A cationic antimicrobial biopolymer influences murine gut community diversity

40 female and 40 male 6-week old CD-1 mice were randomly divided into four groups and segregated by sex (i.e. 10 female and 10 male mice per group) and fed a 20% high-fat diet supplemented with (i) maltodextrin alone (MD) that served as the control, (ii) maltodextrin + ε-polylysine (PL), (iii) maltodextrin + pectin (P), and (iv) maltodextrin + ε-polylysine + pectin (PL-P). Previous studies showed that mice co-housed together exhibit similar gut microbial communities.38, 39 Thus, pooled fecal pellets from each cage were collected in 24-h metabolic cages and analyzed at three points: week 1 (baseline), week 5 (intermediate phase), and week 9 (final phase) (Fig. 1). Body weight and food consumption did not vary regardless of treatment group and across the entire experimental period.

Fig. 1 Study design of timeline (a) and grouping (b). Forty female and 40 male 6-week old CD-1 mice were randomly divided into four groups and segregated by sex and fed a 20% high-fat diet supplemented with (i) maltodextrin alone (MD), (ii) maltodextrin + ε-polylysine (PL), (iii) maltodextrin + pectin (P), and (iv) maltodextrin + ε-polylysine + pectin (PL-P). Five mice were co-housed and pooled fecal pellets from each cage were collected in 24-h metabolic cages and analyzed at three points: week 1, week 5, and week 9 Full size image

In order to characterize phylogenetic diversity, the 16S rRNA gene V3/V4 fragment was sequenced to yield 15,739,734 quality reads following filtering.40 This provided a mean sample depth of 327,911 sequencing reads per bacterial community. To assess the α-diversity within a given community, the number of observed operational taxonomic units (OTUs) was calculated using weighted UniFrac.41 Rarefaction curves for the observed OTUs (Fig. S1) approached an asymptote independent of diet, sampling point, and sex to indicate sequencing depth sufficiently covered OTU diversity present in the communities extracted from fecal samples.

At the phylum level, the summation of Actinobacteria, Bacteroidetes, Deferribacteres, Firmicutes, Proteobacteria, Verrucomicrobia constituted over 99% of OTUs identified in all samples analyzed. As previously reported,42, 43 the murine gut microbiome consists of relatively large contributions provided by the phyla Bacteroidetes and Firmicutes (Fig. 2). This is consistent with other mammalian gut communities, including humans and non-human primates.44, 45 However, the relative abundances of Bacteriodetes (p < 0.05) and Firmicutes (p < 0.05) were altered in response to the particular dietary biopolymer (multi-way ANOVA) (Fig. 2). Interestingly, mice fed the ε-polylysine–pectin complex exhibited an increase of Bacteriodetes at 8.82% (p < 0.05, multi-way ANOVA Tukey HSD post-hoc) with a corresponding decreasing of OTUs assigned to Firmicutes by 11.13% (p < 0.05, multi-way ANOVA Tukey HSD post-hoc). This is relative to the community structure determined in the maltodextrin-fed control group (Table S1). Moreover, the ε-polylysine (i.e. no pectin complex) fed mice exhibited a community relatively deficient for Firmicutes at the intermediate phase (i.e. 5 weeks) of the study. Remarkably, Firmicute OTUs rebounded to its initial concentration at the 9-week sampling point (baseline: 55.24%, intermediate: 34.71%, final: 59.01%, baseline vs. intermediate: p < 0.05, intermediate vs. final: p < 0.05, multi-way ANOVA Tukey HSD post-hoc) (Fig. 2 and Table S3). Exhibiting the same adaptive response, the relative fraction of Bacteriodetes OTUs transiently increased at 5 weeks of feeding and converged to initial concentrations at the final time point (baseline: 35.40%, intermediate: 51.18%, final: 28.82%, baseline vs. intermediate: p < 0.05, intermediate vs. final: p < 0.05, multi-way ANOVA Tukey HSD post-hoc) (Fig. 2 and Table S3). A similar transient surge in Verrucomicrobia occurred in mice fed pectin alone, to fall to original levels at the final sampling point (baseline: 0.59%, intermediate: 5.46%, final: 1.01%, baseline vs. intermediate: p < 0.05, intermediate vs. final: p < 0.05 multi-way ANOVA Tukey HSD post-hoc) (Fig. 2 and Table S4). In aggregate, these results indicate that specific food grade biopolymers transiently direct phyla representation within the murine gut. This was observed when both ε-polylysine and pectin were incorporated individually. However, when ε-polylysine was complexed with the anionic pectin, this phenomenon was not observed. It is noteworthy that significant population fluxes within Actinobacteria, Deferribacteres, and Proteobacteria were not observed regardless of diet (Table S5).

Fig. 2 Relative abundances of bacteria phyla in response to biopolymer feeding. Pooled fecal samples were collected from two female and two male cages per group at each time point. Each bar represents the average relative abundance bacterial phyla within a treatment group during each time point with each colored box representing a bacterial phylum taxon. Bbaseline, M intermediate, F final, MD maltodextrin, PL ε-polylysine, P pectin, PL+P ε-polylysine–pectin complexes Full size image

In addition to phylum-level community disruption, several bacterial genera shifted in response to dietary biopolymers. This includes members of the genus Bacteroides that were the most frequently encountered taxa within the mouse gut (14.32 ± 9.58% across all the samples). In total (across both sexes and sampling points), Bacteroides representation varied with respect to biopolymer feeding group. Mirroring the response by the phylum Bacteroidetes, ε-polylysine (p < 0.05, multi-way ANOVA Tukey HSD post-hoc) and ε-polylysine–pectin complexed treatment (p < 0.05, multi-way ANOVA Tukey HSD post-hoc) increased the Bacteroides spp. populations by 7.95 and 7.46%, respectively, in comparison to the maltodextrin control group (Fig. 3 and Table S6). Other bacterial populations that were modulated by feeding regimes include, Adlercreutzia, Lactobacillus, Turicibacter, and Ruminococcus (multi-way ANOVA, p < 0.05). Specifically, the abundance of Adlercreutzia decreased regardless of biopolymer relative to the maltodextrin-fed group. Their relative populations decreased 0.18%, 0.22%, 0.24% in mice fed ε-polylysine, pectin, and ε-polylysine–pectin complexes, respectively. In addition, the genus Ruminococcus significantly decreased by 1.39% in response to ε-polylysine and decreased by 1.44% in the pectin group. Furthermore, the ε-polylysine–pectin complexed diet significantly decreased the Lactobacillus content by 4.95%, reflecting overall diminishment of Firmicutes in this group. This is in contrast to the pectin diet that enriched for Turicibacter relative to the other three diets. A full catalog of genera differing in response to biopolymer conditions is provided in Table S6.

Fig. 3 Relative abundance of bacterial genera in response to dietary biopolymers. Pooled fecal samples were collected from two female and two male cages per group at each time point. Each bar represents the average relative abundance of a treatment group during each time point and each colored box represents a bacterial genus taxon. B baseline, M intermediate, F final, MD maltodextrin, PL ε-polylysine, P pectin, PL+P ε-polylysine–pectin complexes Full size image

Maltodextrin is commonly employed as a thickening agent or filler in various nutritional applications. This polysaccharide was used in the formulation of all treatment diets, and thus served as a control to determine if maltodextrin alone would enrich for bacteria capable of hydrolyzing the α-1-4 glycosidic linkages between d-glucose residues. As such, the relative abundance of Coprococcus in the mouse gut was enriched while consuming maltodextrin incorporated within their food. The response trajectory included a significant increase between baseline and intermediate sampling points and between baseline and final time point (baseline: 0.56%, intermediate: 0.98%, final: 0.91%, baseline vs. intermediate: p < 0.05, baseline vs. final: p < 0.05) (Fig. 3 and Table S7).

In the ε-polylysine treatment group, the relative abundance of Bacteroides transiently increased, consistent with the oscillation at the phylum level (baseline: 8.85%, intermediate: 34.40%, final: 8.74%, baseline vs. intermediate: p < 0.05, intermediate vs. final: p < 0.05). A similar response was observed for Oscillospira (baseline: 4.96%, intermediate: 2.51%, final: 6.13%, baseline vs. intermediate: p < 0.05, intermediate vs. final: p < 0.05). This is contrasted with a transient decrease in OTUs assigned to Ruminococcus (baseline: 2.17%, intermediate: 0.97%, final: 2.10%, baseline vs. intermediate: p < 0.05, intermediate vs. final: p < 0.05), and Adlercreutzia (baseline: 0.49%, intermediate: 0.24%, final: 0.34%, baseline vs. intermediate: p < 0.05) (Fig. 3 and Table S8). Furthermore, Coprococcus spp. exhibited a sustained enrichment during feeding, with significant increases between baseline and final time point (baseline: 0.47%, intermediate: 0.71%, final: 0.91%, baseline vs. final: p < 0.05) (Fig. 3 and Table S8). This is consistent with the same trend observed within the maltodextrin control group. However, Coprococcus populations remain relatively static in mice-fed pectin and ε-polylysine–pectin complexes.

Pectin transiently enriched for the genus Akkermansia (baseline: 0.59%, intermediate: 5.46%, final: 1.01%, baseline vs. intermediate: p < 0.05, intermediate vs. final: p < 0.05) contributing to the observed intermediate increase of Verrucomicrobia. In contrast, Adlercreutzia populations were diminished in the intermediate sampling point and remained depressed in the final observation (Adlercreutzia baseline: 0.48%, intermediate: 0.23%, final: 0.26%, baseline vs. intermediate: p < 0.05). Candidate genus rc4-4 OTU representation diminished proportionally, though exhibited incomplete rebound to initial states (rc4-4 baseline: 1.94%, intermediate: 1.04%, final: 1.62%, baseline vs. intermediate: p < 0.05) (Fig. 3 and Table S9). Interestingly, Ruminococcus spp. maintained a diminishing trajectory across the feeding study with significant differences between baseline and final time points (baseline: 2.32%, intermediate: 1.63%, final: 1.14%: baseline vs. final: p < 0.05) (Fig. 3 and Table S9).

Although most genera did not shift in response to ε-polylysine–pectin complexes, Ocscillospira transiently increased prior to falling below initial levels (baseline: 3.56%, intermediate: 4.70%, final: 2.44%, intermediate vs. final: p < 0.05). In contrast, Parabacteroides populations were generally inhibited by any of the dietary treatments (baseline: 3.44%, intermediate: 0.79%, final: 0.55%, baseline vs. intermediate: p < 0.05, baseline vs. final: p < 0.05). This is similar to rc4-4 (baseline: 2.82%, intermediate: 0.77%, final: 0.48%, baseline vs. intermediate: p < 0.05, baseline vs. final: p < 0.05). In totality, gut microbiota genera respond to food grade additives at the genus level, in particular ε-polylysine (Fig. 3 and Table S10).

In addition to dietary biopolymers influencing specific taxa, the structural composition of the community had discernable and non-random changes in aggregate. ANOSIM46 with 999 permutations was used to test significant differences between sample groups based on weighted UniFrac.41 As expected, maltodextrin did not significantly shift the murine gut microbial community fed this control in either female or male mice (Fig. 4a, ANOSIM with 999 permutations, p > 0.05). Accordingly, pectin (Fig. 4c, ANOSIM with 999 permutations, p > 0.05) and ε-polylysine–pectin complexes (Fig. 4d, ANOSIM with 999 permutations, p > 0.05) did not promote significant shifts within the community. This is in remarkable contrast to the gut microbiomes that were transiently altered by ε-polylysine alone. As observed with specific taxonomic groups at the phylum and genus levels, the community structure was perturbed at the 5-week point to be subsequently resolved at the final sampling time. This suggests that the population composition was corrected to its initial state through adaptation to the continuously fed biopolymer (Fig. 4b, ANOSIM with 999 permutations, p < 0.05). This was not observed in the ε-polylysine–pectin complex treated mice, indicative of a shielding interaction with the microbial community.

Fig. 4 Principal coordinate analysis (PCoA) plots of microbiome response to maltodextrin (a), ε-polylysine (b), pectin (c) ε-polylysine-pectin complexes (d). PCoA plots based on weighted UniFrac distances. Each sphere represents the pooled communities from 5 mice that were co-housed during each sampling point. The red circle indicates communities extracted from female mice and blue from male mice. The red and blue boundaries are delineated arbitrarily and provided solely to aid visualization of each sex group. Principal coordinate PC1, PC2, and PC3 explain 63.02% of the total variance observed Full size image

ε-polylysine transiently shifts predicted metagenome function

The metagenomic potential inherent to gut microbiomes were inferred by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) based on 16S rRNA phylogenetic data. A total of 6,854,103,780 observations were predicted across 6909 Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology groups (KO) within the 48 gut communities that were profiled by PICRUSt. The resultant data were categorized into 254 functional pathways encompassing all of the 48 communities.

In total, there were 44 pathways that were predicted to significantly shift transiently while mice were consuming ε-polylysine (ANOVA with Bonferroni correction, p < 0.05) (Fig. 5). As with alterations to taxonomic structure, the intermediate samples taken at 5 weeks displayed a significantly different profile relative to baseline and final sampling points. Among these 44 pathways or networks, 42 pathways are involved in bacterial metabolism or are otherwise predicted to mediate host–microbial interactions, with 18 pathways present at 0.5% relative abundance based on the average of the three sampling points (Fig. 5). Of these, eight pathways were predicted to decrease at 5 weeks and return to basal levels at the final sampling. Conversely, 10 predicted pathways exhibited the opposite trend and temporarily increased in abundance. Accordingly, genes and their pathways related to general solute transport (baseline: 7.53%, intermediate: 5.88%, final: 7.68%, p < 0.05) and ABC transporters (baseline: 3.35%, intermediate: 2.76%, final: 3.44%, p < 0.05) were suppressed at the intermediate community state and ultimately rebounded to baseline levels. This suggests that metabolic needs, and/or environmental concentrations of desirable solutes, may be briefly diminished prior to restoration of microbiome structure. Moreover, predicted central metabolic processes involved in carbohydrate and protein metabolisms transition to a reversible state, while the host consumes the ε-polylysine-enriched diet. This is reflected in glycolytic/fermentative pathways (baseline: 1.05%, intermediate: 1.13%, final: 1.08%, p < 0.05), pyruvate metabolism (baseline: 1.01%, intermediate: 1.07%, final: 1.02%, p < 0.05), fructose and mannose metabolisms (baseline: 0.085%, intermediate: 0.099%, final: 0.089%, p < 0.05), and genes associated with oxidative phosphorylation (baseline: 1.12%, intermediate: 1.23%, final: 1.08%, p < 0.05). The latter KO likely involved in anaerobic respiration and transiently enriched in the intermediate time point. In addition to carbohydrate catabolism, pathways associated with nitrogen flux were shifted at 5 weeks including amino sugar and nucleotide sugar metabolisms (baseline: 1.47%, intermediate: 1.60%, final: 1.50%, p < 0.05), and histidine metabolism (baseline: 0.062%, intermediate: 0.067%, final: 0.061%, p < 0.05). We had initially hypothesized that hallmarks of lysine catabolism would be enriched in the predicted metagenomes of mice-fed ε-polylysine, either in the PL or PL-P diet. However, this signal was not observed in the PICRUSt analysis, suggesting that ε-polylysine did not select bacterial populations that increased the lysine catabolic potential.

Fig. 5 Effect of ε-polylysine on predicted metagenome function over time. The relative abundance of intermediate time points show significant difference from baseline and final time points for all pathways (p < 0.05) Full size image

Whereas the predicted metagenomes responded to dietary ε-polylysine, no significant differences were detected in the other three feeding groups. This includes mice-fed ε-polylysine complexed with pectin, providing further support for electrostatic shielding to mitigate the anti-microbial influence of the ε-polylysine. Pectin alone does not alter the community structure or predicted function.

Host sex influences the basal microbome but not the response trajectory

Both male and female mice were observed to determine if biopolymer activity within the microbiome is sex-dependent. Accordingly, several bacterial taxa colonized male and female animals asymmetrically and in a non-random manner. This includes the phylum Verrucomicrobia found at higher concentrations in female mice than males in aggregate (female: 4.96% of 24 samples, male: 2.63% of 24 samples, p < 0.05, multi-way ANOVA) (Table S11). Much of this may be accounted for by differences in Akkermansia populations (female: 4.50%, male: 2.63% p < 0.05). In addition, female mice harbored significantly greater populations of bacterial genera Parabacteroides (female: 2.47%, male: 0.5%, p < 0.05) and Bilophila (female: 2.13%, male: 0.01%, p < 0.05). In contrast, male mice were colonized by greater concentrations of Odoribacter (female: 0%, male: 0.92%, p < 0.05), Turicibacter (female: 0.02%, male: 0.21%, p < 0.05), Clostridium (female: 0.01%, male: 0.10%, p < 0.05), and candidate genus rc4-4 (female: 0.16%, male: 2.46%, p < 0.05) (Table S12).

In addition to taxonomic differences, there are structural differences to the community attributable to animal sex evident in UniFrac distance visualized by principal coordinate analysis (PCoA) in Fig. 6a. Accordingly, gut microbiota observed in female and male mice cluster together by sex, and in a manner more similar within their respective sex than they are to each other (Fig. 6a, ANOSIM with 999 permutations, p < 0.05). In addition, hierarchical clustering of microbiomes and bacterial genera based on their relative abundance exhibited a similar pattern in that bacterial communities within the same sex tend to cluster (Figs. S2 and S3). The average within group phylogenetic diversity of female male is smaller than male mice (Fig. 6b, t-test, p < 0.05), while differences were not observed between female and male mice in the total number of observed OTUs and Chao 1 index (Fig. S4).

Fig. 6 Sex difference in gut microbiome structure (a), and phylogenetic diversity (b). Red dots represents female mice microbiomes and blue dots represent those analyzed from male mice. The PCoA plot is based on weighted UniFrac distances between all OTUs identified in female and male mice. Female mice showed a significant difference from male mice by ANOSIM with 999 permutations analysis (p < 0.05). In b, microbiomes harbored in female mice exhibited a significantly lower PD value than male mice. * p < 0.05 Full size image

In contrast to structural differences between female-hosted and male-hosted microbiomes, only three predicted metagenomic pathways significantly varied. This includes transcription-related operations (female: 0.0092%, male: 0.0051%, p < 0.05), aminoglycoside antibiotic biosynthesis (female: 0.087%, male: 0.080%, p < 0.05) and glycerophospholipid metabolism (female: 0.55%, male: 0.52%, p < 0.05). It is unclear whether these underlie expressed metabolic differences between the two host sexes. Conservation of function despite taxonomic variation is consistent with redundancy in genetic potential previously observed within other microbial communities.46, 47

Despite sex-dependent features, the specific effect of biopolymer treatments remains independent of sex as indicated by PCoA analysis (Fig. 3). Specifically, ε-polylysine transiently alters the murine microbiome at the intermediate sampling point regardless of sex. Whereas pectin or pectin complexed with ε-polylysine does not alter female and male mice harbored microbiota. A similar response path is evident in fluxes at the phylum level, as Bacteriodes and Firmictues representation is temporarily shifted in response to ε-polylysine in both sexes (Fig. S5). In addition, the gut microbiomes derived from both sexes exhibited the same change in Verrucomicrobia when fed pectin (Fig. S5). Furthermore, relative to the maltodextrin-fed group, the ε-polylysine–pectin complexed diet increased Bacteriodetes and diminished the Firmicutes independent of sex. These results indicate that sex-dependent traits (e.g. hormones) did not act synergistically or antagonistically with dietary biopolymers to alter community structure overall, and within major phyla.

Interestingly, dietary biopolymers may alter the genus representation that is somewhat dependent on sex. The relative abundance of Parabacteroides (sex*treatment p < 0.05, multiway ANOVA), Clostridium (sex*treatment p < 0.05, multiway ANOVA), Coprococcus (sex*treatment, p < 0.05, multiway ANOVA), and Bilophila (sex*treatment p < 0.05, multiway ANOVA) exhibited modest dependence on host sex (Fig. S6). In female mice, the Coprococcus content was higher in the pectin group relative to the other three groups in female mice (MD: 0.69%, PL: 0.63%, P: 0.98%, PL+P: 0.65%, MD vs. P: p < 0.05, PL vs. P: p < 0.05, P vs. PL+P: p < 0.05). However, in male mice, Coprococcus OTUs of pectin group were decreased in the microbiomes compared to the other three groups (MD: 0.94%, PL: 0.77%, P: 0.45%, PL+P: 0.78%, MD vs. P: p < 0.05, PL vs. P: p < 0.05, P vs. PL+P: p < 0.05). Also, Bilophila was reduced in female mice-fed ε-polylysine relative to ε-polylysine–pectin complexed diet (MD: 0.51%, PL+P: 1.63%, p < 0.05), whereas the microbiome of male mice did not exhibit this sex-linked population flux. In addition, the interactions of sex, sampling points, and biopolymer influenced the observed relative abundance of the genus Turicibacter (p < 0.05), Clostridium (p < 0.05), Coprococcus (p < 0.05), and the candidate genus rc4-4 (p < 0.05).