diet increased the fraction of dendritic cells (CD11c⁺: P = 0.007), i.e. both activated dendritic cells (CD80⁺CD11c⁺ P = 0.001), and tolerogenic dendritic cells (CD11b⁺CD11c⁺: P = 0.000) were increased by the gluten-free diet (Fig 5B).

Antibiotics significantly reduced the fraction of T cells (CD3⁺; P = 0.006) and CD4⁺ T cells (P = 0.003), and borderline reduced the fraction of B cells (CD19⁺: P = 0.086) in the MLN (Fig 5A). However, there was no specific effect on the fractions of CD4⁺CD3⁺ cells (T_reg and Th) or FoxP3⁺CD4⁺CD3⁺ cells (T_reg). In the spleen antibiotics lowered the fraction of activated T cells (CD69⁺/CD4+: P = 0.040; CD69⁺/CD8+: P = 0.003) and the fraction of tolerogenic dendritic cells (CD11c⁺/CD11b⁺: P = 0.037) (Fig 5B).

Diet or antibiotics had only minor impact on systemic cytokine levels or spleen gene expression

To describe whether the gluten-free diet or the vaccination had an impact on serum cytokine levels the cytokines IL-1α, IL-2, IL-5, IL-6 and GM-CSF were monitored at the termination of study A. They were all present in detectable amounts in blood serum, but there were no significant differences in relation to either diet or vaccination (data can be found in the repository).

To detect whether antibiotics or vaccination had an impact on immune gene expression the spleens were sampled for gene expression by qPCR at the termination of study B. Although there was a significant difference in fold changes from the spleens of the genes Cxcl10, Hp, Ifng, Klf2 and Tlr4 in individual Kruskal Wallis tests, no significant differences in gene expression were revealed after false discovery rate (FDR) correction (S2 Table).

Discussion

Feeding a gluten-free diet to mice altered the GM, and it lowered the initial anti-tetanus IgG response to the potent tetanus toxoid vaccine with the strong adjuvant aluminium-oxide hydrate. As expected antibiotics also induced GM changes and reduced anti-tetanus IgG following the first tetanus vaccination. There seemed to be a clear difference between the way that a gluten-free diet and antibiotics had an impact on antibody response. Antibiotics did not in the increase the variation in response, and except for one mouse all antibiotics treated mice had a response below the average for non-treated mice. After boosting the responses in both gluten-free and antibiotic fed mice were comparable to the control mice.

In humans, it has been shown that gluten-free diet induced GM changes are essential for the increased T_reg levels [51], although also a direct anti-inflammatory effect of a gluten-free diet has previously been shown in mice [52]. From studies in two-generation studies in non-obese diabetic mice, it is known that the effects of a gluten-free diet on the immune system can be transferred over generations both dependently and independently of the GM [15, 53]. In the short term study C it was difficult to verify any major anti-tetanus IgG titer effect of the gluten-free diet one week after vaccination, and the impact of the gluten-free feeding was also minor compared to the two other studies. However, there was still in terms of cell counts a clear impact on the immune system, which therefore either responds to even small GM changes and/or directly to the changed diet composition. Whether the impact on vaccine response is GM dependent might be further elucidated through a fecal matter transplantation to germ-free mice.

It might be important for future mechanistic studies that there was an increased relative abundance of Bifidobacterium spp. in mice fed the gluten-free diet. This is in accordance with our previous observations that the gluten-free diet increases the number of T_reg [26], which fits well with a reduced vaccine response. In the present study we found that the gluten-free diet lowered the levels of T_reg locally in the gut, while in the spleen, which should be regarded as an expression of the systemic effect, the gluten-free diet increased T_reg fractions, CD4⁺ T cell activation, and tolerogenic dendritic cell fractions and activation, thereby extending the downregulating effect of the T_reg [54]. Therefore, the systemic effect of the gluten-free diet seems mainly tolerogenic. The inter-individual variation in Bifidobacterium spp. relative abundances of the gluten-free fed mice was huge, while Bifidobacterium spp. were completely absent in all gluten fed mice. This may very well explain the huge inter-individual variation in the antibody response of the gluten-free fed mice. Feeding oligosaccharides, which are used to promote anti-inflammatory bacteria, also negatively affected IgG titers to a tetanus toxoid vaccine in male mice [55]. We observed a correlation with anti-tetanus IgG in study B, i.e. the antibiotics treated mice. However, this should not be over-interpreted, because in the antibiotics treated group, which had a reduced anti-tetanus IgG production, there was reduced relative abundances of Bacteroidetes, and we found no correlations in study A.

In accordance with our previous observations both a gluten-free diet and antibiotics increased the relative abundance of Proteobacteria, such as Parasutterella spp. [15]. These contain the MAMP lipopolysaccharide (LPS), which through TLR4 stimulates TNF-α production [56]. We did observe decreased Tlr4 expression in antibiotics treated mice, although non-significant after FDR correction. LPS from the gut drives expansion of T_reg and reduces later life severity of ulcerative colitis in mice [57, 58], and we have previously observed that in both Peyer’s patches and in the spleen a low concentration of dietary LPS induces the formation of CD103⁺ dendritic cells [59], which are required for the induction of tolerogenic responses [60]. A low amount of proteobacterial LPS in the gut the first 1–2 years of life in Finnish compared to Russian children has been used as an explanation of their lower number of T_reg and their increased risk of autoimmune diseases [61]. Such differences between children in different geographical areas are also likely to explain vaccine response differences. In horses a relative abundance of Prevotellaceae disposes for a high expression of the T_reg marker FoxP3 [62], while a high relative abundance disposes for glucose intolerance in mice [63]. Immediately after treatment ampicillin has been shown to reduce Peyer’s patch T_reg fractions [31]. Although antibiotics seemed to have a weaker effect than the gluten-free diet in the spleen, it downregulated tolerogenic dendritic cell activation, and it increased cytotoxic T cell activation. Therefore, both locally in the MLN and systemically in the spleen, antibiotics and gluten-free diet seem to follow different pathways in downregulating IgG. Ampicillin enters the blood stream and may elicit systemic effects by itself, while a gluten-free diet mostly has its effect on the GALT, and its systemic effects are probably secondary.

In this study, mice were treated with ampicillin throughout the study, which is much longer than humans normally would be treated. During ampicillin treatment the majority of naturally gut inhabiting bacteria will either be eradicated or heavily suppressed, and when ampicillin treatment in mice is terminated, some microorganisms will recover from the host, while other will recover from the environment, and, therefore, ampicillin treated mice will have a microbiota different from non-treated mice [31]. It is unknown whether such a microbiota change will have long term impact on the immune system, and, therefore, our studies cannot be used to state whether the general use of antibiotics in children hampers their responses to vaccines; especially not if they are not treated during vaccination.

The dietary impact on the microbiome not only relates to the bacterial community of the host. Even specific pathogen free mice harbours a gut virome both in the form of phages [64] and mammal viruses [65]. These may have a major impact on host responses [66]. The microbiomic as well as the host related digestion produces a metabolome, and the components of this may equally well facilitate differences in immune responses [67]. From an applied point of view it may be easier to transplant phages than entire microbiotas to change the microbiota in the direction of a stronger vaccine response [68].

Laboratory mice are often very clean with a low microbiota diversity [69], which may be regarded as unfavourable in vaccine development using mice [70]. Human transcriptional responses to influenza vaccination are better recapitulated and humoral responses are dampened in ‘dirty’ mice [71]. The increased Proteobacteria dominance with increased LPS impact in both gluten-free fed and antibiotic treated mice, may, although contradictory, make them more ‘dirty’ comparable to the situation of some human populations. Additionally, our observations add to the understanding that mouse studies are often difficult to reproduce. In large rodent facilities standard diets are purchased in bulk and all mice in different studies are currently fed the latest and often different batches during the same study, although batch variation for certain micronutrients may be substantial in natural ingredient diets [72]. Therefore, scientists should be more aware of reporting exact data on diet use in scientific papers, for example by adhering to the ARRIVE guidelines [73].

Limitations

Studies in mice typically give some basic information, but they are quite often not translatable to humans, i.e. our data cannot be taken as a solid statement that a gluten-free diet has the same impact in humans. Also, there were differences in the experimental setup when testing the impact of a gluten-free diet and the impact of antibiotics. So, although it seemed as if the way these two factors impacted the vaccine responses differed, this interpretation should be made with the precaution that the two studies are not directly comparable. The two-way setup for testing the impact on cell counts does not include a non-vaccinated group, so it is only possible to make conclusions on the relative impact of the experimental factors. Finally, these studies were performed with a tetanus toxoid vaccine, which globally in humans is known as a highly efficient vaccine [39], and to which the immune system responds in ways, which can be different from responses to other vaccines. The effectiveness of viral vaccines seems to vary far more. Titers to influenza varies significantly between vaccinated humans in different geographical regions [1], and even the most efficient COVID-19 vaccines do not offer full protection against infection in humans [74]. Therefore, our studies in mice should not be used to question the efficiency of tetanus vaccination in humans, and from a more applied point of view it would be equally or more relevant to study the impact of the GM on such vaccines; especially in the light of the COVID-19 pandemic.

Conclusions

We studied the impact of the GM on the response of a tetanus vaccine. From a basic point of view our experiment supports the hypothesis that GM has an impact on the response to vaccines [75]. The GM with its potential to engage both innate and adaptive immune responses [76, 77], is, therefore an obvious target for manipulation in regard to optimizing vaccine strategies. Diet is a strong modulator of the GM [13], and therefore diet and indirectly factors such as geographical habitat need consideration in the development of vaccines in studies in mice as well as in humans.

Supporting information

S1 Fig

Growth curves for mice fed a gluten free diet (a) or antibiotics (b). (a) BALB/cBomTac mice were vaccinated with a tetanus vaccine (Vaccinated control) or not (Control) and fed a standard Altromin wheat based diet (‘gluten’), or they were vaccinated and fed a modified Altromin diet, in which wheat protein was replaced with casein (‘gluten free’). (b) BALB/cBomTac mice were vaccinated twice with a tetanus vaccine, either in combination with ampicillin (antibiotics) in the drinking water or with pure drinking water (control). Borderline p-values are written in italics.

(PDF)

Click here for additional data file.^{(131.9KB, pdf)}

S1 Table. Genes for which expressions were monitored by qPCR in the spleens of tetanus vaccinated antibiotics treated and control mice.

(PDF)

Click here for additional data file.^{(294.4KB, pdf)}

S2 Table. Spleen gene expressions for which a significant difference between tetanus vaccinated antibiotics treated and control mice was found by Kruskal–Wallis test (P).

No significances were found if P-values were corrected by false discovery rate (Q).

(PDF)

Click here for additional data file.^{(184.2KB, pdf)}

S3 Table. Correlations of taxa with anti-tetanus IgG in BALB/cBomTac mice vaccinated once or twice with a tetanus toxoid vaccine.

Only correlations significant after FDR correction are shown.

(DOCX)

Click here for additional data file.^{(14.3KB, docx)}

Acknowledgments

Mette Nelander and Helene Farlov are kindly acknowledged for taking care of the animals.

Data Availability

Raw sequencing data was deposited in the NCBI SRA database (https://www.ncbi.nlm.nih.gov/sra) under the Bioproject PRJNA703942. Clinical and immunological data are stored at the Open Science Framework https://osf.io/s47np/.

Funding Statement

The study was supported by a grant (2013-4) from LIFEPHARM (www.lifepharm.ku.dk) to AKH. The funder had no role in the project.

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PLoS One. doi: 10.1371/journal.pone.0266719.r001

Decision Letter 0

Anne Wertheimer

27 Jun 2021

PONE-D-21-12086

Dietary Gut Microbiota Perturbations Influence Murine Vaccine ResponseDietary Gut Microbiota Perturbations Influence Murine Vaccine Response

PLOS ONE

Dear Dr. Kornerup Hansen,

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Additional Editor Comments:

Hansen et. al present studies which address important aspects relevant to vaccination success. Examination of diet as well as antibiotic therapy are both relevant conditions. There are a few areas of concern which must be appropriately addressed prior to acceptance.

Major concerns:

Figure 2e and Figure 4e though providing the same type of data (IgG response after one vaccination) yet in the different study groups (Study A and C) the vaccinated control and vaccinated gluten Free cohort had statistically different levels of IgG in Study A but not in Study C. The variability of the vaccinated control cohort was also considerably less in Study A. Please address.

Since there was neither a gluten-free nor an antibiotic treatment cohort which were unvaccinated all reference to the gluten free cohort and antibiotic treated cohort must be stated as the "vaccinated" gluten free cohort and the "vaccinated" antibiotic treated cohort for clarity. Sentences such as line 298 "To describe whether the gluten-free diet or the vaccination had an impact on serum..." as well as line 302 "To detect whether antibiotics or vaccination had an impact on immune gene expression" must be restated and analysis adjusted accordingly because there was not a antibiotic cohort that was not vaccinated. For example line 302 could be rephrased to state "To detect whether vaccination in the presence of antibiotics had an impact..."

Verify that the n for each figure is correctly reflected in the number of symbols for each cohort. For example in 4e there appear to be an n=13 in the figure yet in the text the cohort is n=15. Define and explain the number of animals represented in figures 5a and 5b. It appears that the number of animals used in this series of experiments varies and is not explained. Why for example were only 5 animals used in the FoxP3+CD3+CD4 vs the CD25+CD4 panel. In addition lines illustrated where the p value applies must be added.

Provide additional detail on the sample preparation and analysis for flow cytometry either in the methods section or within Table 1; specifically the number of cells stained and the final number of cells within the analysis gate.

For p=0.000 restate as p< 0.005. The images were very pixelated.

The additional findings from Reviewer 1 must also be addressed in your resubmission.

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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: Yes

**********

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: No

**********

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: In this manuscript Kihl and colleagues have looked at the effect of diet and vaccine response. While this manuscript focusses on the effect of gluten-free diet on many avenues such as gut microbiome, host immune response, tetanus specific IgA and serum cytokines, some questions still remain.

Major concerns:

1. It seems like the mouse experiments used only female BALB/cBomTac mice for their experiments. Please explain why male mice were not used for these experiments?

2. Study A: Impact of gluten on primary and boosting vaccination cohort. While there were two groups fed normal diets (vaccinated and placebo), there is no placebo group for the gluten free diet (Altromin modified). These analyses, therefore do not allow the separation of the effects of gluten-free diet from that of vaccinations alone.

3. It is not clear why samples were collected the same day as vaccination for Study A and C and a few days after vaccination in Study B.

4. Was ampicillin administered throughout the duration of the study? Did these animals get diarrhea? If yes, then did the animals that developed diarrhea show differential gut microbiota and immune response as well as serum cytokines etc.

Minor concerns:

1. The figures are pixelated and very hard to read.

**********

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Reviewer #1: No

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PLoS One. 2022 Apr 13;17(4):e0266719. doi: 10.1371/journal.pone.0266719.r002

Author response to Decision Letter 0

26 Aug 2021

Dear editor

I hereby submit the revised manuscript.

We have at our best tried to follow the valuable comments of ypu and the reviewer, as described in the cover letter.

Best wishes

Axel Kornerup Hansen

PLoS One. doi: 10.1371/journal.pone.0266719.r003

Decision Letter 1

Brenda A Wilson

13 Jan 2022

PONE-D-21-12086R1Dietary Gut Microbiota Perturbations Influence Murine Vaccine ResponsePLOS ONE

Dear Dr. Kornerup Hansen,

Both reviewers note a substantial number of serious concerns that must be addressed before further consideration can be made.

Please submit your revised manuscript by Feb 27 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're 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.

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). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Brenda A Wilson, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

As the second academic editor to review this manuscript, it was difficult to discern where the improvements in the revision were since the second set of reviewers expressed very similar concerns to that of the first round of reviewers as well as additional ones. After reading the manuscript through myself, I would agree with these two reviewers that major revision of the manuscript is needed before further consideration can be made.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

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

Reviewer #2: Partly

Reviewer #3: Yes

**********

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

Reviewer #2: Yes

Reviewer #3: No

**********

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

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

Reviewer #2: No

Reviewer #3: No

**********

6. Review Comments to the Author

Reviewer #2: The paper describes an observation that mice when fed with a gluten-free diet or treated with ampicillin have slightly lower primary antibody IgG response against a tetanus vaccine, but the secondary Ab response seems normal. The authors conclude that dietary or gut microbiota factors should be considered when testing vaccines. The data in most part are correlative, no mechanistic study is engaged.

(1) Fig5 is problematic, it is not known which two groups are different from each other simply by showing a p-value. The same thing is true for Fig4a,b, and e.

(2) Ampicillin treatment in study B is a little bit too long. Does short-term one-week treatment also have an impact?

(3) Can the author demonstrate that the gluten-free diet-induced microbiota changes drive the lower primary antibody response by fecal transfer type of experiment? Or can the author demonstrate which cell population influenced by the diet reduced the antibody response?

(4) The language can be modified further. p10 L223, please delete the ' mark.

Reviewer #3: General comments

This is the reviewer’s first reading of this article, although it appears it has already gone through one round of reviews. Apologies to the authors if the have already gone through a round of reviews.

The article aims to characterize the impact of microbiome alteration (either through diet or antibiotics) on tetanus vaccine immunogenicity in mice. The article is a nice addition to the literature that suggests that alteration of the intestinal microbiome alters host immune response to both vaccines and pathogens. The authors have performed experiments with a large sample sizes and evaluated microbiome, immune cells, and gene expression resulting in an interesting data set that suggests gluten free-diet and antibiotic administration diminish anti-tetanus antibodies following intial vaccination, possibly through different mechanisms.

Major comments

The reviewer requests a better rationale for why tetanus vaccine was used for this study, given that it is known to elicit consistently high antibody responses across geography and across ages.

Also suggest to reference more of the recent (human and murine) literature on how microbiota alters vaccine immunogenicity.

Study design - Studies A, B and have differing intervals of treatment (antibiotic/diet) and differing timing of prime and boost of vaccination as well as measurement of antibody responses making it difficult to extrapolate results across the studies. The rationale for choices are not clearly described.

Analysis – Given the use of antibody titers, request that the authors repeat antibody statistical analyses using transformed data/geometric mean titers.

Article can often be confusing to read and suggest input from a native English speaker. Some hypotheses in introduction and conclusion suffer from large jumps across subjects without clear delineation of whether data comes from human or animal subjects. Suggest to review and adjust claims accordingly.

Minor comments

Abstract

Line 26 Wording is confusing, isn’t the primary purpose of the study to evaluate the effect of diet ( gluten-free or gluten-containing) and antibiotics (ampicillin or not) on tetanus vaccine immunogenicity? Suggest to adjust wording

Line 28 suggest change ‘lowered’ to ‘was associated with’

Line 29 low-responder not defined in abstract or text, suggest to define if this is a statistical outcome or otherwise remove

Line 29 relative abundance or abundance?

Line 30 remove word massively, change to significantly if this is the case. If hypothesis is that diet altered microbiota which then altered vaccine response, suggest to start with change in microbiota in this sentence

Line 30, suggest to remove ‘similarly’- suggests that antibiotics altered microbiota similarly to diet?

Line 31, add significance for all findings

Line 31, define ‘boosting’

Line 32, what was definition of” influenced’’?

Line 36, suggest to alter sentence, “these results suggest …..”

Introduction –

Line 44 The authors describe diminished vaccine efficacy in low-middle income settings, however tetanus vaccines have never been shown to have diminished efficacy in low or middle income settings. Rather, they have high immunogenicity and good protection globally, with possible higher immunogenicity in low-income settings. Please correct

Line 46 Suggest to use the term low-middle income and high income and not ‘developing”and developed”as terminology

Line 48 – all citations have to do with changing vaccine immunogenicity by genetics and age and do not support differential vaccine performance by geography. Please correct

Line 71, remove the word óbviously’, suggest to make less definitive statements, add “can cause” and add that this study was in mice

Line 74, modify that this is a study that was performed in mice

Line 76, add that this is for influenza vaccination

Line 83, cite literature that shows this

Line 88, citation is not about Bangladeshi children

Study Design

Line 136, what was the rationale for the different timing of tetanus vaccination between the three studies? Both timing of prime following arrival and timing of boost differed between Study A and B as well as the time of measurement of the immunoglobulin response following the second vaccination. For study A, why were antibodies measured 2,5 weeks after vaccine dose 1 but 3,5 weeks after vaccine dose 2

Line 145 and 151, describe when antibody titers were measured in relation to vaccination

Stud C, Line 153, antibody titers are measured 1 week following vaccination, why was this time point chosen? Why was a different interval chosen for duration of diet and antibiotics in relation to stud a and c?

Line 233 – How were titers accounted for in the statistics, why were antibody titers not transformed? Please give rationale or log-transform antibodies/present as geometric mean titers

Lines 258/262, list test used for significance

Line 259 – please define TM7

Line 263 – Phylum should not be italicized

Line 269, which microbiome metric is being given a significance here?

Line 272, what was the impact of antibiotics on weight in study C

Line 276, missing figure legend for figure 1?

Figure 2, e and f, list time of blood draw in relation to vaccination; list timing of fecal sample collection, list timing of vaccination in figure or figure legend. Correct figure label for e/f to be anti-tetanus IgG

Figure 3, list timing of fecal sample collection for microbiome, list timing of IgG in relation to vaccination, list timing of vaccination. Correct figure legends to be anti-tetanus IgG

Line 280/285/294 –is this absolute or relative abundance?

Figure 4e, significance is listed as text but not shown for antibiotics – what has a significance of p= 0.008

Table 2, describe duration of time mice were fed diet (4,5 weeks from Study C or 2 weeks from Study A?) Add n for column control and gluten-free

Line 309, figure 1 does not show a serum sample 2 weeks after the first vaccination for Study B, please adjust.

Line 312, what data/statistical test supports the borderline lower variation. Please list statistical test for all p-values.

Line 316, please indicate which comparison is being made for the significance here

Lines 321-337, please do not report trends, only significant values

Figure 5, please indicate which comparisons are significant in the figure rather than describing them on the figure. Please indicate how many mice were specifically in each group (e.g. n=10/group, not 10 overall?). Please label the individual plots, rather than 5a/b alone. Figure 5B seems to be missing?

Line 367, suggest to specify IgG with anti-tetanus IgG

Line 368, remove reference to ‘low-responder’ unless this term is defined and tested with a statistical bound.

Line 369, suggest to remove dramatic, suggest to specify ‘reduced anti-tetanus IgG following the first tetanus vaccination”

Line 372, inter-individual variation in GM or antibody response?

Lines 372-374, this sentence’s meaning is confusing

Line 383, these findings were associative, do the authors mean, for future mechanistic explanations?

Line 384/393, suggest correlating bacterial abundance to antibody titer/Treg to support such an association.

Line 395, see earlier comment on definition high/low responder

Please provide a limitations section, in which differences in experimental design between the study arms are taken into account. Also please address the limitation of doing this study in mice and looking only at tetanus vaccine. Please address the potential impact of the metabolome as mediator of a microbiome effect as well as other components of the microbiome, such as virome/fungiome that have not currently been measured.

**********

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Reviewer #2: No

Reviewer #3: No

PLoS One. 2022 Apr 13;17(4):e0266719. doi: 10.1371/journal.pone.0266719.r004

Author response to Decision Letter 1

27 Jan 2022

Our point-to-point replies are as follows:

Reviewer #2:

Fig5 is problematic, it is not known which two groups are different from each other simply by showing a p-value. The same thing is true for Fig4a,b, and e.

We understand the concerns of the reviewer, because it is very common to analyse such data by a one-way ANOVA followed by, what in this case would be a Tukey’s post hoc test. However, if the study as in this case is planned accordingly the most powerful way to analyse these data are by a two-way ANOVA, and in a two-way ANOVA you get a p-value for each factor across the groups. We do not find that it is statistically appropriate (although offered by some statistical software packages) to supply it with a post-hoc test, as the beauty of a two-way ANOVA is that you get one p-value for each factor, and attempts to calculate more p-values increases the risk of type I errors without actually adding any value to the evaluation. In addition, the p-values to these factors fully respond to the hypothesis. However, if the editor prefers that we do it, we will of course do it and put it into the table.

Ampicillin treatment in study B is a little bit too long. Does short-term one-week treatment also have an impact?

We are a bit uncertain with how the reviewer defines ‘too long’, but we understand it as if it should be compared to a human situation. In this study ampicillin treatment was used to block microbiota impact on the vaccine response to show if there was a microbiota related effect. It is common practice in antibiotic depletion studies to start out by a depletion for the entire study period, i.e. in this case during the vaccination and until the last antibody monitoring. So, this is what we have done. A short term depletion changes the microbiota afterwards, and we are in the process of studying whether such a change can have long term effects. We do not at present have the basis for further studies on such short term treated animals, and more basic studies of potential immune changes are needed to make out, when to expect changes in a vaccine response. However, we admit that our studies cannot be used to state anything about how the general use of ampicillin/amoxicillin for children affects their immune response; especially not if they are not treated with it at vaccination time point. This should have been better discussed, and we have now introduced the following in the discussion:

L430-438: In this study, mice were treated with ampicillin throughout the study, which is much longer than humans normally would be treated. During ampicillin treatment the majority of naturally gut inhabiting bacteria will either be eradicated or heavily suppressed, and when ampicillin treatment in mice is terminated, some microorganisms will recover from the host, while other will recover from the environment, and, therefore, ampicillin treated mice will have a microbiota different from non-treated mice [31]. It is unknown whether such a microbiota change will have long term impact on the immune system, and, therefore, our studies cannot be used to state whether the general use of antibiotics in children hampers their responses to vaccines; especially not if they are not treated during vaccination.

We have also explained this better at the end of the introduction:

LN99-100: To block the impact of the GM, some of the mice were treated or not treated with ampicillin.

Can the author demonstrate that the gluten-free diet-induced microbiota changes drive the lower primary antibody response by fecal transfer type of experiment?

We agree that this I a perspective for further studies, which has already been mentioned in the discussion (‘To verify this further studies should attempt to transfer the GM effect to germ-free mice through a fecal matter transplantation’). We have a manuscript accepted for Journal of Autoimmunity, in which we in a two-generation show that a gluten-free diet effect is transferred over generations, and some of the effect is microbiota dependent and some is microbiota independent. We have inserted a reference to this:

L383-393: In humans, it has been shown that gluten-free diet induced GM changes are essential for the increased Treg levels [51], although also a direct anti-inflammatory effect of a gluten-free diet has previously been shown in mice [52]. From studies in two-generation studies in non-obese diabetic mice, it is known that the effects of a gluten-free diet on the immune system can be transferred over generations both dependently and indepently of the GM [15, 53]. In the short term study C it was difficult to verify any major anti-tetanus IgG titer effect of the gluten-free diet one week after vaccination, and the impact of the gluten-free feeding was also minor compared to the two other studies. However, there was still in terms of cell counts a clear impact on the immune system, which therefore either responds to even small GM changes and/or directly to the changed diet composition. Whether the impact on vaccine response is GM dependent might be further elucidated through a fecal matter transplantation to germ-free mice.

Can the author demonstrate which cell population influenced by the diet reduced the antibody response?

FACS data were generated on study C mice, which was too short to show the immediate effects of the first vaccination, as this was when a difference was observed. However, this should have been mentioned in the discussion. We have now written:

LN387-389: In the short term study C it was difficult to verify any major anti-tetanus IgG titer effect of the gluten-free diet one week after vaccination, and the impact of the gluten-free feeding was also minor compared to the two other studies.

The language can be modified further. p10 L223, please delete the ' mark.

We have made sure that there is no such mark in L223. We have gone through the manuscript with the department translator, and it has be substantially changes. If this from an English language point of view is not enough, we will after acceptance pass it through an editorial service if requested by the editor.

Reviewer #3:

Major comments

The reviewer requests a better rationale for why tetanus vaccine was used for this study, given that it is known to elicit consistently high antibody responses across geography and across ages.

This is a quite obvious and understandable request from the reviewer. When we planned the study, , we found – as we tried to relate the effect to bacteria of the gut – that it would be most relevant in the first place to study this in a vaccine based upon a bacterial product known to induce a strong Th1 reaction, and therefore we chose the tetanus vaccine. Obviously, in the light of COVID-19 pandemic, it would probably have been relevant to base our studies on a virus vaccine. Having said that we can also see from some of the work we do today that the responses we see in relation to viral vaccines is stronger in their CD8 than in their CD4 reaction, and the knowledge we have built from our work with gluten-free diets over the last decade points in the direction of a gluten-free impact on CD4 rather than CD8. We have changed the last part of the introduction into:

LN90-100: We hypothesized that gluten-free diet induced GM perturbations would influence vaccine response in mice. We found it most relevant to study this in relation to a vaccine based upon a bacterial product, and, therefore, we chose to study the impact on a tetanus toxoid vaccine, although this vaccine generally have high immunogenicity and protection globally [39]. Tetanus toxoid is a bacterial product, which when used as vaccine, is known to raise a strong Th reaction [40], and it has traditionally been used with aluminium oxide hydrate adjuvant, which is expected to drive a Th2 rather than a Th1 response [41]. An increase in Treg relative abundance and subsequent IL-10 secretion, as induced by a gluten-free diet, will reduce both Th1 and Th2 and, thereby antibody producing B cell relative abundance [24, 42]. Therefore, we used the production of specific IgG as primary readout in mice fed a gluten-free or a standard gluten containing diet. To block the impact of the GM, some of the mice were treated or not treated with ampicillin.

We have also touched upon it in the limitations:

LN463-471: Finally, these studies were performed with a tetanus toxoid vaccine, which globally in humans is known as a highly efficient vaccine [39], and to which the immune system responds in ways, which can be different from responses to other vaccines. The effectiveness of viral vaccines seems to vary far more. Titers to influenza varies significantly between vaccinated humans in different geographical regions [1], and even the most efficient COVID-19 vaccines do not offer full protection against infection in humans [74]. Therefore, our studies in mice should not be used to question the efficiency of tetanus vaccination in humans, and from a more applied point of view it would be equally or more relevant to study the impact of the GM on such vaccines; especially in the light of the COVID-19 pandemic.

Also suggest to reference more of the recent (human and murine) literature on how microbiota alters vaccine immunogenicity.

Having gone through the references we admit that some of these were somewhat old, and that certain subjects could be better elucidated by some more recent references, which we have now included in the manuscript.

There are some differences, but the way we have presented the study setups make it look more different than it is. In study A and study B mice were vaccinated at 8 weeks of age, but in the previous manuscript we wrote, when they were vaccinated in relation to the arrival. This is, of course, relevant in relation to how long they were fed gluten-free diet or antibiotics, but this was mostly decided by the vendors delivery plans and not by biological considerations. Normally when we do long term feeding/drinking water intake experiments we put the mice on the diet/water at arrival to avoid stressful changes more than once. After study A we discussed whether 2,5 weeks between the two vaccinations was too short and we decided to use four weeks instead. In study C, when we did the vaccinations only once, we wanted to be sure to have mice with a full functioning immune system and, therefore, we decided to give them an extra week before vaccination.

We have introduced the following under materials and methods:

LN 129-137: We set up three studies in BALB/cBomTac mice, to investigate the influence of gut microbiota manipulations on the response to a tetanus vaccine. Two studies (A and B) to study the impact of either a gluten-free diet or antibiotics on the antibody production after a boosted vaccination regime, and one study (C) to study the immediate impact of one vaccination on immune cells counts in gluten-free fed or antibiotics treated mice. In study A we boosted with a second vaccination after two and a half weeks, while we in study B reconsidered this and did the boosting after four weeks. In study C we used only one vaccination, because the aim was to see the cell counts in relation to our observations after the first vaccination in study A and B, and, therefore, we also sampled the animals only one week later.

Analysis – Given the use of antibody titers, request that the authors repeat antibody statistical analyses using transformed data/geometric mean titers.

We have ranked all titer values and re-analyzed them. Outcomes were not dramatically changed. Graphs have been changed to show medians instead of means.

Reading the manuscript again we fully agree. We have been thoroughly through the paper together with the department translator, and the introduction and the discussion have both been essentially reorganized. If this from an English language point of view is not enough, we will after acceptance pass it through an editorial service if requested by the editor.

Minor comments

Abstract

Point taken. It now reads:

LN26-27: The purpose of this study was to compare the effect of a tetanus vaccine on immunoglobulin G titers and immune cell levels in female BALB/c mice fed either a gluten-free or a gluten containing diet and treated or not treated with ampicillin.

Line 28 suggest change ‘lowered’ to ‘was associated with’

Done

Line 29 low-responder not defined in abstract or text, suggest to define if this is a statistical outcome or otherwise remove

All references to ‘Low responders’ have been removed.

Line 29 relative abundance or abundance?

It no reads ‘the relative abundance’

‘Massively’ has been replaced with ‘significantly’

Line 30, suggest to remove ‘similarly’- suggests that antibiotics altered microbiota similarly to diet?

‘Similarly’ has been replaced with ‘also’.

Line 31, add significance for all findings

‘Significantly’ has been inserted

Line 31, define ‘boosting’

‘Boosting’ has been replaced with ‘a second vaccination’

Line 32, what was definition of” influenced’’?

‘Influenced’ has been replaced with ‘reduced’

Line 36, suggest to alter sentence, “these results suggest …..”

Done

Introduction

This is a general statement, which is indeed true for some vaccines. We have later in the introduction explained our rationale for choosing the tetanus vaccine, and we have inserted a sentence describing that it is generally efficient:

LN91-98: We found it most relevant to study this in relation to a vaccine based upon a bacterial product, and, therefore, we chose to study the impact on a tetanus toxoid vaccine, although this vaccine generally have high immunogenicity and protection globally [39]. Tetanus toxoid is a bacterial product, which when used as vaccine, is known to raise a strong Th reaction [40], and it has traditionally been used with aluminium oxide hydrate adjuvant, which is expected to drive a Th2 rather than a Th1 response [41]. An increase in Treg relative abundance and subsequent IL-10 secretion, as induced by a gluten-free diet, will reduce both Th1 and Th2 and, thereby antibody producing B cell relative abundance [24, 42].

Line 46 Suggest to use the term low-middle income and high income and not ‘developing”and developed”as terminology

Good point. Done.

Line 48 – all citations have to do with changing vaccine immunogenicity by genetics and age and do not support differential vaccine performance by geography. Please correct

The references have been replaced

Line 71, remove the word óbviously’, suggest to make less definitive statements, add “can cause” and add that this study was in mice

The sentence now reads:

LN79: Antibiotics, such as ampicillin, may have a strong impact on GM, which causes decreased abundances of Treg and Th in both mice [31] and humans [32].

Line 74, modify that this is a study that was performed in mice

Done

Line 76, add that this is for influenza vaccination

Done

Line 83, cite literature that shows this

Done

Line 88, citation is not about Bangladeshi children

This has been corrected

Study Design

This has been clarified and corrected above.

Line 145 and 151, describe when antibody titers were measured in relation to vaccination

This has been clarified in a previous comment to the reviewer. We have revised the study plan descriptions accordingly.

Line 233 – How were titers accounted for in the statistics, why were antibody titers not transformed? Please give rationale or log-transform antibodies/present as geometric mean titers

Antibody titers were calculated according to the standard curve made up according to the suppliers instructions. This has been put into materials and methods (LN204). The statistics have been recalculated as described above.

Lines 258/262, list test used for significance

The tests have already been described in the statistics section.

Line 259 – please define TM7

The bacterium used to have the candidate name TM7, but it has been reclassified as Saccharibacteria_ Saccharimonadaceae. This has been put as a footnote in the table.

Line 263 – Phylum should not be italicized

Corrected

Line 269, which microbiome metric is being given a significance here?

Relative abundances. This has been written in the legend now.

Line 272, what was the impact of antibiotics on weight in study C

The mice were not weighed at the end of this study.

Line 276, missing figure legend for figure 1?

It has now been inserted (LN127).

Done

Figure 3, list timing of fecal sample collection for microbiome, list timing of IgG in relation to vaccination, list timing of vaccination. Correct figure legends to be anti-tetanus IgG

Line 280/285/294 –is this absolute or relative abundance?

All ‘abundance’ have been replaced with ‘relative abundance’.

Figure 4e, significance is listed as text but not shown for antibiotics – what has a significance of p= 0.008

This is a P-value calculated in a two-way ANOVA. The test gives a P-value for each factor, i.e. antibiotics+/- and gluten-free/gluten. The P-value for the factor antibiotics+/- is 0.008 (actually after ranking the data it is now 0.002). There is no significant effect of a gluten-free diet. We cannot really see other ways to write this, and this is also how we normally write the outcome of a two-way ANOVA in papers.

Table 2, describe duration of time mice were fed diet (4,5 weeks from Study C or 2 weeks from Study A?) Add n for column control and gluten-free

Done

Line 309, figure 1 does not show a serum sample 2 weeks after the first vaccination for Study B, please adjust.

This has been corrected.

Line 312, what data/statistical test supports the borderline lower variation. Please list statistical test for all p-values.

This was shown by Levene’s test, which has now been stated.

Line 316, please indicate which comparison is being made for the significance here

A two-way ANOVA on ranked data, which has now been stated.

Lines 321-337, please do not report trends, only significant values

Point taken. It has been omitted.

Figure 5, please indicate which comparisons are significant in the figure rather than describing them on the figure.

As also stated for reviewer No 2, these P-values have been calculated in a two-way ANOVA, in which you get a P-value for each factor. We do not consider it appropriate statistics to do post-hoc tests after a two-way ANOVA, as the increased search for P-values increases the risk of type I error, and the P-values generated by the two-way ANOVA fully responds to the hypothesis. However, if the editor wants us to do it, we will do it and put it into the figures.

Please indicate how many mice were specifically in each group (e.g. n=10/group, not 10 overall?).

Done

Please label the individual plots, rather than 5a/b alone.

The individual plots are labelled.

Figure 5B seems to be missing?

We are not aware in which part of the process this problem has been generated, but it has been submitted with this revision.

Line 367, suggest to specify IgG with anti-tetanus IgG

Done

Line 368, remove reference to ‘low-responder’ unless this term is defined and tested with a statistical bound.

Done

Line 369, suggest to remove dramatic, suggest to specify ‘reduced anti-tetanus IgG following the first tetanus vaccination”

Done

Line 372, inter-individual variation in GM or antibody response?

This phrase has been deleted from the restructured discussion.

Lines 372-374, this sentence’s meaning is confusing

We agree, and it has disappeared in the revised discussion.

Line 383, these findings were associative, do the authors mean, for future mechanistic explanations?

Yes, we have now written for future mechanistic studies.

Line 384/393, suggest correlating bacterial abundance to antibody titer/Treg to support such an association.

We have correlated all OTU’s of the gut microbiota sequencing with the IgG, and it gave a little that we have inserted as a S3 Table. We are not convinced that it makes sense to highlight it very much in the paper.

We write as follows:

LN273-277: We found a significant correlation after FDR correction of especially species within the phylum Bacteroidetes with the pooled IgG levels of both time points in the antibiotic treated mice compared to their controls (Study B), while no correlations were found after the first vaccination, in singe groups or in study A (S3 Table).

LN406-409: We observed a correlation with anti-tetanus IgG in study B, i.e. the antibiotics treated mice. However, this should not be over-interpreted, because in the antibiotics treated group, which had a reduced anti-tetanus IgG production, there was reduced relative abundances of Bacteroidetes, and we found no correlations in study A.

Line 395, see earlier comment on definition high/low responder

We have omitted all talk about high and low responders.

We have inserted a limitations section after the discussion, and removed the last part of the discussion to a conclusions section:

LN458-471: Studies in mice typically give some basic information, but they are quite often not translatable to humans, i.e. our data cannot be taken as a solid statement that a gluten-free diet has the same impact in humans. Also, there were differences in the experimental setup when testing the impact of a gluten-free diet and the impact of antibiotics. So, although it seemed as if the way these two factors impacted the vaccine responses differed, this interpretation should be made with the precaution that the two studies are not directly comparable. Finally, these studies were performed with a tetanus toxoid vaccine, which globally in humans is known as a highly efficient vaccine [39], and to which the immune system responds in ways, which can be different from responses to other vaccines. The effectiveness of viral vaccines seems to vary far more. Titers to influenza varies significantly between vaccinated humans in different geographical regions [1], and even the most efficient COVID-19 vaccines do not offer full protection against infection in humans [74]. Therefore, our studies in mice should not be used to question the efficiency of tetanus vaccination in humans, and from a more applied point of view it would be equally or more relevant to study the impact of the GM on such vaccines; especially in the light of the COVID-19 pandemic.

Please address the potential impact of the metabolome as mediator of a microbiome effect as well as other components of the microbiome, such as virome/fungiome that have not currently been measured.

We have now inserted the following in the discussion:

LN439-445: The dietary impact on the microbiome not only relates to the bacterial community of the host. Even specific pathogen free mice harbours a gut virome both in the form of phages [64] and mammal viruses [65]. These may have a major impact on host responses [66]. The microbiomic as well as the host related digestion produces a metabolome, and the components of this may equally well facilitate differences in immune responses [67].

Attachment

Submitted filename: Rebuttal letter.pdf

Click here for additional data file.^{(401.2KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0266719.r005

Decision Letter 2

Brenda A Wilson

28 Feb 2022

PONE-D-21-12086R2Dietary Gut Microbiota Perturbations Influence Murine Vaccine ResponsePLOS ONE

Dear Dr. Kornerup Hansen,

While some of the previous issues raised by the reviewers were addressed, there remain a number of concerns that still need to be more adequately addressed. In particular, the concerns of reviewer 2 regarding the immune cell responses (figure 5) and gluten-free diets are still valid and should be better addressed.

Please submit your revised manuscript by Apr 14 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're 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.

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Brenda A Wilson, Ph.D.

Academic Editor

PLOS ONE

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

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

Reviewer #2: Partly

Reviewer #3: Yes

**********

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

Reviewer #2: No

Reviewer #3: Yes

**********

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

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #2: I am not satisfied with the authors response.

The examination of the immune cell responses in Figure 5 needs to be clarified a little bit more.

1) what is the baseline levels of all the immune cell population without vaccination?

2) why the n number is not consistent (e.g., for Treg n=5, while total CD3 T n=10?)

3) how to explain the cell number change differences between spleen and MLN?

4) Pls indicated which two groups were compared when indicated there is a statistcial significance.

In my opinion, a fecal transfer experiment to demonstrate the effect of gluten-free diet on IgG response is dependent on gut microbiota should be performed to strength this manuscript.

Reviewer #3: The authors have addressed the majority of my comments and questions

Small comments:

with reference to the revised track changes text

(page 54) Abstract: line 32, add lower initial vaccine titer

(page 58) line 114: although this vaccine generally has high immunogenicity….

(line 161) ‘we reconsidered this’, suggest to include a rationale here

(lines 176/ 183) body weights of mice … were monitored. What was the impact of antibiotics and diet on weight in studies A/B (this could be confounding)

(line 314/315) describe the direction of the correlation and clarify if correlation was for the phylum or species level.

Line 317 typo, ‘single’

Line 347, Table 2 – list all FDRs in table or indicate which FDR level was used to generate table. Relative repeated twice in table legend

Please review text for typos

**********

7. 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 #2: Yes: Yugang Wang

Reviewer #3: No

PLoS One. 2022 Apr 13;17(4):e0266719. doi: 10.1371/journal.pone.0266719.r006

Author response to Decision Letter 2

3 Mar 2022

Reviewer #2:

The examination of the immune cell responses in Figure 5 needs to be clarified a little bit more.

1) what is the baseline levels of all the immune cell population without vaccination?

4) Pls indicated which two groups were compared when indicated there is a statistcial significance.

With due respect to the reviewer, we think that the reviewer has misunderstood the experimental setup. The hypotheses decided upon during the planning of the study were (1) ‘Does gluten have an impact on immune cell populations?’ and (2) ‘Does antibiotics have an impact on immune cell populations’? It is standard within experimental design to answer such two-factorial research questions in a two-factorial setup evaluated by a two-way ANOVA. The set-up looks as follows:

Factor 1 Gluten

+ -

Factor 2 + Group 1 Group 3

Antibiotics - Group 2 Group 4

The two-way ANOVA will give an individual p-value for each of the factors. Of course, the groups can be compared in a post-hoc test, such as Tukey’s post hoc comparison, but we have no hypothesis relating to differences between the individual groups and the study was not planned for this. The only statistical effect will be that we get more p-values, which we subsequently will have to create hypotheses to explain. This is not good experimental design and statistics.

Alternatively, the study could have been set up for evaluation by a one-way ANOVA, i.e. an unvaccinated group to be compared with different groups with or without gluten and antibiotics. If an overall significant p-value was found in the one-way ANOVA these groups could subsequently be compared with the control group in a Dunnett’s post hoc test. This is, in our eyes, a much weaker design, because it is difficult to interpret the effects of the two factors individually, and it implies multiple testing, which is FDR corrected in the Dunnett’s post hoc test.

However, no matter, which design is preferred, the simple answer is that we planned and did the two-way setup and this cannot subsequently be changed into a one-way setup.

As mentioned in our previous rebuttal letter, if the editor wants us to do the post-hoc test, it can, of course, be done, but in our eyes, it still would not be correct. However, the data in Figure 5 is a minor part of the study, and we do not want them to be a blocker for publication in PLOS One, so we will do as he editor prefers.

2) why the n number is not consistent (e.g., for Treg n=5, while total CD3 T n=10?)

For rationalization, we chose to limit the number of mice tested for some of the antibodies. A few cell preparations were unsuccessful, and for those few groups n was reduced accordingly. It was already explained in the previous version of the manuscript in line 226-228: ‘For rationalization some antibodies were only tested on randomly selected mice, and 5, 10 or 15 mice were tested on each level (Figure 5a-b). In some groups some of the preparations were unsuccessful and, therefore, n was reduced accordingly.’

3) how to explain the cell number change differences between spleen and MLN?

The mesenteric lymph nodes represent the immune reaction locally in the gut, while the spleen is regarded as an expression of the systemic response. Not all reactions in the gut are translated into a systemic response. This was already explained in line 396 – 399 in the previous version of the manuscript: ‘In the present study we found that the gluten-free diet lowered the levels of Treg locally in the gut, while in the spleen, which should be regarded as an expression of the systemic effect, the gluten-free diet increased Treg fractions, CD4+ T cell activation, and tolerogenic dendritic cell fractions and activation, thereby extending the downregulating effect of the Treg’.

In my opinion, a fecal transfer experiment to demonstrate the effect of gluten-free diet on IgG response is dependent on gut microbiota should be performed to strength this manuscript.

The reviewer has a point but there is already a large data amount in the present paper, and the paper has been on a long track with the journal. We have already mentioned this in the discussion in the previous version of the manuscript (ln 390-392): ‘Whether the impact on vaccine response is GM dependent might be further elucidated through a fecal matter transplantation to germ-free mice.’ We also refer to another study we have published, while awaiting the progression of the present paper, showing how immune effects of a gluten-free diet can be both microbiota dependent and independent. We are in a process of doing further studies within this subject, and fecal matter transplantation is, of course, relevant. However, we also acknowledge the input from reviewer 3 that we should consider other infectious agents, and, therefore, it is not relevant to put these data into this manuscript.

Reviewer #3

The authors have addressed the majority of my comments and questions

Thank you.

Small comments:

(page 54) Abstract: line 32, add lower initial vaccine titer

Done

(page 58) line 114: although this vaccine generally has high immunogenicity….

Done

(line 161) ‘we reconsidered this’, suggest to include a rationale here

The sentence now reads’ while we in study B considered that his might be too short and did the boosting after four weeks’.

(lines 176/ 183) body weights of mice … were monitored. What was the impact of antibiotics and diet on weight in studies A/B (this could be confounding)

This is the ‘materials and methods’ section, and therefore probably it is not the right place to give results. However, the weight curves are shown in S1 Figure and the interpretation that both diet and antibiotics influence weight are referred to in the first sub-section of ‘Results’ (ln 270-273): ‘Mice fed the Altromin modified gluten-free diet weighed significantly more than mice fed the standard Altromin diet in study A (S1 Figure a, P = 0.000). Antibiotics in the drinking water reduced the weight significantly in study B (S1 Figure b, P = 0.001), but this was mostly due to a weight decrease in the first weeks on antibiotics.’

(line 314/315) describe the direction of the correlation and clarify if correlation was for the phylum or species level

Done

Line 317 typo, ‘single’

Done

Line 347, Table 2 – list all FDRs in table or indicate which FDR level was used to generate table. Relative repeated twice in table legend

Done

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(16.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0266719.r007

Decision Letter 3

Brenda A Wilson

9 Mar 2022

PONE-D-21-12086R3Dietary Gut Microbiota Perturbations Influence Murine Vaccine ResponsePLOS ONE

Dear Dr. Kornerup Hansen,

Both reviewers agreed that the revised manuscript was significantly improved. However, Reviewer 2 still has some concerns about the study design and analysis, which really could only be addressed by substantial additional experimentation, which I agree is probably outside the scope of the study since Figure 5 is not a large portion of the overall study. In lieu of that, a title that reflects the manuscript content better and inclusion of additional statistical analysis, as per the reviewer's suggestion, could help address this. But, it will be important to include additional comparative discussion of the results, including caveats and limitations of the study design in light of the results and perhaps suggestions for future studies.

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Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

Reviewer 2 still has some issues with the authors' responses regarding Figure 5 and the goals of the study. I think some of this could be addressed by changing the title to be more reflective of the manuscript content (as is, it is a bit sweeping in nature). I suggest something on the order of: "Effect of gluten-free diet and antibiotics on murine gut microbiota and immune response to tetanus vaccination." I think it would also be good for the authors' to include the Dunnett's post hoc test (in addition to what has already been done) and provide a brief comparative discussion of the results, including caveats to the analyses and limitations of the study design.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

**********

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

Reviewer #2: No

Reviewer #3: (No Response)

**********

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

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

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

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

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

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

6. Review Comments to the Author

Reviewer #2: 1) The authors claim that "Gut Microbiota Perturbations Influence Murine Vaccine Response", but have no intentions to prove their conclusions by providing more experimental data.

2) The authors claim that CD3 T cells are reduced by feeding with a Gluten-free diet in Fig 5A, however, it is really hard to believe that it is a biologically significant reduction at least for the "vacc GF" group, although statistically maybe there is a difference. The two-way ANOVA analysis is mathematically correct, but the way the authors presented it in the current format is hard to interpret.

Reviewer #3: (No Response)

**********

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Reviewer #2: No

Reviewer #3: No

PLoS One. 2022 Apr 13;17(4):e0266719. doi: 10.1371/journal.pone.0266719.r008

Author response to Decision Letter 3

11 Mar 2022

We have updated the reference:

53. Hansen CHF, Larsen CS, Zachariassen LF, Mentzel CMJ, Laigaard A, Krych L, et al. Gluten-free diet reduces autoimmune diabetes mellitus in mice across multiple generations in a microbiota-independent manner. J Autoimmun. 2022;127:102795. Epub 2022/02/02. doi: 10.1016/j.jaut.2022.102795. PubMed PMID: 35101708.

We have changed the title to: ‘Effect of gluten-free diet and antibiotics on murine gut microbiota and immune response to tetanus vaccination’.

I think it would also be good for the authors' to include the Dunnett's post hoc test (in addition to what has already been done) and provide a brief comparative discussion of the results, including caveats to the analyses and limitations of the study design.

We have done Dunnett’s post hoc comparisons on all data in Figure 5 comparing the factorial groups to the ‘Vacc’ group. We have explained this in the statistics section and in the figure legend. We have introduced a sentence under ‘Limitations’: ‘The two-way setup for testing the impact on cell counts does not include a non-vaccinated group, so it is only possible to make conclusions on the relative impact of the experimental factors.’

Attachment

Submitted filename: Response to reviewers.pdf

Click here for additional data file.^{(109.7KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0266719.r009

Decision Letter 4

Brenda A Wilson

28 Mar 2022

Effect of gluten-free diet and antibiotics on murine gut microbiota and immune response to tetanus vaccination

PONE-D-21-12086R4

Dear Dr. Kornerup Hansen,

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

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Brenda A Wilson, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0266719.r010

Acceptance letter

Brenda A Wilson

4 Apr 2022

PONE-D-21-12086R4

Effect of gluten-free diet and antibiotics on murine gut microbiota and immune response to tetanus vaccination

Dear Dr. Kornerup Hansen:

I'm 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 let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, 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.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Brenda A Wilson

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig

(PDF)

Click here for additional data file.^{(131.9KB, pdf)}

S1 Table. Genes for which expressions were monitored by qPCR in the spleens of tetanus vaccinated antibiotics treated and control mice.

(PDF)

Click here for additional data file.^{(294.4KB, pdf)}

S2 Table. Spleen gene expressions for which a significant difference between tetanus vaccinated antibiotics treated and control mice was found by Kruskal–Wallis test (P).

No significances were found if P-values were corrected by false discovery rate (Q).

(PDF)

Click here for additional data file.^{(184.2KB, pdf)}

S3 Table. Correlations of taxa with anti-tetanus IgG in BALB/cBomTac mice vaccinated once or twice with a tetanus toxoid vaccine.

Only correlations significant after FDR correction are shown.

(DOCX)

Click here for additional data file.^{(14.3KB, docx)}

Attachment

Submitted filename: Rebuttal letter.pdf

Click here for additional data file.^{(401.2KB, pdf)}

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(16.9KB, docx)}

Attachment

Submitted filename: Response to reviewers.pdf

Click here for additional data file.^{(109.7KB, pdf)}

Data Availability Statement

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PERMALINK

Effect of gluten-free diet and antibiotics on murine gut microbiota and immune response to tetanus vaccination

Pernille Kihl

Lukasz Krych

Ling Deng

Lars H Hansen

Karsten Buschard

Søren Skov

Dennis S Nielsen

Axel Kornerup Hansen

Roles

Abstract

Introduction

Methods

Mouse experiments

Fig 1. Overall study plan for testing vaccine impact from diet and antibiotics.

Study A: Impact of gluten on primary and boosting vaccination

Study B: Impact of antibiotics on primary and boosting vaccination

Study C: Antibiotic impact on initial immune functions after primary vaccination

Gut microbiota characterization

Sequencing data analysis

Tetanus specific IgG

Serum cytokines

Spleen gene expression

Fluorescence-activated cell sorting (FACS)

Table 1. Markers and gates for flow cytometry.

Fig 5. Effects of a gluten-free diet or antibiotics on immune cell counts as a response to a tetanus vaccine.

Statistics

Results

Gluten-free diet as well as treatment with ampicillin had significant impact on the gut microbiota compared to mice fed standard diet

Fig 2. The impact of a gluten-free diet on gut microbiota and anti-tetanus IgG after tetanus vaccination.

Fig 3. The impact of a antibiotics on gut microbiota and IgG response to tetanus vaccination.

Fig 4. The impact of a gluten-free diet and antibiotics on gut microbiota and IgG response to tetanus vaccination.

Gluten-free diet and antibiotics lowered antibody production after the first vaccination

The fractions of essential immune cell subsets and their activation were reduced in the mesenteric lymph nodes, while it was increased in the spleens of mice fed the gluten-free diet

Diet or antibiotics had only minor impact on systemic cytokine levels or spleen gene expression

Discussion

Limitations

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Anne Wertheimer

Roles

Author response to Decision Letter 0

Decision Letter 1

Brenda A Wilson

Roles

Author response to Decision Letter 1

Decision Letter 2

Brenda A Wilson

Roles

Author response to Decision Letter 2

Decision Letter 3

Brenda A Wilson

Roles

Author response to Decision Letter 3

Decision Letter 4

Brenda A Wilson

Roles

Acceptance letter

Brenda A Wilson

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

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