Alteration of microbiota antibody‐mediated immune selection contributes to dysbiosis in inflammatory bowel diseases
2022; Springer Nature; Volume: 14; Issue: 8 Linguagem: Inglês
10.15252/emmm.202115386
ISSN1757-4684
AutoresEva Michaud, Louis Waeckel, Rémi Gayet, Roman Goguyer‐Deschaumes, Blandine Chanut, Fabienne Jospin, Katell Bathany, Magali Monnoye, Coraline Genet, Amélie Prier, Caroline Tokarski, Philippe Gérard, Xavier Roblin, Nicolas Rochereau, Stéphane Paul,
Tópico(s)Gut microbiota and health
ResumoArticle4 July 2022Open Access Transparent process Alteration of microbiota antibody-mediated immune selection contributes to dysbiosis in inflammatory bowel diseases Eva Michaud Eva Michaud CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France CIC Inserm 1408 Vaccinology, Saint-Etienne, France Contribution: Formal analysis, Validation, Investigation, Methodology, Writing - original draft Search for more papers by this author Louis Waeckel Louis Waeckel orcid.org/0000-0002-4941-2415 CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France CIC Inserm 1408 Vaccinology, Saint-Etienne, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Rémi Gayet Rémi Gayet CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis Search for more papers by this author Roman Goguyer-Deschaumes Roman Goguyer-Deschaumes CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Investigation, Writing - review & editing Search for more papers by this author Blandine Chanut Blandine Chanut CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Investigation Search for more papers by this author Fabienne Jospin Fabienne Jospin CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Investigation Search for more papers by this author Katell Bathany Katell Bathany Chimie et Biologie des Membranes et des Nano-objets (UMR 5248), Université de Bordeaux, CNRS, Bordeaux INP, Pessac, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Magali Monnoye Magali Monnoye orcid.org/0000-0003-0222-4908 Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Coraline Genet Coraline Genet Inserm UMR 1098 Right, Université Bourgogne Franche-Comté, Besançon, France Contribution: Investigation Search for more papers by this author Amelie Prier Amelie Prier CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Investigation Search for more papers by this author Caroline Tokarski Caroline Tokarski Chimie et Biologie des Membranes et des Nano-objets (UMR 5248), Université de Bordeaux, CNRS, Bordeaux INP, Pessac, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Philippe Gérard Philippe Gérard orcid.org/0000-0001-9521-0067 Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France Contribution: Formal analysis, Supervision, Investigation, Methodology, Writing - original draft Search for more papers by this author Xavier Roblin Xavier Roblin CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Supervision, Validation, Investigation, Methodology, Writing - original draft Search for more papers by this author Nicolas Rochereau Nicolas Rochereau CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Supervision, Investigation Search for more papers by this author Stéphane Paul Corresponding Author Stéphane Paul [email protected] orcid.org/0000-0002-8830-4273 CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Eva Michaud Eva Michaud CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France CIC Inserm 1408 Vaccinology, Saint-Etienne, France Contribution: Formal analysis, Validation, Investigation, Methodology, Writing - original draft Search for more papers by this author Louis Waeckel Louis Waeckel orcid.org/0000-0002-4941-2415 CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France CIC Inserm 1408 Vaccinology, Saint-Etienne, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Rémi Gayet Rémi Gayet CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis Search for more papers by this author Roman Goguyer-Deschaumes Roman Goguyer-Deschaumes CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Investigation, Writing - review & editing Search for more papers by this author Blandine Chanut Blandine Chanut CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Investigation Search for more papers by this author Fabienne Jospin Fabienne Jospin CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Investigation Search for more papers by this author Katell Bathany Katell Bathany Chimie et Biologie des Membranes et des Nano-objets (UMR 5248), Université de Bordeaux, CNRS, Bordeaux INP, Pessac, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Magali Monnoye Magali Monnoye orcid.org/0000-0003-0222-4908 Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Coraline Genet Coraline Genet Inserm UMR 1098 Right, Université Bourgogne Franche-Comté, Besançon, France Contribution: Investigation Search for more papers by this author Amelie Prier Amelie Prier CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Investigation Search for more papers by this author Caroline Tokarski Caroline Tokarski Chimie et Biologie des Membranes et des Nano-objets (UMR 5248), Université de Bordeaux, CNRS, Bordeaux INP, Pessac, France Contribution: Formal analysis, Investigation, Writing - original draft Search for more papers by this author Philippe Gérard Philippe Gérard orcid.org/0000-0001-9521-0067 Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France Contribution: Formal analysis, Supervision, Investigation, Methodology, Writing - original draft Search for more papers by this author Xavier Roblin Xavier Roblin CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Supervision, Validation, Investigation, Methodology, Writing - original draft Search for more papers by this author Nicolas Rochereau Nicolas Rochereau CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Formal analysis, Supervision, Investigation Search for more papers by this author Stéphane Paul Corresponding Author Stéphane Paul [email protected] orcid.org/0000-0002-8830-4273 CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France Contribution: Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Author Information Eva Michaud1,2, Louis Waeckel1,2, Rémi Gayet1, Roman Goguyer-Deschaumes1, Blandine Chanut1, Fabienne Jospin1, Katell Bathany3, Magali Monnoye4, Coraline Genet5, Amelie Prier1, Caroline Tokarski3, Philippe Gérard4, Xavier Roblin1, Nicolas Rochereau1 and Stéphane Paul *,1 1CIRI – Centre International de Recherche en Infectiologie, Team GIMAP (Saint-Etienne), Université Claude Bernard Lyon 1, Inserm, U1111, CNRS, UMR5308, Lyon, France 2CIC Inserm 1408 Vaccinology, Saint-Etienne, France 3Chimie et Biologie des Membranes et des Nano-objets (UMR 5248), Université de Bordeaux, CNRS, Bordeaux INP, Pessac, France 4Micalis Institute, INRAE, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France 5Inserm UMR 1098 Right, Université Bourgogne Franche-Comté, Besançon, France *Corresponding author. Tel: +33 (0) 477 421 484; Fax: +33 (0) 477 421 486; E-mail: [email protected] EMBO Mol Med (2022)14:e15386https://doi.org/10.15252/emmm.202115386 [Correction added on 8 August 2022, after first online publication: the authors' affiliations have been corrected.] PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Human secretory immunoglobulins (SIg) A1 and SIgA2 guide mucosal responses toward tolerance or inflammation, notably through reverse-transcytosis, the apical-to-basal transport of IgA2 immune complexes via M cells of gut Peyer's patches. As such, the maintenance of a diverse gut microbiota requires broad affinity IgA and glycan–glycan interaction. Here, we asked whether IgA1 and IgA2-microbiota interactions might be involved in dysbiosis induction during inflammatory bowel diseases. Using stool HPLC-purified IgA, we show that reverse-transcytosis is abrogated in ulcerative colitis (UC) while it is extended to IgA1 in Crohn's disease (CD). 16S RNA sequencing of IgA-bound microbiota in CD and UC showed distinct IgA1- and IgA2-associated microbiota; the IgA1+ fraction of CD microbiota was notably enriched in beneficial commensals. These features were associated with increased IgA anti-glycan reactivity in CD and an opposite loss of reactivity in UC. Our results highlight previously unknown pathogenic properties of IgA in IBD that could support dysbiosis. Synopsis IBD (both CD and UC) is characterized by dysbiosis and altered immune pathways that lead to and sustain prolonged inflammation in the gut. As IgA are the main drivers of commensal selection in the healthy gut, this study aimed at assessing subclass-related structure and functions of IgA in both CD and UC. Evidence of a chain of subclass-dependent functional disparities between CD and UC IgAs affecting antibody glycosylation, transport across epithelia, and affinity, which may interfere in optimal commensal selection to promote dysbiosis While only IgA2 could undergo RT in non-IBD, IgA1 in CD had the ability to do so and neither IgA1 nor IgA2 were able to in UC. Despite predominant dual IgA1 and IgA2 binding on stool microbiota, CD associates with enriched commensal binding in the IgA1+ fraction, and UC with a marked reduction in IgA overall reactivity Introduction Mutualism between host immunity and microbial communities at the gut mucosal surface is critical for the education of the immune system and the processing of digested foods. Intestinal epithelial cells allow the transcytosis of secretory IgA (SIgA) to promote the maintenance of beneficial taxa. SIg are characterized by J-chain-mediated multimerization and secretory component (SC) binding, enabling their efficient trafficking to and from the mucosal surface (Brandtzaeg, 1981). SIgA promotes the establishment of bacterial networks (Mathias et al, 2014; Rios et al, 2016) through both glycan–glycan interactions (Perrier et al, 2006; Rollenske et al, 2018) and Fab binding (Sterlin et al, 2020), a process known as antibody-mediated immune selection (AMIS; Donaldson et al, 2018; Hoces et al, 2020; Moor et al, 2017; Nagashima et al, 2017; Pabst, 2012; Rollenske et al, 2018). Both low-affinity natural SIgA and high-affinity SIgA contribute to AMIS and are thought to, respectively, promote commensal selection (T-independent signals), and selectively identify fast-replicating bacteria as pathogenic (T-dependent signals; Bansept et al, 2019; Hoces et al, 2020; Moor et al, 2017; Neumann et al, 2019). Heavy glycosylation of SIgA favors mucus entrapment of SIgA-bound bacteria and symbiosis within the microbiota (Donaldson et al, 2018; Rollenske et al, 2018; Steffen et al, 2020). Human IgA1 and IgA2 have distinct patterns of glycosylation as IgA1 is mostly O-glycosylated (Novak et al, 2012; Ohyama et al, 2020), and IgA2 is mostly N-glycosylated (Steffen et al, 2020). On their shared two sites of N-glycosylation, sialylation of IgA1 appears to dampen its natural pro-inflammatory effects (Steffen et al, 2020). Moreover, anti-commensal IgA1 signaling tends to elicit tolerogenic signals such as Treg induction and IL-10 secretion (Sterlin et al, 2020). Sialylation and N-glycosylation of SIgA2 enables reverse-transcytosis (RT), a process by which antigen-bound SIgA2 travels from the lumen toward the subepithelial dome of Peyer Patches by binding Dectin-1 receptors on M-cells (Rochereau et al, 2013). Strong evidence supports that dysbiosis within the intestinal microbiota—that is, the alteration of resident commensal ecosystems in favor of non-beneficial communities—is responsible for inflammatory bowel diseases (IBD) defects (Joossens et al, 2011; Ni et al, 2017). In both Crohn's disease (CD) and ulcerative colitis (UC), the Firmicutes/Bacteroidetes ratio decreases (Mariat et al, 2009; Fuentes et al, 2017; Ni et al, 2017; Pascal et al, 2017). In CD, this is mostly attributed to reduced diversity amongst Firmicutes, the resurgence of atypical species such as segmented filamentous bacteria (SFB) and the colonization of the mucosa by oropharyngeal species (Rengarajan et al, 2019; Yamada et al, 2019). As such, CD has been strongly and extensively associated with the loss of short-chain fatty acids (SCFA) producers (Liu et al, 2016; Quévrain et al, 2016; Takahashi et al, 2016; Yamada et al, 2019; Yilmaz et al, 2019). Dysbiosis in UC is associated with the reduction in both Firmicutes and Bacteroidetes abundance, despite a higher diversity than in CD (Yilmaz et al, 2019), and decreased SCFA producers abundance (Machiels et al, 2014; Mirsepasi-Lauridsen et al, 2018). A noticeably lower representation of the mucolytic Akkermansia species was also evidenced in UC patients compared with healthy controls (den Besten et al, 2013; Moor et al, 2017; Lopez-Siles et al, 2018). In healthy humans, despite IgA1 binding to bacteria usually being concomitant to that of IgA2, IgA1 displays a preference toward Actinobacteria selection while IgA2 identification favors Bacteroidetes selection (Sterlin et al, 2020), suggesting dual contributions to microbiome diversity. Coincidentally, IBD patients' stools show increased levels of IgA-bound bacteria (Rengarajan et al, 2019), either commensal or opportunistic, and shift from dimeric IgA secretion toward monomeric IgA secretion (MacDermott et al, 1986). It is very likely that SIgA repertoires are affected over the course of IBD, resulting in aberrant responses to normally tolerated strains. This would leave room for opportunistic species to colonize niches they do not normally have access to. Current therapeutic strategies rely on anti-inflammatory and immunosuppressive biological agents. Noticeably in CD, anti-TNF failure is associated with low microbiota diversity and loss of short-chain fatty acids (SCFA)-producing taxa (Yilmaz et al, 2019). Other agents such as antibiotics, thiopurines, and corticosteroids enhance the effect of anti-TNF therapies (Bernstein, 2015; Feuerstein & Cheifetz, 2017; Townsend et al, 2019), but most available drugs are associated with long lists of adverse effects that have yet to be overcome. Fecal microbiota transplantation (FMT) could limit the use of such aggressive therapies but has been met with heterogenous outcome and reproducibility rates in IBD studies; it mostly results in short-term improvements in IBD patients, and sometimes triggers IBD flares (Shi et al, 2016; Allegretti et al, 2017; Bak et al, 2017; Benech & Sokol, 2020). We believe that the role of IgA and its selection properties in IBD might have been overlooked and could, at least in part, explain this mosaicism. Here, the functional abilities of human secretory IgA1 and IgA2 in terms of receptor recognition, glycosylation pattern, trafficking, and microbial selection in a small cohort of CD and UC patients has been explored. Fecal SIgA in IBD are abnormally reactive to self and commensal glycans, and we describe novel specific IgA1-associated and IgA2-associated microbial profiles in CD and UC, respectively. Moreover, we show that while CD is concurrent with enriched microbial selection by SIgA1, UC occurrence is on the contrary associated with a striking loss in both IgA functionality and reactivity. Results Patients with IBD have altered SIgA1 and SIgA2 levels To account for the homogeneity of the IBD spectrum and to avoid analysis bias as much as possible, we included patients based on their endoscopic scores at sample collection and treatment history but regardless of phenotype. To explore the biological significance of both human IgA subclasses during chronic mucosal inflammation, we first measured total IgA, IgA1, and IgA2 concentrations in stool homogenates in Non-IBD, CD, and UC individuals. In CD, IgA1 and IgA2 levels only tended to increase in CD relative to non-IBD (Fig 1A and B), while decreasing significantly in UC compared with CD patients (Fig 1C). UC samples also trended toward lower total SC levels (Fig 1D). Disease activity at the time of sample collection did not affect IgA1 and IgA2 concentrations in CD (Fig 1E and F), while a significant decrease in active UC IgA2 stool concentration was evidenced compared with both active CD disease (Fig 1F). Interestingly, in all assays, the distribution of data points hinted at subgroups within IBD groups and particularly in the CD cohort. These clusters of patients with high versus low IgA, IgA1, and IgA2 levels were not correlated with age, disease duration, phenotype, or sex (Appendix Table S2). Figure 1. Purified fecal IgA1 and IgA2 from IBD patients have altered functionality related to Dectin-1 binding A–D. ELISA assay of fecal IgA1 (A), IgA2 (B), total IgA (C), and secretory component (D) levels from non-IBD (n = 7), CD (n = 18), and UC (n = 12) patients' stool. E, F. Data were further separated according to disease activity for IgA1 (E) and IgA2 (F). G, H. In vitro assay of purified IgA1 (G) and IgA2 (H) reverse-transcytosis abilities on an inverted model of FAE from Caco2 and Raji cells co-culture. I, J. (I) ELISA assay of IgA1-Dectin-1 binding, at a rate of one receptor per 10 IgA; (J) ELISA assay of IgA2-Dectin-1 binding, at a rate of one receptor per 10 IgA. K–N. Percent of IgA1 (K, L) and IgA2 (M, N) reverse-transcytosis for weak (K, M) and strong (L, N) Dectin-1 binding. Data information: Data were analyzed using Kruskall–Wallis multiple comparisons with Dunn's correction, when possible, or a Mann–Whitney test. P-values are as follows: (A) **P = 0.0098; (B) *P = 0.0406; (C) Non-IBD vs. UC *P = 0.0479, CD vs. UC *P = 0.0166; (F) *P = 0.0167; (G) *P = 0.0441; (H) *P = 0.423; (J) Non-IBD vs. UC *P = 0.0199, CD vs. UC *P = 0.0243; (K) *P = 0.0221; (L) *P = 0.0486. (G–N) For some patients, antibody purification did not yield a high enough concentration, so samples had to be excluded. N are thus as follows: IgA1: Non-IBD: n = 7; CD: n = 8; UC: n = 4; IgA2: Non-IBD: n = 7; CD: n = 8; UC: n = 5. All patient samples (biological replicates) have been tested in technical duplicates meaning n × 2. Download figure Download PowerPoint SIgA retro-transport is distinctly modified in CD and UC As there was no evident change in IgA1 and IgA2 concentrations in patients' stool, we next asked whether IgA functionality remained intact relative to the non-IBD cohort. Using a previously described in vitro model of FAE (Rochereau et al, 2013), the reverse-transcytosis (RT) potential for stool-purified IgA1 and IgA2 was evaluated. Of note, stool IgA have undergone digestion when they are purified and were probably damaged in the process. While this is unavoidable, it is probably why the efficiency of the antibody purification was lower than that of serum IgA. In non-IBD patients, we confirm that only IgA2 could perform RT (Fig 1H), as IgA1 percent RT was negligible (Fig 1G). In IBD groups, purified CD IgA1 but not UC IgA1 was also able to undergo RT (Fig 1G). Oppositely, no RT could be evidenced when using UC IgA2 (Fig 1H). As IgA2 RT activity is associated with Dectin-1 binding, we performed an ELISA-based Dectin-1 binding assay using IgAs from the same patients. Regardless of the group, IgA1 binding to Dectin-1 was generally low and without significant differences between our non-IBD, CD, and UC groups (Fig 1I). IgA1 percent RT was, however, correlated with Dectin-1 binding, contrary to Non-IBD or UC IgA1 (Appendix Table S2). This was surprising, given IgA1 from CD appeared to have gained RT functions (Fig 1G). We thus explored whether this discrepancy could originate from changes in binding affinity to the RT co-receptor Siglec-5. A similar ELISA-based assay demonstrated there was no significant difference in binding affinities for Siglec-5 in CD IgA1 (Appendix Fig S2A). For IgA2, we observed a significantly lower affinity for Dectin-1 compared with both non-IBD and CD individuals in the UC group (Fig 1J), hinting that the lower levels of RT observed in UC could be attributed to defective Dectin-1 recognition. As we used IgAs from the same patients for both Dectin-1 binding and RT experiments, strong and weak Dectin-1 binders according to their level of RT were compared. Strong IgA2 binding of non-IBD samples was associated with higher RT percentages (Appendix Fig S2B). For weak binding, our cohort only included one weak IgA2 binder in the non-IBD group (Appendix Fig S2B). In CD, strong IgA1 binding to Dectin-1 was associated with higher levels of RT than those of strong IgA2 binding (Appendix Fig S2C). Weak Dectin-1 IgA1 binders in CD still retained a significantly higher RT levels than non-IBD weak binding IgA1 (Fig 1K). This suggests that the regulation of IgA1 exclusion at the M-cell apical membrane for the induction of RT might be dysregulated in those CD patients. Consistently, high levels of IgA1 RT were also correlated with strong Dectin-1 binding in CD relative to non-IBD IgA1 (Fig 1L and Appendix Table S3). Weak and strong IgA1 to Dectin1 binding affinity was confirmed by biolayer interferometry and representative association-dissociation curves are depicted in Appendix Fig S2E. Oppositely, IgA2 binding strength was not discriminative for RT levels between non-IBD nor CD IgA2 (Appendix Table S3) as non-IBD and CD IgA2 had high levels of RT regardless of Dectin-1 affinity (Fig 1M and N). There were no strong IgA1 or IgA2 binders in UC (Fig 1K–N and Appendix Fig S3D), which further suggest defective recognition for IgAs in UC. Overall, these results hint at a possible aberrant functions of IgA1 in CD and the loss of typical IgA2 functions in UC IgA2. Glycosylation profiles from stool-purified IgA differ between CD and UC patients Because interaction with Dectin-1 and Siglec-5 is highly dependent on IgA glycosylation recognition (Rochereau et al, 2013), we hypothesized that changes in retransport ability of both CD and UC patients' IgAs could originate from structural alterations. Particularly, we expected differential glycosylations profiles that would enhance or dampen receptor binding and could potentiate uptake by M cells, which we evaluated by mass spectrometry. IgA1 (UniProtKB P01876) has two N-linked glycans located on N144 and N340 residues (enumerated starting from the N-terminal residue of the heavy constant chain), and a hinge region including five serine and four threonine residues that are nine potential O-glycosylation sites. The constant region of the heavy chain of IgA2 (UniProtKB P01877) is glycosylated on four asparagine residues: N92, N131, N205, and N327. Appendix Table S4 shows the N/O-glycosylations carrying peptides of IgA1 and IgA2 consistently with our experimental design based on trypsin digestion. N-glycan microheterogeneity We characterized N-glycopeptides spanning the two N-glycosylation sites of IgA1 and all the sites of IgA2 except the N327 C-terminus site (Glycan heterogeneity listed in Appendix Table S5). The N-glycosylation identified on N340 in CD IgA1 (73.5–74.5 and 80.0–81.0 min for sialo-glycopeptides) is mainly composed of high mannose structures and bi-antennary complex type N-glycans mostly truncated complex structures with terminal GlcNAc (Fig 2A). Several single fucosylated glycans were identified as core fucosylated (Fig 2A). Surprisingly, these structures had a very low sialylation rate with only one N-glycan carrying a terminal Neu5Ac sialylation. This is of particular interest given sialylation, especially on IgA1 (but not limited to) appears to have an immunosuppressive effect (Colucci et al, 2015; Steffen et al, 2020). Several of these forms were previously described for SIgA (Royle et al, 2003; Huang et al, 2015a) and serum IgA1 (Chandler et al, 2019) such as Man5 to Man8 structures and G0 (IgG glycans naming system) to G2 structures including bisecting GlcNAc (e.g., G0B, G0FB, and G1B). MS/MS spectra have discriminated several isobaric structures such as Man3B instead of G0-N (m/z 1,148.1846 on Fig 2A) using glycopeptide fragment ions with consecutive loss of two hexose moieties. The presence of hypothetical hybrid and tri-antennary structures was not confirmed by our MS/MS dataset. Despite good peptide sequence coverage, lower S/N spectra were obtained for UC IgA1 N-glycan that prevent a confident structural identification on this sample subpopulation. Figure 2. CD IgA1 N and O-glycosylations do not recapitulate conventional IgA glycosylation patterns A. Full MS spectrum of glycopeptides released from CD IgA1 trypsin digest. Main N340-glycoforms of the IgA1 glycopeptide [332–353] (LAGKPTHVNVSVVMAEVDGTCY) are annotated using CFG nomenclature. Appendix Table S4 summarizes a list of N-glycopeptides identified. # is the peptide [43–76] of immunoglobulin kappa constant chain (UniProtKB P01834). *Isobaric structures not differentiated by MS/MS experiments (not exhaustive N-glycans illustrations). (HYTNPSQDVTVPCPVPSTPPTPSPSTPPTPSPSCCHPR). B. O-glycoforms identified for CD. C. O-glycoforms identified for UC. Data information: *corresponds to IgA1 peptide [264–273] (WLQGSQELPR). #shows contamination by other multiply charge species covering the glycoforms signals. Details related to O-glycoforms are given in Appendix Table S7. CD: n = 3; UC: n = 1 (biological replicates). All patient samples have been tested in technical duplicates. Download figure Download PowerPoint The identified N-linked glycans of IgA2 heavy chain are localized as expected on N92, N131, and N205 residues. Similar structures were identified for CD and UC samples: G0F and G0FB-like structures were identified on N92 site of the [89–102] peptide (HYTNSSQDVTVPCR) and high mannose and bi-antennary complex type N-glycans were identified on N131 and N205 (Appendix Table S6). Whereas high mannose N-glycans were similarly observed in IgA1 and IgA2 region of sequence identity, bi-antennary and bisecting glycans with higher complexity were observed for IgA1 up to G2 structures (G0/G0B for IgA2). O-glycan microheterogeneity The IgA1 hinge region contains up to nine potential O-glycosylation sites resulting in a highly heterogeneous patterns of O-glycoforms as shown in previous studies related to SIgA (Royle et al, 2003;Huang et al, 2015a; Plomp et al, 2018) or serum IgA1 (Tarelli et al, 2004; Renfrow et al, 2007; Takahashi et al, 2010; Franc et al, 2013; Ohyama et al, 2020; Steffen et al, 2020). Several of these nine sites were shown to be O-glycosylated (see UniProtKB P01876 and (Renfrow et al, 2007; Wada et al, 2010) for details). Our experimental design based on the study of the glycopeptide [89–126] resulted in the identification of
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