New Results

Glycan-Based Shaping Of The Microbiota During Primate Evolution

Sumnima Singh, Patricia Bastos-Amador, Jessica A. Thompson, Mauro Truglio, Bahtiyar Yilmaz, Silvia Cardoso, Daniel Sobral, Miguel P. Soares
doi: https://doi.org/10.1101/2021.02.10.430443

Abstract

Genes encoding certain glycosyltransferases are thought to be under relatively high selection pressure, due to the involvement of the glycans that they synthesize in host-microbe interactions. Here we used a mouse model to investigate whether the loss of α-1,3-galactosyltransferase (GGTA1) function and Galα1-3Galβ1-4GlcNAcβ1-R (αGal) expression during primate evolution might have affected host-microbiota interactions. We found that Ggta1 deletion in mice shaped the composition of the gut microbiota in relation to the bacterial species present. This occurred via an immunoglobulin (Ig)-dependent mechanism, associated with IgA targeting of αGal-expressing bacteria. Systemic infection by the Ig-shaped microbiota elicited a less severe form of sepsis than infection with the non-Ig-shaped microbiota. This suggests that in the absence of host αGal, the microbiota is shaped towards lower pathogenicity, likely providing a fitness gain to the host. We infer that high selection pressure exerted by bacterial sepsis may have contributed to increase frequency of GGTA1 loss-of-function mutations in ancestral primates that gave rise to humans.

Introduction

As initially proposed by J.B.S. Haldane, infectious diseases are a major driving force of natural selection (Haldane, 1949), occasionally precipitating “catastrophic-selection” events: the replacement of an entire, susceptible, parental population by mutant offspring that are resistant to a given infectious disease (Lewis, 1962). Such an event is proposed to have occurred during primate evolution between 20–30 million□years□ago, possibly in response to an airborne, enveloped virus carrying a Galα1-3Galβ1-4GlcNAc (αGal)-like glycan (Galili, 2016, 2019). If proven correct, this would contribute to our understanding of the evolutionary pressures that led to the independent fixation of several loss-of-function mutations in the GGTA1 gene of ancestral primates (Galili et al., 1988).

Loss of the α1,3-galactosyltransferase enzyme, encoded by GGTA1, eliminated the expression of protein-bound αGal, allowing for immune targeting of this non-self glycan (Galili et al., 1987). This increased resistance to infection by αGal-expressing pathogens (Repik et al., 1994; Takeuchi et al., 1996), including parasites of the Plasmodium spp. (Soares and Yilmaz, 2016; Yilmaz et al., 2014), the causative agents of malaria, which exerted a major impact on human evolution (Allison, 1954).

We recently uncovered a fitness advantage associated with loss of GGTA1 function in mice, which acts independently of αGal-specific immunity (Singh et al., 2020). Namely, the loss of αGal from the immunoglobulin (Ig)G-associated glycan structures increases IgG effector function (Singh et al., 2020) and resistance to bacterial sepsis, a life-threatening organ dysfunction caused by a deregulated response to infection (Singer et al., 2016), that accounts for 20% of global human mortality (Rudd et al., 2020).

The pathogenesis of sepsis is modulated by stable symbiotic associations between the host and microbial communities composed of bacteria, fungi and viruses, known as the microbiota (Rudd et al., 2020; Vincent et al., 2009). While host-microbiota interactions provide a broad range of fitness advantages to the host (Lane-Petter, 1962; Vonaesch et al., 2018), they also carry fitness costs, for example, when bacterial pathobionts (Chow et al., 2011) translocate across host epithelial barriers to promote the development of sepsis (Rudd et al., 2020; Vincent et al., 2009). On the basis of this evolutionary trade-off (Stearns and Medzhitov, 2015), the immune system may have emerged, in part, to mitigate the pathogenic effects of the microbiota (Hooper et al., 2012; McFall-Ngai, 2007). Central to this host defence strategy is the generation of copious amounts of IgA natural antibodies (NAb) targeting immunogenic bacteria in the microbiota (Macpherson et al., 2000).

IgA can undergo transepithelial secretion and target a broad but defined subset of immunogenic bacteria in the microbiota (Bunker et al., 2017; Bunker et al., 2015; Macpherson et al., 2000). In doing so, IgA can exert negative or positive selection pressure on the recognized bacteria, shaping the microbiota composition, ecology, and potentially its pathogenicity (Kubinak and Round, 2016). Negative selection can occur, for example, when IgA limit bacterial growth (Moor et al., 2017). Positive selection can occur, for example, when IgA promotes bacterial interactions with the host, favoring bacterial retention, fitness and colonization (Donaldson et al., 2018; McLoughlin et al., 2016). Moreover, IgA can interfere with cognate interactions between bacteria and resident immune cells at epithelial barriers, regulating systemic microbiota-specific immune responses characterized by the production of circulating IgM and IgG NAb (Kamada et al., 2015; Zeng et al., 2016).

Here we provide experimental evidence in mice to suggest that the fixation of GGTA1 loss-of-function mutations during primate evolution could have exerted a major impact on the composition of their gut microbiota. In support of this notion, we found that mice in which Ggta1 is disrupted (Ggta1-/-), mimicking human GGTA1 loss-of-function mutations, modulate the gut microbiota composition. Shaping of the gut microbiota occurs predominantly via an Ig-dependent mechanism associated with an enhanced systemic IgA response, which, upon secretion into the gut, targets αGal-expressing bacteria in the gut microbiota. The pathogenicity of the Ig-shaped microbiota is reduced, failing to elicit the development of lethal forms of sepsis upon systemic infection. We propose that GGTA1 loss-of-function mutations could have conferred a selective benefit during primate evolution by shaping commensal bacteria in the microbiota to mitigate the pathogenesis of sepsis.

Results

Ggta1 deletion shapes the microbiota composition

We have previously established that Ggta1-/- mice harbor a distinct microbiota composition to that of wild type (Ggta1+/+) mice (Singh et al., 2020). This is illustrated by the relative abundance of specific bacterial taxa, such as an increase in Proteobacteria, Tenericutes and Verrucomicrobia as well as a reduction in Bacterioidetes and Deferribacteres phyla in Ggta1-/- mice when compared to Ggta1+/+ mice (Figure 1A, S1,2)(Singh et al., 2020). The relative increase of Proteobacteria, a phylum containing several strains associated with pathogenic behavior, i.e. pathobionts; in the gut microbiota of Ggta1-/- mice was not, however, associated with the development of histological lesions in the gastrointestinal tract (Figure S3A). Absence of intestinal inflammation was assessed by the levels of fecal lipocalin-2 (Lcn-2) (Figure S3B) (Chassaing et al., 2012). There were also no lesions in the liver, lungs, kidney and spleen (Figure S3C), suggesting that Ggta1-/- mice maintain symbiotic interactions with these pathobionts, without compromising organismal homeostasis.

Figure 1.
Figure 1. Ggta1 deletion alters the gut microbiota.

A) Linear discriminant analysis (LDA) scores generated from LEfSe analysis, representing taxa enriched in the fecal microbiota of Ggta1+/+ (green) (n=15) and Ggta1-/- (red) (n=14) mice. B) Breeding strategy where F0 Ggta1-/- males were crossed with Ggta1+/+ females to generate F1 Ggta1+/- mice, which were bred to generate F2 Ggta1+/+ vs. Ggta1-/- littermates. These were subsequently bred to generate F3 to F5 Ggta1+/+ vs. Ggta1-/- mice. Microbiota Principal Coordinate Analysis of Unweighted Unifrac distance in fecal samples from C) F0 Ggta1+/+ (n=15), F1 Ggta1+/- (n=15), F2 Ggta1+/+ (n=11) and F2 Ggta1-/- (n=10) mice, D) F3 Ggta1+/+ (n=9) and Ggta1-/- (n=8) mice, E) F4 Ggta1+/+ (n=13) and Ggta1-/- (n=7) mice and F) F5 Ggta1+/+ (n=7) and Ggta1-/- (n=12) mice generated as in (B). Data from 1 experiment with 2-3 independent breedings/cages per genotype. Symbols (C-F) are individual mice. P values (C-F) calculated using PERMANOVA test.

To establish that the observed differences in the bacterial species present in the gut microbiota of Ggta1-/- vs. Ggta1+/+ mice is propelled by host genetics, we used an experimental system, whereby the microbiota is vertically transmitted over several generations (Ubeda et al., 2012) from Ggta1+/+ mice to Ggta1-/- and Ggta1+/+ offspring (Figure 1B). This approach enables the effects exerted by the host genotype on microbiota composition to predominate over those exerted by environmental factors (Gálvez et al., 2017; Vonaesch et al., 2018), diet (Sonnenburg et al., 2016), cohousing or familial transmission (Ubeda et al., 2012), albeit not accounting for putative cage effects or genetic drift (Spor et al., 2011).

The microbiota composition of F1 Ggta1+/- as well as F2 Ggta1+/+ and Ggta1-/- mice diverged from that of the original F0 Ggta1+/+ mice (Figure 1C). While indistinguishable in F2 Ggta1+/+ and Ggta1-/- littermates (Figure 1C) (Singh et al., 2020), the microbiota composition diverged between Ggta1+/+ and Ggta1-/- mice in F3 (Figure 1D), F4 (Figure 1E) and F5 (Figure 1F) generations, suggesting that the Ggta1 genotype per se alters microbiota composition. There was an enrichment of some bacterial taxa, such as Helicobactereaceae, in the microbiota of F2 to F5 Ggta1-/- and Ggta1+/+ mice (Figure S4), despite the absence of these bacteria in the original F0 Ggta1+/+ microbiota (Figure S4). This suggests that while the Ggta1 genotypes shapes the gut microbiota composition, this occurs via a process that is probably influenced by colonization by environmental pathobionts (Gálvez et al., 2017).

Ggta1 deletion enhances IgA responses to the gut microbiota

Considering that IgA shapes the bacterial species present in the microbiota (Bunker et al., 2015; Macpherson et al., 2018; Peterson et al., 2007), we asked whether differences in IgA responses could contribute to shape the microbiota of Ggta1-/- vs. Ggta1+/+ mice. In keeping with this notion, the relative levels of microbiota-reactive circulating IgA were higher in Ggta1-/- vs. Ggta1+/+ mice, when maintained under specific pathogen-free (SPF) but not germ-free (GF) conditions (Figure 2A). When maintained under SPF conditions Ggta1-/- mice had similar levels of secreted (Figure S5A) and circulating (Figure S5B) total IgA, when compared to Ggta1+/+ mice. These were reduced to a similar extent under GF conditions (Figure S5A-B). This suggests that Ggta1 deletion preferentially enhances the microbiota-specific IgA response without interfering with total IgA.

Figure 2.
Figure 2. Ggta1 deletion enhances IgA responses to the gut microbiota.

A) Relative binding of IgA in the serum of Ggta1+/+ (n=10) and GF Ggta1+/+ (n=5) mice to fecal extract from Ggta1+/+ mice, and Ggta1-/- (n=6) and GF Ggta1-/- (n=6) mice to fecal extract from Ggta1-/- mice; 1 experiment. B) Relative binding of IgA in the serum of GF Ggta1+/+ (n=7) and GF Ggta1-/- (n=10) mice to cecal extract from Ggta1-/- mice at indicated time-points after colonization with cecal extract from Ggta1-/- mice; 2 experiments. C) Median Fluorescence Intensity (MFI) of αGal+ bacterial strains stained with BSI-B4 lectin relative to unstained control; 7 experiments. D) Representative flow cytometry plots showing bacteria stained for IgA and αGal in the small intestinal content of Ggta1+/+ (n=5) and Ggta1-/- (n=11) mice; 4 independent experiments. E) Quantification of αGal+, IgA+ and IgA+αGal+ bacteria in the same samples as in (D). F) Concentration of anti-αGal IgM in serum of Ggta1+/+ (n=2), Ggta1-/- (n=12), Iga-/-Ggta1+/+ (n=10) and Iga-/-Ggta1-/- (n=12) mice before and after streptomycin treatment, 2 experiments. G) Concentration of anti-αGal IgG, in the same mice as (F). Symbols (A, B, E, F, G) are individual mice. Red bars (A, B, E, F, G) correspond to mean values. Error bars (A, B, C, E, F, G) correspond to SD. P values in (A, B, F, G) calculated using Kruskal-Wallis test using Dunn’s multiple comparisons test and in (E) using Mann-Whitney test. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns: not significant.

In further support of the notion that Ggta1 deletion modulates the production microbiota-specific IgA, colonization of GF Ggta1-/- mice with the microbiota from Ggta1-/- mice elicited the production of higher levels of microbiota-reactive circulating IgA, compared to GF Ggta1+/+ mice colonized by the same microbiota (Figure 2B). This difference was not observed upon colonization of GF Ggta1-/- vs. Ggta1+/+ mice by a microbiota isolated from Ggta1+/+ mice (Figure S5C). This suggests that the enhanced microbiota-reactive IgA response of Ggta1-/- vs. Ggta1+/+ mice is induced by immunogenic bacteria present specifically in the microbiota of Ggta1-/- mice.

Of note, the levels of circulating IgA were reduced in Tcrβ-/-Ggta1-/- mice lacking T cells, when compared to Ggta1-/- mice (Figure S5D), suggesting that the production of circulating IgA NAb in Ggta1-/- mice occurs, in part, via a T-cell dependent mechanism, which is consistent with previous reports in Ggta1+/+ mice (Bunker et al., 2017; Fagarasan et al., 2010; Macpherson et al., 2000).

We then asked whether Ggta1-/- mice shape their microbiota via a mechanism associated with immune targeting of αGal-expressing bacteria. Consistent with a number of bacteria in the human gut microbiota carrying genes orthologous to the mammalian α1,3-galactosyltransferase (Montassier et al., 2019), several human probiotic bacteria expressed αGal-like glycans at the cell surface when cultured in vitro (Figure 2C, S6). Subsequent in vivo analyses demonstrated that approximately 20% of the bacteria in the small intestine of Ggta1+/+ mice expressed αGal-like glycans at the cell surface (Figure 2D,E, S5E). Nearly 30% of these αGal+ bacteria were immunogenic (Figure 2D,E), as defined by the detection of surface-bound IgA (Palm et al., 2014), which predominantly targets bacteria in the small intestine (Bunker et al., 2017; Bunker et al., 2015). These IgA+αGal+ bacteria accounted for roughly 50% of all the immunogenic (IgA+) bacteria in the small intestine (Figure 2D,E). These were also present, although at a lower extent, in the cecum, colon and feces (Figure S5F).

Ggta1-/- mice harbored a relatively lower percentage of immunogenic IgA+αGal+ bacteria in the small intestine, when compared to Ggta1+/+ mice (Figure 2D,E), while the percentage of immunogenic IgA+ bacteria was similar in Ggta1-/- vs. Ggta1+/+ mice (Figure 2D,E). This is consistent with the idea of a specific mechanism altering the microbiota of Ggta1-/- mice that presumably, at least in part, involves targeting immunogenic αGal+ bacteria by IgA. Whether this mechanism involves the recognition of bacterial αGal-like glycans by IgA is not clear.

We than compared the effect of IgA on the levels of systemic IgM and/or IgG NAb directed against antigens expressed by bacteria present in the microbiota (Kamada et al., 2015; Zeng et al., 2016). Induction of dysbiosis by streptomycin, increased the levels of circulating αGal-specific IgM and IgG in Iga-/-Ggta1-/- vs. Iga+/+Ggta1-/- mice (Figure 2F,G). This illustrates again that the IgA response of Ggta1-/- mice is distinct from that of Ggta1+/+ mice, reducing systemic IgM and IgG responses against antigens expressed by bacteria in the microbiota, as illustrated for αGal-like glycans. Presumably this occurs via a mechanism, whereby IgA prevents αGal+ bacteria or bacterial products associated to αGal from translocating across epithelial barriers and inducing systemic immune responses against this glycan.

Ggta1 deletion shapes the gut microbiota via an antibody (Ig)-dependent mechanism

Maintenance of microbiota composition across generations is sustained via maternal IgG transfer to the offspring through the placenta during the fetal period, and maternal IgM, IgG and IgA transfer via lactation during the neonatal period (Gensollen et al., 2016; Koch et al., 2016). Over time, newborns generate IgA that target immunogenic bacteria in the microbiota (McLoughlin et al., 2016; Moor et al., 2017), shaping its composition throughout adult life (Kawamoto et al., 2014). We hypothesized that the mechanism via which Ggta1 deletion shapes the gut microbiota involves targeting of immunogenic bacteria by both maternally-and offspring-derived immunoglobulins (Ig). To test this hypothesis, we used a similar experimental approach to that described above (Figure 1B) (Ubeda et al., 2012), whereby the microbiota from Ggta1+/+ mice was vertically transmitted to Ggta1+/+ or Ggta1-/- offspring that express Ig (Jht+/+) or not (Jht-/-) (Figure 3A). Crossing of F0 Jht+/+Ggta1+/+ (female) with Jht-/-Ggta1-/- (male) mice produced F1 Jht+/-Ggta1+/- mice, which were interbred to generate F2 Jht+/+Ggta1+/+, Jht+/+Ggta1-/-, Jht-/-Ggta1+/+ and Jht-/- Ggta1-/- mice, harboring a microbiota composition indistinguishable among genotypes (Figure S7A,B). Consistent with our previous observations (Figure 1C) (Singh et al., 2020), this suggests that maternal Ig transfer predominates over offspring Ig production in shaping the offspring microbiota, regardless of the genotype (Ubeda et al., 2012).

Figure 3.
Figure 3. Ggta1 deletion shapes the gut microbiota via an Ig-dependent mechanism.

A) Breeding strategy where F0 Jht-/-Ggta1-/- males were crossed with Jht+/+Ggta1+/+ females to generate F1 Jht+/-Ggta1+/- mice, which were bred to generate F2 and F3 Jht+/+Ggta1+/+, Jhf-/-Ggta1+/+, Jht+/+Ggta1-/- and Jht-/-Ggta1-/- mice. Microbiota Principal Coordinate Analysis of B) Weighted and C) Unweighted Unifrac and D) Distance of Weighted and Unweighted Unifrac of 16S rRNA amplicons, in fecal samples from F3 Jht+/+Ggta1+/+ (n=13) vs. Jht-/-Ggta1+/+ (n=16) mice and F3 Jht+/+Ggta1-/- (n=13) vs. Jht-/-Ggta1-/- (n=11) mice generated as in (A). E) Cladogram and F) Linear discriminant analysis (LDA) scores generated from LEfSe analysis, representing taxa enriched in the fecal microbiota of the same mice as in (B-D). Data from 1 experiment with 2-3 independent breedings/cages per genotype. Symbols (B, C, D) are individual mice. Red bars (D) correspond to mean values. Error bars (D) correspond to SD. P values in (B, C) calculated using PERMANOVA and in (D) using Mann-Whitney test. **P < 0.01, ns: not significant.

To dissect the relative contribution of the Ggta1 from the Ig genotype in shaping the microbiota, F2 littermates were interbred to generate F3 offspring carrying a microbiota targeted by antibodies (Jht+/+Ggta1+/+ and Jht+/+Ggta1-/-) or not (Jht-/-Ggta1+/+ and Jht-/-Ggta1-/-) (Figure 3A). Consistent with our previous observations (Figure 1), there was a marked separation of the microbiota community structure between F3 Jht+/+Ggta1-/- vs. Jht+/+Ggta1+/+ mice, as assessed by Principal Coordinate Analyses (PCA) for Weighted and Unweighted Unifrac (Figure 3B,C). Considering that Weighted Unifrac accounts for the relative abundance of the bacterial taxa while Unweighted Unifrac accounts for only the presence or absence of the taxa in the microbial community (Lozupone and Knight, 2005), they represent differences exerted by high and low abundant bacterial taxa respectively. This suggests that Ggta1 deletion shapes the microbiota when maternal and/or offspring-derived antibodies (i.e., Ig) are present.

LefSe analysis showed that the microbiota from Jht+/+Ggta1-/- mice was enriched in specific bacterial taxa, including Proteobacteria, as compared to the microbiota from Jht+/+Ggta1+/+ mice (Figure S7C). This suggests that Ggta1 deletion favors gut colonization by pathobionts in an Ig-dependent manner.

We then asked whether Ig are functionally involved in shaping the microbiota composition of Ggta1-/- vs. Ggta1+/+ mice. In the absence of Ig (Jht-/-), there were no differences in the microbiota composition of F3 Jht-/-Ggta1-/- vs. Jht-/-Ggta1+/+ mice, as assessed by PCA for Weighted Unifrac (Figure 3B). This suggests that shaping of highly abundant taxa in the microbiota of Ggta1-/- vs. Ggta1+/+ mice occurs via an Ig-dependent mechanism. In contrast, the microbiota composition of F3 Jht-/-Ggta1-/- mice remained distinct from that of Jht-/-Ggta1+/+ mice, as assessed by PCA for Unweighted Unifrac (Figure 3C). This suggests that shaping of low abundance bacterial taxa in the microbiota of Ggta1-/- vs. Ggta1+/+ mice occurs in an Ig-independent manner.

To address the extent to which Ggta1 deletion promotes shaping of the microbiota via an Ig-dependent mechanism, we compared the Unifrac distances between Jht+/+Ggta1+/+ and Jht-/-Ggta1+/+ mice vs. Jht+/+Ggta1-/- and Jh-/-Ggta1-/- mice, similar to what was previously described (Lozupone and Knight, 2005). The Weighted Unifrac distance of microbiota from Jht+/+Ggta1-/- vs. Jht-/-Ggta1-/- mice was higher than that from Jht+/+Ggta1+/+ vs. Jht-/-Ggta1+/+ mice (Figure 3D). This suggests that the relative impact of Ig on the gut microbiota community structure exerted by highly abundant bacterial taxa is enhanced in Ggta1-/- vs. Ggta1+/+ mice. This was confirmed by LefSe analysis showing an enhanced Ig-dependent enrichment of several bacterial taxa in the microbiota of Ggta1-/- mice (Figure 3E-F), compared to that of Ggta1+/+ mice (Figure S7D). In contrast, the Unweighted Unifrac distance of Jht+/+Ggta1+/+ vs. Jht-/-Ggta1+/+ mice was higher compared to Jht+/+Ggta1-/- vs. Jht-/- Ggta1-/- mice (Figure 3D). This suggests that the relative impact of Ig on the microbiota community structure of low abundant bacterial taxa is less pronounced for Ggta1-/- vs. Ggta1+/+ mice.

We then asked whether Ig exert a higher impact on the relative abundance of pathobionts in the gut microbiota of Ggta1-/- vs. Ggta1+/+ mice. In strong support of this notion, the gut microbiota from Jht-/-Ggta1-/- mice, lacking Ig, was enriched with Helicobactereaceae family from Proteobacteria phylum as compared to Jht+/+Ggta1-/- mice expressing Ig (Figure 3E, F). This is consistent with our previous finding that the gut microbiota of Rag2-/-Ggta1-/- mice, lacking adaptive immunity, is highly enriched in Proteobacteria, including Helicobacter (Singh et al., 2020). Of note, this was not observed in Jht-/-Ggta1+/+ vs. Jht+/+Ggta1+/+ mice (Figure S7D). These data suggest that the absence of host αGal favors colonization of the gut microbiota by pathobionts, the expansion of which is restrained by Ig.

Ggta1 deletion reduces microbiota pathogenicity

We then asked whether the Ig-dependent shaping of the microbiota in Ggta1-/- mice affects the pathogenesis of sepsis due to systemic infections emanating from gut microbes. Ggta1-/- mice were protected against systemic infections (i.p.) by a cecal inoculum isolated from Rag2-/-Ggta1-/- mice, reflecting a microbiota not shaped by Ig (Figure S8A,B). This is consistent with our previous finding showing Ggta1 deletion enhances protection against systemic bacterial infections (i.p.) via a mechanism involving IgG NAb (Singh et al., 2020). Moreover, Ggta1-/- mice were also protected against a systemic infection (i.p.) by a cecal inoculum isolated from Ggta1-/- mice, reflecting their own Ig-shaped microbiota (Figure S8A,B). This is in keeping with the previously shown enhanced protection of Ggta1-/- mice against cecal ligation and puncture (Singh et al., 2020). Surprisingly Jht-/-Ggta1-/- mice lacking B cells (Figure S8C), Tcrβ-/- Ggta1-/- mice lacking α/β T cells (Figure S8D) and Rag2-/-Ggta1-/- mice lacking B and T cells (Figure S8E) remained protected against systemic infections by the cecal inoculum isolated from Ggta1-/- mice. This suggests that the previously described IgG-dependent mechanism that protects Ggta1-/- mice from a systemic infection by a cecal inoculum isolated from Rag2-/-Ggta1-/- mice (Singh et al., 2020) is distinct from that protecting Ggta1-/- mice from a systemic infection by their own cecal inoculum. We reasoned that this can be explained by a reduction of the overall pathogenicity of the Ig-shaped microbiota of Ggta1-/- mice, compared to the non-Ig-shaped microbiota of Rag2-/-Ggta1-/- mice. To test this hypothesis, we compared the lethal outcome of Rag2-/-Ggta1-/- mice upon a systemic infection by Ig-shaped vs. a non-Ig-shaped microbiota.

Rag2-/-Ggta1-/- mice remained protected against systemic infections by the cecal inoculum isolated from Ggta1-/- mice, while succumbing to a systemic infection by a cecal inoculum isolated from Rag2-/-Ggta1-/- mice (Figure 4A,B). Lethality was associated with a 106-107-fold increase in bacterial load (Figure 4C), suggesting that the Ig-shaped microbiota of Ggta1-/- mice is less pathogenic, when compared to the non-Ig-shaped microbiota from Rag2-/-Ggta1-/- mice.

Figure 4.
Figure 4. Ggta1 deletion reduces microbiota pathogenicity.

A) Schematic showing infection of Rag2-/-Ggta1-/- mice with a cecal inoculum from either Ggta1-/- or Rag2-/-Ggta1-/- mice. B) Survival of Rag2-/-Ggta1-/- (n=9) mice after infection with a cecal inoculum from Ggta1-/- mice, and of Rag2-/-Ggta1-/- (n=9) mice after infection with a cecal inoculum from Rag2-/-Ggta1-/- mice; 2 experiments. C) Colony forming units (CFU) of aerobic (Ae) and anaerobic (An) bacteria in Rag2-/-Ggta1-/- mice (n=5 per group), 24 hours after infection as in (B); 2 experiments. D) Schematic showing infection of Rag2-/-Ggta1+/+ mice with a cecal inoculum from either Ggta1+/+ or Rag2-/- Ggta1+/+ mice. E) Survival of Rag2-/-Ggta1+/+ (n=5) mice after infection with a cecal inoculum from Ggta1+/+ mice, and of Rag2-/- Ggta1+/+ (n=5) mice after infection with a cecal inoculum from Rag2-/-Ggta1+/+ mice; 1 experiment. F) CFU of Ae and An bacteria in Rag2-/-Ggta1-/- mice (n=4 per group), 24 hours after infection as in (E); 1 experiment. G) Survival of Ggta1-/- mice receiving vehicle (PBS) (n=9) or Anti-Gr1 Ab (n=8), 24 hours before infection with cecal inoculum from Ggta1-/- mice; 2 experiments. H) CFU of Ae and An bacteria in Ggta1-/- mice receiving vehicle (PBS) (n=4-5) or Anti-Gr1 Ab (n=4-5), 24 hours after infection as in (G); 5 experiments. Symbols (C, F, H) represent individual mice. Red lines (C, F, H) correspond to median values. P values in (B, E, G) calculated with log-rank test and in (C, F, H) with Mann-Whitney test. Peritoneal cavity (PC). *P < 0.05, **P < 0.01, ***P < 0.001, ns: not significant.

We then asked whether the reduction of microbiota pathogenicity imposed by the adaptive immune system of Ggta1-/- mice is also operational in Ggta1+/+ mice. However, Rag2-/-Ggta1+/+ mice succumbed to the same extent to systemic infection (i.p.) with a cecal inoculum isolated from either Rag2+/+Ggta1+/+ vs. Rag2-/-Ggta1+/+ mice (Figure 4D-E), developing similar bacterial loads (Figure 4F). This suggests that the mechanism via which the adaptive immune system of Ggta1-/- mice shapes and reduces the pathogenicity of its microbiota is not operational in Ggta1+/+ mice.

Having established that in the absence of adaptive immunity, Ggta1-/- mice are resistant against systemic infection by a low pathogenic Ig-shaped microbiota (Figure S8C-E), we asked whether the mechanism of resistance relies on the innate immune system. Depletion of Ly6C+/Ly6G+ myeloid cells (i.e., polymorphonuclear cells and inflammatory monocytes) using an anti-GR1 monoclonal Ab (Figure S8F) (Daley et al., 2008) increased the susceptibility of Ggta1-/- mice to systemic infection by their cecal inoculum (Figure 4G). This was associated with a 102-105-fold increase in bacterial load, compared to control Ggta1-/- mice (Figure 4H). Of note, monocyte/macrophage depletion by Clodronate liposomes (Figure S8G) (Sunderkötter et al., 2004a; Sunderkötter et al., 2004b) failed to compromise the survival of Ggta1-/- mice upon infection by the same cecal inoculum (Figure S8H). This suggests that polymorphonuclear cells are essential for resistance against systemic infection emanating from the less pathogenic Ig-shaped microbiota of Ggta1-/- mice.

Discussion

While loss-of-function mutations in genes encoding glycosyltransferases can provide major fitness advantages against infection, these can also compromise the physiologic functions of the eliminated self-glycan, as illustrated by the occurrence of reproductive senescence upon the loss of GGTA1 function in mice (Singh et al., 2020). In an evolutionary context, such a trade-off could explain why these loss-of-function mutations are rare, and in some cases unique, to the human lineage, as illustrated for the loss of CMP-N-acetylneuraminic acid hydroxylase (CMAH) function, which eliminated sialic acid N-glycolylneuraminic acid (Neu5Gc) expression in humans (Ghaderi et al., 2011).

Ancestral hominids co-evolved with commensal bacteria in their microbiota over millions of years (Dethlefsen et al., 2007; Huttenhower et al., 2012; Moeller et al., 2016). The fitness advantages associated with these stable symbiotic associations include, among others, an overall optimization of nutrient intake from diet, regulation of different aspects of organismal metabolism, and colonization resistance against pathogenic bacteria (Buffie and Pamer, 2013). Here we propose that the loss of αGal expression, as it occurred during primate evolution, might have exerted a major impact on the nature of the symbiotic associations with bacteria in the microbiota. In support of this notion, Ggta1 deletion in mice was associated with major changes in the composition of the gut microbiota, in relation to the bacterial species present, over several generations (Figure 1). This occurred under experimental conditions of exposure to environmental pathobionts while minimizing the relative impact exerted by other environmental factors on microbiota composition (Ubeda et al., 2012), arguing that the Ggta1 genotype modulates the microbiota composition.

The mechanism via which Ggta1 deletion shapes the bacterial species present the gut microbiota is associated with targeting of αGal-expressing bacteria by IgA (Figure 2). Consistent with this notion, a relatively large proportion of probiotic bacteria as well as bacteria present in the mouse microbiota express αGal-like glycans at the cell surface (Figure 2). About 30% of these carry IgA at the cell surface in the mouse microbiota and, as such, are considered as immunogenic (Palm et al., 2014). The proportion of IgA+αGal+ bacteria was reduced in the microbiota of Ggta1-deleted mice and was presumably eliminated (Figure 2). This suggests that Ggta1 deletion probably broadens bacterial recognition by IgA to include immunogenic αGal+ bacteria, which as a result are probably purged from the microbiota. Whether this occurs via a mechanism involving the recognition of αGal-like glycans and/or other related epitopes expressed at the surface of these bacteria by IgA has not been established. Of note, these are not mutually exclusive possibilities since: i) IgA can target αGal-like glycans and modulate bacterial pathogenicity (Hamadeh et al., 1995a; Hamadeh et al., 1995b), ii) IgA are poly-reactive and can target common antigens expressed by bacteria (Bunker et al., 2017; Bunker et al., 2015) and iii) αGal-reactive antibodies present a degree of poly-reactivity against non-αGal related bacterial epitopes (Bernth Jensen et al., 2020).

The identity of the αGal+ bacteria targeted by IgA remains elusive but likely includes Gram-negative pathobionts from the Enterobacteriaceae family, as demonstrated for Escherichia (E.) coli O86:B7 (Yilmaz et al., 2014), which expresses the αGal-like glycan Galα1-3Gal(Fucα1-2)β1-3GlcNAcβ1-4Glc as part of the lipopolysaccharide (LPS) O-antigen (Guo et al., 2005). Of note, this pathobiont can induce a systemic αGal-specific NAb response in humans (Springer and Horton, 1969) as well as in Ggta1-deleted mice, which is protective against infection by pathogens expressing αGal-like glycans (Yilmaz et al., 2014). The finding that several commensal bacteria in the human gut microbiota express αGal-like glycans (Figure 2, S5) suggests that other bacteria might contribute to this protective response.

Our findings also suggest that Ggta1 deletion shapes the bacterial community structure among highly abundant bacterial taxa in the microbiota via an Ig-dependent mechanism, and among low abundant bacterial taxa independently of Ig (Figure 3). Presumably, the shaping of highly abundant taxa by Ig occurs via a mechanism that involves not only IgA produced by the offspring, but also maternal IgG transferred through the placenta as well as IgM, IgG and IgA transferred through maternal milk (Koch et al., 2016). These regulate neonatal innate (Gomez de Agüero et al., 2016) and adaptive (Koch et al., 2016) immunity, shaping the offspring microbiota composition (Gensollen et al., 2016; Koch et al., 2016). Whether this occurs via targeting of αGal-like glycans, as discussed above, and/or via other bacterial antigens expressed by immunogenic bacteria has not been established.

Shaping of lowly abundant bacterial taxa independently of Ig (Figure 3) suggests that other mechanisms contribute to shape the microbiota of Ggta1-deleted mice. These probably include the modulation of nutritional or spatial niches due to the loss of αGal from complex glycosylated structures present at epithelial barriers, such as the mucus, as demonstrated for other glycans (Pickard et al., 2014).

The selective pressure exerted by the adaptive immune system of Ggta1-/- mice on the bacterial species present in the microbiota probably allows for the establishment of a more diverse ecosystem containing pathobionts (Singh et al., 2020), such as Helicobactereaceae (Figure 1, S1,2). These can elicit the production of antibodies targeting and exerting negative selective pressure over other bacterial symbionts and releasing ecological niches, thus further shaping the microbiota. Expansion of these pathobionts in the microbiota of Ggta1-/- mice is restrained by Ig, which probably explains the lack of associated pathology (Figure S3). This suggests that the loss of GGTA1 function in ancestral primates fostered mutualistic interactions with more diverse bacterial ecosystems, incorporating pathobionts such as Helicobacter pylori, associated with fitness costs (Atherton and Blaser, 2009) and gains (Linz et al., 2007).

Our findings suggest that the Ig-shaping of the bacterial species present in the gut microbiota of Ggta1-/- mice reduces its pathogenicity, as illustrated by the lethal outcome of systemic infections by the Ig-shaped vs. non-shaped microbiota (Figure 4A-F, S8A,B). This reduction in pathogenicity makes that the effector mechanism underlying resistance against systemic infection by the Ig-shaped microbiota does not rely on the adaptive immune system (Figure S8C-E), but instead on cellular components of the innate immune systems, namely, neutrophils (Figure 4G,H).

The notion of host mechanisms shaping the microbiota composition towards a reduction of its pathogenicity is in keeping with host microbial interactions not being hardwired but instead shifting between symbiotic to pathogenic depending on host and microbe cooperative behaviors (Ayres, 2016; Vonaesch et al., 2018). For example, when restricted to the microbiota, bacterial pathobionts can behave as commensals posing no pathogenic threat to the host (Vonaesch et al., 2018), while triggering sepsis (Haak and Wiersinga, 2017) upon translocation across epithelial barriers (Caruso et al., 2020). The high fitness cost imposed to modern humans by sepsis (Rudd et al., 2020) suggests that mutations shaping the composition of the microbiota towards a reduced capacity to elicit sepsis should be associated with major fitness advantages. Our findings suggest that loss-of-function mutations in GGTA1 act in such a manner.

In conclusion, protective immunity against αGal-expressing pathogens was likely a major driving force in the natural selective events that led to the fixation of loss-of-function mutations in the GGTA1 gene of ancestral Old World primates (Galili, 2016; Soares and Yilmaz, 2016). Moreover, in the absence of αGal, the glycan structures associated with the Fc portion of IgG, can increase IgG-effector function and resistance to bacterial infections, irrespectively of αGal-specific immunity (Singh et al., 2020). The net survival advantage against infection provided by these traits came alongside the emergence of reproductive senescence (Singh et al., 2020), a major fitness cost presumably outweighed by endemic exposure to highly virulent pathogens (Singh et al., 2020). Here we provide experimental evidence for yet another fitness advantage against infection, associated with the loss of GGTA1, driven by Ig-shaping and reduction of microbiota pathogenicity. We infer that ancestral Old World primates carrying loss-of-function mutations in GGTA1 probably shaped their microbiota to minimize its pathogenic effect, providing a major fitness advantage against sepsis.

Materials and Methods

Mice

Mice were used in accordance with protocols approved by the Ethics Committee of the Instituto Gulbenkian de Ciência (IGC) and Direção Geral de Alimentação e Veterinária (DGAV), following the Portuguese (Decreto-Lei no. 113/2013) and European (directive 2010/63/EU) legislation for animal housing, husbandry and welfare. C57BL/6J wild-type (Ggta1+/+), Ggta1-/- (Tearle et al., 1996), Jht-/-Ggta1-/- (Gu et al., 1993), Tcrβ-/-Ggta1-/- (Yilmaz et al., 2014), μs-/-Ggta1-/-(Yilmaz et al., 2014), Iga-/-Ggta1-/- (Singh et al., 2020) and Rag2-/-Ggta1-/-(Singh et al., 2020) mice were used. Mice were bred and maintained under specific pathogen-free (SPF) conditions (12 h day/night, fed ad libitum), as described (Yilmaz et al., 2014). Germ-free (GF) C57BL/6J Ggta1+/+ and Ggta1-/- animals were bred and raised in the IGC gnotobiology facility in axenic isolators (La Calhene/ORM), as described (Yilmaz et al., 2014) (Singh et al., 2020). Sterility of food, water, bedding, oral swab and feces were confirmed as described (Singh et al., 2020). Both male and female mice were used for all experiments. All animals were studied between 9-16 weeks of age unless otherwise indicated.

Breeding experiments

Vertical transmission of the microbiota from Ggta1+/+ mice to Ggta1-/- and Ggta1+/+ offspring over several generations was achieved, as described (Ubeda et al., 2012) (Singh et al., 2020). Briefly, two or more breeding pairs were established, consisting of two Ggta1+/+ females and one Ggta1-/- male per cage. The male was removed after one week and the females were placed in a clean cage until delivery. F1 Ggta1+/- pups were weaned at 3-4 weeks of age and then co-housed until 8 weeks of age. Two or more F1 Ggta1+/- breeding pairs were established randomly using one male and two females per cage. F2 pups were weaned at 3-4 weeks of age, genotyped and segregated according to their Ggta1-/- vs. Ggta1+/+ genotype in separate cages until adulthood. F3 to F5 pups were generated in a similar manner. Fecal pellets from 2-3 cages per genotype were collected (10-12 weeks of age) for microbiota analysis.

The effect of Ggta1 genotype and Ig on microbiota composition derived from Ggta1+/+ mice was achieved essentially as described (Singh et al., 2020). Briefly, two or more breeding pairs were established, consisting of two Jht+/+Ggta1+/+ females and one Jht-/-Ggta1-/- male per cage. The male was removed after one week and the females were placed in a clean cage until delivery. F1 Jht+/-Ggta1+/- pups were kept with mothers until weaning at 3-4 weeks of age and co-housed until 8 weeks of age. Two or more F1 Jht+/-Ggta1+/- breeding pairs were established randomly using one male and two females per cage. Littermate F2 pups were weaned at 3-4 weeks of age, genotyped and segregated according to their Jht+/+Ggta1-/-, Jht-/-Ggta1-/-, Jht+/+Ggta1+/+ and Jht-/-Ggta1+/+ genotypes in separate cages until adulthood. F3 pups were generated in a similar manner. Fecal pellets from 2-3 cages per genotype were collected (10-12 weeks of age) for microbiota analysis.

Genotyping

Mice were genotyped from tail biopsies (0.5-1 cm) by PCR of genomic DNA as per manufacturer’s protocols (KAPA mouse genotyping kit #KK7352) as described (Singh et al., 2020).

Cecal Slurry Injection

Cecal slurry injection was performed essentially as described (Singh et al., 2020). Microbiota pathogenicity experiments were performed by preparing cecal slurry from Ggta1-/- vs. Rag2-/-Ggta1-/- mice or from Ggta1+/+ vs. Rag2-/-Ggta+/+ mice in parallel and injecting to recipient mice (i.p. 1 mg/g body weight). Mice were monitored every 12 h for survival for 14 days or euthanized at various time points for analysis of different parameters.

Pathogen Load

Quantification of pathogen load in the mice was performed 24 h after cecal slurry injection, essentially as described (Singh et al., 2020).

Neutrophil depletion

Anti-Gr1 mAb (Clone: RB6-8C5, 300 μg in 200 μL PBS) was injected (i.p.) to mice 24 h before cecal slurry injection. Neutrophil depletion was confirmed by flow cytometry, using CD11b+Ly6G+ cell staining in the blood.

Monocyte/Macrophage depletion

Clodronate or PBS liposomes (www.Clodronateliposomes.org) was injected (10 μL/g, i.p.) to mice 72 h before cecal slurry injection. Monocyte/macrophage depletion was confirmed by flow cytometry, using CD11b+F4/80+ and CD11b+Ly6C+ staining in the peritoneal lavage.

ELISA

ELISA for IgA binding to cecal extracts was done essentially as described (Kamada et al., 2015; Zeng et al., 2016). Cecal lysate was prepared as described (Singh et al., 2020). 96-well ELISA plates (Nunc MaxiSorp #442404) were coated with the cecal lysate (100 μL/well, 4°C, overnight), washed (3x, PBS 0.05% Tween-20, Sigma-Aldrich #P7949-500ML), blocked (200 μL, PBS 1% BSA wt/vol, Calbiochem #12659-100GM, 3 h, RT) and washed (3x, PBS 0.05% Tween-20). Plates were incubated with serially diluted (50 μL) mouse sera (1:20 to 1:100 in PBS 1% BSA, wt/vol, 2 h, RT) and washed (5x, PBS/0.05% Tween-20). IgA was detected using horseradish peroxidase (HRP)-conjugated goat anti-mouse IgA (Southern Biotech #1040-05), in PBS/1 %BSA/0.01% Tween-20 (100 μL, 1:4,000 vol/vol, 1 h, RT) and plates were washed (5x, PBS/0.05% Tween-20).

For quantification of total serum and small intestinal IgA, 96-well ELISA plates (Nunc MaxiSorp #442404) were coated with goat anti-mouse IgA (Southern Biotech #1040-01, 2 μg/mL in Carbonate-Bicarbonate buffer, 100 μL/well, overnight, 4°C), washed (3x, PBS 0.05% Tween-20, Sigma-Aldrich #P7949-500ML), blocked (200 μL, PBS 1% BSA wt/vol, 2 h, RT) and washed (3x, PBS 0.05% Tween-20). Plates were incubated with serially diluted serum or gut content (50 μL, PBS 1% BSA, wt/vol, 2 h, RT) and standard mouse IgA (Southern Biotech #0106-01, prepared in duplicates) and washed (5x, PBS/0.05% Tween-20). IgA was detected using HRP-conjugated goat anti-mouse IgA (Southern Biotech #1040-05) in PBS/1%BSA/0.01% Tween-20 (100 μL, 1:4,000 vol/vol, 1 h, RT) and plates were washed (5x, PBS/0.05% Tween-20).

For quantification of anti-αGal IgG, IgM and IgA, 96-well ELISA plates (Nunc MaxiSorp #442404) were coated with αGal-BSA (Dextra, 5 μg/mL in Carbonate-Bicarbonate buffer, 50 μL/well, overnight, 4°C). Wells were washed (3x, PBS 0.05% Tween-20, Sigma-Aldrich #P7949-500ML), blocked (200 μL, PBS 1% BSA wt/vol, 2 h, RT) and washed (3x, PBS 0.05% Tween-20). Plates were incubated with serially diluted serum or fecal content (50 μL, PBS 1% BSA, wt/vol, 2 h, RT) and standard mouse anti-αGal IgG, IgM or IgA and washed (5x, PBS/0.05% Tween-20). Anti-αGal Abs were detected using HRP-conjugated goat anti-mouse IgG, IgM and IgA in PBS/1 %BSA (100 μL, 1:4000 vol/vol, 1.5 h, RT) and plates were washed (5x, PBS/0.05% Tween-20).

HRP activity was detected with 3,3’,5,5’-Tetramethylbenzidine (TMB) Substrate Reagent (BD Biosciences #555214, 50 μL, 20-25 min., dark, RT) and the reaction was stopped using sulfuric acid (2N, 50 μL). Optical densities (OD) were measured using a MultiSkan Go spectrophotometer (ThermoFisher) at λ=450 nm and normalized by subtracting background OD values (λ= 600 nm).

For measurement of fecal Lipocalin (Lcn-2), feces were resuspended with sterile PBS (100 mg/mL), vortexed (5 min.), and centrifuged (12,000 rpm, 4°C, 10 min.). Lcn-2 levels were determined in fecal supernatants using a LEGEND MAX™ Mouse NGAL (Lipocalin-2) ELISA Kit (BioLegend #443708).

Flow cytometry of bacterial staining for IgA and αGal

Overnight cultures of bacteria were prepared as follows. Samples of 5-20 μL of each bacterial culture depending on OD600 measurements, and corresponding to approximately 106-107 cells, were fixed in PFA (4% wt/vol in PBS) and washed with filter-sterilized PBS. For detection of IgA binding and αGal expression by gut microbes, small intestinal, cecal, colon and fecal samples were homogenized (5 mg/ml in PBS) by vortexing (maximum speed, 5 min., RT) and filtered (BD Falcon™, 40 μm cell strainer # 352340). Larger debris were pelleted by centrifugation (600 g, 4°C, 5 min.). 50 μL supernatant (containing bacteria) per condition was added to a 96-well v-bottom plate (Corning Costar #3894) for staining. Bacteria were pelleted by centrifugation (3,700 g, 10 min., 4°C) and suspended in flow cytometry buffer (filter-sterilized 1xPBS, 2% BSA, wt/vol). Bacterial DNA was stained using SYTO®41 Blue Fluorescent Nucleic Acid Stain (Molecular Probes #S11352, 1:200 vol/vol, wt/vol) in flow cytometry buffer (100 μL, 30 min., RT). Cecal content from germ free (GF) mice was used as control. Bacteria were washed in flow cytometry buffer (200 μL), centrifuged (4000 g, 10 min., 4°C) and supernatant was removed by flicking the plate. Bacteria were incubated in Fluorescein Isothiocyanate (FITC)-conjugated BSI-B4 lectin from Bandeiraea (Griffonia) simplicifolia (Sigma-Aldrich, #L2895-1MG, 50 μL, 40 μg/mL in PBS, 2 h) for detection of αGal and anti-mouse IgA-PE mAb (mA-6E1, eBiosciences # 12-4204-82, 1:100 in PBS 2% BSA wt/vol, 30 min.) and washed as above. E coli O86:B7 (about 107 per tube) was used as a positive control for bacterial αGal expression. Samples were re-suspended in flow cytometry buffer (300 μL), transferred to round-bottom tubes (BD Falcon™ #352235) and centrifuged (300 g, 1 min., RT). Samples were analyzed in LSR Fortessa SORP (BD Biosciences) equipped with a high-throughput sampler (HTS) using the FACSDiva Software (BD v.6.2) and analyzed by FlowJo software (v10.0.7) as described (Singh et al., 2020)..

Extraction of bacterial DNA from feces

Bacterial DNA from fecal pellets was extracted according to manufacturer’s instructions (QIAamp Fast DNA Stool Mini Kit #50951604) as described (Singh et al., 2020).

Amplicon Sequencing: 16S amplicons sequencing and analysis

The 16S rRNA V4 region was amplified and sequenced following the Earth Microbiome Project (http://www.earthmicrobiome.org/emp-standard-protocols/), and analyzed using QIIME 1.9.1 as described (Singh et al., 2020). 16S sequencing data was submitted to the Sequence Read Archive (SRA), with the BioProject reference PRJNA701192.

Statistical analysis

All statistical tests were performed using GraphPad Prism Software (v.6.0). All statistical details of experiments including statistical tests, exact value of n, what n represents, definition of center, dispersion and precision measures are provided in each figure legend.

Data availability

All data generated during this study are included in the manuscript and supporting files. 16S sequencing data was submitted to the Sequence Read Archive (SRA), with the BioProject reference PRJNA701192.

Author contributions

S.S. contributed critically to study design and performed most experimental work and data analyses. P.B.A. performed flow cytometry analysis of probiotic bacterial strains with B.Y., and experiments pertaining to the role of IgA in vivo. J.A.T. performed flow cytometry analysis of mouse microbiota and contributed to study interpretation. S.C. generated mouse strains with S.S. D.S. and M.T. performed 16S rRNA sequencing analysis. M.P.S. drove the study design and wrote the manuscript with S.S.

Declaration of interests

The authors declare no conflict of interests.

Supplementary Figure legends

Suppl. Figure 1. Analyses of gut microbiota composition of Ggta1+/+ and Ggta1-/- mice. Relative abundance of bacteria at all levels of taxonomy, present at >2% frequency, in the same mice as in Figure 1A. Symbols represent individual mice. Red bars correspond to mean values. Error bars correspond to SD. Adjusted P values calculated using Benjamini-Hochberg correction. *P < 0.05, **P < 0.01, ***P < 0.005, ****P < 0.001.

Suppl. Figure 2. Analyses of gut microbiota composition of Ggta1+/+ vs. Ggta1-/- mice. Relative abundance of bacteria at all levels of taxonomy, present at >2% frequency in the same mice as in Figure 1A. Stacked bars represent the mean of the bacterial taxa. Colors represent the relative fraction of each taxon. Data from 1 experiment.

Suppl. Figure 3. Ggta1 deletion does not cause inflammation at steady state. A) Representative H/E sections of the small intestine, large intestine, liver, spleen, lung and kidney of Ggta1+/+ (n=5) and Ggta1-/- (n=5) mice at steady state. B) Fecal Lcn-2 concentrations in Ggta1+/+ (n=10) and Ggta1-/- (n=10) mice at steady state. Symbols represent individual mice. Red bars correspond to mean values. Error bars correspond to SD, ns: not significant.

Suppl. Figure 4. Ggta1 deletion shapes the gut microbiota composition. Relative abundance of bacteria at all levels of taxonomy, present at >2% frequency in the same mice as in Figure 1C-F. Stacked bars represent the mean of the bacterial taxa. Colors represent the relative fraction of each taxon. Data from 1 experiment.

Suppl. Figure 5. Ggta1 deletion enhances IgA responses to the gut microbiota. A) Concentration of total IgA in serum of Ggta1+/+ (n=9), GF Ggta1+/+ (n=5), Ggta1-/- (n=5) and GF Ggta1-/- (n=6) mice. B) Concentration of total IgA in the small intestinal content of Ggta1+/+ (n=10), GF Ggta1+/+ (n=5), Ggta1-/- (n=10) and GF Ggta1-/- (n=5) mice. C) Relative binding of IgA in the serum of GF Ggta1+/+ (n=5) and GF Ggta1-/- (n=5) mice to fecal extract from Ggta1+/+ mice at indicated time-points after colonization with cecal extract from Ggta1+/+ mice; 2 experiments. D) Concentration of total IgA in serum of Ggta1-/- (n=7), Tcrβ-/- Ggta1-/- (n=12) mice. E) Representative plots showing the gating strategy for staining of intestinal content with Syto41, BSI-B4 and Anti-IgA. F) Quantification of αGal+, IgA+ and IgA+αGal+ bacteria in the cecum, colon and feces of the same mice as in Figure 2D-E. Symbols (A, B, C, D, F) are individual mice. Red bars (A, B, C, D, F) correspond to mean values. Error bars (A, B, C, D, F) correspond to SD. P values in (A, B, C) calculated using Kruskal-Wallis test using Dunn’s multiple comparisons test and in (D, F) using Mann-Whitney test. *P < 0.05, **P < 0.01, ns: not significant.

Suppl. Figure 6. αGal expression by probiotic bacteria. Representative flow cytometry plots of the data in Figure 2C showing probiotic bacterial strains unstained or stained with BSI-B4 lectin.

Suppl. Figure 7. Ggta1 deletion shapes the gut microbiota via an Ig-dependent mechanism. Microbiota Principal Coordinate Analysis of A) Weighted and Unweighted Unifrac and B) Distance of Weighted and Unweighted Unifrac of 16S rRNA amplicons, in fecal samples from F2 Jht+/+Ggta1+/+ (n=8) vs. Jht-/-Ggta1+/+ (n=11) mice and F2 Jht+/+Ggta1-/- (n=5) vs. Jht-/-Ggta1-/- (n=8) mice generated as described in Figure 3A. C-D) Cladogram and linear discriminant analysis (LDA) scores generated from LEfSe analysis, representing taxa enriched in the fecal microbiota of the same C) F3 Jht+/+Ggta1+/+ vs. Jht+/+Ggta1-/- mice and D) F3 Jht-/-Ggta1+/+ vs. Jht+/+Ggta1+/+ mice as in Figure 3B-D. Symbols (A, B) are individual mice. Red bars (B) correspond to mean values. Error bars (B) correspond to SD. P values in (A) calculated using PERMANOVA and in (B) using Mann-Whitney test. ns: not significant.

Suppl. Figure 8. Ggta1 deletion reduces microbiota pathogenicity. A) Schematic showing infection of Ggta1-/- mice with a cecal inoculum from either Ggta1-/- mice or Rag2-/-Ggta1-/- mice. B) Survival of Ggta1-/- (n=14) mice after infection with a cecal inoculum from Ggta1-/- mice and of Ggta1-/- (n=13) mice after infection with a cecal inoculum from Rag2-/-Ggta1-/- mice; 2 experiments. C) Survival of Jht+/+Ggta1-/- (n=9) and Jht-/-Ggta1-/- (n=8) mice after infection with a cecal inoculum from Ggta1-/- mice; 2 experiments. D) Survival of Tcrβ+/+Ggta1-/- (n=8) and Tcrβ+/+ Ggta1-/- (n=12) mice infected as in (C); 2 experiments. E) Survival of Rag2+/+Ggta1-/- (n=9) and Rag2-/- Ggta1-/- (n=23) mice infected as in (C); 5 experiments. F) Representative plots showing depletion of CD11b+Ly6G+ cells in the blood 24 hours after Anti-Gr1 Ab injection (i.p.) in the same mice as in Figure 4G. G) Representative plots showing depletion of CD11b+F4/80+ and CD11b+Ly6C+ cells in the peritoneal lavage 72 hours after injection (i.p.) with Clodronate liposomes. H) Survival of Ggta1-/- mice receiving PBS liposomes (n=7) or Clodronate liposomes (n=8), 72 hours before infection (i.p.) with cecal inoculum from Ggta1-/- mice; 2 experiments. P values in (B, C, D, E, H) calculated with log-rank test. Peritoneal cavity (PC). ns: not significant.

Acknowledgements

We thank our colleagues J. Howard and I. Gordo (Instituto Gulbenkian de Ciência; IGC) for critical review of the manuscript, IGC Genomics, Flow Cytometry, Antibody, Histopathology and Animal House Facilities. S.S. was supported by Fundac□ão para a Cie□ncia e Tecnologia (FCT; SFRH/BD/52177/2013), J.A.T. by an ESCMID Research Grant and FCT (SFRH/BPD/112135/2015) and M.P.S. by the Gulbenkian, “La Caixa” (HR18-00502) and Bill & Melinda Gates (OPP1148170) Foundations and FCT (5723/2014 and FEDER029411).

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Posted February 10, 2021.
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Glycan-Based Shaping Of The Microbiota During Primate Evolution
Sumnima Singh, Patricia Bastos-Amador, Jessica A. Thompson, Mauro Truglio, Bahtiyar Yilmaz, Silvia Cardoso, Daniel Sobral, Miguel P. Soares
bioRxiv 2021.02.10.430443; doi: https://doi.org/10.1101/2021.02.10.430443
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