Inhibition of IL-22-producing cells by Sutterella sp. bacteria

Inhibition of IL-22-producing cells by Sutterella sp. bacteria | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Inhibition of IL-22-producing cells by Sutterella sp. bacteria Louise Dupraz , Giovanna Orianne , Grégory Da Costa , Romain Gauthier , Amy Blondeau , Marie Boinet , Laura Creusot , Aurélie Magniez , Loïc Chollet , Nathalie Rolhion , Camille Danne , Zdenek Dvorák , Philippe Seksik , Harry Sokol , Marie-Laure Michel doi: https://doi.org/10.1101/2025.03.20.644103 Louise Dupraz 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France 2 Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Saint-Antoine Hospital, Gastroenterology department , F-75012 Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Giovanna Orianne 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Grégory Da Costa 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Romain Gauthier 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amy Blondeau 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Marie Boinet 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laura Creusot 2 Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Saint-Antoine Hospital, Gastroenterology department , F-75012 Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Aurélie Magniez 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Loïc Chollet 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nathalie Rolhion 2 Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Saint-Antoine Hospital, Gastroenterology department , F-75012 Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Camille Danne 2 Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Saint-Antoine Hospital, Gastroenterology department , F-75012 Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zdenek Dvorák 3 Department of Cell Biology and Genetics, Faculty of Science, Palacky University , Olomouc, Czech Republic Find this author on Google Scholar Find this author on PubMed Search for this author on this site Philippe Seksik 2 Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Saint-Antoine Hospital, Gastroenterology department , F-75012 Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Harry Sokol 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France 2 Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, CRSA, AP-HP, Saint-Antoine Hospital, Gastroenterology department , F-75012 Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Marie-Laure Michel 1 Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute , 78350 Jouy-en-Josas, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: marie-laure.michel{at}inrae.fr Abstract Full Text Info/History Metrics Supplementary material Preview PDF SUMMARY The gut microbiota constitutes a complex ecosystem essential for host defense against infection and maturation of the immune system. Inflammatory bowel diseases (IBD), such as ulcerative colitis and Crohn’s disease, are characterized by a severe inflammation of the intestine, arising from dysregulated control of host-microbiota crosstalk. However, neither the genetic bases of IBD nor the immune responses involved are fully understood. The pathobionts are currently under investigation for their active role in the development and the severity of IBD. These bacteria are present in the microbiota of healthy individuals without causing disease but have pathogenic potential when the intestinal environment is disturbed. Here, we highlighted Sutterella sp. as a new commensal pathobiont for its capacity to modulate the host immune functions. This anaerobic Gram-negative bacterium inhibits IL-22 production and AhR activity in mice and humans. The effectors responsible for the biological activity are large (>30 kDa) protein-based compounds secreted by Sutterella sp. These data enhance our understanding of the mechanisms that regulate host immune functions and pave the way for new therapeutic strategies to control gut inflammation. INTRODUCTION The gut microbiota forms a complex ecosystem that plays a crucial role in host defense against infections and the maturation of the immune system 1 . Inflammatory bowel diseases (IBD), such as ulcerative colitis (UC) and Crohn’s disease (CD), are characterized by severe intestinal inflammation resulting from dysregulated interactions between the host and its microbiota 1 . These pathologies require long-term treatments based on anti-inflammatory and immunosuppressive therapies, which are often associated with drug-related side effects. Moreover, some patients exhibit poor responses to existing therapies, highlighting the need for novel treatment approaches. Modulation of the gut microbiota is an actively studied strategy, notably through the use of probiotics, prebiotics, or fecal transplantation to enhance beneficial microbial species (such as Faecalibacterium prausnitzii ) or microbiota-derived metabolites (such as short-chain fatty acids and aryl hydrocarbon receptor (AhR) ligands) that support gut health 2 . The pathobionts are also currently under investigation for their active role in the development and severity of IBD 3 . These are bacteria present in the microbiota of healthy individuals without causing disease but they can become pathogenic when the intestinal environment is disturbed. Research has primarily focused on adherent invasive Escherichia coli (AIEC), Helicobacter hepaticus or Ruminococcus gnavus 3 . Identifying additional pathobionts and deciphering their mechanisms of action could lead to a better understanding and management of IBD pathophysiology and pave the way for a new generation of treatment. Interleukin-22 (IL-22) is a member of IL-10 family, crucial to maintain epithelial barrier function, promote tissue repair and protect against pathogens and pathobionts 4 , 5 . This cytokine is produced by αβ CD4 + T helper 17 (Th17) cells, T helper 22 (Th22) cells, γδ T cells and ROR-γt + innate lymphoid cells (ILC3 CD4 + and CD4 neg ), in response to IL-23 and IL-1β produced by dendritic cells and macrophages. IL-22 targets mainly tissue epithelial cells that express IL-22R1, stimulates the production of protective mucus from goblet cells, and induces the production of antimicrobial peptides (RegIIIβ, RegIIIγ and β-defensins) 6 . IL-22 protects the intestine against bacterial pathogens such as Citrobacter rodentium 7 and Clostridium difficile 8 , but favors Salmonella typhimurium colonization 9 and Toxoplasma gondii -induced immunopathology 10 . During intestinal inflammation, IL-22 is present in high quantities in the blood of patients with Crohn’s disease (CD). It protects intestinal mucosa from inflammation via the maintenance of epithelial barrier integrity in CD 11 . It also has a protective effect in DSS (dextran sulfate sodium)-induced colitis mouse model 12 , since genetic or pharmacological ablation of IL-22 induces an exacerbated epithelial destruction and colonic inflammation. However, IL-22 also worsens inflammation in a chronic colitis model that is induced by an adoptive transfer of memory CD4 + T cells 13 . IL-22 was thus shown to play beneficial or deleterious roles in intestinal inflammation contexts, mainly depending on the cytokine environment. Considering its dual implication, to understand the interactions between the gut microbiota (especially the pathobionts) and IL-22-producing cells, could identify promising targets for IBD therapy. Here, we identify Sutterella sp., as a new pathobiont belonging to the betaproteobacteria class and the Burkholderiales order. This anaerobic Gram-negative bacterium can inhibit IL-22 in vitro and in vivo by regulating AhR activity, without affecting ROR-γt expression. The effectors of activity are secreted by Sutterella and are protein-based (>30 kDa). RESULTS The Sutterella sp. bacteria correlate negatively with gut IL-22- and IL-17-producing cells The gut microbiota is essential to maintain gut IL-22 and IL-17A (IL-17)-producing cells 14 , 15 . Therefore, as previously reported 16 , 17 , we found that vancomycin or a mix of antibiotics decrease the production of these two cytokines by αβ CD4 + T cells, γδ T cells, CD4 + CD3 neg or CD4 neg CD3 neg cells (gated as described in Figure S1A) in the small intestine (SI), and colon ( Figures 1A-B ; Figures S1B, S1C). Only colonic γδ T cells are differentially regulated since their production of IL-17 and IL-22 were increased with antibiotics treatment (Figures S1B-S1C), as we previously observed 17 . Download figure Open in new tab Figure 1. IL-22 and IL-17-producing cells reduce with antibiotics while bacteria from Sutterellaceae family increase. (A, B) Percentage of IL-22 (A) and IL-17 (B) among gated CD4 + αβ T cells, γδ T cells, CD3 neg CD4 + and CD3 neg CD4 neg cells from small intestine obtained from untreated mice (control, CTL), neomycin (Neo)-, vancomycin (Vanco)– or neomycin+vancomycin (Mix)-treated mice. Cells were stimulated with PMA + ionomycin + IL-1β + IL-23 for 4 hours. (C, D) Correlation by Spearman r between percentage of IL-22 (C) and IL-17 (D) -producing cells gated as in A and Sutterellacae abondance in small intestine. (E) SEM images of S. wadsworthensis and S. parvirubra . Error bars are SEM from 5 to 10 mice per group (A, B) and from 16 mice (C, D). Significant differences were determined using Kruskal-Wallis test (A, B): *p < 0.05; **p < 0.01; ***p < 0.001. See also Figure S1. Although several commensals and microbiota-derived metabolites have been shown to regulate IL-22- and IL-17-producing cells 12 , 14 , 17 , 18 , we analysed a 16S sequencing in order to identify new candidate commensals species controlling IL-22 and/or IL-17 production in the small intestine and colon of antibiotics-treated and untreated mice. The proportion of IL-17 + and IL-22 + cells correlated positively with the abundance of Segmented Filamentous Bacteria (SFB, Candidatus arthromitus ) in the small intestine (Figure S1D), which is in line with the well described stimulatory effect of SFB on Th17 cells in the mouse small intestine, thus validating our approach. Interestingly, we also observed a negative correlation between IL-22 and IL-17 productions and bacteria from the family Sutterellaceae ( Figures 1C-D ; Figures S1E-S1F), suggesting that members from this family could inhibit IL-22 and IL-17 production. Highly prevalent in the human intestinal mucosa 19 , 20 , the genus Sutterella is increased in the faecal microbiota of patients with UC, and is thus a genus of interest in intestinal inflammation contexts. The two main species of Sutterella found in humans are S. wadsworthensis and S. parvirubra , with a mix of two different morphologies in pure culture: rod and oval shaped ( Figure 1E ). The Sutterella sp. bacteria inhibit IL-22 and IL-17 production in vitro To test the effect of Sutterella sp. on IL-22 and IL-17 production, we used the culture supernatant of S. wadsworthensis and S. parvirubra to stimulate the immune cells isolated from the SI lamina propria. S. wadsworthensis and S. parvirubra supernatants inhibited IL-22 production ( Figure 2A ) and, to a lower extent, IL-17 production ( Figure 2B ) by murine immune cells in vitro . Flow cytometry analysis revealed that S. wadsworthensis inhibited IL-22 and IL-17 production by αβ CD4 + T cells, γδ T cells, CD4 + CD3 neg or CD4 neg CD3 neg cells from SI, as early as 4h ( Figure 2C ). To evaluate the generality of these observations, we analyzed cells from peripheral lymph nodes and found that the proportion and the quantity of IL-22 and IL-17 produced by peripheral γδ T cells and CD4 + CD3 neg cells, were also inhibited by S. wadsworthensis supernatants ( Figures 2D-E ), without inducing any toxicity (Figure S2A). Within four hours of incubation, S. parvirubra only decreased the proportion of IL-22 + γδ T cells (Figure S2B) without any toxic effects (Figure S2C). Of note, other members of the Pseudomonadota phylum, such as E. coli , or Burkholderiales order, such as Achromobacter denitrificans , did not exhibit any inhibitory effect on IL-22 and IL-17 productions ( Figure 2F ). Download figure Open in new tab Figure 2. Sutterella regulates IL-17 and IL-22 productions in vitro. (A, B) Cells from LP of small intestine were cultured for 24h with BHI (black) or S. wadsworthensis (Sw, blue) or S. parvirubra (Sp, red) culture supernatant and stimulated with PMA + Ionomycin + IL-1β + IL-23. IL-22 and IL-17 productions were measured in the supernatants. (C) Intracellular analysis of IL-17 and IL-22 expression by gated αβ CD4+ T cells, γδ T cells, CD3 neg CD4 + cells and CD3 neg CD4 neg cells from small intestine cultured with BHI (top), Sw (bottom) culture supernatant and stimulated for the 3 last hours with PMA + Ionomycin + IL-1β + IL-23. Data are representative of three independent experiments (D) Intracellular analysis of IL-22 (left) and IL-17 (right) expression by gated γδ T cells and CD3 neg CD4 + cells from pLN cultured with BHI (black), Sw (blue) culture supernatant and stimulated as in C. (E) Normalized geometric mean fluorescence intensity for IL-22 (left) and IL-17 (right) in gated γδ T cells and CD3 neg CD4 + cells obtained as described in D. (F) Cells from pLN were cultured for 24h with BHI (black), S. wadsworthensis (Sw, blue), S. parvirubra (Sp, red), E. coli (Ecoli, green) or A. denitrificans (Ad, violet) culture supernatant and stimulated as in A. IL-22 (top) and IL-17 (bottom) productions were measured in the supernatants. (G) Intracellular analysis of IFN-γ expression by gated γδ T cells obtained as described in D. (H) Normalized geometric mean fluorescence intensity for IFN-γ in gated γδ T cells obtained as described in G. Error bars are SEM with 8-9 mice (A), 5 mice (B), 13 mice (D-F). ns, not significant, *P < 0.05, **P < 0.005, ***P < 0.001, ****P < 0.0001; by Wilcoxon test or Friedman test. See also Figure S2 Although it has been previously speculated that Sutterella sp. has a proinflammatory profile 20 , it does not seem to be the case in our hands. Besides the inhibition of IL-17 and IL-22, S. wadsworthensis and S. parvirubra did not affect either the production of the pro-Th1 cytokine IFN-γ by peripheral γδ T ( Figures 2G-H ; Figure S2D), or the release of IL-6, TNF-α and IFN-γ by SI lamina propria cells (Figure S2E). Finally, Sutterella did not alter IL-8 production by epithelial cell line, unstimulated or stimulated with TNF-α, in comparison to control (Figure S2F). The Sutterella sp. bacteria inhibit IL-22 production in vivo In line with in vitro results, intragastric gavage of S. wadsworthensis induced a significant reduction in the frequency of IL-22-producing CD4 + CD3 neg cells in SI (Figure S3A) and decreased production of IL-22 by all populations (αβ CD4 + T cells, γδ T cells, CD3 neg CD4 + and CD3 neg CD4 neg ) as demonstrated by geometric mean fluorescence intensity (MFI) analysis (Figure S3B). Regarding IL-17, only its quantity produced by αβ CD4 + T cells was reduced in S. wadsworthensis -treated compared to control mice (Figure S3C, S3D). Because dead bacteria pellet has no effect in vitro on IL-17 and IL-22 production (Figure S3E), we next analyzed the capacity of Sutterella culture supernatants to regulate these cytokines in vivo . While the proportion of IL-22-producing αβ CD4 + T cells from distal SI and IL-22-producing CD3 neg CD4 + cells from proximal SI were reduced by S. wadsworthensis and S. parvirubra culture supernatant ( Figure 3A-B , Figure S3F), the quantity of IL-22 produced was reduced for all populations (αβ CD4 + T cells, γδ T cells, CD3 neg CD4 + and CD3 neg CD4 neg ) from distal and proximal SI, in both strains-treated mice in comparison to control mice ( Figure 3A, 3C ; Figure S3G). Thus, Sutterella sp. is able to inhibit IL-22 production in vitro and in vivo . Concerning IL-17, as observed with alive bacteria (Figure S3C), the culture supernatants did not affect the proportion ( Figure 3D , Figure S3H) but reduced the quantity of cytokine produced by αβ CD4 + T cells from distal SI of S. wadsworthensis and S. parvirubra -treated mice ( Figure 3E , Figure S3I). Download figure Open in new tab Figure 3. Sutterella regulates IL-17 and IL-22 productions in vivo. (A) Representative plots of gated αβ CD4+ T cells (top, left), γδ T cells (top, right), CD3 neg CD4+ (bottom left), CD3 neg CD4 neg (bottom right) cells from distal small intestine obtained from BHI (left), S. wadsworthensis (Sw, middle) or S. parvirubra (Sp, right) culture supernatant - treated mice. (B-E) Intracellular analysis of IL-22 (B) and IL-17 (D) expression and normalized geometric mean fluorescence intensity for IL-22 (C) and IL17 (E) by gated αβ CD4+ T cells, γδ T cells, CD3 neg CD4 + , CD3 neg CD4 neg cells obtained as in A. In each case, cells were stimulated 3 hours with PMA + Ionomycin + IL-1β + IL-23. Error bars are SEM with 7-9 mice per group for each experiment. *P < 0.05, **P < 0.005, by Kruskal-Wallis test. See also Figure S3 Sutterella sp. bacteria inhibit IL-22 independently of RORγt and STAT3 and likely through AhR As ROR-γt is required to stimulate IL-22 and IL-17 production 21 , the expression of this transcription factor was assessed after stimulation of cells from pLN with S. wadsworthensis and S. parvirubra culture supernatant. Although we observed an inhibition of IL-22 mRNA expression following incubation with Sutterella supernatants, the expression of RORc gene was maintained ( Figure 4A ). The proportion of total ROR-γt + cells was not altered by S. wadsworthensis and S. parvirubra culture supernatant ( Figure 4B ), as also observed at the γδ T lymphocyte level (Figure S4A). Moreover, among RORγt + ILC3 (CD3 neg CD4 + RORγt + cells), S. wadsworthensis and S. parvirubra culture supernatants reduced the proportion of IL-22-competent cells ( Figure 4C ). Therefore, Sutterella sp. acts on IL-22 and IL-17 production independently of RORγt inhibition. Download figure Open in new tab Figure 4. Sutterella regulates directly IL-22 producing cells by the inhibition of AhR. (A) Cells from pLN were cultured for 4 hours with BHI (black) or S. wadsworthensis (Sw, blue) or S. parvirubra (Sp, red) culture supernatant and stimulated with PMA + Ionomycin + IL-1β + IL-23 for the 3 last hours. IL-22 (top) and RORc (bottom) mRNA were quantified by qPCR. (B) Proportion of ROR-γt + cells among total cells from LN cells cultured and stimulated as in A. (C) Proportion of IL-22 + cells among ROR-γt + CD3 neg CD4 + cells from LN cells cultured and stimulated as in A. (D) Flow cytometric detection of intracellular pSTAT3 in gated γδ T cells from pLN, cultured 2h with BHI or S. wadsworthensis (Sw, top) or S. parvirubra (Sp, bottom) culture supernatant and stimulated with IL-23 for the last hour. Open and shaded areas indicate IL-23 treatment and controls, respectively. (E) IL-22 mRNA quantification by qPCR in sorted αβ CD4 + T cells cultured 4h with BHI (black) or S. wadsworthensis (Sw, blue) or S. parvirubra (Sp, red) culture supernatant and stimulated as in A. Mice were treated with DSS and αβ CD4 + T cells were sorted from mesenteric LN. (F) AhR reporter cell line activation without or with FICZ, in presence of BHI (black) or S. wadsworthensis (Sw, blue) or S. parvirubra (Sp, red) culture supernatant. Error bars are SEM with 10 mice (A), 6 mice (B, C), 8 mice (D), 7-10 mice (E) and 3 biological replicates (F). *P < 0.05, **P < 0.005, ***P < 0.0005; by Wilcoxon test. See also Figure S4 IL-23 signals are primarily transduced by STAT3 22 . However, IL-23-dependent STAT3 phosphorylation was comparable among cells cultured with the control medium or the supernatants of S. wadsworthensis and S. parvirubra ( Figure 4D and Figure S4B). Sorted αβ CD4 + T cells were examined to assess the direct effect of Sutterella supernatants. Upon stimulation, the induced production of IL-22 and IL-17 was inhibited by S. wadsworthensis and S. parvirubra culture supernatants ( Figure 4E and Figure S4C). Thus, Sutterella effectively inhibits αβ CD4 + T cells functions through direct effects. Another mechanism that could explain Il-22 and IL-17 inhibition is the modulation of AhR (Aryl hydrocarbon Receptor) pathway 5 . Using an AhR reporter system, we found that S. wadsworthensis and S. parvirubra supernatants reduced AhR activation ( Figure 4F ). A 30>kDa protein produced by Sutterella sp. inhibits IL-22 The Sutterella effectors responsible for IL-22 and IL-17 inhibition are secreted molecules, since the culture supernatant has a repressor effect ( Figure 2 ), unlike the bacterial wall (Figure S3E). To assess the nature of these effectors, the supernatants were heated, treated with proteinase K and/or filtered with different molecular weight cutoff membranes. S. wadsworthensis culture supernatants heated and treated with proteinase K lost their inhibitory effect on IL-22 production (Figure S5A). Moreover, the fraction below 3 kDa of S. wadsworthensis culture supernatant had no effect on IL-22 production by γδ T cells, CD3 neg CD4 + cells, while the fraction above 3 kDa could inhibit this cytokine ( Figure 5A ), without affecting cell viability (Figure S5B). The > 30 kDa fraction of S. wadsworthensis culture supernatant also significantly reduced IL-22 production ( Figure 5B ), while the > 30 kDa fractions treated with proteinase and/or heated lost their inhibitory effect on γδ T cells ( Figure 5C ) and CD3 neg CD4 + cells ( Figure 5D ). Such as non-treated culture supernatant, the > 30 kDa fraction had no effect on cell viability (Figure S5C) or IFN-γ production (Figure S5D). Taken together, these results identified that the effectors of S. wadsworthensis activity are not metabolites (previously identified in other bacterial commensals) 12 , 14 , 17 , 18 but proteins larger than 30 kDa. Download figure Open in new tab Figure 5. A >30kDa protein from Sutterella regulates IL-22 productions. (A, B) Intracellular analysis of IL-22 expression by gated γδ T cells and CD3 neg CD4 + cells from pLN cultured 4 hours with 3 kDa fractions (A) or >30 kDa (B) of BHI or Sw culture supernatant and stimulated with PMA + Ionomycin + IL-1β + IL-23 for the 3 last hours. (C, D) Intracellular analysis of IL-22 expression by gated γδ T cells (C) and CD3 neg CD4 + cells (D) from pLN cultured 4 hours with >30 kDa of BHI or Sw culture supernatant (pretreated with proteinase K (PK) and/or pre-heated (Heat shock, HS)) and stimulated as in A. Error bars are SEM from 6 mice (A), 7 mice (B) and 5 mice (C, D). Significant differences were determined using paired t test (A) and Wilcoxon test (B-D): *P < 0.05, **P < 0.005, ****P < 0.0001. See also Figure S5 Sutterella sp. inhibits human IL-22 and IL-17 Next, we examined the significance of these results in a human context. We treated peripheral blood mononuclear cells (PBMC) 24h and 48h with S. wadsworthensis and S. parvirubra supernatants and measured the production of IL-22 and IL-17. As in mice, Sutterella inhibit the production of human IL-22 and IL-17 ( Figure 6 ). Download figure Open in new tab Figure 6. Sutterella regulates IL-17 and IL-22 productions in human. Cells from peripheral blood mononuclear cells (PBMCs) were cultured for 24h or 48h with BHI (black), S. wadsworthensis (Sw, blue) or S. parvirubra (Sp, red) culture supernatant and stimulated with anti-CD3 and anti-CD28. IL-22 (A) and IL-17 (B) productions were measured in the supernatants.Error bars are SEM from n = 4-9 donors. Significant differences were determined using Wilcoxon test, *P < 0.05, **P < 0.005. DISCUSSION In this study, we observed that antibiotics treatment increases the proportion of betaproteobacteria from Sutterellaceae family, which correlates negatively with the proportion of IL-22 and IL-17 producing cells in murine small intestine and colon. In vitro and in vivo analysis then showed that two species from this bacterial family, S. wadsworthensis and S. parvirubra , are capable of inhibiting these two cytokines produced by αβ CD4 + T cells, γδ T cells, CD4 + CD3 neg or CD4 neg CD3 neg cells. These findings are relevant in human since Sutterella sp. also reduces the level of IL-22 and IL-17 secreted by human PBMCs. The regulation of IL-22 production is primarily associated to gut microbiota-derived metabolites, such as tryptophan metabolites 12 , short-chain fatty acids 17 , 18 and secondary bile acids 23 . Here, we demonstrated that the bio-active effectors of Sutterella sp. are > 30 kDa proteins that act directly on lymphoid cells. The production of IL-22 can be regulated through several signaling pathways. IL-23 signal is primarily transduced by STAT3 22 . However, IL-23-dependent STAT3 phosphorylation was comparable between cells incubated with Sutterella culture supernatant and culture medium. AhR is another major transcription factor, essential for IL-22 production by ILC3 24 , Th17 cells 25 and γδ T cells 26 . It can modulate Th17 development independently to ROR-γt expression and STAT3 phosphorylation 27 . However, AhR does not act alone but cooperates with other transcription factors to induce IL-17 or IL-22 production. AhR facilitates notably ROR-γt recruitment at the IL-22 locus to induce its expression 28 . In line with this, our data suggest that Sutterella sp. inhibits IL-22 and IL-17 productions, by reducing AhR activity without affecting ROR-γt expression. Although it has been shown that S. wadsworthensis has a mild pro-inflammatory activity, we did not observe the induction of IL-8 by epithelial cells or pro-Th1 cytokines by immune cells in presence of Sutterella culture supernatant. Therefore, instead of directly triggering inflammation, Sutterella impairs the intestinal immune response, notably by inhibiting IL-22 and IL-17 productions, and could lead to a favorable environment for the invasion of epithelial cells by other pathobionts. In line with this, Moon et al. showed in 2015 the ability of Sutterella sp . to degrade IgA antibodies, thus disrupting the mucosal defense 29 . Patients with UC exhibit an increased amount of Sutterella in their fecal microbiota 30 and a reduced number of IL-22-producing cells in actively inflamed tissues 31 , suggesting a link between Sutterella and IL-22 in humans and in IBD. Given the beneficial role of IL-22 in IBD 4 , Sutterella sp. may have a deleterious effect and represents a promising target for IBD therapy. This is also a potential biomarker for IBDs diagnosis. In exploring this promising hypothesis and identifying the implicated bio-active proteins, we will pave the way to develop innovative clinical strategies to control gut inflammation. Author contributions L.D., H.S. and M.-L.M. designed the study, analyzed and interpreted the data. L.D., G.O., R.G., A.B., M.B. and M.-L.M. performed experiments. G.D.C., A.M. and L.C. provided technical help. L.D., R.G., A.B., M.B., N.R., C.D., Z.D., P.S., H.S. and M.-L.M. discussed the experiments and results. H.S. and M.-L.M. wrote the manuscript. All authors read and approved the final manuscript. Declaration of Interests The authors declare no competing interests. MATERIELS AND METHODS Mice C57Bl/6J mice (7-9-week-old females) were bred and maintained under specific pathogen-free conditions. Animal experiments were performed according to local ethical panel and the Ministère de l’Education Nationale, de l’Enseignement Supérieur et de la Recherche, France under agreement Apafis#20977-2019041215549049. Human samples PBMCs were isolated from the peripheral blood of healthy donors obtained from Etablissement Français du Sang (EFS). Bacterial culture Escherichia coli (K-12/MG1655), Sutterella wadsworthensis (DSM 14016), isolated from human abdominal fluid, and Sutterella parvirubra (DSM 19354), isolated from human faeces, were grown at 37°C in LYHBHI medium [Brain–heart infusion medium supplemented with 0.5% yeast extract (Difco) and 5 mg/liter hemin] supplemented with Formate (1.8 mg/ml; Sigma), Fumarate (1.8 mg/ml; Sigma), cysteine (0.5 mg/ml; Sigma), vitamin K1 (0.0001%, Sigma) and vitamin K3 (3.2 µg/ml, Sigma) in an anaerobic chamber. Achromobacter denitrificans (DSM 30026), isolated from soil, was grown at 37°C in the same medium, with agitation in aerobic conditions. Strains are cultured for 18h, until the end of exponential growth phase/beginning of stationary growth phase. Cell concentration is measured with a flow cytometer (CytoFLEX, Beckman Coulter). After a centrifugation for 15 minutes at 4500 rpm, 4°C, in flying buckets, the supernatants are filtered in 0.2 µm membrane and aliquoted for storage at -20°C. Bacterial cell pellets are resuspended in PBS at a concentration of 1×10 9 cells/ml, then heat killed at 70°C for 30 minutes. These suspensions are aliquoted for storage at -20°C. Antibiotic and Sutterella treatments Mice were treated with vancomycin (500 mg/L; Mylan) and/or neomycin (1 mg/mL; Euromedex) in the drinking water and water solutions were prepared and changed every three days. Fluid intake was monitored and the antibiotic solution was changed every 3 days. In some experiments, mice were pre-treated 4 days with streptomycin sulfate salt (5mg/mL, Sigma) in the drinking water and then inoculated daily via intragastric gavage with a bacterial suspension of 10 9 CFU/mL in 200 μL of PBS/glycerol or control medium (PBS/glycerol) for 3 weeks. In some other experiments, mice were inoculated daily via oral gavage with 200 μL of filtrated bacterial supernatant or control medium, during 1 week. DSS treatment To obtain IL-22-producing CD4 + αβ T cells from mesenteric lymph nodes, mice were administrated drinking water supplemented with 2% DSS (MP Biomedicals) for 7 days, and then allowed to recover by drinking supplemented water for the next 2 days. Fractionation or treatment of Sutterella supernatants Heat shock treatment at 90°C for 35 minutes was performed. S. wadsworthensis , S. parvirubra culture supernatants and LYHBHI medium were also treated with proteinase K (Qiagen) overnight at 56°C, and finally heated for 20 minutes at 96°C to inactivate the enzyme. In some experiments S. wadsworthensis , S. parvirubra culture supernatants and LYHBHI medium were fractionated by size using 3-kDa-molecular-weight-cutoff (MWCO) or 30-kDa-MWCO centrifugal filters (Amicon). Filters were rinsed once with PBS 1% BSA (Sigma). Then, 3 mL of bacterial culture supernatants or LYHBHI medium were added to the filter and centrifuged at 3,000 g at 4°C. The flowthroughs and the top fractions were resuspended in LYHBHI medium up to 3 mL. Fecal and ileal fluid DNA extraction Fecal and ileal fluid DNA were extracted from the weighted samples as previously described 12. Murine cell preparation Isolation of mononuclear cells from mouse lamina propria: small intestine between stomach and cecum, large intestine between cecum and anal verge were cut out and open longitudinally. Tissues were washed with cold PBS1X to remove the fecal and then were cut cross-sectionally into 0.5–1 cm long pieces and then mixed with 5 mL pre-warmed HBSS/FCS/EDTA/DTT in the shaker at 37°C for 20 min. The supernatants were discarded and pellets were washed with cold PBS1X. The tissue pieces were then transferred to a new tube and digested with collagenase type IV (Gibco) or the mouse Lamina Propria Dissociation Kit (Miltenyi) and DNAse (Roche) for 30 min. All the contents were passed through a 100 μm cell strainer. LPLs were obtained using the 40/80 Percoll centrifugation (GE Healthcare). Mouse lymph nodes preparation: peripheral lymph nodes (pLN, axillary, brachial, and inguinal) or mesenteric lymph nodes (mLN) were homogenized and washed in RPMI 1640 medium (Gibco) + 10% (vol/vol) FCS (Sigma-Aldrich) + 1% Hepes (Gibco) + 100 U/mL Penicillin and 100 μg/mL Streptomycin (Gibco). Human PBMCs isolation Heparinized whole blood was diluted with PBS 1:1, layered over Histopaque-1077 (Sigma-Aldrich) and centrifuged at 400g for 20 min without brake at room temperature. The peripheral blood mononuclear cell (PBMC) fraction was then washed in cold PBS and used for in vitro culture assays. In vitro Culture Assays and stimulation Murine cells and human PBMCs were cultured in RPMI 1640 medium (Gibco) supplemented with 10% (vol/vol) FCS (Sigma-Aldrich) + 1% Hepes (Gibco) + 100 U/mL Penicillin and 100 μg/ml Streptomycin (Gibco), in the presence of BHI or Sutterella supernatant at 2, 5 or 10% or dead Sutterella (MOI 10:1), during 4 or 24 hours. Murine cells were prepared at 5×10 5 cells (at 2.5×10 6 cells/mL) per 96-well plate (CellStar) and stimulated for the 3 or 23 last hours in culture medium with 50 ng/mL phorbol 12myristate 13-acetate (Sigma-Aldrich), 1 mg/mL ionomycin (Sigma-Aldrich), 20 ng/mL mouse IL-23 recombinant protein and 10 ng/mL mouse IL-1β recombinant protein (R&D Systems). PBMCs were prepared at 1×10 6 cells (at 1×10 6 cells/mL) per 24-well plate (CellStar) and stimulated 24h in culture medium with coated anti-human CD3 (2 μg/mL, Biolegend) and soluble anti-human CD28 (4 μg/mL, Biolegend). The culture supernatants were frozen at -20°C until processing. HT29 cell line (ATCC HTB-38) was cultured in Dulbecco’s Modified Eagle Medium (DMEM, Gibco) with glutamax supplemented with 10% (vol/vol) FCS (Sigma-Aldrich) + 100 U/mL Penicillin and 100 μg/ml Streptomycin (Gibco), at 37°C in a 5% CO2 atmosphere. For some experiments, cell lines (5×10 5 cells per well, plated 72 hours before the experiment in 24-well plate) were cultured with BHI or Sutterella supernatant at 5% and stimulated 24 hours with human recombinant TNF-α (5 ng/mL, Preprotech). Flow Cytometry and Cell Sorting Flow cytometry was carried out by using BD-LSRII machines. αβ CD4 + T cells were sorted by using BD-Aria machine or mouse CD4 + T Cell Isolation Kit (Miltenyi). Single cell suspensions were prepared in FACS buffer (PBS + 2% (vol/vol) FCS + 0.01% (vol/vol) sodium azide; Sigma-Aldrich). Cells were stained on ice in PBS 1X (GIBCO) with Fixable Viability Dye eFluor 506 (eBioscience) or Zombie Aqua Fixable Viability Kit (BioLegend). Cells were surface stained in FACS buffer with the following antibodies ; from eBioscience: FITC–labeled anti-CD3ε (145-2C11), PE-labeled anti-CD4 (RM4-5), anti-CD16/32 (93), PECy7-labeled anti–IFN-γ (XMG1.2), eF450-labeled anti-IL-17 (17B7), PECy7-labeled anti-ROR-γT (B20); from BioLegend: APC-labeled anti-TCRγδ (GL3)PE-labeled anti-IL-22 (Poly5164), BV785-labeled anti-CD4 (RM4-5), BV605-labeled anti-CD8α (53-6.7). Cells were washed in FACS buffer before analysis. In mouse, γδ T cells are CD3 + TCRγδ + CD4 neg CD8 neg , CD4 + T lymphocytes are CD3 + TCRγδ neg CD4 + CD8 neg , CD4 + CD3 neg cells are γδ TCR neg CD3 neg CD4 + CD8 neg and CD4 neg CD3 neg cells are γδ TCR neg CD3 neg CD4 neg CD8 neg . For intracellular analysis of IL-17, IL-22 and IFN-γ, mouse cells were first stimulated in the presence of 10 μg/mL Brefeldin-A (Sigma-Aldrich). After surface staining, cells were fixed and permeabilized by using 4% (wt/vol) PFA in conjunction with 0.5% saponin in PBS1X. We performed intracellular staining for ROR-γt according to the manufacturers’ instructions (FOXP3/Transcription Factor Staining Buffer Set, Invitrogen). Data were analysed by using FlowJo software. RNA Expression Analysis Total RNA was isolated with RNeasy Micro Kit or Mini Kit (Qiagen) as per manufacturer’s instructions. For real-time RT-PCR analysis, RNA was reverse transcribed with LunaScript® RT SuperMix kit (New England Biolabs) by a mix of random hexamers and oligos-dT primers. Quantitative PCR was performed with Luna® Universal qPCR Master Mix (NEB) on StepOne equipment (Applied Biosystems). Relative expression is displayed in arbitrary units normalized to GAPDH via ΔΔCt method. Primer sequences are available upon request. Cytokine quantification ELISAs were performed on the supernatants to quantify mouse IL-22 and IL-17A cytokines (Invitrogen) and human IL-8 cytokine (R&D Systems), according to the manufacturer’s instructions, with Tween 20 (Sigma-Aldrich) and H2SO4 (VWR Chemicals). Legendplex (Mouse Th17 Panel, BioLegend) assay on cell supernatants was performed according to the manufacter recommendations. AhR activity measurement The AhR activity was measured using HepG2-Lucia™ AhR reporter cells (InvivoGen, France) as described before 12 . FICZ (6-Formylindolo[3,2-b]carbazole) was purchased from Enzo Life Sciences. 16S sequencing Bacterial DNA was extracted from the weighted stool samples or ileal fluids as previously described 12 . 16S rDNA gene sequencing was performed as previously described 12 . Scanning electron microscopy 50 µL of the bacterial culture were directly fixed in 2 mL volume of 2 % glutaraldehyde buffered with sodium cacodylate 0.1M, during 2 h at room temperature then overnight at 4°C, in a 24-well plate (TPP 92024, Switzerland) that contains 1cm x 1cm glass slides at the bottom of the well. The glass slides were previously cleaned by 70% Ethanol, 10 min plasma cleaner, then cut with a diamond pen, sonicated 15min in 100% Ethanol, then in MiliQ water, and coated with 0,01% Poly-L-lysin (Sigma Merck P4707-50mL) during 5 min and finally rinsed with MiliQ water. Samples thus attached to the glass slides at the bottom of the wells were rinsed twice during 10 min in 0.2 M sodium cacodylate buffer, then in successive baths of ethanol (50, 70, 90, 100, and anhydrous 100 %), and finally dried using a Leica EM300 critical point apparatus with slow 20 exchange cycles, and 2 min delay between steps. Samples were mounted on aluminum stubs with adhesive carbon (EMS, LFG France) and coated with 6 nm of Au/Pd using a Quorum SC7620, 50 Pa of Ar, 180 s of sputtering at 3.5 mA. Samples were observed using the SE detector of a FEG SEM Hitachi SU5000, 2 KeV, 30 spot size, 5 mm working distance. All the preparation steps were done using the MIMA2 core facility, INRAE, Jouy-en-Josas, France ( https://doi.org/10.15454/1.5572348210007727E12 ). Quantification and statistical analysis Results are expressed as the mean ± standard error of the mean (SEM). All statistical analysis was performed using GraphPad Prism 10 software, using two-tailed Man-Whitney test or Wilcoxon test to compare two groups; and ordinary one-way ANOVA or Friedman test to compare 3 groups. Correlation significance was determined using linear regression. *, p < 0.05; **, p < 0.01; ***, p < 0.001. n represents the number of mice or human donors per group. Statistical details of experiments and exact value of n can be found in the figure legends. Acknowledgments We thank the employees of the animal facility at the IERP platform, INRAE, UE0907 (Jouy-en-Josas, France) for their technical assistance. We also acknowledge Marie-Laure Aknin, CYM core facility from the “Unité Mixte de Service – Ingénierie et Plateformes au Service de l’Innovation” (UMS-IPSIT, Paris Saclay, France), for access to its equipment and infrastructures and technical assistance. We thank Ambrine Farfar, Rand Fatouh, Chloé Michaudel, Julien Planchais, Ugo Sardo, Mathias L. Richard and Vlad Costache (MIMA2 core facility, INRAE, Jouy-en-Josas, France) for assistance. L.D. was supported by the Foundation for Medical Research. Footnotes Contact Info REFERENCES 1. ↵ Zheng D , Liwinski T , Elinav E. Interaction between microbiota and immunity in health and disease . Cell Res . 2020 Jun ; 30 ( 6 ): 492 – 506 . doi: 10.1038/s41422-020-0332-7 . 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