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      Gut microbiota as a potential key to modulating humoral immunogenicity of new platform COVID-19 vaccines

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          Abstract

          Dear Editor, Coronavirus disease 2019 (COVID-19) is a novel respiratory infectious disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which led to a global pandemic. Although vaccination is the best measure to overcome a pandemic, the immunogenicity of vaccines can be influenced by diverse factors, including intrinsic (age, sex, genetics, and comorbidities), extrinsic (diet, nutrition, and behavior), and vaccine-associated characteristics. 1 In addition, the microbiome may play an essential role in controlling the immune response to both oral and parenteral vaccines. 2 A recent human microbiome intervention study with a trivalent influenza vaccine suggested that microbiota dysbiosis was associated with increased inflammation and decreased vaccine immune response. 3 Antibiotic abuse, obesity, diabetes, and other individual factors could cause intestinal microbiota dysbiosis, which might affect vaccine immunogenicity. Contrary to the influenza vaccine, in the case of COVID-19 vaccines, it would be possible to better evaluate the influence of gut microbes on vaccine immunogenicity in the absence of pre-existing immunity. In this study, we investigated the serial correlations between the gut microbiota and serum SARS-CoV-2 antibody levels after vaccination and analyzed the potential effects of vaccine platform (adenovirus-vectored versus mRNA vaccines). We conducted a prospective cohort study of healthy adult participants fully vaccinated with BNT162b2 (mRNA vaccine) and ChAdOx1 (adenovirus-vectored vaccine) COVID-19 vaccines and collected stool and blood samples prior to the administration of the first (V1) and second doses (V2) and three weeks after the administration of the second dose (V3) (Fig. 1a). Overall and vaccine platform-dependent baseline characteristics and antibody responses are presented in supplementary Tables 1, 2, and 3. Examination of gut microbiota alterations following vaccination revealed that the mean community richness and microbial diversity (alpha diversity) gradually decreased from V1 to V2 to V3 in the ChAdOx1-vaccinated group (Fig. 1b and supplementary Fig. 1). Analysis using the Wilcoxon signed-rank test showed significant differences in Shannon diversity between V1 and V2 (p = 0.008) and V1 and V3 (p = 0.004) in ChAdOx1 recipients. Similarly, principal coordinate analysis of Bray–Curtis distances (beta diversity) using permutational multivariate analysis of variance indicated significantly distinct inter-set distances between the metagenome at V1 and that at V2 (p = 0.028) or V3 (p = 0.001) in ChAdOx1 recipients, but not in BNT162b2 recipients (Fig. 1b). Notable differences in changes in the distribution of bacterial taxonomic groups and their relative abundances at V1, V2, and V3 were also observed following ChAdOx1 vaccination compared to those observed following BNT162b2 vaccination (Fig. 1b and supplementary Fig. 2). Our results demonstrated that the two novel vaccine platforms differentially affected gut microbiota alteration. The interaction between the adenovirus vector and gut microbiome may have contributed to the platform-dependent differences in vaccine immunogenicity. Fig. 1 Serial associations between the gut microbiota, serum SARS-CoV-2 antibody levels and food intakes in adenovirus-vectored or mRNA vaccinees. a Schematic diagram of sample collection and survey. b Changes in alpha (Shannon) and beta diversity, and ternary plots following the administration of two different vaccine platforms. Changes in fecal microbiota diversity based on the Shannon index following ChAdOx1 and BNT162b2 vaccination. Beta diversity results assessed using principal coordinate analysis (PCoA) of Bray–Curtis distances at V1, V2, and V3 are shown for ChAdOx1 and BNT162b2 groups. Genus-level microbiota changes at V1, V2, and V3 are presented as ternary plots for ChAdOx1 and BNT162b2 groups. Each circle represents one genus, and the size of the circle reflects its relative abundance. c Baseline differences in the microbiome composition with respect to the immunogenicity of the vaccine platforms. Baseline differences in microbiota species richness (ACE) and inter-set distances with respect to the immunogenicity of the two different vaccine platforms. Comparison of high and low responders revealed a higher baseline ACE index. d Linear discriminant analysis effect size (LEfSe) analysis to identify taxonomic biomarkers. LEfSe was used to differentiate between high and low responders. The linear discrimination analysis scores revealed significant differences in microbiota composition according to vaccine immunogenicity in ChAdOx1- and BNT162b2-vaccinated groups. Only taxa with p < 0.05 are presented. e Linear discriminant analysis effect size analysis to identify functional biomarkers between high and low responders. Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologs abundant in ChAdOx1- and BNT162b2-vaccinated groups are presented. Only orthologs with p < 0.05 are presented. f, g Taxonomy markers and significant items among 112 food items. Spearman rank analysis was conducted to evaluate the association between immunogenicity-related taxonomic biomarkers and 112 listed food items in f ChAdOx1 and g BNT162b2 recipients, respectively. The color gradients indicate the degree of correlation from red (positive correlation) to blue (negative correlation). *p < 0.05; **p = 0.01–0.001; ***p < 0.001 Next, to evaluate the role of the human gut microbiota in the humoral immune response to COVID-19 vaccines, the study participants were categorized as high or low responders according to their anti-SARS-CoV-2 S IgG titers at V3. Interestingly, we found that baseline microbial species richness (alpha diversity) was positively associated with humoral immunogenicity (Fig. 1c and supplementary Fig. 3). Subsequently, linear discriminant analysis effect size was used to determine and distinguish the composition of the gut microbiome based on immune responses in both ChAdOx1- and BNT162b2-vaccinated groups (Fig. 1d, supplementary Fig. 4, and supplementary Tables 4 and 5). In particular, a high abundance of the genus Parasutterella and the species Eubacterium PAC001034_s and Blautia_uc prior to vaccination was associated with high humoral immune responses in ChAdOx1 recipients. Bacteria of the genus Parasutterella produce succinate and enhance the abundance of tryptophan metabolites, which may exert potential beneficial effects on intestinal mucosal homeostasis by elevating hypoxanthine levels. 4 Furthermore, Parasutterella has been suggested to play a potential role in the metabolism of cholesterol and maintenance of bile acids, especially secondary bile acids. 5 Consistent with a previous finding that the reduction in secondary bile acid levels is associated with a diminished vaccine response, 3 Parasutterella was noted as a crucial taxonomic biomarker for high immunogenicity in ChAdOx1 vaccine recipients. The species Eubacterium PAC001034_s and the genus Blautia belong to the families Rumonococcaceae and Lachnospiraceae, respectively, which are the primary producers of short-chain fatty acids that act as immunomodulatory metabolites. Moreover, similar to Parasutterella, Blautia also strengthens the intestinal barrier by inducing the expression of tight junction proteins and production of mucin by enterocytes and converting primary bile acids into secondary bile acids via 7-α-hydroxylation. 6 In BNT162b2 recipients, a high abundance of the genera Ruminococcaceae PAC000661_g, Romboutsia, and Lachnospiraceae PAC001043_g and species Clostridium PAC001136_s, Lachnospiraceae PAC001043_g PAC001449_s, Eubacterium LT907848_s, Romboutsia timonensis, and Roseburia cecicola prior to vaccination was associated with a high immune response. The interaction of each microbiota may contribute to maintaining intestinal homeostasis and enhancing the vaccine immune response. Clostridium PAC001136_s was reported to be associated with mucosal healing. 7 Roseburia species, a butyrate producer, is known to play a beneficial role in maintaining gut health and immune defense. 8 Lachnospiraceae families might be associated with high immune response in both ChAdOx1 and BNT162b2 recipients owing to their ability to produce butyrate. Based on taxonomic differences in each participant, we investigated the functional profiles that predicted vaccine response between the microbiota of the high and low-responder groups (Fig. 1e, supplementary Fig. 5, and supplementary Tables 6 and 7). Using the PICRUSt algorithm, a significant abundance of the module M00701 (multidrug resistance, efflux pump EmrAB) was observed in ChAdOx1 high responders, whereas the M00088 (ketone body biosynthesis) module and ko00380 (tryptophan metabolism) pathway were observed in BNT162b2 high responders. This may be related to the fact that the gut microbiome produces the butyrate metabolite 3-hydroxybutyrate and the essential amino acid tryptophan, which are involved in colonic homeostasis, mucosal integrity maintenance, and immunoregulation. 9 Because the microbiota metabolizes food ingredients, diet is one of the significant determinants of microbiome composition and functional activity. 1 The correlation analysis of taxonomic biomarkers with 112 food items, energy, and 13 nutrients was conducted before vaccination to examine the dietary link between the microbiome and humoral immune response (Fig. 1f, g and supplementary Figs. 6 and 7). We found that energy, carbohydrates, and sodium intakes were associated with a low abundance of the genus Parasutterella. Consistent with the findings of previous studies, 10 high-fat consumption was negatively correlated with Parasutterella abundance in the present study. Consuming eggs and coffee resulted in a low abundance of Anaerotignum PAC001031_s, which exerts potentially beneficial effects on immunogenicity. Although riboflavin, niacin, and vitamin C intake may be beneficial owing to their positive correlation with bacteria enriched in high responders (the genus Romboutsia and the species Eubacterium LT907848_s and Romboutsia timonensis), these nutrients also correlated positively with bacteria enriched in low responders (M. indica). Because each nutrient can influence several bacteria differently, the effects of diet on microbiota and vaccine immunogenicity should be interpreted with caution. There are several limitations in this study. First, the sample size was small, particularly because we excluded the intermediate responder group. However, we believe that clearer conclusion could be derived as we divide the participants into high or low responders, excepting intermediate responders (gray zone). Second, we could not evaluate the impact of microbiota among inactivated COVID-19 vaccine recipients because it was not avaialble during study periods. At the time of the study, SARS-CoV-2-naive adults were vaccinated against COVID-19 for the first time in their lives, but now more than 80% of the general population has experienced SARS-CoV-2 infection at least once. Moreover, bivalent COVID-19 vaccination is in progress. Thus, direct comparison might not be feasible with inactivated vaccine recipients in this study. In the previous study evaluating the correlation between gut microbiota composition and SARS-CoV-2 vaccines, Bifidobacterium adolescentis was persistently higher in subjects with high neutralizing antibodies to CoronaVac vaccine (inactivated COVID-19 vaccine), while BNT162b2 vaccinees showed a positive correlation with the total abundance of bacteria with flagella and fimbriae including Roseburia faecis. Further studies are warranted. Collectively, this study revealed that the gut microbiome affects the immune response after COVID-19 vaccination and that the adenovirus vector induces changes in the microbiota that can affect the immune response after repeated vaccination. Moreover, we identified the specific taxonomic biomarkers, functional pathways, and potential nutrient factors that affect humoral immunogenicity. Further evaluation is warranted to validate the relevant biomarkers. Supplementary information Supplementary information

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          Most cited references10

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          Antibiotics-Driven Gut Microbiome Perturbation Alters Immunity to Vaccines in Humans

          Emerging evidence indicates a central role for the microbiome in immunity. However, causal evidence in humans is sparse. Here we administered broad spectrum antibiotics to healthy adults prior and subsequent to seasonal influenza vaccination. Despite a 10,000-fold reduction in gut bacterial load and long-lasting diminution in bacterial diversity, antibody responses were not significantly affected. However, in a second trial of subjects with low pre-existing antibody titers, there was significant impairment in H1N1-specific neutralization and binding IgG1 and IgA responses. In addition, in both studies antibiotics treatment resulted in: (i) Enhanced inflammatory signatures (including AP-1/NR4A expression), observed previously in the elderly, and increased dendritic cell activation; (ii) Divergent metabolic trajectories, with a 1000-fold reduction in serum secondary bile acids which was highly correlated with AP-1/NR4A signaling and inflammasome activation. Multi-omics integration revealed significant associations between bacterial species and metabolic phenotypes, highlighting a key role for the microbiome in modulating human immunity.
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            Roseburia spp.: a marker of health?

            The genus Roseburia consists of obligate Gram-positive anaerobic bacteria that are slightly curved, rod-shaped and motile by means of multiple subterminal flagella. It includes five species: Roseburia intestinalis, R. hominis, R. inulinivorans, R. faecis and R. cecicola. Gut Roseburia spp. metabolize dietary components that stimulate their proliferation and metabolic activities. They are part of commensal bacteria producing short-chain fatty acids, especially butyrate, affecting colonic motility, immunity maintenance and anti-inflammatory properties. Modification in Roseburia spp. representation may affect various metabolic pathways and is associated with several diseases (including irritable bowel syndrome, obesity, Type 2 diabetes, nervous system conditions and allergies). Roseburia spp. could also serve as biomarkers for symptomatic pathologies (e.g., gallstone formation) or as probiotics for restoration of beneficial flora.
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              Defining the role of Parasutterella, a previously uncharacterized member of the core gut microbiota

              The genus of Parasutterella has been defined as a core component of the human and mouse gut microbiota, and has been correlated with various health outcomes. However, like most core microbes in the gastrointestinal tract (GIT), very little is known about the biology of Parasutterella and its role in intestinal ecology. In this study, Parasutterella was isolated from the mouse GIT and characterized in vitro and in vivo. Mouse, rat, and human Parasutterella isolates were all asaccharolytic and producers of succinate. The murine isolate stably colonized the mouse GIT without shifting bacterial composition. Notable changes in microbial-derived metabolites were aromatic amino acid, bilirubin, purine, and bile acid derivatives. The impacted bile acid profile was consistent with altered expression of ileal bile acid transporter genes and hepatic bile acid synthesis genes, supporting the potential role of Parasutterella in bile acid maintenance and cholesterol metabolism. The successful colonization of Parasutterella with a single environmental exposure to conventional adult mice demonstrates that it fills the ecological niche in the GIT and contributes to metabolic functionalities. This experiment provides the first indication of the role of Parasutterella in the GIT, beyond correlation, and provides insight into how it may contribute to host health.
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                Author and article information

                Contributors
                infection@korea.ac.kr
                Journal
                Signal Transduct Target Ther
                Signal Transduct Target Ther
                Signal Transduction and Targeted Therapy
                Nature Publishing Group UK (London )
                2095-9907
                2059-3635
                3 May 2023
                3 May 2023
                2023
                : 8
                : 178
                Affiliations
                [1 ]GRID grid.222754.4, ISNI 0000 0001 0840 2678, Department of Internal Medicine, , Korea University College of Medicine, ; Seoul, Republic of Korea
                [2 ]GRID grid.222754.4, ISNI 0000 0001 0840 2678, Asia Pacific Influenza Institute, , Korea University College of Medicine, ; Seoul, Republic of Korea
                [3 ]GRID grid.222754.4, ISNI 0000 0001 0840 2678, Vaccine Innovation Center, Korea University College of Medicine, ; Seoul, Republic of Korea
                [4 ]GRID grid.15444.30, ISNI 0000 0004 0470 5454, Department of Biomedical Systems Informatics, , Yonsei University College of Medicine, ; Seoul, Republic of Korea
                [5 ]GRID grid.254229.a, ISNI 0000 0000 9611 0917, Department of Food and Nutrition, , Chungbuk National University, ; Cheongju, Republic of Korea
                [6 ]GRID grid.411725.4, ISNI 0000 0004 1794 4809, Department of Internal Medicine, , Chungbuk National University Hospital, ; Cheongju, Republic of Korea
                [7 ]GRID grid.222754.4, ISNI 0000 0001 0840 2678, Medical Science Research Center, , Korea University College of Medicine, ; Seoul, Republic of Korea
                Article
                1445
                10.1038/s41392-023-01445-0
                10154741
                37137906
                481ce508-d3f8-49da-af06-796e1673be9e
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 December 2022
                : 20 February 2023
                : 15 April 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003569, Ministry of Food and Drug Safety (MFDS);
                Award ID: 21172MFDS179
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100002701, Ministry of Education (Ministry of Education of the Republic of Korea);
                Award ID: NRF-2021R1I1A1A01050391
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003621, Ministry of Science, ICT and Future Planning (MSIP);
                Award ID: NRF-2021M3E5D1A01015187
                Award Recipient :
                Categories
                Letter
                Custom metadata
                © The Author(s) 2023

                vaccines,predictive markers,infectious diseases
                vaccines, predictive markers, infectious diseases

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