Vaccination with an HIV T-cell immunogen induces alterations in the mouse gut microbiota

doi:10.21203/rs.3.rs-1997415/v1

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Vaccination with an HIV T-cell immunogen induces alterations in the mouse gut microbiota

https://doi.org/10.21203/rs.3.rs-1997415/v1

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published 30 Dec, 2022

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The gut microbiota is emerging as a crucial factor modulating vaccine responses; however, few studies have investigated if vaccines, in turn, can alter the microbiota and to what extent such changes may improve vaccine efficacy. To understand the effect of T-cell vaccination on the gut microbiome, we administered an HIV-1 T-cell immunogen (HTI arm) or PBS (control) to C57Bl/6 mice following a heterologous prime-boost scheme. The longitudinal dynamics of the mice gut microbiota were characterized by 16S ribosomal RNA sequencing in fecal samples collected from cages, as well as from three gut sections (caecum, small and large intestine). Serum and spleen cells were obtained at the study endpoint to assess immune correlates using IFNγ ELISPOT and cytokine Luminex® assays. Compared with PBS, HTI vaccination increased several Clostridiales genera associated with anti-inflammatory responses, such as Eubacterium xylanophilum group, Roseburia and Ruminococcus. Such shifts were observed after the first HTI dose and remained throughout the study follow-up (18 weeks). Hoverer, the enriched Clostridiales specific genera were different between feces and gut sections. The abundance of HTI-enriched bacteria positively correlated with the magnitude of vaccine-induced responses and a set of pro-inflammatory cytokines, especially IL-6. This longitudinal analysis reveals that, in mice, T-cell vaccination promotes the increase of anti-inflammatory gut bacteria in parallel to significant associations with proinflammatory cytokines, suggesting an adaptation of the gut microbial milieu to T-cell-induced systemic inflammation.

It has been well established that the resident gastrointestinal microbiota plays a pivotal role in the development and regulation of both innate and adaptive immune responses ¹. Of the different determinants of the adaptive immune response, T cell response polarization might be especially affected by the gut bacteria composition ². In fact, the absence of specific bacteria has been associated with reduced frequencies of Treg cells in the gut ³ or dysregulated Th17 cell responses in germ-free and antibiotic-treated mice ⁴. Abnormal ratios of these T cell subpopulations (Th17 and Treg) have been frequently associated with metabolic or immunologic diseases ⁵.

Given the tight interaction and co-evolution of gut microbiota and immune system ⁶, increasing evidence suggests that certain bacterial taxa might also modulate vaccine-induced immune responses ⁷, by exerting local or systemic effects ⁸. In recent years, several clinical and animal studies have shown that the composition and functions of the gut microbiota are crucial determinants of the immunogenicity and efficacy of oral and injectable vaccines ^9,10. So far, most work in this area has been focused on the role of the microbiota in modulating vaccine-induced antibody responses ⁷. Of note, the importance of T cell-mediated immunity has been increasingly recognized in the protection induced by several immunization strategies, including those against pathogens such as HIV-1 ¹¹ or SARS-CoV-2 ¹². Yet, a limited number of studies have directly investigated the relationship between the pre-existing gut microbiota and T cell responses to vaccination ¹³.

The effect of vaccine administration on the intestinal microbiota has gathered even less attention. Previous works investigating the effects of HIV-1 ^14,15 and oral typhoid ¹⁶ vaccines on the human gut microbiota reported no discernible perturbations of the microbial community structure induced by vaccination. In contrast, an increase in the Firmicutes/Bacteroidetes ratio following HIV-1 DNA/protein immunization was observed in the rectal microbiome of non-human primates ¹⁷. Also, a recent study comparing two SARS-CoV-2 vaccination strategies reported changes in the human gut microbiota one month after immunization, characterized by lower alpha diversity and increased abundance of a certain bacterial species, such as Bacteroides caccae ¹⁸. Collectively this provides at least circumstantial evidence that vaccination can influence the resident microbiota. Therefore, understanding how vaccines promote changes in the host intestinal immune milieu and alter the microbial community structure, may provide important insight into this interplay and, in turn, the identification of specific bacteria that positively modulate vaccination outcome.

In the present study, HIV-1 T-cell immunogen (HTI) expressing vaccine vectors ^19,20 were used to assess vaccine-induced changes in the gut microbiota and to identify potential correlates with the immunological response to vaccination in a murine model. To this end, 16S rRNA gene sequencing was used to characterize longitudinal fecal microbiome and intestinal content profiles in mice receiving a prime-boost HTI immunization regimen (three DNA.HTI primes followed by a ChAd.HTI and MVA.HTI booster) or PBS (control group). Correlations between gut microbial signatures, T cell vaccine response and cytokines after full immunization were also assessed.

Study design and sequencing analysis

To investigate the effects of HTI vaccination on the gut microbiota, two experimental groups receiving the HTI immunogen (Immunized, n= 20) or PBS (Mock, n= 20) were compared (Fig. 1). Fecal samples were collected longitudinally from cages and from three gut sections for gut microbiome profiling by 16s rRNA gene sequencing; serum and splenocytes were obtained at the end of the study to assess vaccine immunogenicity and cytokine profiles, respectively (Supplementary Fig. S1). Two weeks before vaccination, the mice gut microbiota was homogenized by antibiotic conditioning followed by mouse-to-mouse fecal microbiota transfer (FMT) to reduce baseline variability, as detailed in Supplementary Text and Supplementary Fig. S2.

Mock and Immunized longitudinal samples had no differences in the number of filtered high-quality reads, with a median of 52,092 and 46,584 reads, respectively (Supplementary Fig. S3a and Table S1). Negative extraction (n=12) and no-template PCR (n=11) controls had significantly lower reads (5,966 and 1,444 mean read number, respectively) compared to the experimental groups (Supplementary Fig. S3a). Despite higher sequencing depth in batch 1 (Supplementary Fig. S3b), no substantial impact on data structure was observed after assessing for batch effect across analyses.

Longitudinal assessment of microbiota composition and diversity after HTI vaccination

Prior vaccination, samples displayed similar bacterial composition (w0, Supplementary Fig. S2) and only the genus Bilophila was found significantly increased in the Immunized group before vaccination (Supplementary Fig. S4a). After segregating by sex, female mice were enriched in Lactobacillus and Muribaculum prior to vaccination (Supplementary Fig. S4b). Family-level analysis showed that microbial community composition in the Immunized group resembled that of Mock throughout the experiment (Fig. 2a). Samples from both fecal and luminal content were dominated by Muribaculaceae (49.8% and 57.9%), Lachnospiraceae (14.2% and 11.4%), Bacteroidaceae (9.4% and 4.8%) and Bifidobacteriaceae (7.1% and 6.2%) (Fig 2a and Supplementary Fig. S5a), except for the small intestine (Supplementary Fig. S5b). In this section of the intestinal tract, reduction in Lachnospiraceae NK4A136 group (0.2%) and Bacteroides (0.05%) was concomitant to an overall increase in the abundance of Lactobacillus (7.7%) and Ligilactobacillus (3.7%) (Supplementary Fig. S5c-d). Despite overall compositional similarities during the vaccine regimen (0w - 15w), samples clustered separately by experimental group (p=0.022), but not by timepoint within each group (p=0.594) (Fig. 2b). Also, no significant differences in alpha diversity (Shannon index) were observed between groups during vaccination (Supplementary Fig. S5e). Clustering by experimental group (p=0.021) and intestinal section (p=0.001) was also observed at the study endpoint, being samples from small intestine separated from those from caecum and large intestine (Fig. 2c). Moreover, samples from the small intestine showed significantly lower alpha diversity in both Mock and Immunized groups when compared to caecum and large intestine, although no differences between the two experimental groups were detected (Fig. 2d).

Gut microbiota alterations associated to HTI vaccination

Longitudinal discriminant analysis showed significant changes in the abundance of certain bacteria after vaccination. While only A2 and Bilophila taxa showed differential abundance between experimental groups at the baseline (Supplementary Fig. S4a), a set of Clostridiales genera exhibited significant enrichment in the Immunized group after vaccination (Fig. 3). The most remarkable observation was an enrichment in Ruminococcus in fecal samples from cages (week 3 to 15) and Roseburia from gut sections (caecum and large intestine), while Eubacterium xylanophilum group remained consistently higher in fecal samples from cages and gut sections after week 3. Also, Ligilactobacillus was specifically increased in samples from the small intestine (Fig. 3). Longitudinal assessment of such genera abundance indicated an increasing trend starting at vaccination in the Immunized group (Supplementary Fig. S6). Conversely, no specific genera were consistently increased in the Mock group over time.

Correlations between gut microbial microbial signatures and immunological responses

To examine the HTI immunogenicity, magnitude and breadth of T cell responses were assessed in splenocytes collected at the study endpoint. No significant differences in the background IFNγ-producing splenocytes were found between Mock and Immunized mice, indicating that the vaccination regimen did not induce noticeable unspecific T cell activation at study endpoint (Supplementary Fig. S7a). After specific re-stimulation with peptide pools covering the HTI sequence, splenocytes obtained from mice in the Mock group did not show any IFNγ responses above the thresholds. In contrast, immunized mice showed strong responses, with significantly higher magnitude (median = 1560 IFN-γ SFC/million splenocytes, p=0.00031, Supplementary Fig. S7b) and breadth (median = 8.0 out of 17 positive pools, p=0.00028, Supplementary Fig. S7c) compared to Mock. When assessing serum levels of 22 serum cytokines involved in the immune response to vaccination, IL-6 was the only cytokine showing significant differences between the Immunized and Mock groups after segregating by sex. Specifically, females from the Immunized group showed lower IL-6 levels than males from both Immunized and Mock groups (Supplementary Fig. S7d). We next examined potential links between HTI-specific responses, serum cytokine and discriminant bacterial genera. Spearman Rank correlation analysis showed that Eubacterium xylanophilum group and Roseburia from the three intestinal compartments were significantly and positively correlated with the strength of the vaccine-induced T response (Fig. 4). Most of the tested cytokines showed positive correlations with Eubacterium xylanophilum group, Roseburia and Ruminococcus, with some exceptions (i.e., IL-33). An opposite trend was observed for Ligilactobacillus, which overall showed negative associations with the serum cytokine levels (Fig. 4). Of note, IL-6 was significantly and positively associated with Eubacterium xylanophilum group, Roseburia and Ruminococcus from the large intestine. Moreover, Roseburia showed significant and positive correlations with GM-CSF, IFNγ, IL-17A (small intestine), IL-27 (caecum) and IL-13 (large intestine). Such associations were confirmed in a hierarchical clustering analysis, in which Eubacterium xylanophilum group, Roseburia and Ruminococcus from the three intestinal compartments clustered close to the HTI-specific responses (magnitude, breadth), also displaying positive associations with a group of cytokines (Supplementary Fig. S8).

To date, limited studies have investigated how vaccine administration may alter the resident microbial communities. The present study showed, in mice, an increase in anti-inflammatory bacteria within the Clostridiales groups following HIV T-cell immunization, which in turn significantly associate with proinflammatory cytokines.

As expected from previous studies in humans ²¹ and animal models ²², the prime-boost regimen used in this study, combining the HTI in different vaccine vectors, induced high HTI-specific responses, in terms of magnitude and breadth.

Increased abundance of Clostridiales genera such as Eubacterium xylanophilum group, Roseburia and Ruminococcus was found in the HTI- compared to PBS-vaccinated mice. Except for Eubacterium xylanophilum group, Clostridiales genera found in feces from cages were different from those found in the three gut sections in the Immunized group. Such differences may be related to the presence of distinct bacteria in the intestinal epithelia compared to the lumen ²³ and the presence of a 50–60% spore forming bacteria in the gut, such as Ruminococcaceae and Lachnospiraceae, more likely to be present in feces ²⁴.

Supporting our data, a recent study in rhesus macaques showed that vaccination with three HIV-1 Env expressing DNA plasmid vaccines followed by a gp140 protein booster induced changes in the rectal microbiota, resulting in increased Firmicutes/Bacteroidetes ratio as well as associations of rectal anti-HIV-1 IgG vaccine responses with increased Clostridium IV and reduced Prevotella¹⁷. Enrichment in Ruminococcus in the intestinal microbiota of piglets was also reported after immunization with Lawsonia intracellularis vaccine ²⁵ as well as a change in nasal microbiota after sow vaccination against virulent strains of Glaesserella parasuis²⁶. In parallel, increased Bacteroides abundance along with alterations in the microbial community structure were found following Mtb vaccine (with ESAT6 adjuvanted with TLR8 agonists) administration in mice ²⁷. Similarly, an enrichment in Bacteroides caccae and reduction in clostridial species, such as Coprococcus comes, Dorea longicatena and Ruminococcus obeum were reported in Covid-19 vaccinees ¹⁸. Such apparently conflictive trends indicate that a more thorough understanding is needed to decipher specific microbial shifts induced by distinct immunization strategies.

Our data also indicated that the abundance of bacteria enriched in HTI-vaccinated mice (Eubacterium xylanophilum group, Roseburia and Ruminococcus), assessed in the three gut sections, positively correlated with vaccine-induced responses as well as with the production of IL-6, GM-CSF, IFNγ, IL-17A, IL-27 and IL-13 after vaccination. In particular, significant correlations between Clostridiales genera described as butyrate producing ²⁸ and T cell vaccine response were observed in small intestine (Eubacterium xylanophilum group) as well as caecum and large intestine (Roseburia). Associations between enriched bacteria and serum cytokines varied across the three intestinal sections. Remarkably, the abundance of the Eubacterium xylanophilum group, Ruminococcus and, especially Roseburia in the large intestine positively correlated with IL-6 pro-inflammatory cytokine levels. This bacterial genus also showed strong correlations with pro-inflammatory type 1 (Th1/Tc1) polarization cytokine IFNγ in the small intestine and IL-27 in the caecum and the large intestine. Of note, IL-27, mainly produced by dendritic cells and macrophages, promotes T cell differentiation to pro-inflammatory Th1 profile while inhibiting anti-inflammatory Th2 polarization, thus regulating the delicate Th1/Th2 balance ²⁹.

Positive correlations between anti-inflammatory bacteria ³⁰ (Roseburia, Ruminococcus and Eubacterium) and pro-inflammatory cytokines (IL-6, IL-27 and IFNγ) might indicate that the gut microbiota tend to adapt to increased systemic inflammation following vaccination. Specifically, increased inflammation may generate a favorable environment for these bacteria to colonize the immune gut milieu, thrive in it, and in turn modulate and quench the inflammatory processes. Also, our results reflect a different crosstalk between gut bacteria and mucosal immune cells in each gut section ³¹, with the most prominent distinction occurring between the small intestine compared to the caecum and large intestine, as previously reported³².

While the exact mechanism by which HTI-immunization would induce changes in the intestinal milieu and promote an increase of specific bacteria remains unclear, cytokine signaling after innate immunity activation is one of the most plausible hypotheses. Specific components of the gut microbiota have been implicated in the production of pleiotropic cytokines by innate immune cells, such as IL-6, and the subsequent expansion of Th17 cells ³³, which might be critical for

vaccine-induced memory immune responses against infectious diseases ³⁴. In addition, flagellin and peptidoglycan produced by certain intestinal bacteria, such as Ruminococcus spp.³⁵, can be sensed by pattern recognition receptors (PRRs) expressed by T cells and B cells and act as natural adjuvants to vaccines ⁷. Consistently, higher abundances of bacteria with flagella and fimbriae, including butyrate-producing such as Roseburia and Eubacterium, may play a beneficial role in vaccine immunogenicity serving as adjuvants through immunomodulatory TLR agonists ³⁶. Notably, members of these bacterial groups, such as Roseburia intestinalis and Eubacterium hallii have been listed as probiotic candidates by the International Scientific Association for Probiotics and Prebiotics ³⁷. Indeed, some Clostridia genera, including those identified in this study, have been shown to modulate the colonic luminal metabolome, regulate T-cell responses and enhance regulatory T-cell functions³⁸ by producing short-chain fatty acids (SCFAs), such as butyrate ^24,39. Furthermore, the prime-boost regimen combining viral vaccine vectors rich in Pathogen Associated Molecular Patterns (PAMP), can activate innate and adaptive immunity, leading to a new equilibrium in the gut mucosal immune system ⁴⁰. Collectively, these data suggest potential mechanisms by which the HTI immunogen may interact with resident bacteria in the intestinal environment. However, further work is needed to identify specific pathways underlying these associations and elucidate the potential gut-associated immunomodulatory role of certain Clostridiales groups.

While the reported observations are novel, this study had several limitations. The small sample size has made it difficult to find further correlations between the microbiota and immune markers. Another intrinsic limitation is the inability of the 16S rRNA gene sequencing to distinguish live organisms from transient microorganism colonization ⁴¹. Also, the lack of longitudinal cytokine measurement did not allow us to identify temporal variations of immune correlates with specific bacterial signatures and link these to the different stage of the vaccine regimen. Future pre-clinical studies, including nonhuman primates, can be expected to validate our results in similar study designs including a modified vaccine regimen. Furthermore, additional multi-omics and in-vitro analyses can help to define the exact role of the reported bacteria enrichment upon vaccination and, then establish whether such findings can be extrapolated to humans.

In summary, our data suggest that gut bacteria can adapt to vaccine-induced inflammation. Also, they establish a framework for future studies to fully capture the dynamics of microbial shifts to T-cell vaccination and, ultimately provide new potential targets for optimizing vaccine efficacy.

Mice and housing

Six-week-old C57BL/6JOlaHsd mice (n= 40, 20 females and 20 males), grown in the same breeding facility, were purchased from Envigo and housed under specific pathogen-free (SPF) conditions at the Centre for Comparative Medicine and Bioimage (CMCiB) animal facility at IGTP in Badalona, Spain. Mice were randomly assigned to cages according to a combination of sex (female/male) and treatment group (Mock/Immunized), with a maximum of 5 animals per cage (Fig. S1 Supplementary) and allowed to acclimate for one week before the initial treatment.

Pre-intervention gut microbial homogenization

To reduce potential baseline differences in the microbiota composition, the mice gut microbiota was homogenized by antibiotic conditioning followed by mouse-to-mouse FMT (one week after arrival and two weeks prior to vaccination). The antibiotic treatment consisted of a combination of ampicillin, amikacin, metronidazole and vancomycin (10mg/ml each antibiotic), administered via oral gavage (200 µl/animal) for 5 days prior to FMT. Mixed stools from five male and five female donor mice (cages MF1 and MM1, Fig. S1 Supplementary) were used for FMT in all animals in the study. Briefly, feces from donors were collected, pooled, aliquoted (350 mg vials) and preserved at -80 °C until use. On the day of the fecal transfer, thawed feces were resuspended in sterile physiological saline serum (2.3 ml per vial), homogenized, centrifuged (500 xg, 1 min) and supernatant administered by oral gavage (100 µl/animal). Bacterial load in FMT was measured using the LIVE/DEAD^® BacLight™ Bacterial Viability and Counting Kit (Invitrogen, Carlsbad, MA, USA).

Immunization strategy

Animals were vaccinated with the HIV T-cell immunogen (HTI), a synthetic protein designed as the fusion of different HIV-1 protein fragments associated with T-cell control of HIV infection ²⁰. HTI vaccine immunogenicity has been previously tested in C57BL/6 mouse model and non-human primates ²² as well as in humans ²¹. In this study, twenty mice (10 females and 10 males) were immunized intramuscularly (caudal thigh muscle) with a heterologous prime-boost regime consisting of three different vaccine vectors expressing HTI: i) three DNA.HTI primes (100 μg/animal), ii) one boost with ChAd.HTI (1x10⁹VP/animal), and iii) a second boost with MVA.HTI (1x10⁶pfu/animal). DNA.HTI vaccinations were administered at weeks 0, 3, and 6, followed by ChAd.HTI and MVA.HTI, separated by a six week interval (weeks 9 and 15, respectively) (Fig. 1 and Fig. S1 Supplementary). Mice in the mock group (n= 20, 10 females and 10 males) were vaccinated with PBS as a control group, following the same immunization schedule.

Sample collection and processing

Microbiota data were generated in two batches (samples extracted and sequenced in 2019 and 2020), as illustrated in Fig. S1 Supplementary. The first sequencing batch included pooled fecal samples longitudinally collected from cages, whereas the second batch included longitudinal pools of feces from cages and individual fecal samples obtained from different sections of the intestinal tract at the study endpoint. Longitudinal fecal samples were collected (one pool per cage, n=5) at animal arrival (week -3), following antibiotic conditioning prior to FMT (week -2) and prior each vaccination (weeks 0, 3, 6, 9 and 15). Donor pool fecal sample (week -1) was also collected and sequenced in batch 1. Three weeks after the last immunization (week 18), mice were euthanized and luminal contents from three intestinal sections (small, caecum and large intestine), whole blood and spleen were harvested. Serum was separated from the whole blood by centrifugation (10000 xg, 5 min) in Serum Gel S/1.1 tubes (Sarstedt) and frozen at -80°C until use. Splenocytes were isolated by mechanical disruption and pressed through a cell strainer (Falcon) using a 5 ml-syringe rubber plunger. Following red blood cell lysis, splenocytes were washed, resuspended in R10 (RPMI 1640 supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 100 U/ml penicillin and 100 µg/ml streptomycin) and cryopreserved in liquid N₂ until use.

DNA extraction and 16S rRNA sequencing

Genomic DNA from fecal samples and intestinal content was extracted using the QIAamp DNA Stool Kit, according to the manufacturer’s instructions, and stored at -80 °C until sequencing. Amplification of the V3–V4 hypervariable region of the 16S rRNA gene was performed using universal primers flanked by standard forward and reverse adapters (16S_F 5′-TCG TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CCT ACG GGN GGC WGC AG-3′; 16S_R 5′-GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GGA CTA CHV GGG TAT CTA ATC C-3′) described in the Illumina MiSeq rRNA Amplicon Sequencing protocol (San Diego, CA, USA). PCR were performed in 25 μL reaction volume, containing 2.5 μL of DNA template, 12.5 μL of KAPA HiFi HotStart Ready Mix (KAPA HiFi HotStart DNA Polymerase, buffer, MgCl₂, and dNTPs, KAPA Biosystems Inc., Wilmington, MA, USA) and 5 μL of each primer at 1 μM. Thermocycling conditions were as follows: initial denaturation step at 95 °C for 3 min, followed by 30 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, extension at 72 °C for 30 s and a final extension step at 72 °C for 10 min. Once the expected amplicon size was confirmed on a 1.0% agarose gel electrophoresis (~460 base pairs), PCR products were stored at −30 °C until sequencing library preparation. Negative extraction and PCR controls (blank controls using DNA-free water as the template) were loaded to assess for potential contamination and processed in the same conditions as any other sample. Amplified DNA templates were cleaned-up with AMPure XP reagent (Beckman Coulter Life Sciences, Indianapolis, USA) for non-DNA molecules and Illumina sequencing adapters and dual indices were attached using Nextera XT index Kit (Illumina Inc.), followed by a corresponding PCR amplification program as described in MiSeq 16S rRNA Amplicon Sequencing protocol (Illumina Inc., San Diego, CA, USA). After the second round of clean-up, amplicon libraries were quantified using a Quant-iT^TM PicoGreen^® dsDNA Assay Kit (Invitrogen, Carlsbad, MA, USA) and diluted in equimolar concentrations (4 nM) for further pooling. Pooled libraries were sequenced on an Illumina MiSeq^TM platform (Illumina Inc., San Diego, CA, USA) at the genomics core facility in Germans Trias i Pujol research campus (Badalona, Spain) using a paired-end 300 base-length protocol.

Microbiome data analysis

The quality of raw sequencing data was estimated using FastQC ⁴² and the analysis of 16S rRNA sequences performed using the DADA2 pipeline (v1.10.1) ⁴³. The pipeline was executed according to default parameters using maxEE = 4.10 in the filtering step. After chimeric reads removal, unique amplicon sequence variants (ASV) were assigned a taxonomy and aligned to the SILVA rRNA gene database⁴⁴. Downstream analyses were conducted in the R environment (v3.5.2) ⁴⁵ using multiple packages, including phyloseq (v1.26.1) ⁴⁶, vegan (v2.5-5) ⁴⁷ ade4 (v1.7-13) ⁴⁸and ggplot2 (v3.2.0) ⁴⁹. ASV counts were normalized and transformed to relative abundance using the phyloseq function transform_sample_counts (100 × (x/sum(x))). Alpha diversity (Shannon entropy index) was evaluated using the estimate_richness on rarefied ASV counts. Beta diversity was calculated based on Bray–Curtis distances (normalized data) and distance matrix used to perform an ordination principal coordinate analysis (PCoA).

Mouse IFNγ ELISPOT assay

ELISPOT assays were performed using the mouse IFNγ ELISPOT kit (ALP) (Mabtech AB, Stockholm, SE), following the manufacturer’s instructions with minor modifications. Briefly, splenocytes were thawed, washed, counted (NucleoCounter® NC-3000, Chemometec), cell density adjusted with R10 at 4 × 10⁵ cells/well and plated in 96-well polyvinylidene plates (Millipore Corp., Bedford, MA), previously coated with IFNγ capture antibody (clone AN-18). Cells were stimulated with 17 HTI- specific peptide pools (14 μg/ml final concentration for each peptide) for 16 h at 37 °C in 5% CO2. A set of 147 overlapping peptides (OLP) of 15 amino acids in length, overlapping by 11 amino acids and covering the entire HTI sequence, were designed using the PeptGen algorithm (Los Alamos HIV database) and synthesized (Synepeptide). To assess responses to HTI, OLP were assembled into 17 separated peptide pools consisting of 7 pools for Gag (8-11 peptides/pool), 7 for Pol (11 or 5 peptides/ pool), 2 for Vif (8 and 6 peptides/pool) and 1 for Nef (2 peptides/pool). Concanavalin A (Sigma-Aldrich Corp., Saint Louis, MO), at 5 µg/ml, was used as a positive control and R10 in triplicate as a negative control. After stimulation, spot-forming cells (SFC) were revealed by adding a biotinylated IFNγ detection antibody (clone R4-6A2), streptavidin conjugated with alkaline phosphatase (AP) and AP Conjugate Substrate Kit (Bio-Rad Laboratories, Inc., Irvine, CA). SFC per well were counted using an automated ELISPOT reader system (CTL Analyzers LLC, Cleveland, OH) together with the ImmunoSpot software and the magnitude of responses expressed as SFC per 10⁶ splenocytes. Threshold for positive responses was defined as responses that were at least 50 SFC/10⁶ spleen cells, the mean SFC/10⁶ spleen cells in negative control wells plus 3 standard deviations of the negative control wells, or three times the mean of negative control wells, whichever was higher. Results were given as total magnitude (accumulated response to all the pools; SFC/10⁶ PBMCs) and breadth (number of positive pools).

Luminex assay

Concentration of CD40 Ligand (CD154), GM-CSF, IFN γ, IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12 (p70), IL-13, IL-15, IL-17A, IL-17E/IL-25, IL-21, IL-22, IL-23, IL-27, IL-31, IL-33, TNFα, TNFß at the end of the study (week 21 wpi) was measured in mice sera. Briefly, serum samples were thawed, vortexed and centrifuged at 10000 xg for 10 min before collecting 25 µl of serum for further testing. The serum concentration of the 22 cytokines was measured simultaneously using sample duplicates in a customized mouse Th17 magnetic bead panel kit (Milliplex) and a Luminex^®200 (Luminex Corp) reader, following manufacturer's instructions.

Statistical analysis

Differences in alpha diversity and taxa abundance within each experimental group at different time points and between groups at each time point were assessed using the Wilcoxon signed-rank and Kruskal-Wallis test (two sided). For beta diversity, statistical significance was assessed using the pairwise permutational multivariate analysis of variance (PERMANOVA, adonis) test. Taxa with differential abundances in the groups were identified using diff_analysis and visualized using ggdiffbox and ggeffectsize in the R/MicrobiotaProcess package. The linear discriminant analysis effect size (LEfSe) ⁵⁰ was performed to identify discriminant bacterial signatures between Mock and Immunized groups (α = 0.05 and LDA score > 2.0). Associations between cytokines, immune response and bacteria were computed based on Spearman correlation coefficients in combination with Benjamini-Hochberg multiple testing correction using the rcorr function within the R/hmisc package. Statistical analyses were performed in the R environment and two-tailed 5% level of significance (p-value ≤ 0.05) was considered significant, unless otherwise stated.

Ethics Statement

All experiments involving animals were approved by the Animal Experimentation Ethics Committee of the Germans Trias i Pujol Hospital (IGTP) and the Generalitat de Catalunya (Project number: 10559).

Data availability

The raw 16S rRNA sequencing reads used in this study have been deposited at the Sequence Read Archive (SRA) repository (Bioproject No. PRJEB52963).

Code availability

R analysis scripts and data associated with this paper are available at https://doi.org/10.5281/zenodo.7017193.

Author contributions

M.N.J., C.B., A.O. and R.P. designed the study and supervised the research. A.B. analyzed the data and wrote the manuscript. A.E.T. contributed to data interpretation and redaction of the manuscript. A.E.T., M.C. and A.O. set up the animal experiments and collected samples. A.E.T., M.C. and M.P performed fecal DNA extraction, library preparation and sequencing. L.R., T.E. and A.O performed cytokine profiling and immune response determinations. F.C.M, M.N.J and A.B. contributed to data processing, management, and storage. All authors edited drafts critically, revised the manuscript, and approved the final version as submitted.

Financial support

The project received funding from the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement Nº 847943 (MISTRAL) and was sponsored in part by Grifols.

Competing interests

The authors declare no competing interests.

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Vaccination with an HIV T-cell immunogen induces alterations in the mouse gut microbiota

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