1. Microbiology and Infectious Disease

The type VI secretion system governs strain maintenance in a wild mammalian gut microbiome

  1. Beth A Shen
  2. Kyle L Asfahl
  3. Bentley Lim
  4. Savannah K Bertolli
  5. Samuel S Minot
  6. Matthew C Radey
  7. Kelsi M Penewit
  8. Billy Ngo
  9. Stephen J Salipante
  10. Christopher D Johnston
  11. S Brook Peterson
  12. Andrew L Goodman
  13. Joseph D Mougous  Is a corresponding author
  1. Department of Microbiology, University of Washington, United States
  2. Microbial Interactions & Microbiome Center, University of Washington, United States
  3. Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, United States
  4. Bioinformatics Core, Fred Hutchinson Cancer Center, United States
  5. Department of Laboratory Medicine and Pathology, University of Washington, United States
  6. Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center Houston, United States
  7. Howard Hughes Medical Institute, University of Washington, United States
https://doi.org/10.7554/eLife.110200.3
Share this article
Cite this article
  1. Beth A Shen
  2. Kyle L Asfahl
  3. Bentley Lim
  4. Savannah K Bertolli
  5. Samuel S Minot
  6. Matthew C Radey
  7. Kelsi M Penewit
  8. Billy Ngo
  9. Stephen J Salipante
  10. Christopher D Johnston
  11. S Brook Peterson
  12. Andrew L Goodman
  13. Joseph D Mougous
(2026)
The type VI secretion system governs strain maintenance in a wild mammalian gut microbiome
eLife 15:RP110200.
https://doi.org/10.7554/eLife.110200.3
  2. Download BibTeX
  3. Download .RIS

eLife Assessment

This fundamental work significantly advances our understanding of how contact-dependent antagonism enables keystone bacteria to establish and maintain their niche over time. The evidence obtained is convincing, supporting most of the conclusions drawn. This work will be of significant interest to the microbiome research community.

https://doi.org/10.7554/eLife.110200.3.sa0

Abstract

Bacteria inhabiting the mammalian gut coexist in dense communities where contact-dependent antagonism mechanisms are widespread. The type VI secretion system (T6SS) is an interbacterial toxin delivery pathway prevalent among gut Bacteroidales, yet its function in naturally evolved microbiomes remains poorly defined. Here, we examine the role of the T6SS in Bacteroides within a physiologically relevant gut community derived from wild mice (the WildR microbiome). Using newly developed genetic tools and a strategy for functional replacement of strains within the WildR community, we demonstrate that the WildR isolate B. acidifaciens employs a T6SS to antagonize co-resident Bacteroidales. We also show that loss of T6SS function compromises the long-term maintenance of B. acidifaciens in the community but not its initial colonization, establishing the system as a determinant of strain persistence. The T6SS we identified resides on an integrative and conjugative element (ICE). ICE-seq, a targeted sequencing approach, reveals that the T6SS-ICE is distributed among select Bacteroidales and Muribaculaceae species in the WildR microbiome, between which it appears to be recently exchanged. We also show that transfer of the T6SS-ICE to WildR isolate Phocaeicola vulgatus confers transient colonization benefits in mice, but is linked to eventual population decline. Our findings demonstrate that the T6SS can stabilize the presence of specific strains within a complex, co-evolved gut microbiome, yet its value is context dependent and constrained by the ecological and physiological landscape of the host community.

Introduction

Pathways for contact-dependent antagonism between bacteria are prevalent among species residing in the densely colonized mammalian gut (Coyne et al., 2016; Verster et al., 2017; Whitney et al., 2017; García-Bayona and Comstock, 2018). Prominent among these is the bacterial type VI secretion system (T6SS), a mechanism employed by Gram-negative species to deliver toxic effector proteins directly to contacting Gram-negative cells (Hood et al., 2010; Schwarz et al., 2010; Coulthurst, 2019). The T6SS is widely distributed among gut resident species belonging to the Bacteroidota phylum. Over half of Bacteroides spp. isolated from mammalian gut samples encode T6SS genes, and Bacteroidales T6SS effector genes can be found in >60% of individual human metagenomic datasets (Verster et al., 2017; García-Bayona et al., 2021). In vitro experiments suggest the T6SS of Bacteroides spp. can target a broad cross section of gut Bacteroidales, while it does not appear to act on Proteobacteria, the second most abundant group of Gram-negative organisms in the gut (Chatzidaki-Livanis et al., 2016).

A number of model murine gut microbiome studies have sought to provide insight into the role of the Bacteroidales T6SS in the gut. Studies employing gnotobiotic animals co-colonized by pairs of strains demonstrate that T6SS-mediated killing can occur in this environment, and show that targeting in laboratory co-cultures is not necessarily diagnostic of an interaction between strains in the murine intestine (Chatzidaki-Livanis et al., 2016; Wexler et al., 2016; Ross et al., 2019; Robitaille et al., 2023; Sheahan et al., 2024). Gnotobiotic experiments in which more complex mixtures of bacteria (up to 12 species) are co-inoculated and colonization of conventional mice with pairs of Bacteroides strains demonstrate T6SS-mediated antagonism can occur in the context of a more diverse assemblage (Hecht et al., 2016; Wexler et al., 2016; Hill et al., 2024). However, these experiments all suffer from a number of limitations. For instance, the species employed are not native to the mouse gut, and the antagonistic interactions being assessed are between strains that may have never co-inhabited a natural community. Gnotobiotic experiments additionally suffer from the lack of community complexity, while experiments employing conventional animals require antibiotic pre-treatment or large inocula to enable strain engraftment (Hecht et al., 2016; Hill et al., 2024). As a result of these limitations, the physiological and ecological role of the T6SS in mammalian gut microbial communities remains largely unknown.

The limited insights available into the function of the T6SS in native gut microbiomes primarily derive from metagenomic analyses of T6SS gene distribution patterns. T6SS gene clusters in Bacteroidales segregate into three Genetic Architectures (GA) 1–3 based on synteny and evolutionary relatedness; however, each contains conserved structural genes and variable effector and cognate immunity genes (Coyne et al., 2016). GA1 and GA2 loci are encoded on mobile elements, and several studies show they can be horizontally exchanged among Bacteroidales strains co-resident in a microbiome, suggesting a selective benefit to obtaining T6SS effector and immunity genes shared by neighboring species (Coyne et al., 2014; García-Bayona et al., 2021; Sheahan et al., 2024). Further evidence supporting selection for compatibility among the T6SS effector repertoire in co-resident species lies in the finding that effector gene diversity in individual microbiomes is low, in contrast to the high degree of effector diversity observed across metagenomes (Verster et al., 2017). Studies have also revealed that gut Bacteroidales species can encode clusters of T6SS immunity genes unlinked to cognate effectors (Ross et al., 2019). One type of these acquired interbacterial defense (AID) gene clusters, designated rAID for recombinase-associated, are widely distributed across Bacteroidales and have features consistent with active acquisition of additional immunity genes. A subset of genes encoded within AID and rAID systems selectively neutralizes T6SS toxins, indicative of the selective benefit of resisting T6SS-based intoxication in the gut environment. However, other evidence suggests that under certain conditions the cost of producing a T6SS can outweigh its benefit. Studies of the prevalence of T6SS genes among B. fragilis strains reveal they are more common in the microbiomes of infants than in adults (Verster et al., 2017; Robitaille et al., 2023). Furthermore, longitudinal sampling of individual human gut microbiomes has revealed instances in which the B. fragilis T6SS acquires inactivating mutations over time (Robitaille et al., 2023). A comprehensive understanding of the physiological role of the T6SS in gut Bacteroidales has thus yet to emerge.

Experimental testing of the hypotheses regarding T6SS function generated from metagenomic and theoretical studies requires a tractable experimental model substantially more representative of natural gut communities than those that have been employed to date. Here, we study the function of a Bacteroidales T6SS in a natural gut community derived from wild mice and reintroduced into gnotobiotic animals (Rosshart et al., 2017). We show that this community retains a similar composition and level of diversity as the wild mouse community from which it derives, and we demonstrate we can functionally replace members of the community by adding an excess of a mutant strain of interest at the time of community introduction. Using this approach, we demonstrate that the T6SS of B. acidifaciens is important for maintaining this species in the community. We also demonstrate T6SS-mediated targeting between Bacteroides species from the same gut microbiome, and provide evidence that not all Bacteroidales in the community benefit from horizontal acquisition of the T6SS. Together, our findings show that the T6SS can be an important fitness determinant in a native gut community of naturally co-occurring organisms, and that its contribution to competitiveness in the gut varies across species.

Results

The WildR microbiome is stable and similar to wild mice microbiomes despite propagation

The WildR microbial community consists of a complex assemblage of organisms obtained from the pooled ileocecal contents of three wild mice and subsequently introduced to germ-free mice for laboratory propagation (Rosshart et al., 2017). This community diverges substantially from that found in lab-reared mice, with a significantly greater proportion of strains from the Bacteroidota and Pseudomonodata phyla, and a lower proportion of Bacillota and Verrucomicrobia. Additionally, the most abundant OTUs in the WildR population are consistently missing from lab mouse microbiomes. Importantly, by the F4 generation of laboratory propagation in mice, much of the diversity of the WildR was retained, and its composition was indistinguishable from that found in the originally gavaged dams (Rosshart et al., 2017).

To establish whether mice colonized by the WildR community could serve as an appropriate model to study T6SS-mediated interactions in the gut, we first sought to determine whether community composition diverged in the subsequent generations of propagation since its initial study. We obtained ileocecal contents of the F7 WildR generation, introduced these to gnotobiotic mice via oral gavage, then harvested and cryopreserved cecal contents after 14 days of in vivo propagation of the community (Figure 1—figure supplement 1A). To assess the phylogenetic composition of the WildR microbiome after this propagation, we performed short-read metagenomic sequencing on DNA extracted from two stored aliquots and two fecal pellets from mice used to propagate the community, generating a total of 63 Gb of sequence data. Reads were then mapped to a mouse microbiome-specific reference database using Kraken 2 (Wood et al., 2019). This analysis revealed that, like the initial wild mouse microbiome samples and F2 generation, the WildR F7 community is enriched for Bacteroidota and depleted in Bacillota compared to that of lab-reared mice (Figure 1A). Comparison of the relative abundance of the 100 most prevalent genera in the wild donor mice across each community indicated extensive similarities between the wild, WildR F2, and Wild F7 communities (Figure 1B, C, Figure 1—figure supplement 1B). In contrast, lab mouse microbiomes diverge substantially from these communities and lack 24 genera found in each wild-mouse-derived microbiome (Figure 1D, E, Figure 1—figure supplement 1C).

Figure 1 with 1 supplement see all
Download asset Open asset
The WildR murine gut microbiome is stable over multiple generations and harbors an ICE-encoded T6SS.

(A) Phylum-level taxonomic composition of the WildR or lab-derived murine gut microbiome at different generations. Data from the initial wild-caught donor mice (Wild), the WildR F2 generation, and the lab mice-derived community derive from new analysis of previously published sequencing data (Rosshart et al., 2017). WildR F7 data derives from two cryopreserved samples of pooled ilocecal contents (labeled A and B) and fecal pellets from two mice (numbers 1 and 2) used to propagate the community; *indicates technical duplicate samples included in WildR F7 sequencing. (B–E) Comparison of the abundance of the 100 genera most prevalent in wild donor mice between the indicated communities. Points are shaded to show overlapping datapoints (darker shades), and Spearman’s correlation for each comparison is indicated (ρ). ND, not detected. (F) To-scale schematic depicting the Bacteroides acidifaciens T6SS gene cluster. (G) Bioinformatic domain predictions for T6SS effector and immunity proteins of B. acidifaciens. Conserved amino acids are indicated in bold.

Figure 1—source data 1

Order-level abundance (percentage) in WildR microbiome generations based on Kraken2 analysis.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig1-data1-v1.xlsx
Figure 1—source data 2

Genus abundance data in WildR microbiome generations.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig1-data2-v1.xlsx

Two WildR species share a mobile T6SS

Having determined that the overall community composition and diversity found in wild mouse microbiomes is preserved in the WildR F7 generation, we aimed to identify organisms in the community that encode T6SS genes. Toward this end, we used metagenomic and long-read sequencing data from WildR F7 samples to assemble high-quality metagenome associated genomes (MAGs). In parallel, we obtained genome sequences for 15 of the 17 strains readily isolated from the community (Supplementary file 4). In total, we generated nine closed and six draft genomes from isolates and 72 MAGs with an average contig N50 of 946 kb (Supplementary file 1). Collectively, these genomes represent ~50% of the species-level diversity present in the community (Figure 1—figure supplement 1D).

Within our collection of WildR-derived genomes, we identified three encoding T6SS genes. These include genomes from isolates of B. acidifaciens and B. caecimuris and an MAG identified as deriving from Mucispirillum schaedleri. The latter species is a member of the Chrysiogenota phylum (formerly Deferribacteres) for which no genetic tools are available. Thus, with the aim to functionally investigate the role of the T6SS using the WildR model, we focused on the more tractable Bacteroides spp. systems. We found that the T6SSs present in the WildR B. acidifaciens and B. caecimuris strains we isolated exhibit the GA1 architecture and are nearly identical across the gene cluster (Figure 1F). Like GA1 systems identified in other species, the T6SS appears to be encoded on an integrative and conjugative element (ICE) (Coyne et al., 2016). The ICE encompasses a 115-kb region, includes genes coding for DNA transfer and assorted other functions, and is identical between the genomes except for a one base-pair deletion within a predicted effector of the B. caecimuris GA1 cluster (Figure 1—figure supplement 1E). This degree of similarity is consistent with recent exchange of the element between the species; previous studies of human microbiome isolates found that GA1 elements from strains co-resident in the same individual share >99% sequence identity, while those of strains isolated from different individuals share 95–98% identity (Coyne et al., 2016; García-Bayona et al., 2021). Interestingly, the T6SS we found in B. acidifaciens and B. caecimuris shares only 82–83% identity with previously identified GA1 systems found in human isolates, suggesting the ICE is not being frequently exchanged between human and murine-adapted Bacteroides species (Supplementary file 2).

Within the B. acidifaciens and B. caecimuris T6SS loci, we identified two candidate secreted effector genes (ACY5BC_08390 and ACY5BC_08440 in B. acidifaciens; Figure 1F, G). The predicted toxins contain N-terminal PAAR and Rhs domains, which are common among T6SS effectors. The C-terminal toxin domains of these proteins share no significant sequence homology or predicted structural similarity with characterized proteins. However, conserved domain analysis and comparison to structural models in the AlphaFold database indicated that both bear features of predicted nuclease toxins. ACY5BC_08390, herein renamed Bae1 (B. acidifaciens effector 1), contains the AHH predicted nuclease domain, while the toxin domain of ACY5BC_08440, renamed Bae2, resembles the enzymatic domain of endonucleases in the GIY-YIG family. Genes conferring immunity to T6SS system toxins are typically small open reading frames encoded immediately downstream of their cognate effector. Indeed, we found a putative immunity gene downstream of bae1 (ACY5BC_08395, renamed bai1); a candidate immunity gene for Bae2 is located just upstream of the toxin gene (ACY5BC_08435, renamed bai2), and encodes a protein domain previously classified as an immunity determinant (Figure 1G). Interestingly, the single base-pair difference between the T6SSs of B. acidifaciens and B. caecimuris occurs within the bae1 gene of B. caecimuris, introducing a likely inactivating frameshift (Figure 1—figure supplement 1E). Therefore, we focused our initial functional studies of the T6SS in the WildR community on B. acidifaciens.

The B. acidifaciens T6SS intoxicates WildR Bacteroidales

As a first step toward understanding the role played by the B. acidifaciens T6SS in WildR-colonized mice, we sought to determine which, if any, members of the community are susceptible to intoxication by this system in vitro. However, these efforts were initially confounded by our inability to genetically manipulate the WildR B. acidifaciens isolate using previously published approaches (García-Bayona and Comstock, 2019; Bencivenga-Barry et al., 2020). We hypothesized that, as in other wild isolates, restriction modification (RM) systems constitute a significant barrier to the introduction of foreign DNA in this strain (Johnston et al., 2019). To circumvent this problem, we applied the previously described RM-silencing SyngenicDNA approach (Johnston et al., 2019). Using single-molecule sequencing, we identified eight distinct methylated motifs in B. acidifaciens (Supplementary file 3), representing a complex RM system barrier within this strain. Elimination of the single methylated motif found in the integrative plasmid pNUB2 enabled us to obtain transconjugants with the plasmid harboring a B. acidifaciens gene of interest (tssC), which was otherwise recalcitrant to transfer (Figure 2—figure supplement 1A). Although conjugation is often considered relatively insensitive to RM barriers, these data indicate that the RM landscape can substantially limit conjugative plasmid transfer in wild Bacteroides (Dimitriu et al., 2024). Thus, we applied this same RM silencing approach to generate a series of improved plasmids for allelic exchange, which were used to successfully inactivate several T6SS effector, immunity, and structural genes from B. acidifaciens.

To confirm that Bae1 and Bae2 are active T6SS effectors, we performed in vitro growth competition assays under contact-promoting conditions using wild-type B. acidifaciens and mutants sensitized to one or both of the toxins by deletion of the predicted immunity determinants. These experiments revealed that co-cultivation with the wild-type strain inhibits the growth of mutants sensitized to Bae1 or Bae2 through immunity gene inactivation (Figure 2A). A strain lacking a functional T6SS (B. acidifaciens ΔtssC) did not inhibit the effector-sensitized strains, indicating both Bae1 and Bae2 are delivered via the T6SS and have the capacity to inhibit target cell growth.

Figure 2 with 1 supplement see all
Download asset Open asset
The B. acidifaciens T6SS intoxicates other WildR Bacteroidales species.

(A) Normalized growth yield (final/initial CFU, mean ± SD) of the indicated strains of B. acidifaciens (recipients) after in vitro growth in competition with B. acidifaciens wild-type or ΔtssC (donors). Data are representative of at least three biological replicates. *p ≤ 0.05 (two-tailed t-test). CFU, colony-forming units; bae, e; bai, i. (B) Mean (± SD) relative fitness of wild-type B. acidifaciens relative to a ΔtssC derivative during in vitro growth competition assays with the indicated species isolated from the WildR community. Data represent three biological replicates. *indicates the T6SS is significantly important for competitiveness (unpaired two-tailed t-test. p < 0.05). (C) Abundance (% reads per kilobase per million) of WildR species in two initial wild-caught donor mice used to establish the WildR (Rosshart et al., 2017). (D) Abundance of B. acidifaciens Δbae1 Δbai1 Δbae2 Δbai2 in mouse fecal samples collected following co-gavage of germ-free mice with this strain and wild-type or T6SS-inactivated (ΔtssC) B. acidifaciens. ND, not detected. *p < 0.05 (mixed-model ANOVA with repeated measures and Šidák’s multiple comparisons tests). (E) Relative abundance (compared to total Bacteroides) of B. caecimuris F5 following co-gavage of germ-free mice with B. acidifaciens wild-type or ΔtssC. *p < 0.05 (two-way ANOVA with repeated measures and Šidák’s multiple comparisons tests). For D and E, n = 6 mice from two independent replicates. Boxplots represent the interquartile range and mean for each condition; whiskers represent minimum and maximum detectable values; points represent individual values.

Figure 2—source data 1

Bacterial population quantification data.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig2-data1-v1.xlsx

Previous studies indicate the Bacteroidales T6SS mediates targeting of other Bacteroidales, but the exploration of targeting beyond this order has been limited to E. coli, which is not intoxicated (Russell et al., 2014; Chatzidaki-Livanis et al., 2016; Wexler et al., 2016). To explore the extent of T6SS-mediated intoxication in our system, we used in vitro competition assays to measure B. acidifaciens T6SS targeting of each of the species we isolated from the WildR community. Like the T6SS of other Bacteroidales, we found that targets of the B. acidifaciens system were restricted to members of the same order (Figure 2B; Russell et al., 2014; Chatzidaki-Livanis et al., 2016; Wexler et al., 2016). Given that the fitness benefit conferred by the T6SS in these experiments was relatively modest (<10-fold), we also generated two additional T6SS inactivated mutants of B. acidifaciens (ΔclpV and ΔtssN). These strains exhibited a similar competitive defect against B. caecimuris F5 and Phocaeicola vulgatus as B. acidifaciens ΔtssC, and the phenotype could be complemented by heterologous expression of the inactivated genes (Figure 2—figure supplement 1B, C). There were also Bacteroidales for which we were unable to observe evidence of targeting by the B. acidifaciens T6SS. As expected, the B. caecimuris strain F12, which carries homologs of bai1 and bai2 within its T6SS gene cluster, is resistant to targeting. With the exception of B. uniformis, the other strains resistant to target are Bacteroidales from outside of the genus Bacteroides. Importantly, examination of the metagenomic data from two of the wild mice used to generate the WildR revealed that B. acidifaciens, and each of the candidate target species we tested were detected in both animals, indicating the interaction patterns we observe are reflective of T6SS targeting between species co-resident within a natural microbiome (Figure 2C). Together, these results demonstrate the potential for T6SS-mediated targeting between members of the same natural gut community.

Previous studies indicate that the range of T6SS-mediated targeting observed for Bacteroides strains during in vitro growth assays does not necessarily predict in vivo interactions (Wexler et al., 2016). Thus, we used co-colonization of gnotobiotic mice assays to evaluate the B. acidifaciens T6SS targeting capacity in the murine gut. As a first test of T6SS activity in this environment, we assessed the ability of B. acidifaciens wild-type or ΔtssC to intoxicate an immunity-deficient target strain (∆bae1∆bai1∆bae2∆bai2). By 14 days after introduction of the strain pairs by co-gavage, we found the immunity-deficient strain was significantly depleted in the presence of wild-type but not T6SS-inactive B. acidifaciens, and decline of the immunity-deficient population continued until the end of the experiment 35 days post-gavage (Figure 2D). We then used this model to evaluate B. acidifaciens T6SS-mediated targeting of two strains we found to be susceptible to intoxication by the system in vitro, B. caecimuris F5 and P. vulgatus. During co-colonization with wild-type B. acidifaciens, in vivo growth of B. caecimuris F5 was largely inhibited, whereas by 28 days post-gavage with B. acidifaciens ΔtssC, this strain became the predominant population in fecal samples (Figure 2E, Figure 2—figure supplement 1D). To our knowledge, these data represent the first demonstration of in vivo T6SS-mediated targeting between Bacteroidales strains derived from the same natural gut microbiome.

In contrast to the dynamics observed during B. acidifaciens–B. caecimuris co-colonization experiments, we found that T6SS inactivation had little impact when B. acidifaciens was introduced to gnotobiotic mice along with P. vulgatus (Figure 2—figure supplement 1E, F). In these experiments, P. vulgatus quickly became the predominant colonizer regardless of the T6SS activity of B. acidifaciens, representing ~80% of the total population by 7 days post-gavage. This overall level of competitiveness of P. vulgatus is consistent with the predominance of this species among Bacteroidales in the WildR community (Figure 2—figure supplement 1G).

A method for modified strain introduction into the WildR

Evaluating the role of the B. acidifaciens T6SS in the context of WildR colonized mice requires a method to introduce mutant strains into the community. Prior studies of strain engraftment indicate that priority effects and competitive exclusion are barriers to introducing a derivative strain to an established microbiome containing the parent or closely related strains (Lee et al., 2013; Maldonado-Gómez et al., 2016; Obadia et al., 2017; Martínez et al., 2018; Segura Munoz et al., 2022). Additionally, previously proposed methods for manipulating microbiomes in situ with antibiotic treatments followed by delivery of a new strain or in situ genetic engineering suffer from the requirement to identify antibiotics or in vivo amenable genetic tools that specifically target a species of interest (Jin et al., 2022; Rubin et al., 2022; Segura Munoz et al., 2022). Given that our method of introducing the WildR community to the murine gut involves oral gavage of the mixed population and its subsequent establishment, we hypothesized that we could circumvent these challenges and facilitate colonization of in vitro modified B. acidifaciens isolates by taking advantage of the natural carrying capacity of the gut microbiome (Lee et al., 2013; Hecht et al., 2016; Segura Munoz et al., 2022). Specifically, we reasoned that the addition of an excess of a B. acidifaciens modified strain to the WildR community during gavage would lead to displacement of the endogenous B. acidifaciens population while maintaining the overall natural composition of the WildR community (Figure 3A).

Figure 3 with 1 supplement see all
Download asset Open asset
Maintenance of B. acidifaciens in the WildR community is mediated by the T6SS.

(A) Schematic of approach to exploit the carrying capacity of the mouse gut to promote modified strain engraftment during WildR microbiome establishment without affecting community structure. Left, design of proof-of-concept experiment to evaluate the effect of increasing the amount of B. acidifaciens relative to the amount of the WildR microbiome during oral gavage. Right, design of experiment to evaluate the importance of the T6SS for B. acidifaciens fitness in the WildR microbiome-colonized mouse gut. Analysis of total (B), or introduced (C, D) B. acidifaciens populations in gavage (day 0) or post-gavage fecal samples from germ-free mice colonized with the WildR and variable levels of B. acidexo. (B) Total abundance of B. acidifaciens calculated from sequencing 16S rRNA genes amplified from DNA extracted from fecal samples. Differences in B. acidifaciens abundance across mice gavaged with different amounts of B. acidexo were not significant (n = 4 mice/sample, mixed-effects analysis). (C) Relative abundance of B. acidexo in the indicated fecal samples compared to total B. acidifaciens as determined by qPCR. (D) Abundance of B. acidexo in the indicated fecal samples as determined by plating for CFU on selective media. (E) Principal coordinate analysis of weighted Unifrac diversity metrics calculated from 16S rRNA gene amplicon sequencing data from feces collected from mice colonized with the WildR and variable amounts of B. acidexo. Quantification of B. acidexo (F, G) or total (H) B. acidifaciens population in gavage (day 0) and post-gavage fecal samples from germ-free mice colonized with the WildR community and 10-fold excess wild-type or ΔtssC B. acidexo. n = 8 mice per strain, across two biological replicates. (F) CFU quantification of B. acidexo and B. acidexo ΔtssC. *p ≤ 0.05 (two-way ANOVA with repeated measures and Šidák’s multiple comparisons test). (G) Abundance of B. acidexo or B. acidexo ΔtssC relative to the total B. acidifaciens population, as determined by qPCR. *p ≤ 0.05 (two-way ANOVA with repeated measures and Šidák’s multiple comparisons test). (H) Total abundance of B. acidifaciens, calculated from 16S rRNA gene amplicon sequencing. Samples from mice colonized by the WildR community alone (no B. acidexo, white bars) are included for comparison. Differences in B. acidifaciens abundance based on B. acidexo genotype were not significant (mixed-model ANOVA test). For panels B–D and F–H, boxplots represent the interquartile range with indicated mean for each condition, whiskers represent maximum and minimum detectable values, and points show values from individual mice.

Figure 3—source data 1

Bacterial population quantification data.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig3-data1-v1.xlsx
Figure 3—source data 2

PCA plot data.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig3-data2-v1.xlsx

To test this hypothesis, we assessed the potential for B. acidifaciens marked with erythromycin resistance (B. acidexo) to replace the endogenous population (B. acidendo) when titrated into the WildR gavage mixture at different levels (Figure 3A). In cryopreserved samples of the F7 WildR community, we determined that B. acidendo is present at ~3 × 104 CFU/ml (see Methods). We then added 1x, 10x, or 100x B. acidexo relative to this population (3 × 104 to 3 × 106 CFU/ml) to aliquots of the reference stocked WildR community and inoculated mice via oral gavage. Supporting our hypothesis that endogenous B. acidifaciens populations represent the carrying capacity for this species in the murine gut microbiome, we found that the addition of 100-fold excess B. acidifaciens in the gavage did not significantly increase the total relative abundance of the species in mice at 7 days post-gavage (Figure 3B). We also observed that at each titration level, we successfully replaced ~80% of the B. acidendo population with the marked strain; this frequency is likely an underestimate due to the detection limit of the qPCR-based method used for distinguishing the strains (Figure 3C). Higher titrations of the marked strain resulted in a trend toward lengthening its persistence in the community, although this effect was not statistically significant (Figure 3D, Figure 3—figure supplement 1A, B). Additionally, β-diversity analyses of 16S rRNA amplicon sequences revealed that B. acidexo addition did not impact overall community composition, regardless of the inoculum level employed (linear mixed effects model P >|z|> 0.05 for all comparisons, Figure 3E). Across all starting inocula, we observed a gradual decline in B. acidexo populations which we hypothesize is attributable to a fitness cost to carrying the erythromycin resistance marker gene.

Long-term maintenance of B. acidifaciens in the WildR community requires the T6SS

With a method in hand for introducing a genetically modified strain into the WildR community, we applied this approach toward dissecting the ecological role of the B. acidifaciens T6SS. Our experiment was designed to test two different possible roles that have been proposed for the T6SS of Bacteroides in the gut microbiome: (1) facilitating niche establishment during initial colonization and (2) population maintenance once stable colonization is achieved (Hecht et al., 2016; Verster et al., 2017; Robitaille et al., 2023). Germ-free mice were co-gavaged with either B. acidexo or B. acidexo ∆tssC and the WildR community (Figure 3A). B. acidexo populations in fecal samples were then monitored over time by plating on selective media, and the proportion of the total B. acidifaciens population represented by B. acidexo was monitored by qPCR. We found that through 14 days post-gavage, population levels of B. acidexo and B. acidexo ∆tssC were indistinguishable (Figure 3F, Figure 3—figure supplement 1C). However, by day 28, B. acidexo ∆tssC was significantly depleted from the community compared to the marked wild-type parent strain. By 56 days post-gavage, we observed a nearly 100-fold difference in the abundance of the two strains in both fecal and cecal content samples (Figure 3—figure supplement 1D). To confirm that inactivation of the T6SS is responsible for the depletion of B. acidexo ∆tssC, and not a secondary site mutation, we sequenced the genomes of the strains employed in the experiment. B. acidexo ∆tssC used in the first replicate of the experiment carried a single synonymous mutation (in cdr) and in the second replicate the strain bore no mutations. Of note, the marked wild-type B. acidexo population also declined over time relative to endogenous B. acidifaciens levels, while the overall abundance of B. acidifaciens in the community remained similar throughout the experiment (Figure 3G, H); we hypothesize that the decline of B. acidexo derives from a fitness cost associated with carrying the erythromycin resistance marker. However, this decline was modest compared to the decrease in abundance of B. acidexo ∆tssC.

To determine which organisms could be the targets of the B. acidifaciens T6SS, we performed 16S rRNA amplicon sequencing on fecal samples from mice colonized by the two B. acidexo strains and parallel control mice colonized with the WildR community alone. This analysis revealed no significant differences between the three communities at any of the time points sampled (Figure 3—figure supplement 1E). One potential explanation for this finding is B. acidifaciens is present at significantly lower abundance in the community than the organism(s) it targets. In this scenario, T6SS-targeting could be required for B. acidifaciens population survival without causing a sufficiently large decrease in the population of the target to be detectable by the relatively low-resolution measurement method we employed. Consistent with this potential explanation for the lack of overall community shift upon inactivation of the B. acidifaciens T6SS, we find that this species is present at 5- to 10-fold lower abundance than five other Bacteroidales species in WildR F7 samples (Figure 2—figure supplement 1G). Together, our results suggest that the T6SS is required for B. acidifaciens population maintenance in the gut, but dispensable for initial colonization.

Distribution of a mobile T6SS in the WildR community

Given the fitness benefit of the T6SS we observed for B. acidifaciens during stable colonization of the mouse gut, and previous observations that T6SS-containing ICE can be present in multiple species in a single microbiome (Coyne et al., 2014; Zhang et al., 2024), we sought to better understand the distribution of the system in the WildR community. To avoid both the biases inherent in screening for the element in cultured isolates and the challenges of assigning repetitive sequences from metagenomic datasets to MAGs, we developed a targeted sequencing-based approach for identifying ICE-carrying strains in DNA extracted directly from WildR-colonized mouse fecal samples. Our method, which we named ICE-seq, is based on techniques used for identifying transposon insertion locations (Gallagher, 2019). In short, we designed primers to specifically amplify and sequence outward from the 5′ and 3′ ends of the ICE to capture the genomic context of the insertion (e.g., ICE junctions; Figure 4—figure supplement 1A). After amplification and sequencing of ICE junctions from fecal pellets collected from four WildR-colonized mice, reads were mapped to a large, dereplicated genome catalog containing the WildR MAGs generated in this study and the comprehensive mouse microbiota genome (CMMG) catalog to identify ICE-containing strains (Gallagher, 2019; Kieser et al., 2022). We assigned a positive identification of an ICE-containing strain based on the presence of reads mapping from either end of the ICE that diverge from a single position on a contig.

Supporting the validity of our approach, we detected ICE insertion within B. acidifaciens and B. caecimuris F12 (Figure 4A). For these and other species, detection of ICE and the proportion of ICE-seq reads each represented varied between mice. For B. acidifaciens and B. caecimuris F12, this appears to reflect their abundance in individual mice; however, we posit that exchange of the ICE on a rapid timescale could explain the additional variability observed. We also found three additional strains harboring the ICE: Muribaculaceae CAG-485 sp002362485, Bacteroides spMGG23559, and Phocaeicola sartorii. In Muribaculaceae CAG-485 sp002362485, we identified four insertion locations for the ICE, suggesting there are multiple populations of this species harboring the element within the community. To our knowledge, T6SS-encoding ICE have not previously been detected in a Muribaculaceae family member. Strikingly, we did not find evidence of ICE insertion in many of the more abundant Bacteroidales species in the community, including P. vulgatus, Bacteroides sp. 910578895, and Parabacteriodes sp. 910577325. These findings suggest that fitness benefits conferred by acquiring the ICE could vary across species.

Figure 4 with 1 supplement see all
Download asset Open asset
P. vulgatus gains a limited fitness benefit from the T6SS-encoding ICE in WildR-colonized mice.

(A) Frequency of mapped ICE junctions deriving from the indicated species as determined by 5′ or 3′ ICE-Seq analysis of DNA extracted from fecal samples collected either 7 or 14 days post-gavage of the WildR into germ-free mice (n = 4). Mice housed in separate or shared cages are indicated. (B) Relative competitive index from in vitro growth competition assays employing P. vulgatus ICE or ICE ΔtssC and recipient strains isolated from the WildR microbiome (Pseudomonadata, gray; Bacteroidota, green). The mean ± SD from three biological replicates is shown. Asterisks indicate recipient species for which the difference in competitive index was statistically significant between donor strains (p < 0.05, unpaired two-tailed t-test). (C) Recovery of P. vulgatus strains containing the indicated versions of the ICE after in vitro growth with B. acidifaciens. The mean ± SD from one biological replicate and its associated technical replicates are shown, which represent results from at least three biological replicates. *p ≤ 0.05 (two-tailed t-test). bae, e; bai, i. (D) Relative abundance of wild-type P. vulgatus in feces collected from mice (n = 4) co-colonized with P. vulgatus ICE or P. vulgatus ICE ΔtssC, as determined by qPCR assays with primers specific for P. vulgatus exo or the parent endogenous strain. Boxplots represent the interquartile range with indicated mean for each condition, whiskers represent minimum and maximum values, points show values from individual mice. *p ≤ 0.05 (two-way ANOVA with repeated measures test and Šidák’s multiple comparisons test). (E) Schematic of experimental design to test the fitness of P. vulexo + T6SS-ICE in the WildR community. (F) Recovery of P. vulexo + ICE (dark blue) or P. vulexo + ICE ΔtssC (light blue) from post-gavage fecal samples of mice co-colonized with the WildR community as depicted in (E). CFUs were determined by plating on selective media (erm). Boxplots represent the interquartile range with indicated mean for each condition, whiskers represent minimum and maximum values, points show values from individual mice. Data in panel F is from two biological replicates with 4 mice per group per replicate (n = 8). *p < 0.05 (two-way ANOVA with repeated measures and Šidák’s multiple comparisons test to compare P. vulgatus ICE and ICE ΔtssC populations), †p < 0.05 (unpaired t-test to compare day 7 and day 56 samples).

Figure 4—source data 1

ICE-seq read mapping quantification.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig4-data1-v1.xlsx
Figure 4—source data 2

Bacterial population quantification data.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig4-data2-v1.xlsx
Figure 4—source data 3

PCA plot data.

https://cdn.elifesciences.org/articles/110200/elife-110200-fig4-data3-v1.xlsx

Acquisition of a T6SS-encoding ICE transiently benefits P. vulgatus

Our finding that the ICE harboring a GA1 T6SS is shared by multiple Bacteroidales species in the WildR community suggests that it can be exchanged among community members. However, we also found that many WildR Bacteroidales species do not contain the element, suggesting the fitness benefit it confers may be species-specific, or that barriers exist that prevent its transmission to certain strains. To gain insight into the mechanisms governing ICE distribution, we focused on P. vulgatus, a prominent member of the WildR community which our ICE-seq analysis indicates does not naturally harbor the element (Figure 4A). Using in vitro conjugation assays with B. acidifaciens in which we introduced a chloramphenicol resistance cassette to the ICE, we were able to obtain integrants of the wild-type ICE and mutant derivatives in P. vulgatus (Figure 4—figure supplement 1B). Sequencing revealed the ICE inserts at multiple locations in this strain characterized by a degenerate, AT-rich sequence (Figure 4—figure supplement 1C). These findings suggest that barriers to horizontal gene transfer are unlikely to explain the lack of acquisition of the element by P. vulgatus in the context of the WildR.

Having obtained P. vulgatus strains carrying the ICE, we next asked whether the transferred T6SS is functional in this context. Surprisingly, we found that P. vulgatus carrying the element is able to use the ICE-encoded T6SS to robustly antagonize a range of Bacteroidales strains isolated from the WildR, including the parent strain lacking the ICE (Figure 4B). We also found that acquisition of the ICE by P. vulgatus enabled this strain to resist antagonism by B. acidifaciens as a result of acquiring the immunity genes bai1 and bai2 (Figure 4C).

While our in vitro experiments suggest multiple potential fitness benefits for P. vulgatus of acquiring the ICE, the fact that we fail to detect the element in this species in WildR-colonized mice suggests it incurs a fitness cost under in situ conditions not captured by our in vitro assays. To evaluate this possibility, we co-gavaged germ-free mice with wild-type P. vulgatus and derivatives marked with an erythromycin resistance cassette integrated at a neutral site and carrying the intact ICE, or a version of the ICE in which the T6SS is inactivated (ICE ΔtssC). Strikingly, we found that despite their 10-fold excess in the gavage sample, each ICE-containing strain was eventually supplanted by the wild-type parent (Figure 4D). Replacement occurred more rapidly when the T6SS on the ICE was inactivated, indicating that T6SS-mediated targeting of the parent strain likely occurred, but was insufficient to compensate for the competitive disadvantage incurred from acquisition of the element.

We next examined the persistence dynamics of P. vulgatus of carrying the ICE in the context of the WildR-colonized mouse intestine. Employing the same carrying capacity-mediated approach for strain engraft we developed with B. acidifaciens, we colonized mice with the WildR community and P. vulgatus strains carrying the wild-type or ΔtssC ICE (Figure 4E). Up to 3 weeks post-gavage, P. vulgatus carrying the wild-type ICE colonized to higher levels than P. vulgatus ICE ΔtssC, and dominated endogenous P. vulgatus populations (Figure 4F, Figure 4—figure supplement 1D). This result suggests that T6SS activity provides an advantage to P. vulgatus early in the establishment of the gut community. However, by the conclusion of the experiment, the abundance of P. vulgatus ICE declined significantly, with a concomitant rise in endogenous P. vulgatus populations (Figure 4F, Figure 4—figure supplement 1D). This contrasts with our findings using germ-free mice co-colonized with endogenous P. vulgatus and P. vulgatus ICE, in which we observed a cost to carrying the ICE at early time points (Figure 4D). We speculate that in the context of the WildR, the competition from the increased diversity of species exerts greater selection for antagonistic capacity. The extent of T6SS-mediated antagonism by P. vulgatus carrying the ICE is supported by analysis of the overall community structure. In fecal samples collected 14–21 days post-gavage, when P. vulgatus ICE and ICE ΔtssC abundance differs, we observe a significant degree of variation between the two communities (Figure 4—figure supplement 1E). At later time points, the communities of mice colonized by the two strains were less distinct, although they remained significantly divergent in one replicate.

The transient nature of the fitness benefit conferred to P. vulgatus by T6SS activity in WildR-colonized mice contrasts with the long-term benefit to T6SS activity we observed for B. acidifaciens (Figure 3E). Given that ICE acquisition by P. vulgatus would likely occur after community establishment – a state in which our data suggest the element does not provide a lasting benefit to P. vulgatus – these results offer an explanation for the lack of ICE in this species. Interestingly, we found that while P. vulgatus ICE ΔtssC was initially less able to colonize mice in the context of the WildR community than P. vulgatus carrying an active T6SS, this strain persisted at similar population levels in a subset of mice throughout the duration of the experiment (Figure 4F). This result was unexpected, given that P. vulgatus ICE ΔtssC was rapidly displaced by the endogenous P. vulgatus strain in pairwise gnotobiotic mouse colonization experiments (Figure 4D). This finding suggests that in the context of the WildR, functions encoded on the ICE beyond toxin delivery by the T6SS provide a benefit to P. vulgatus. Of note, P. vulgatus ICE ΔtssC carries the intact immunity genes and therefore retains the capacity to resist intoxication by Bae1 and Bae2 (Figure 4C); these may contribute to the fitness benefit of the element in the presence of the WildR, where these toxins could be delivered by other T6SS-ICE encoding strains.

Discussion

In the stable mammalian gut microbiome, where individual strains can persist throughout the lifetime of an individual, the role of interbacterial antagonism pathways is not well understood. Modeling-based studies suggest that antagonistic relationships between community members can be stabilizing to the community as a whole, but how these pathways are employed in an established community and the degree to which active targeting occurs between community members in this setting is unexplored (Coyte et al., 2015; Coyte and Rakoff-Nahoum, 2019). Here, we show that an active T6SS is required for persistence of the mouse commensal B. acidifaciens in a natural murine gut community. To our knowledge, our results represent the first evidence of T6SS-mediated targeting between naturally co-resident gut species. The species targeted by the B. acidifaciens T6SS in vivo could not be confidently ascertained by the approach we employed, likely because this strain represents a small fraction of the community and its antagonistic activity did not detectably affect other populations. However, in vitro experiments demonstrate that other Bacteroidales species from the same community are effectively targeted by the T6SS of this organism. We postulate that B. acidifaciens relies on T6SS-mediated antagonism to prevent displacement by competing Bacteroides. This model for the role of the T6SS in gut Bacteroidales is consistent with metagenomic analyses showing that in adult human gut microbiomes, B. fragilis is most likely to carry the T6SS if the overall prevalence of Bacteroides species is high (Verster et al., 2017; Robitaille et al., 2023). The lytic nature of T6SS-mediated killing could also contribute to the adaptive benefit of the system for Bacteroidales species by releasing nutrients from targeted organisms (Borgeaud et al., 2015; Stubbusch et al., 2025).

Under our experimental conditions, the T6SS of B. acidifaciens appears to be dispensable for initial colonization of the murine gut. This result was unexpected, as the T6SS is more prevalent in human infant gut microbiomes than in adults, suggesting that T6SS-mediated competition between Bacteroides is important during microbiome establishment (Verster et al., 2017; Robitaille et al., 2023). The colonization dynamics associated with WildR introduction to adult animals differ from the natural process of gut microbiome development. Modifications to our carrying capacity-driven approach to strain engraftment will be needed to establish a model that more faithfully replicates the early stages of natural gut microbiome establishment. Additionally, our experiments did not address the role of the T6SS in resilience following disturbance, nor in preventing strain invasion, both of which are questions that should be amenable to future studies employing the WildR model.

A feature shared by the widely distributed GA1 and GA2 T6SSs is their placement within an ICE (Coyne et al., 2016). Previous studies show these can be exchanged between species within the gut of an individual human or mouse, suggesting selection for compatibility among the effector repertoires they encode (Coyne et al., 2014; García-Bayona et al., 2021; Sheahan et al., 2024). However, the factors governing the extent to which the ICE-encoded T6SSs spread among co-resident Bacteroides species are not well understood. We show using ICE-seq that an ICE-encoded GA1 T6SS is present in a minority of Bacteroides species within the gut of a natural mouse community. The ICE present in two species, B. acidifaciens and B. caecimuris, shares >99% sequence identity across the element, indicating it was recently exchanged between them. Interestingly, we find that T6SS activity contributes to B. acidifaciens competitiveness toward B. caecimuris during co-colonization of gnotobiotic mice, suggesting these species may occupy a similar niche, and thus be in direct competition in their native habitat. Accordingly, ICE acquisition by one of these species could be expected to exert strong selective pressure for acquisition and retention of the element in the second species, allowing it to resist intoxication by its competitor.

In contrast, we find that P. vulgatus has not acquired the T6SS-encoding ICE in the WildR gut community. We show that the T6SS is active in this species, and it can promote initial gut colonization by P. vulgatus. However, during stable gut colonization, the fitness cost of harboring the element appears to outweigh its benefit. One potential explanation for these results is that P. vulgatus relies on mechanisms other than T6SS-mediated antagonism to maintain its niche in the gut. An alternative possibility is that the fitness cost incurred by T6SS expression in P. vulgatus is higher than in species that maintain the element, such as B. caecimuris and B. acidifaciens. In support of this, we observed that T6SS activity provided up to a 100-fold competitive advantage over 2 days to P. vulgatus during growth in competition with WildR Bacteroidales isolates, whereas in B. acidifaciens, the degree of T6SS-dependent competitiveness was considerably more modest (up to fivefold). This difference suggests that P. vulgatus may lack a regulator that modulates the activity of the T6SS in B. acidifaciens, thus increasing the cost of producing the system in this species. This observation is in-line with a proposal by Comstock and colleagues that dysregulation is a factor limiting GA1 and GA2 mobility within communities (García-Bayona et al., 2021). Whether other factors, such as the functions encoded by non-T6SS genes on the ICE, contribute to the differences in the fitness costs and benefits conferred by ICE acquisition across species remains to be determined.

Our finding that the T6SS of a gut Bacteroides species is important for stable colonization of its native habitat expands the diversity of demonstrated benefits to T6SSs in natural environments. In both the midgut of honeybees and the light organ of bobtail squid, the T6SS appears to be primarily important for intraspecies competition (Speare et al., 2018; Motta et al., 2024). Strains of the squid symbiont Vibrio fischeri encoding a T6SS exclude T6SS-deficient competitors from the light organ crypts they colonize (Speare et al., 2018). Similarly, T6SS-encoding honeybee gut resident Snodgrassella alvi excludes T6SS-deficient strains from bee gut colonization (Motta et al., 2024). In contrast, the T6SS of Pseudomonas species appears to be important for colonization of soil and the plant roots, and one study found that T6SS activity of P. protegens affected overall community composition in the tomato rhizosphere (Durán et al., 2021; Vázquez-Arias et al., 2025). Additional studies across more habitats and species will serve to build a complete picture of the ecological and evolutionary factors that have led to the dissemination of the T6SS across such a wide diversity of species.

A key challenge facing the field of microbiome research is how to investigate gut microbe functions of interest in a physiologically relevant context that recapitulates the complexity of native gut communities. In this study, we have developed a number of resources and methods to facilitate the use of WildR-colonized mice as a model microbiome composed of co-evolved species native to the murine gut environment. We have isolated 16 species from the community and obtained genomes representing 55% of the phylogenetic diversity of the community. Our finding that the carrying capacity of the WildR community can be exploited to facilitate functional replacement of endogenous strains with modified derivatives is a generalizable method that can be used to study the role of the T6SS in other organisms, such as M. schaedleri, or to address unrelated questions pertaining to other aspects of gut microbiome biology. These resources and methods should further encourage adoption of the WildR community as a valuable tool for advancing mechanistic gut microbiome research.

Materials and methods

Strains and culture conditions

Request a detailed protocol

Strains employed in this study are listed in the Key Resource Table. E. coli strains employed include E. coli EC100D pir+ (for cloning), and E. coli S17-1 λpir and E. coli S17-1 λpir +RK231 (for conjugation into Bacteroidales sp.). E. coli was grown aerobically at 37°C in LB. Other bacterial strains employed in this study were isolated from the WildR community as described below. Isolates and their culture conditions are listed in Supplementary file 4. A hard-sided anaerobic workstation (Don Whitley Scientific) containing 10% CO2, 10% H2, and 80% N2 was used for all anaerobic microbiology procedures. If required, antibiotics were supplemented at the following concentrations: 25 µg erythromycin (erm)/ml, 200 µg gentamicin (gent)/ml, 25 µg chloramphenicol (cm)/ml, and 100 ng anhydrotetracycline (aTc)/ml.

Generation of WildR reference stocks

Request a detailed protocol

Cryopreserved stocks of the WildR microbiome were prepared as previously described with modifications as described below (Rosshart et al., 2017). All procedures were approved by the Yale University Institutional Animal Care and Use Committee (IACUC) under protocol #2025-11423. Mice (C57BL/6) were originally purchased from Jackson Laboratory and bred in-house to generate experimental cohorts. Male and female 6- to 8-week-old mice were housed in singles or pairs in flexible plastic gnotobiotic isolators with a 12-hr light/dark cycle. Mice were provided standard chow (5K67 LabDiet; Purina) and water ad libitum. Frozen ileo-cecal contents from mice colonized with the F6 generation of the WildR microbiome originally published by Rosshart et al. were obtained from Taconic Biosciences (https://www.taconic.com/services/microbiome/wild-mouse-microbiome; Rosshart et al., 2017). To propagate this community, six germ-free C57BL6 mice were inoculated with the WildR microbiome by oral gavage (100 µl/mouse) on two consecutive days. Fecal samples were collected 14 days after gavage. After 14 days post-gavage, fecal samples were collected for downstream characterization, mice were euthanized and transferred to an anaerobic chamber. The contents of the ileum, cecum, and colon (gut) were collected and pooled from each mouse. Pooled gut contents were diluted in pre-reduced, sterile PBS-C (PBS pH 7.4 with 1% cysteine) at 15 ml/g gut contents before passing through a 70-µm cell strainer. Material was then diluted in an equal volume of storage buffer (PBS-C with 40% glycerol final concentration), aliquoted into Wheaton vials to maintain an anaerobic environment, and stored at –80°C.

Metagenomic sequencing of the WildR community

Request a detailed protocol

For shotgun sequencing on the Illumina platform, genomic DNA was extracted from two aliquots of the propagated, cryopreserved WildR stock (~250 mg of pelleted cells) and fecal pellets (~50 mg) from two of the six mice inoculated with the Taconic WildR material using the MoBio PowerFecal DNA Isolation kit (catalog #12830-50, MoBio Laboratories, California, USA). Sequencing libraries were prepared using an in-house protocol (Salipante et al., 2014) and sequenced on the Illumina NextSeq using the NextSeq 500/550 Highoutput kit v2.5 300 cycles (Cat # 20024908). Samples were processed in technical duplicates to correct for PCR errors. Raw reads have been deposited with links to BioProject PRJNA1367654 in the NCBI database.

For long-read sequencing (Oxford Nanopore MinION), high-molecular weight (HMW) gDNA was extracted from ~500 µl of the WildR cryopreserved stock using the QIAGEN Genomic-tip 20/G (Cat#13323) following the protocol for bacterial DNA extraction, except 5 µl of QIAGEN lytic enzyme (catalog #158928) and 10 µl of MetaPolyzme (Millipore Sigma MAC4L-5MG resuspended in 750 µl of water) were added instead of lysosome for more efficient enzymatic lysis of diverse bacteria in the community (Maghini et al., 2021). HMW DNA was then cleaned and concentrated with an isopropanol precipitation, as described, and eluted in 100 µl of water, as previously described (Maghini et al., 2021). DNA was incubated at 55°C for 1 hr before placing it at 4°C for 3 days to increase resuspension of HMW gDNA fragments. Quality and quantity of HMW gDNA were assessed by NanoDrop UV-Vis spectroscopy and Qubit dsDNA HS fluorimetry assay (Cat# Q33231), respectively, and the presence of fragments >10 kb was confirmed by agarose gel electrophoresis. Libraries for sequencing using the Oxford Nanopore MinION were prepared using the Oxford Nanopore SQK-LSK110 kit and 902 ng of WildR HMW gDNA as the starting material. The sequencing library was loaded onto an R9.4.1 SpotON flow cell and run for 74 hr on the Mk1C until ~50 pores remained. The run resulted in 22 Gb of sequencing data from 8.6 million reads, with an N50 of 5.3 kb. Raw reads have been deposited with links to BioProject PRJNA1367654 in the NCBI database.

Taxonomic classification of WildR-derived metagenomic sequences

Request a detailed protocol

Metagenomic reads, generated from Illumina sequencing of either WildR reference stocks or fecal samples from mice 14 days post-gavage with cecal contents from Taconic, were cleaned to remove adapter sequences using Trimmomatic (v0.39) (Bolger et al., 2014) and any reads mapping to the mouse (Mus musculus) genome (RefSeq GCF_000001635.27) using bowtie2 (Langmead and Salzberg, 2012). Taxonomic classification of each read was performed using a publicly available custom Kraken2-Bracken Snakemake pipeline based on the CMMG catalog (Lu et al., 2017; Wood et al., 2019; Kieser et al., 2022; Kieser, 2026; https://github.com/SilasK/Krak). To ensure high-fidelity alignment, the pipeline was modified to include a confidence of 0.51 in the Kraken2 command, and a threshold of 1000 reads per sample was applied to the Bracken analysis. The same classification pipeline was applied to metagenomic sequencing data from other WildR generations and lab mice previously published by Rosshart and colleagues (Rosshart et al., 2017). Classifications were condensed at the order and genus levels for downstream analyses.

Metagenome assembly

Request a detailed protocol

WildR metagenome-assembled genomes (MAGs) were generated from Illumina and MinION reads using the MUFFIN 1.0.6 pipeline (Van Damme et al., 2021; Van Damme et al., 2025; https://github.com/RVanDamme/MUFFIN). Briefly, short and long reads were filtered for high-quality before performing hybrid assembly with MetaFlye (version 2.7; Kolmogorov, 2020; https://github.com/mikolmogorov/Flye). Instead of the default polishing step using Pilon, we modified the MUFFIN pipeline to reduce error by using Polypolish for short read polishing of our assemblies (Wick and Holt, 2022; Wick et al., 2026; https://github.com/rrwick/Polypolish). Binning was performed with Concot (version 1.1.0) (Alneberg et al., 2014), Metabat2 (version 2.13) (Kang et al., 2019), and Maxbin2 (version 2.2.7) (Wu, 2020; https://sourceforge.net/projects/maxbin2/), and refined by metawrap (version 1.2.2) (Uritskiy et al., 2018). Hybrid reassembly was then performed with Unicycler (version 0.4.7) (Wick et al., 2017). Bin quality was determined using CheckM (version 1.0.13) (Parks et al., 2015), and taxonomic classification was performed with GTDB-tk (version 2.1.0) (Chaumeil et al., 2019). Finally, all genomes were annotated with Prokka (version 1.12) (Seemann, 2014). The assembly details and quality for each MAG are listed in Supplementary file 1. MAG sequences are available at https://doi.org/10.5281/zenodo.17716312.

WildR isolate collection and identification

Request a detailed protocol

Media used for cultivation of isolates from the WildR community include supplemented Brucella-blood agar [BBL Brucella broth (BD Cat#90000-076), 50 mg hemin/l, 0.5 mg menadione/l, and 5% defibrinated horse blood], Tryptone Yeast Extract Glucose (TYG) Medium (20 g tryptone/l, 10 g yeast extract/l, 5 g glucose/l, 1 g cysteine/L, 71 µM CaCl2, 78 µM MgSO4, 0.3 mM KH2PO4, 0.3 mM K2HPO4, 1.4 mM NaCl, 5 mg hemin/l, and 0.2% NaHCO3) (Bacic and Smith, 2008), BHIS-FBS [Brain heart infusion (BHI) powder supplemented with 5 mg hemin/l, 0.2 mg menadione/l, 0.5 g cysteine/l, and 10% fetal bovine serum], BHIS-blood agar (BHI supplemented with 5 mg hemin/l, 1 g cysteine/l, 0.2% NaHCO3, 5% defibrinated horse blood, and 1.5% agar), Columbia-blood agar [Columbia broth powder (BD #294420) supplemented with 0.5 mg menadione/l and 5% defibrinated horse blood], MRS [MRS broth (BD #288130), supplemented with 1.5% agar if required], YCFAC [Yeast casitone fatty acids with carbohydrates broth (#AS-680) or agar (#AS-675) purchased from Anaerobe Systems], and BG [23.1 g Bryant and Burkey Medium (BB)/l (Sigma-Aldrich #91903) and 12.5 g modified Gifu Anaerobic Medium (mGAM)/l (Himedia Laboratorires #M2079), which is a 70:30 ratio of BB:mGAM] (Javdan et al., 2020). All media was degassed for at least 24 hr before culturing.

Dilutions of the WildR reference stock or fresh fecal pellets collected from WildR-colonized mice resuspended in PBS were plated on anaerobic media and incubated anaerobically at 37°C for 2–4 days. Single colonies were picked and used to inoculate broth cultures or were restruck on fresh plates and incubated at 37°C anaerobically for 2 days. For storage, sterile, pre-reduced 50% glycerol was added to cultures to a final concentration of 25%, and the mixture was stored at –80°C. Cultures were then screened for taxonomic identity by full-length 16S rRNA gene or gyrB gene sequencing (primer sequences provided in the Key Resources Table). Target genes were amplified from ~2 µl of cultured cells resuspended in 20 µl TE (10 mM Tris, pH 8; 1 mM EDTA). PCR products were cleaned up with Exo-SAP-IT (Thermo Fisher, catalog #78201.1.ML) and then sequenced by Sanger sequencing. Resulting reads were trimmed and assigned putative taxonomy using blastn against the 16S ribosomal RNA sequences (Bacteria and Archaea) database (Altschul et al., 1990). After initial screening, representative cultures from each species identified were subjected to an additional round of strain purification by streaking for single colonies, and species identity was reconfirmed by Sanger sequencing of the full-length 16S rRNA gene amplicons. Strains isolated and their growth conditions are listed in Supplementary file 4.

Whole-genome sequencing of WildR isolates

Request a detailed protocol

De novo genome sequencing of WildR isolates was performed using a combination of short (Illumina) and long-read sequencing. High molecular weight gDNA was extracted from Bacteroidales sp. using the QIAGEN genomic tip (20/G) kit following the standard protocol for Gram-negative extraction. The HMW DNA extraction kit from NEB (#T3060) was used for extracting HMW gDNA from L. murinus following the standard input protocol except the lysis buffer contained 5 µl of QIAGEN lytic enzyme (catalog #158928) and 10 µl of metapolyzme (Millipore Sigma MAC4L-5MG resuspended in 750 µl of water). HMW gDNA was extracted from L. reuteri and L. johnsonii using the Promega Wizard HMW DNA Extraction kit (#A2920). For M. intestinale, M. gordoncarteri, S. musculi, and D. freteri, gDNA was extracted with mechanical lysis and column clean up. To lyse cells, 500 µl of PB (QIAGEN), 250 µl 20% SDS, 550 µl of phenol:chloroform:isoamyl alcohol (24:24:1), and ~250 µl of 0.1-mm-zirconia-silica beads were added to ~2 × 109 cells. Cells were then mechanically lysed with bead beating (RT, 1 min at high speed, 2 cycles) (BioSpec). Genomic DNA was further purified using columns from the QIAGEN Blood and Tissue kit (#69504) and washed following the standard protocol. Extraction of genomic DNA from modified B. acidifaciens and P. vulgatus clones for resequencing was performed using the QIAGEN Blood & Tissue kit (#69504) following the protocol for Gram-negative bacteria. For all gDNA extractions, the quality and size of gDNA was assessed by Qubit assays (ThermoFisher Scientific), A260/A280 ratio, and agarose gel electrophoresis before sequencing library preparation.

Libraries for short-read whole-genome sequencing were prepared with the Illumina DNA prep kit (catalog #20018704), multiplexed using barcoded adapters purchased from IDT (IDT for Illumina DN/RNA UD Indexes SetA, catalog #20027213), and sequenced on either the Illumina iSeq or the MiniSeq, which included a 5% PhiX spike-in, to obtain paired-end reads (2 × 150 bp).

To facilitate generation of closed genomes, Bacteroidales and Lactobacillales spp. were also sequenced on the Oxford Nanopore MinION. Libraries for long-read sequencing were prepared using LSK-110 with modifications to include ligation of barcodes (EXP-NBD104) following the protocol described for the LSK-109 kit. Briefly, DNA was repaired following the LSK-110 protocol using NEB buffers. Then, barcodes were ligated using Blunt/TA ligase following steps described for the LSK-109 kit. Finally, after barcode ligation, adapter sequences were ligated as described for LSK-110. The sequencing library was loaded onto a R.9.4.1 SpotON flow cell and run on the Mk1C until ≥200,000 reads were collected for each sample. If more reads were required, the flow cell was washed, and more libraries were loaded.

For Bacteroidales and Lactobacillales spp., genomes were assembled from long reads using Trycycler (v0.5.3, Wick et al., 2021). Briefly, reads were subsampled and assembled with either Flye (v2.9-b1768; Kolmogorov et al., 2019), Miniasm (v0.3-r179)+Minipolish (v0.1.2) (Wick and Holt, 2019), or Raven (v1.8.1; lbcb-sci, 2022; https://github.com/lbcb-sci/raven) before combining similar assemblies to generate a single consensus sequence as described in the Trycycler wiki (Wick, 2025; https://github.com/rrwick/Trycycler/wiki). Assemblies were polished with Illumina reads using Polypolish (version 0.5.0; Wick and Holt, 2022) and Pilon (version 1.24; Walker et al., 2014). For Phocaeicola vulgatus, genomes were assembled using the hybrid assembly feature in Unicycler (version 0.4.8; Wick et al., 2017). Finally, genomes were annotated with Prokka (version 1.14.6; Seemann, 2014). For other species, adapters were removed from reads using BBDuk (version 38.84) in Geneious Prime (2024.0.5) (https://www.geneious.com), and then genomes were assembled with the Geneious assembler. For genomes deriving from modified clones of B. acidifaciens and P. vulgatus, spontaneous mutations were determined by aligning short reads to assembled genomes from the parental strains using BreSeq (Deatherage and Barrick, 2014). Genome and assembly metrics for each isolate genome are listed in Supplementary file 1, and all genomes have been deposited with links to BioProject PRJNA1367654 in the NCBI database.

Determining the abundance of species in the WildR community

Request a detailed protocol

Abundance of species for which we had obtained a genome sequence (MAG or isolated-derived) was assessed by quantifying the frequency of metagenomic sequencing reads mapping to the genome of interest. Cleaned short, metagenomic reads from either wild donor, F2 WildR mice (Rosshart et al., 2017), or F7 WildR cryopreserved stocks were mapped to a catalog containing WildR F7 MAGs and isolate genomes using BWA-MEM (https://arxiv.org/abs/1303.3997), retaining only correctly paired read alignments using samtools (Li et al., 2009). Reads for all contigs in a MAG or isolate genome were summed, and the percentage of reads per kilobase per million reads was calculated. For each sample, the total reads mapping to this catalog was retrieved using samtools flagstat. The same metagenomic reads were also mapped to all genomes in the CMMG catalog (https://ezmeta.unige.ch/CMMG/) using the same BWA-MEM command.

Identification and bioinformatic characterization of an ICE-encoded T6SS in WildR genomes

Request a detailed protocol

To identify T6SS gene clusters present in WildR strains, we first searched for genes annotated to encode T6SS-related functions in the genomes of Bacteroidales isolates from the community. This led to the identification of candidate T6SS gene clusters in strains of B. acidifaciens and B. caecimuris. Blastp searches against the NCBI non-redundant protein sequence database with each of the candidate T6SS genes in the clusters found that each predicted T6SS component shares ≥80% identity with previously characterized T6SS proteins in other Bacteroidales species, and confirmed that the gene clusters contain the complete complement of genes required to constitute a functional T6SSiii (Altschul et al., 1990; Russell et al., 2014; Coyne et al., 2016). Putative effector genes were identified based on proximity of genes to the T6SS structural genes (e.g., VgrG) and the presence of N-terminal domains associated with T6SS effectors (e.g., PAAR). Effector activity of the C-terminal region of candidate effectors (~100 aa) was predicted using CD-Search and Foldseek (Marchler-Bauer et al., 2009; van Kempen et al., 2024). For the latter, positive hits from the AFDB50 database were defined by a probability score of 1. Immunity genes were assigned based on proximity to a putative effector, length (<200 aa), and presence of immunity domains identified by CD-Search.

The boundaries of the 115 kb T6SS-ICE were determined based on loss of 100% identity in a pairwise alignment between the B. acidifaciens and B. caecimuris F12 T6SS neighboring sequences (Geneious). Putative functions were assigned to each gene based on similar blastp hits (>30% identity) and classified according to functions typically encoded in ICEs (Coyne et al., 2014).

B. acidifaciens methylome identification

Request a detailed protocol

For long-read sequencing using Pacific Biosciences (HiFi/SMRT sequencing), HMW genomic DNA from each isolate was extracted as described above for the Oxford Nanopore workflow. PacBio HiFi libraries were prepared using the SMRTbell Express Template Prep Kit v2.0 (Pacific Biosciences) according to the manufacturer’s recommendations for microbial HiFi genome sequencing, starting with 5–10 µg of HMW DNA per sample. Sequencing was performed on a PacBio Sequel II instrument at the Fred Hutchinson Cancer Center, generating circular consensus sequence (CCS) reads. Raw subreads were processed in SMRT Link (v11.0.0.146107), and CCS reads were used as input for the Microbial Assembly workflow, which performs long-read assembly, polishing, and contig finishing. For each genome, assembly statistics, CCS concordance, contiguity, depth of coverage, and base modification metrics were obtained directly from the SMRT Link analysis reports. Methylation analysis was carried out using the Base Modification and Motif Analysis module with default m6A/m4C detection models. Final polished assemblies and methylome calls for all strains (B. acidifaciens, B. caecimuris F12, B. thetaiotaomicron, B. uniformis, P. vulgatus, and P. distasonis) were exported from SMRT Link and used for downstream comparative analysis. Genome assemblies have been deposited with links to BioProject PRJNA1367654 in the NCBI database.

Genetic manipulation of Bacteroides strains

Request a detailed protocol

Standard molecular procedures were employed for creation, maintenance, and transformation of plasmids in E. coli. The primers, plasmids, and strains employed in this study are listed in the Key Resources Table, and synthetic DNA fragments utilized in construct generation are listed in Supplementary file 5. All primers were purchased from Integrated DNA Technologies (IDT), and geneblocks were synthesized by Twist Biosciences. Enzymes such as OneTaq polymerase, restriction enzymes, and Gibson Assembly reagents were purchased from New England Biolabs (NEB). To generate pNBU2-erm-us1311::tssC-singleRMsilent, a two bp change was introduced in the GATATC motif found in the plasmid using quickchange. To generate pLGB13-RMsilent and pNBU2-erm-RMsilent::P5E4, all B. acidifaciens methylation sites were identified in the parent plasmid by sequence homology (eight and four, respectively), and then single base pair mutations were designed to remove specific motifs. Plasmids were assembled from synthesized geneblocks containing mutations and amplified fragments of unmodified regions using Gibson assembly and validated by whole plasmid sequencing (Plasmidsauraus).

Gene knockouts in B. acidifaciens using either pSIE1 or pLGB13 derivatives were generated following previously published protocols with the following modifications (García-Bayona and Comstock, 2019; Bencivenga-Barry et al., 2020). Briefly, plasmids were mobilized from E. coli S17 into B. acidifaciens via overnight anaerobic mating at 37°C where E. coli was mixed with a 10-fold excess of B. acidifaciens. To further improve mating efficiency, E. coli S17 harboring the RK231 helper plasmid was also included in the mating mixture at equal CFU to E. coli S17 harboring the plasmid for allelic exchange (Smith et al., 1992). Merodiploids were isolated by plating on selective media, passaged once in BHIS-FBS without antibiotics to allow for plasmid excision, and plated on Brucella-blood agar supplemented with aTc for counter selection of the plasmid. Resulting colonies were patched onto selective Brucella-blood agar plates to confirm loss of the plasmid, and the gene disruption of interest was confirmed by colony PCR. For select mutants employed in germ-free mouse colonization experiments, we performed whole-genome sequencing using an Illumina MiniSeq to identify second site mutations, as described above. Strains expressing heterologous copies of clpV were generated by cloning clpV and an intrinsic terminator from pWW3855 downstream of the P5E4 promoter in pNBU2-ermG-RMsilent::P5E4 as previously described (Whitaker et al., 2017).

Integration of pNBU2-ermG or derivatives was performed as previously described (Wang et al., 2000; Koropatkin et al., 2008; Whitaker et al., 2017), but with modified mating conditions as indicated above. Resulting transconjugants were selected on Brucella-blood agar supplemented with gentamycin and erythromycin, colony purified to confirm ErmR, and stocked.

Interbacterial transfer of the GA1 T6SS-encoding ICE

Request a detailed protocol

To transfer the T6SS-encoding ICE from B. acidifaciens to P. vulgatus, we modified previously described methods for spontaneous in vitro mobile element transfer (Figure 4—figure supplement 1A; Ross et al., 2019). First, we used allelic exchange as described above to insert a chloramphenicol resistance gene under the control of the constitutive P1 promoter in a neutral site in the ICE in B. acidifaciens. Then, CmR B. acidifaciens cells from overnight cultures were mixed with ErmR P. vulgatus cells at a 10:1 ratio (OD600 6) on Brucella-blood plates. Following 24 hr of anaerobic co-culture growth, cells were harvested, resuspended in PBS, and plated on Brucella-blood supplemented with chloramphenicol and erythromycin to select transconjugants. Resulting transconjugants were colony purified, and whole-genome sequencing was performed using the Illumina platform as described above. Resulting reads that aligned to both the ICE and P. vulgatus genome, determined using minimap2, were used to identify the ICE insertion sites (Li, 2018). Reads generated in this sequencing have been deposited with links to BioProject PRJNA1367654 in the NCBI database.

In vitro bacterial growth competition assays

Request a detailed protocol

For intra- and interspecies growth competition experiments, donor and recipient strains were spread as lawns on plates and incubated anaerobically at 37°C for 24–48 hr. Most Bacteroides sp., Parabacteroides distasonis, and Phocaeicola vulgatus were grown on Brucella-blood agar plates, except for B. sp910578895, which was grown on BHIS-blood agar. Other media such as Columbia-agar (S. musculi, M. intestinale), MRS agar (L. murinus), LB agar (E. fergusonii), and YCFAC (D. freteri, M. gordoncarteri) were used to culture additional recipient species tested (Supplementary file 4). Cells were harvested from plates and resuspended in 1 ml PBS before measuring the OD600 and diluting to OD 20 or OD 0.2 for donor and recipient strains, respectively. Cell dilutions were combined at a 1:1 ratio (100:1 final donor:recipient ratio), 10 µl of the mixture was spotted onto plates, and mixtures were incubated anaerobically at 37°C for 16–20 hr. Most assays were performed on Brucella-blood plates supplemented with 3% agar, except for competitions performed on BHIS-blood with 3% agar (B. sp910578895 and E. gallinarum), Columbia-blood with 3% agar (S. musculi and M. intestinale), or YCFAC (M. gordoncarteri, D. freteri). Growth competitions with strict anaerobes (S. musculi, M. intestinale, M. gordoncarteri, and D. freteri) were performed entirely under anaerobic conditions using pre-reduced media. After incubation, all cells were harvested and resuspended in 1 ml of PBS. Quantification of species abundance at the start and end of each assay was performed by enumerating CFUs or qPCR. CFU enumeration was used to quantify species abundance for intraspecies (recipients, EmR) or interspecies (donors, B. acidifaciens CmR; recipients P. vulgatus, B. uniformis, B. thetaiotaomicron, B. caecimuris F5, B. caecimuris F12, and P. distasonis, EmR or E. gallinarum (BHI-blood, aerobic), L. murinus (MRS, anaerobic), or E. fergusonii (LB, aerobic)) growth competitions. Interspecies growth competitions with strict anaerobes, B. sp910578895, or P. vulgatus donors were quantified by qPCR using strain specific primers (Key Resources Table). For qPCR, genomic DNA from cell pellets of competition mixtures was extracted using either the QIAGEN Blood & Tissue kit following the protocol for extraction from Gram-negative organisms or via mechanical lysis as described above. DNA was quantified via Qubit (Thermo Fisher) and diluted before using as template DNA in qPCR (SsoAdvanced, Bio-Rad). All experiments were performed with technical triplicates for at least three biological replicates.

Gnotobiotic mouse colonization studies

Animal care

Request a detailed protocol

All animal studies were performed in accordance with protocols approved by the University of Washington Institutional Animal Care and Use Committee (IACUC #4038-04). Germ-free Swiss Webster mice were originally obtained from Taconic Biosciences (Tac:SW) and bred in-house in flexible isolators to generate mice for experimental studies. Germ-free 5- to 12-week-old male and female Swiss Webster mice from multiple litters were randomly selected and housed in pairs in single Techniplast cages with a 12-hr light/dark cycle and fed a standard lab diet (Laboratory Autoclavable Rodent Diet 5010, LabDiet). Blinding was not performed. For each experiment, the number of animals per group (n = 4) was selected based on Lemorte power calculations to measure a difference of ~10-fold bacterial abundance with a p < 0.05 at 80% power along with housing and maintenance considerations for gnotobiotic mice. Mouse feces were confirmed to be sterile prior to colonization by PCR with primers targeting the 16S rRNA gene.

Mouse colonization procedures

Request a detailed protocol

Bacterial strains to be employed in germ-free mouse colonization experiments were grown anaerobically on Brucella-blood plates, resuspended in BHI broth, and diluted. For experiments to determine strain competitiveness in a simplified context, pairs of strains were combined at a 100:1 (109:107 CFU, B. acidifaciens: P. vulgatus) or 10:1 ratio (109:108 CFU, all other donor–recipient pairs), as determined by prior calculation of the OD600 to CFU correspondence. This mixture was introduced into germ-free mice via oral gavage (200 µl per mouse).

To colonize mice with the WildR microbiome and a genetically modified WildR isolate (e.g., B. acidexo), we first estimated the approximate abundance of the endogenous isolate (e.g., B. acidendo) in the WildR stocks using a combination of CFU enumeration, qPCR, and 16S rRNA sequencing. The total CFU of Bacteroidales strains from the Bacteroides, Phocaeicola, and Parabacteroides in the WildR reference stocks was determined by plating on Brucella-blood agar supplemented with gentamycin, a condition selective for the order. The abundance of B. acidifaciens relative to total Bacteroidales levels in WildR stocks was then determined using qPCR with species and order-specific primers on DNA extracted from WildR reference stocks, and this measurement was used to estimate the contribution of CFUs from B. acidifaciens to the total Bacteroidales population (~3 × 104 CFU/ml of WildR cryopreserved stocks). An estimate for the abundance of P. vulgatus CFUs in WildR stocks (~3 × 106 CFU/ml) was calculated in a similar manner, except the fraction of total Bacteroidales represented by this strain was determined by counting reads from 16S rRNA gene sequencing of amplicons from WildR reference stock genomic DNA, as described below.

Modified strains to be introduced to mice along with the WildR community were grown and suspended in BHI broth as described above for isolate colonization studies. Suspensions were then diluted to the desired CFU level (~3 × 104, 3 × 105 or 3 × 106 B. acidexo CFU or ~3 × 107 P. vulexo CFU) in 1 ml of the WildR reference stock under anaerobic conditions. After preparation, the mixture was stored in Wheaton crimp top vials to maintain an anaerobic environment and then introduced into germ-free Swiss Webster mice via a single oral gavage (150–200 µl per mouse). For all germ-free mouse colonization experiments, levels of introduced strains in the gavage mixtures were determined by diluting and plating on selective media.

Quantification of bacterial populations in fecal and cecal samples

Request a detailed protocol

Fresh fecal pellets were collected from colonized animals at regular intervals, and cecal contents were collected from euthanized animals at the conclusion of the experiment as described for WildR reference stock generation. To enumerate CFUs of marked strains, fresh fecal pellets or cecal contents (~50–100 mg/sample) were homogenized in PBS using sterile pestles. Insoluble material was removed via gentle centrifugation (500 xg, 30 s), and the resulting supernatant was diluted in PBS. Dilutions were plated on selective media (e.g., Brucella-blood supplemented with erythromycin and gentamicin to isolate B. acidexo from the WildR community) and incubated anaerobically at 37°C. Final CFU counts were normalized to initial fecal weights. Remaining fecal or cecal material from these collections was stored at –80°C for gDNA extraction.

The abundance of modified strains relative to total bacteria present or endogenous populations in WildR-colonized mice was determined by qPCR. Genomic DNA was extracted from thawed fecal pellets or cecal contents (~50–100 mg/sample) by first combining samples with 200 µl of 0.1-mm-diameter zirconia/silica beads (BioSpec Products, Bartlesville, OK), 500 µl of CP Buffer (Omega Biotek, #PDR042), or PB Buffer (QIAGEN), 250 µl of 20% SDS, and 550 µl of phenol:chloroform:isoamyl alcohol (24:24:1) (Thermo Fisher). Microbial cells were mechanically lysed with a bead beater at room temperature (BioSpec Products; instrument on high for 1 min; 2 cycles) and then centrifuged at 10,000 × g for 10 min to separate phases. All of the aqueous phase containing gDNA (~400–500 µl/sample) was applied to E-Z 96 DNA plates (Omega Biotek; #BD96-01) or QIAGEN Blood and Tissue columns and cleaned following the standard protocol. DNA was quantified by fluorimetry (Qubit, Thermo Fisher) and then diluted to ~5 ng/µl in EB (10 mM Tris-HCl pH 8.5; Omega Biotek PDR048). Relative species or strain abundance was determined by qPCR using primers described in the Key Resources Table. All qPCR was performed using a CFX96 instrument (Bio-Rad) and SsoAdvanced Universal SYBR Green Supermix (Bio-Rad).

Community structure analysis by 16S rRNA gene amplicon

Request a detailed protocol

The V3–V4 region of the 16S rRNA gene was amplified from genomic DNA extracted from fecal and cecal samples following the standard Illumina protocol for 16S metagenomic sequencing (Illumina Part # 15044223 Rev. B) with the following modifications. Briefly, purified gDNA was quantified by Qubit, diluted to 5 ng/µl, and amplified using primers 16S_v3v4_fwd_Illumina and 16S_v3v4_rev_Illumina (Key Resources Table) and 2x KAPA HiFi HotStart ReadyMix (Roche). PCR was performed in triplicate to avoid jackpot amplification. Reactions were prepared in a biosafety cabinet to prevent contamination, and each run included no-template controls. Pooled PCR products for each sample were cleaned using AmpureXP beads (Bruker). A second PCR was performed to add sequencing adapters and barcodes (IDT for Illumina UD Indexes Plates A-D) using 2x KAPA HiFi HotStart ReadyMix. Final PCR products were cleaned and normalized with the Sequalprep Normalization Plate kit (Thermo Scientific). The size and quantity of DNA libraries from select samples were confirmed by agarose gel electrophoresis and fluorimetry (Qubit), respectively.

Equal volumes of 16S rRNA libraries prepared from up to 384 samples were pooled and quantified for sequencing. Libraries were denatured, diluted, and combined with PhiX spike-in before sequencing on the MiSeq or NextSeq2000 (300 bp paired reads; dual 10 bp indexes; 10 or 25% PhiX, respectively). Samples were demultiplexed with onboard software for each instrument. All data generated from this sequencing have been deposited with links to BioProject PRJNA1367654 in the NCBI database.

Analysis of 16S rRNA sequencing data was performed using Qiime2 (v2020.11; Bolyen et al., 2019). Primers were trimmed using the qiime cutadapt plugin before using DADA2 for ASV calling and counting to determine the relative abundance of each ASV. Beta diversity metrics (Unifrac) were calculated from rarefied data using the qiime diversity plugin, and statistical tests were performed with the qiime longitudinal plugin. Principal component analysis plots were generated in R using cmdscale. To quantify total B. acidifaciens abundance, we performed a custom taxonomic assignment of ASVs. The top taxonomic hit for each ASV was obtained by a BLAST search of each ASV in the WildR MAG and isolate genome catalog. These new taxonomic assignments were combined with the relative abundance of each ASV calculated from the DADA2 analysis to determine relative frequencies of B. acidifaciens.

ICE-seq library preparation and data analysis

Request a detailed protocol

Genomic DNA was extracted from fecal samples as described above and used to prepare ICE-seq libraries following previously described methods with the modifications described below (Gallagher, 2019; Figure 4—figure supplement 1A). Briefly, DNA was sheared to ~500 bp average size and C-tailed. Sequences outside of the ICE at either the 5′ or 3′ ends of the ICE were specifically amplified using primers annealing within the ICE at either the 5′ or 3′ end (‘ICE junction’) and a C-tailed specific primer (Key Resources Table). After DNA purification, a second round of PCR was performed to amplify the ICE junctions and add adapter and index sequences for sequencing. Samples were pooled, and multiplexed samples were sequenced as 75 bp single-end reads on an Illumina MiniSeq with 30% PhiX DNA spiked in using a custom mix containing three primers for sequencing the 5′, 3′, and PhiX sequences.

Illumina sequencing reads were analyzed using a portion of a previously described custom Python script (Gallagher, 2019). Sequences were filtered for those containing the first 5 bp (ATAAT) or 7 bp (ATTATTG) of the ICE 5′ and 3′ ends, respectively. Then reads were aligned using a BWA aligner to a composite CMMG-WildR catalog, which was dereplicated (at 99% ANI) using dRep (v3.5.0) (Olm et al., 2017; Kieser et al., 2022). Reads per insertion site were tallied, and insertion sites were filtered to include only sites where reads mapped in opposite directions from both ends of the ICE. To calculate the percentage of ICE reads mapping in a sample, the total of mapped reads fitting these criteria was calculated, and the fraction of each insertion site was then determined. The percentage was independently calculated for reads generated from either end of the ICE. Sequencing reads have been deposited with links to BioProject PRJNA1367654 in the NCBI database.

Statistical analysis

Request a detailed protocol

Statistical analysis was performed using GraphPad Prism (version 10.2.3 for Mac OS X, GraphPad Software, Boston, Massachusetts, USA, https://www.graphpad.com) using tests described in the main text and figure legends.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain, strain background (Bacteroides acidifaciens)WR-F2WildR isolate (this study)Genome accession: JBUERP000000000
Strain, strain background (B. caecimuris)WR-F5; F5WildR isolate (this study)Genome accession: JBUERM000000000
Strain, strain background (B. caecimuris)WR-F12; F12WildR isolate (this study)Genome accession: JBUERL000000000
Strain, strain background (B. uniformis)WR-A2WildR isolate (this study)Genome accession: JBUERN000000000
Strain, strain background (B. thetaiotaomicron)WR-F3WildR isolate (this study)Genome accession: JBUERK000000000
Strain, strain background (B. sp910578895)WildR isolate (this study)WildR MAG #bin69
Strain, strain background (Duncaniella freteri)WR-YR29WildR isolate (this study)Genome accession: JBUERU000000000
Strain, strain background (Enterococcus casseliflavus)WR-B2WildR isolate (this study)Genome accession: JBUERQ000000000
Strain, strain background (Escherichia fergusonii)WildR isolate (this study)
Strain, strain background (Lactobacillus johnsonii)WR-F4WildR isolate (this study)Genome accession: JBUPWC000000000
Strain, strain background (Ligilactobacillus murinus)WR-A5WildR isolate (this study)Genome accession: JBUERI000000000
Strain, strain background (Limosilactobacillus reuteri)WR-E9WildR isolate (this study)Genome accession: JBUERJ000000000
Strain, strain background (Muribaculum caecicola)WR-YR7WildR isolate (this study)Genome accession: JBUERR000000000
Strain, strain background (Muribaculum intestinale)WR-C85WildR isolate (this study)Genome accession: JBUERS000000000
Strain, strain background (Parabacteroides distasonis)WR-A11WildR isolate (this study)Genome accession: JBUERO000000000
Strain, strain background (Phocaeicola vulgatus)WR-A6; parentalWildR isolate (this study)Genome accession: JBUPWD000000000
Strain, strain background (Sporofaciens musculi)WR-N50WildR isolate (this study)Genome accession: JBUERT000000000
Strain, strain background (Escherichia coli)EC100D pir+ (plasmid maintenance)PMID: 8125283Genotype: F- mcrA Δ(mrr-hsdRMS-mcrBC) φ80dlacZΔM15 ΔlacX74 recA1 endA1 araD139 Δ(ara, leu)7697 galU galK λ- rpsL (StrR) nupG pir+ (DHRF).
Strain, strain background (E. coli)S17-1 λpir (conjugation)PMID: 6340113Genotype: recA pro hsdR RP4-2-Tc::Mu-Km::Tn7 λ-pir.
Strain, strain background (E. coli)S17-1 λpir + RK231 (conjugation)PMID: 1615064Genotype: E. coli S17 lambda pir with RK231 plasmid, KanR.
Strain, strain background (B. acidifaciens)ErmR; B. acidexo (marked strain with erythromycin resistance, ErmR)This paperGenotype: att1::pNBU2-ermG.
Strain, strain background (B. acidifaciens)∆tssC (inactive T6SS)This paperGenotype: ∆ACY5BC_08310.
Strain, strain background (B. acidifaciens)∆tssC; B. acidexo ∆tssC (ErmR)This paperGenotype: ∆ACY5BC_08310, att1::pNBU2-ermG.
Strain, strain background (B. acidifaciens)∆e1 ∆i1 (ErmR)This paperGenotype: ∆ACY5BC_08390, ∆ACY5BC_08395, att::pNBU2-ermG.
Strain, strain background (B. acidifaciens)∆e2 ∆i2 (ErmR)This paperGenotype: ∆ACY5BC_08435, ∆ACY5BC_08440, att::pNBU2-ermG.
Strain, strain background (B. acidifaciens)∆e1 ∆i1 ∆e2 ∆i2 (ErmR)This paperGenotype: ∆ACY5BC_08390, ∆ACY5BC_08395, ∆ACY5BC_08435, ∆ACY5BC_08440, att::pNBU2-ermG.
Strain, strain background (B. acidifaciens)∆tssN (inactive T6SS)This paperGenotype: ∆ACY5BC_08340.
Strain, strain background (B. acidifaciens)∆clpV (inactive T6SS)This paperGenotype: ∆ACY5BC_08330.
Strain, strain background (B. acidifaciens)∆clpV + pNBU2-ermG::emptyThis paperGenotype: ∆ACY5BC_08330, att::pNBU2-ermG.
Strain, strain background (B. acidifaciens)∆clpV + pNBU2-ermG::P5E4-clpVThis paperGenotype: ∆ACY5BC_08330, att::pNBU2-ermG-P5E4-clpV.
Strain, strain background (B. acidifaciens)CmR (CAT gene located on ICE)This paperGenotype: P1-GH023-CAT-term_intergenic(BA_01751/BA_01752).
Strain, strain background (B. acidifaciens)∆tssC CmR (CAT gene located on ICE)This paperGenotype: ∆ACY5BC_08310, P1-GH023-CAT-term_intergenic(BA_01751/BA_01752).
Strain, strain background (B. acidifaciens)∆e1 ∆i1 ∆e2 ∆i2 CmR (CAT gene located on ICE)This paperGenotype: ∆ACY5BC_08390, ∆ACY5BC_08395, ∆ACY5BC_08435, ∆ACY5BC_08440, P1-GH023-CAT-term_intergenic(BA_01751/BA_01752).
Strain, strain background (B. caecimuris)F5 ErmRThis paperGenotype: att::pNBU2-ermG.
Strain, strain background (B. uniformis)ErmRThis paperGenotype: att::pNBU2-ermG.
Strain, strain background (B. thetaiotaomicron)ErmRThis paperGenotype: att::pNBU2-ermG.
Strain, strain background (B. caecimuris)F12 ErmRThis paperGenotype: att::pNBU2-ermG.
Strain, strain background (P. distasonis)ErmRThis paperGenotype: att::pNBU2-ermG.
Strain, strain background (P. vulgatus)ErmRThis paperGenotype: att2::pNBU2-ermG.
Strain, strain background (P. vulgatus)ICE; P. vulgatus exo + ICEThis paperGenotype: ICE -intergenic(ACZBVK_01235/ACZBVK_01240), ICE genotype[CmR], att2::pNBU2-ermG.
Strain, strain background (P. vulgatus)ICE ΔtssC; P. vulgatus exo + ICE ΔtssCThis paperGenotype: ACZBVK_12250::ICE, ICE genotype[∆ACY5BC_08310, CmR], att2::pNBU2-ermG.
Strain, strain background (P. vulgatus)ErmR + ICE ∆baei1 ∆baei2 CmR; ∆e1 ∆i1 ∆e2 ∆i2This paperGenotype: ICE-intergenic(ACZBVK_12055/ACZBVK_12060), ICE genotype[∆ACY5BC_08390, ∆ACY5BC_08395, ∆ACY5BC_08435, ∆ACY5BC_08440,CmR], att2::pNBU2-ermG.
Strain, strain background (Mus musculus, M/F)Swiss WebsterTaconic BiosciencesTac:SWGerm-free.
Strain, strain background (M. musculus, M/F)C57BL/6Germ-free.
Biological sample (M. musculus)WildR reference microbiome (F6 generation ileo-cecal contents)Taconic Biosciences; https://www.taconic.com/services/microbiome/wild-mouse-microbiome
Recombinant DNA reagentpSIE1PMID: 31712278Suicide vector, allelic exchange in Bacteroides, ErmR, AmpR.
Recombinant DNA reagentpSIE1::∆Ba-tssCThis paperDeletion construct carrying 1 kb flanking regions of ACY5BC_08310 (tssC), ErmR, AmpR.
Recombinant DNA reagentpLGB13PMID: 31409684Suicide vector, allelic exchange in Bacteroides, ErmR, AmpR.
Recombinant DNA reagentpLGB13-RMsilentThis paperSuicide vector with 8 point mutations to remove B. acidifaciens specific methylated motifs and facilitate plasmid transfer.
Recombinant DNA reagentpLGB13-RMsilent::∆Ba-bae1-bai1This paperDeletion construct carrying ~1 kb flanking regions of ACY5BC_08390 and ACY5BC_08395 (effector-immunity pair #1), ErmR, AmpR.
Recombinant DNA reagentpLGB13-RMsilent::∆Ba-bae2-bai2This paperDeletion construct carrying ~1 kb flanking regions of ACY5BC_08435 and ACY5BC_08440 (effector-immunity pair #2), ErmR, AmpR.
Recombinant DNA reagentpLGB13-RMsilent::∆Ba-tssNThis paperDeletion construct carrying ~1 kb flanking regions of ACY5BC_08340 (tssN), ErmR, AmpR.
Recombinant DNA reagentpLGB13-RMsilent::∆Ba-clpVThis paperDeletion construct carrying ~1 kb flanking regions of ACY5BC_08330 (clpV), ErmR, AmpR.
Recombinant DNA reagentpLGB13-RMsilent::Ba-ICE-P1-GH023-CAT-termThis paperInsertion construct carrying ~1 kb flanking regions to integrate P1 promoter, GH023 RBS, CAT gene, and terminator between BA_01751 and BA_01752 (on the ICE), ErmR, AmpR, CmR.
Recombinant DNA reagentpNBU2-ermGPMID: 18611383Integrates into single NBU2 attB site in Bacteroides genomes, ErmR, AmpR.
Recombinant DNA reagentpNBU2-ermG-us1311PMID: 26918244Derivative of pNBU2-ermG containing constitutive promoter (us1311) to drive expression of inserted gene, ErmR, AmpR.
Recombinant DNA reagentpNBU2-ermG-us1311::tssCThis paperPNBU2 integrative vector containing constitutive promoter (us1311) to drive expression of tssC (ACY5BC_08310) from B. acid, ErmR, AmpR.
Recombinant DNA reagentpNBU2-ermG-us1311::tssC_singleRMsilentThis paperDerivative of pNBU2-ermG-us1311::tssC with a two bp mutation in the plasmid to remove a single methylated site (GATATC). Other methylated motifs still exist in the plasmid. ErmR, AmpR.
Recombinant DNA reagentpNBU2-ermG::P5E4PMID: 28431251Integrates into single NBU2 attB site in Bacteroides genomes, contains constitutive promoter and RBS site (P5E4), ErmR, AmpR.
Recombinant DNA reagentpNBU2-ermG-RMsilent::P5E4This paperIntegrative vector with 4 point mutations to remove B. acidifaciens specific methylated motifs and facilitate plasmid transfer, ErmR, AmpR.
Recombinant DNA reagentpNBU2-ermG-RMsilent::P5E4-clpVThis paperIntegration plasmid construct to express clpV from P5E4 promoter sequence, ErmR, AmpR.
Sequence-based reagentgyrB-UP-1PMID: 21948050Species/strain identification primer for initial identification of Bacteroides sp isolated from the WildR.
GAAGTCATCATGACCGTTCTGCAYGCNGGNGGNAARTTYGA
Sequence-based reagentgyrB_UP-2rPMID: 21948050Species/strain identification primer for initial identification of Bacteroides sp isolated from the WildR.
AGCAGGGTACGGATGTGCGAGCCRTCNACRTCNGCRTCNGTCAT
Sequence-based reagentgyrB-UP-1SPMID: 21948050Species/strain identification primer for initial identification of Bacteroides sp isolated from the WildR.
GAAGTCATCATGACCGTTCTGCA
Sequence-based reagent8FPMID: 16672469Species/strain identification primer for strain identification by amplifying entire 16S rRNA gene and sequencing.
AGAGTTTGATCCTGGCTCAG
Sequence-based reagent1391RPMID: 17416689Species/strain identification primer for strain identification by amplifying entire 16S rRNA gene and sequencing.
GACGGGCGGTGWGTRCA
Sequence-based reagent16 S_v3v4_fwd_IlluminaPMID: 22933715Sequencing primer for sequencing V3V4 region of 16S rRNA for bacterial identification in the WildR community.
TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG
Sequence-based reagent16S_v3v4_rev_IlluminaPMID: 22933715Sequencing primer for sequencing V3V4 region of 16S rRNA for bacterial identification in the WildR community.
GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC
Sequence-based reagentICE-3p_1aThis paperSequencing primer for generating sequencing libraries of ICE-genome junctions from the 3' end of the GA1 T6SS ICE.
GGAAATGCACTCCCCAAGACAAGTAAATGA
Sequence-based reagentICE-3p_2This paperSequencing primer for generating sequencing libraries of ICE-genome junctions from the 3' end of the GA1 T6SS ICE.
AATGATACGGCGACCACCGAGATCTACACCATTTTATAATATACTGATTATAAGTGCATTGCGGTGATATTTTTATGACAGTTTTG
Sequence-based reagentICE-3p_seqThis paperSequencing primer for sequencing ICE-genome junctions from the 3' end of the GA1 T6SS ICE.
AAGTGCATTGCGGTGATATTTTTATGACAGTTTTG
Sequence-based reagentICE-5p_1bThis paperSequencing primer for generating sequencing libraries of ICE-genome junctions from the 5' end of the GA1 T6SS ICE.
CTGAAAACAACGGAAAGAAACAACAACCAC
Sequence-based reagentICE-5p_2*This paperSequencing primer for generating sequencing libraries of ICE-genome junctions from the 5' end of the GA1 T6SS ICE.
AATGATACGGCGACCACCGAGATCTACACGTTTGTTTATATTTTCCTGTATCTTGTTTTCATTTTACACACATCTATAAG
Sequence-based reagentICE-5p_SEQThis paperSequencing primer for sequencing ICE-genome junctions from the 5' end of the GA1 T6SS ICE.
TCCTGTATCTTGTTTTCATTTTACACACATCTATAAG
Sequence-based reagentolj376_1PMID: 30798550Sequencing primer for generating sequencing libraries of ICE-genome junctions. Primer amplifies from the polyC-tail added to sheared gDNA in conjunction with either ICE-3p_1a or ICE-5p_1b.
GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTGGGGGGGGGGGGGGGG
Sequence-based reagentTdT_i8_U7001PMID: 30798550Indexing primer #1 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-3p_2.
CAAGCAGAAGACGGCATACGAGATCGCTCAGTTCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentTdT_i8_U7002PMID: 30798550Indexing primer #1 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-3p_2.
CAAGCAGAAGACGGCATACGAGATTATCTGACCTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentTdT_i8_U7003PMID: 30798550Indexing primer #1 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-3p_2.
CAAGCAGAAGACGGCATACGAGATATATGAGACGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentTdT_i8_U7004PMID: 30798550Indexing primer #1 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-3p_2.
CAAGCAGAAGACGGCATACGAGATCTTATGGAATGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentTdT_i8_U7011PMID: 30798550Indexing primer #5 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-5p_2.
CAAGCAGAAGACGGCATACGAGATGAACATACGGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentTdT_i8_U7012PMID: 30798550Indexing primer #5 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-5p_2.
CAAGCAGAAGACGGCATACGAGATCCTATGACTCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentTdT_i8_U7013PMID: 30798550Indexing primer #5 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-5p_2.
CAAGCAGAAGACGGCATACGAGATTAATGGCAAGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentTdT_i8_U7014PMID: 30798550Indexing primer #5 for generating sequencing libraries of ICE-genome junctions. Index sequence modified to contain 10 bases compared to primers described in original publication. Use with ICE-5p_2.
CAAGCAGAAGACGGCATACGAGATGTGCCGCTTCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT
Sequence-based reagentRead1_SeqPMID: 30798550Sequencing primer: Sequencing primer to amplify PhiX reads from ICE-seq sample run.
ACACTCTTTCCCTACACGACGCTCTTCCGATCT
Sequence-based reagentPVirpA-qPCR-FThis paperqPCR primer to quantify P. vulgatus wildR isolate by qPCR.
CATGGTGGGAAAAGAGTGAAGC
Sequence-based reagentPVirpA-qPCR-RThis paperqPCR primer to quantify P. vulgatus wildR isolate by qPCR.
CTGTAATCCGTCCAAGTCCAAAG
Sequence-based reagentBCF5DessicResist-qPCR-FThis paperqPCR primer to quantify B. caecimuris F5 wildR isolate by qPCR.
CTAACGGAGGTATATCAGTAGGCC
Sequence-based reagentBCF5DessicResist-qPCR-RThis paperqPCR primer to quantify B. caecimuris F5 wildR isolate by qPCR.
TTTCCCTTGCCCAGATTAGGAG
Sequence-based reagentBApehX-qPCR-FThis paperqPCR primer to quantify B. acidifaciens wildR isolate by qPCR in in vitro competitions.
CTTCGTGACCCTGTATTTTGGAAC
Sequence-based reagentBApehX-qPCR-RThis paperqPCR primer to quantify B. acidifaciens wildR isolate by qPCR in in vitro competitions.
AATTCCGTCCGTATTAGTCCAGTC
Sequence-based reagentBUamyX-qPCR-FThis paper.qPCR primer to quantify B. uniformis wildR isolate by qPCR.
ATCTACGTGACTTTACCGCCTC
Sequence-based reagentBUamyX-qPCR-RThis paperqPCR primer to quantify B. uniformis wildR isolate by qPCR.
TATACCCCCAACTGTCGTTTCC
Sequence-based reagentBTphoA-qPCR-FThis paperqPCR primer to quantify B. thetaiotaomicron wildR isolate by qPCR.
TATGGAGTAGACTTGGTGCTTCAG
Sequence-based reagentBTphoA-qPCR-RThis paperqPCR primer to quantify B. thetaiotaomicron wildR isolate by qPCR.
GAAAGACAAACGGTAACTCTTCGG
Sequence-based reagentPBDnanM-qPCR-FThis paperqPCR primer to quantify P. distasonis wildR isolate by qPCR.
CACGTCCGATAATTCTTGGAGC
Sequence-based reagentPBDnanM-qPCR-RThis paperqPCR primer to quantify P. distasonis wildR isolate by qPCR.
GTTACCTCTACGTCCACCTATGAG
Sequence-based reagentPv_att2_qPCR_FThis paperqPCR primer to quantify unmarked P. vulgatus when present with erm-marked P. vulgatus strain by qPCR.
TTTGCAATTCTTTCCAGCGG
Sequence-based reagentPv_att2_qPCR_RThis paperqPCR primer to quantify unmarked P. vulgatus when present with erm-marked P. vulgatus strain by qPCR.
GTGGCAGAGTGGTCGATTGC
Sequence-based reagentermG-qPCR-FThis paperqPCR primer to detect strain marked with pNBU2-erm by qPCR.
AACATCTTTGAAATAGGTGCAGGG
Sequence-based reagentermG-qPCR-RThis paperqPCR primer to detect strain marked with pNBU2-erm by qPCR.
TCTATCGCCGTTACAAAATTACATC
Sequence-based reagentrpsR-bacteroides-qPCR-FThis paperqPCR primer to quantify total Bacteroides, Parabacteroides, and Phocaeicola sp in WildR samples by qPCR.
CAATCAGAAATCAGATATTTAACTCCG
Sequence-based reagentrpsR-bacteroides-qPCR-RThis paperqPCR primer to quantify total Bacteroides, Parabacteroides, and Phocaeicola sp in WildR samples by qPCR.
CAAGAATTTCTTCAAGAATTCAGGATC
Sequence-based reagentBA-qPCR-FThis paperqPCR primer to quantify B. acidifaciens by qPCR in wildR samples.
CTGGAGGCAAAAACGTATTCAGAG
Sequence-based reagentBA-qPCR-RThis paperqPCR primer to quantify B. acidifaciens by qPCR in wildR samples.
CTTTTGACCGTCCAATCGTATAGC
Sequence-based reagentMi-qPCR-FThis paperqPCR primer to quantify Muribaculum intestinale by qPCR in in vitro competitions.
AGGCTTGTAGACCTTGATGAGATG
Sequence-based reagentMi-qPCR-RThis paperqPCR primer to quantify Muribaculum intestinale by qPCR in in vitro competitions.
CACTGTGCATATATGTTGAGCCTG
Sequence-based reagentSm-qPCR-FThis paperqPCR primer to quantify Sporofaciens musculi by qPCR in in vitro competitions.
TGTTGTTCAGCAGGTAGATACTCC
Sequence-based reagentSm-qPCR-RThis paperqPCR primer to quantify Sporofaciens musculi by qPCR in in vitro competitions.
CTACAAAGTTCATCTGCGGTGATC
Sequence-based reagentMg-qPCR-FThis paperqPCR primer to quantify Muribaculum caecicola by qPCR in in vitro competitions.
TACTGTGTGCATGGATCTATACGG
Sequence-based reagentMg-qPCR-RThis paperqPCR primer to quantify Muribaculum caecicola by qPCR in in vitro competitions.
ACACAACGTCTTTATGCCTTGATG
Sequence-based reagentDf-qPCR-FThis paperqPCR primer to quantify Duncaiella freteri by qPCR in in vitro competitions.
ATAATGGTCAGGCTCGGTAGAATC
Sequence-based reagentDf-qPCR-RThis paperqPCR primer to quantify Duncaiella freteri by qPCR in in vitro competitions.
GAGGAGGCAAGGGATATCTATTGG
Sequence-based reagentBsp95-qPCR-FThis paperqPCR primer to quantify Bacteroides sp. 910578895 by qPCR in in vitro competitions.
ACTATCCTAACGGTGTATTGGCAG
Sequence-based reagentBsp95-qPCR-RThis paperqPCR primer to quantify Bacteroides sp. 910578895 by qPCR in in vitro competitions.
AGAGTAGTTCACACCCAAAGTAGC
Sequence-based reagentpSIE1-Ba-tssC-frag1-FThis paperCloning primer (allelic exchange) to amplify ~1 kb flanking regions around tssC (ACY5BC_08310) from B. acidifaciens genome to insert into pSIE1 digested with SpeI and NotI. Corresponding plasmid: pSIE1::∆Ba-tssC.
ATTAGCATTATGAGGATCCACCACGGTTATCTGTGCCTTTC
Sequence-based reagentpSIE1-Ba-tssC-frag1-RThis paperCloning primer (allelic exchange) to amplify ~1 kb flanking regions around tssC (ACY5BC_08310) from B. acidifaciens genome to insert into pSIE1 digested with SpeI and NotI. Corresponding plasmid: pSIE1::∆Ba-tssC.
CAGAAGATTACATCTTGCTAAAAGATTAAAGTTCTACC
Sequence-based reagentpSIE1-Ba-tssC-frag2-FThis paperCloning primer (allelic exchange) to amplify ~1 kb flanking regions around tssC (ACY5BC_08310) from B. acidifaciens genome to insert into pSIE1 digested with SpeI and NotI. Corresponding plasmid: pSIE1::∆Ba-tssC.
TAGCAAGATGTAATCTTCTGAACAGTTTTAAATTTACAG
Sequence-based reagentpSIE1-Ba-tssC-frag1-RThis paperCloning primer (allelic exchange) to amplify ~1 kb flanking regions around tssC (ACY5BC_08310) from B. acidifaciens genome to insert into pSIE1 digested with SpeI and NotI. Corresponding plasmid: pSIE1::∆Ba-tssC.
TTCCCCTCCACCGCGGTGGCTCAACTCTTGTTGCGTCTG
Sequence-based reagentpLGB13-RM silent-Frag1-FThis paperCloning primer (allelic exchange) to amplify part of pLGB13 backbone (no mutations) for assembly into pLGB13-Rmsilent. Corresponding plasmid: pLGB13-RMsilent.
GTTTACTCATAACGCGTCAATTC
Sequence-based reagentpLGB13-RM silent-Frag1-RThis paperCloning primer (allelic exchange) to amplify part of pLGB13 backbone (no mutations) for assembly into pLGB13-Rmsilent. Corresponding plasmid: pLGB13-RMsilent.
AATTCCCATGTCAGCCGTTAAG
Sequence-based reagentpLGB13-RM silent-Frag2-FThis paperCloning primer (allelic exchange) to amplify part of pLGB13 backbone (no mutations) for assembly into pLGB13-Rmsilent. Corresponding plasmid: pLGB13-RMsilent.
AGCAGCTCTAATGCGCTGTTAATCAC
Sequence-based reagentpLGB13-RM silent-Frag2-RThis paperCloning primer (allelic exchange) to amplify part of pLGB13 backbone (no mutations) for assembly into pLGB13-Rmsilent. Corresponding plasmid: pLGB13-RMsilent.
CGTACCGCTGACACCAAGTCCG
Sequence-based reagentpLGB13-RM silent-Frag3-FThis paperCloning primer (allelic exchange) to amplify part of pLGB13 backbone (no mutations) for assembly into pLGB13-Rmsilent. Corresponding plasmid: pLGB13-RMsilent.
CCTTACTTGTGCCTGTTCTATTTC
Sequence-based reagentpLGB13-RM silent-Frag3-RThis paperCloning primer (allelic exchange) to amplify part of pLGB13 backbone (no mutations) for assembly into pLGB13-Rmsilent. Corresponding plasmid: pLGB13-RMsilent.
GTCGCTATATAATTTGGTGAATTG
Sequence-based reagentpLBG13-RMsilent-baei1-Frag1-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08390 and ACY5BC_08395 (baei1) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae1-bai1.
CGGTGTAAGATTAGCATTATGAGTGGATCCGGGATTGGGAGGATTTCTC
Sequence-based reagentpLBG13-RMsilent-baei1-Frag1-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08390 and ACY5BC_08395 (baei1) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae1-bai1.
ACTTATAATCAACGTCCGCGAGTAACATGGC
Sequence-based reagentpLBG13-RMsilent-baei1-Frag2a-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08390 and ACY5BC_08395 (baei1) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae1-bai1.
TTACTCGCGGACGTTGATTATAAGTAAAAATTGCTATTG
Sequence-based reagentpLBG13-RMsilent-baei1-Frag2a-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08390 and ACY5BC_08395 (baei1) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae1-bai1.
TAACATATCTGGAGTAAATAACCGAATGCTC
Sequence-based reagentpLBG13-RMsilent-baei1-Frag2b-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08390 and ACY5BC_08395 (baei1) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae1-bai1.
TCGGTTATTTACTCCAGATATGTTAAGGGAATTGAAC
Sequence-based reagentpLBG13-RMsilent-baei1-Frag2b-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08390 and ACY5BC_08395 (baei1) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae1-bai1.
CCATCACTGGAAGATAGGCAATTAGTCGACGTTGGCGTATGATATAGTATATG
Sequence-based reagentpLBG13-RMsilent-baei2-Frag2-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08435 and ACY5BC_08440 (baei2) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae2-bai2.
ACATATTCAGGAATCTTGAGGTCATTGATGAATCTTTTGG
Sequence-based reagentpLBG13-RMsilent-baei2-Frag2-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08435 and ACY5BC_08440 (baei2) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-bae2-bai2.
ACTGGAAGATAGGCAATTAGTCGACTTGATTATTAAACGAATAGTATTCTC
Sequence-based reagentpLGB13-RMsilent-Ba-tssN-Frag1-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08340 (tssN) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-tssN.
TAAGATTAGCATTATGAGTGGATCCAAACAATCAAGCCGGGTG
Sequence-based reagentpLGB13-RMsilent-Ba-tssN-Frag1-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08340 (tssN) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-tssN.
TTTTTCTCTATTTGTACGCGC
Sequence-based reagentpLGB13-RMsilent-Ba-tssN-Frag2-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08340 (tssN) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-tssN.
CGCGTACAAATAGAGAAAAAATC
Sequence-based reagentpLGB13-RMsilent-Ba-tssN-Frag2-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08340 (tssN) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-tssN.
ACTGGAAGATAGGCAATTAGTCGACTCGTATATTAGCCCGGTC
Sequence-based reagentpLGB13-RMsilent-Ba-clpV-Frag1-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08330 (clpV) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-clpV.
TAAGATTAGCATTATGAGTGGATCCCGAAGGAGAGCATCGAGAG
Sequence-based reagentpLGB13-RMsilent-Ba-clpV-Frag1-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08330 (clpV) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-clpV.
TTTCGATAGTTTATGATGATACTGTCG
Sequence-based reagentpLGB13-RMsilent-Ba-clpV-Frag2-FThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08330 (clpV) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-clpV.
ATCATCATAAACTATCGAAACG
Sequence-based reagentpLGB13-RMsilent-Ba-clpV-Frag2-RThis paperCloning primer (allelic exchange) for deletion of ACY5BC_08330 (clpV) by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::∆Ba-clpV.
ACTGGAAGATAGGCAATTAGTCGACAAGTCCGTTTCTCCGTAC
Sequence-based reagentpLGB13-RMsilent-ICE-CmR-Frag1-FThis paperCloning primer (allelic exchange) for insertion of P1-GH023-CAT-term on ICE by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::Ba-ICE-P1-GH023-CAT-term.
CGGTGTAAGATTAGCATTATGAGTGGATCCTACGCTCTATGATGTGTC
Sequence-based reagentpLGB13-RMsilent-ICE-CmR-Frag1-RThis paperCloning primer (allelic exchange) for insertion of P1-GH023-CAT-term on ICE by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::Ba-ICE-P1-GH023-CAT-term.
GGCTTTCTTCTCTTGGAAAG
Sequence-based reagentpLGB13-RMsilent-ICE-CmR-Frag3-FThis paperCloning primer (allelic exchange) for insertion of P1-GH023-CAT-term on ICE by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::Ba-ICE-P1-GH023-CAT-term.
GAGAAGGCCATCCTGACG
Sequence-based reagentpLGB13-RMsilent-ICE-CmR-Frag3-RThis paperCloning primer (allelic exchange) for insertion of P1-GH023-CAT-term on ICE by Gibson Assembly into BamHI and SalI linearized pLGB13-RMsilent. Corresponding plasmid: pLGB13-RMsilent::Ba-ICE-P1-GH023-CAT-term.
CCATCACTGGAAGATAGGCAATTAGTCGACATTATCGGTTTATCCTGTACGC
Sequence-based reagentpNBU2-erm-us1311-tssC-FThis paperCloning primer (allelic exchange) to amplify B. acidifaciens tssC gene to insert into pNBU2-ermG-us1311 digested with NdeI and XbaI. Corresponding plasmid: pNBU2-ermG-us1311::tssC.
CTCCAAATCTGTTTTTAACATATGAAGCAGGAAACGCAACAAC
Sequence-based reagentpNBU2-erm-us1311-tssC-RThis paperCloning primer (allelic exchange) to amplify B. acidifaciens tssC gene to insert into pNBU2-ermG-us1311 digested with NdeI and XbaI. Corresponding plasmid: pNBU2-ermG-us1311::tssC.
GCCCGGGGGATCCACTAGTTCTAGATTATTCCTGGTGATATTCGCTTTC
Sequence-based reagentpNBU2-tssC-singleRMsilent-QCprimerThis paperCloning primer (allelic exchange): Primer for quick change to remove a single methylated motif from pNBU2-ermG-us1311::tssC plasmid. Bold residues indicate two modified bases in the final plasmid on the template strand. Corresponding plasmid: pNBU2-ermG-us1311::tssC_singleRMsilent.
GGATCCCCCGGGCTGTGGGAATTCGATATCAAGCTTATCGATACC
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag1-FThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
AGCTTGTTGGTACATCCG
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag1-RThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
CAGACCGATACGCATATC
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag2-FThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
GAACGTACTCATGGTTCATC
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag2-RThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
TGACAGTTACCAATGTTTAATCAGTGAGGCACCTATC
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag3-FThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone and introduce a point mutation to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
GCCTCACTGATTAAACATTGGTAACTGTCAGACCAAGTTTAC
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag3-RThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone and introduce a point mutation to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
TCACAATATGAGCAACAAG
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag4-FThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone and introduce a point mutation to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
CTTGATGTCGAATTCCTACAGCCCGGGGGATCCACC
Sequence-based reagentpNBU2-ermG-P5E4-RMsilent-Frag4-RThis paperCloning primer (allelic exchange) to amplify part of pNBU2-ermG::P5E4 backbone and introduce a point mutation to assemble plasmid without B. acidifaciens methylated motifs. Corresponding plasmid: pNBU2-ermG-RMsilent::P5E4.
TGTAGGAATTCGACATCAAGCTTATCGATACCG
Commercial assay or kitPowerFecal DNA Isolation KitMoBio LaboratoriesCat# 12830-50
Commercial assay or kitNextSeq 500/550 High Output Kit v2.5 (300 cycles)IlluminaCat# 20024908
Commercial assay or kitGenomic-tip 20/GQIAGENCat# 13323
Commercial assay or kitQubit dsDNA HS Assay KitThermo Fisher ScientificCat# Q33231
Commercial assay or kitLigation Sequencing KitOxford Nanopore TechnologiesCat# SQK-LSK110
Commercial assay or kitHMW DNA Extraction KitNew England BiolabsCat# T3060
Commercial assay or kitWizard HMW DNA Extraction KitPromegaCat# A2920
Commercial assay or kitDNeasy Blood & Tissue KitQIAGENCat# 69504
Commercial assay or kitIllumina DNA Prep KitIlluminaCat# 20018704
Commercial assay or kitIDT for Illumina DNA/RNA UD Indexes, Set AIntegrated DNA TechnologiesCat# 20027213
Commercial assay or kitExoSAP-ITThermo Fisher ScientificCat# 78201.1.ML
Commercial assay or kitSMRTbell Express Template Prep Kit v2.0Pacific Biosciences
Commercial assay or kitE-Z 96 DNA KitOmega Bio-tekCat# BD96-01
Commercial assay or kitAMPure XP beadsBruker
Commercial assay or kitSequalPrep Normalization Plate KitThermo ScientificCat# A1051001
Commercial assay or kitKAPA HiFi HotStart ReadyMix (2x)Roche
Commercial assay or kitSsoAdvanced Universal SYBR Green SupermixBio-Rad
Software, algorithmTrimmomaticBolger et al., 2014v0.39
Software, algorithmBowtie2Langmead and Salzberg, 2012
Software, algorithmKraken2-Bracken Snakemake pipeline (custom, CMMG-based)https://github.com/SilasK/Krak
Software, algorithmMUFFINVan Damme et al., 2021; https://github.com/RVanDamme/MUFFINv1.0.6
Software, algorithmMetaFlyeKolmogorov et al., 2019; Kolmogorov, 2020;
https://github.com/mikolmogorov/Flye		v2.7
Software, algorithmPolypolishWick and Holt, 2022; https://github.com/rrwick/Polypolishv0.5.0
Software, algorithmCONCOCTAlneberg et al., 2014v1.1.0
Software, algorithmMetaBAT2Kang et al., 2019v2.13
Software, algorithmMaxBin2https://sourceforge.net/projects/maxbin2/v2.2.7
Software, algorithmmetaWRAPUritskiy et al., 2018v1.2.2
Software, algorithmUnicyclerWick et al., 2017v0.4.7
Software, algorithmUnicyclerWick et al., 2017v0.4.8
Software, algorithmCheckMParks et al., 2015v1.0.13
Software, algorithmGTDB-tkChaumeil et al., 2019v2.1.0
Software, algorithmProkkaSeemann, 2014v1.12
Software, algorithmProkkaSeemann, 2014v1.14.6
Software, algorithmBWA-MEMLi, 2013
Software, algorithmsamtoolsLi et al., 2009
Software, algorithmTrycyclerWick et al., 2021v0.5.3
Software, algorithmFlyeKolmogorov et al., 2019v2.9-b1768
Software, algorithmMiniasm / MinipolishWick and Holt, 2019v0.3-r179; v0.1.2
Software, algorithmRavenlbcb-sci, 2022; https://github.com/lbcb-sci/ravenv1.8.1
Software, algorithmPilonWalker et al., 2014v1.24
Software, algorithmBreSeqDeatherage and Barrick, 2014v0.38.3
Software, algorithmminimap2Li, 2018
Software, algorithmCD-SearchMarchler-Bauer et al., 2009
Software, algorithmFoldseekvan Kempen et al., 2024
Software, algorithmGeneious PrimeGeneious; https://www.geneious.com2024.0.5
Software, algorithmBBDukOther (BBTools, distributed within Geneious Prime)v38.84
Software, algorithmSMRT LinkPacific Biosciencesv11.0.0.146107
Software, algorithmQIIME 2Bolyen et al., 2019v2020.11
Software, algorithmdRepOlm et al., 2017; Kieser et al., 2022v3.5.0
Software, algorithmGraphPad PrismGraphPad Softwarev10.2.3
Software, algorithmCustom ICE-seq analysis scriptGallagher, 2019

Data availability

Strains generated in this study are available for research purposes by request from the corresponding author. Use for commercial purposes is restricted by a transfer agreement from Taconic, the provider of the WildR community. Numeric data presented in figures is provided in source data files accompanying the manuscript. Raw sequencing reads from metagenomic and strain sequencing along with assembled genome sequences are available through NCBI (BioProject: PRJNA1367654). Sequences of metagenome assembled genomes are deposited on Zendo (https://doi.org/10.5281/zenodo.17716312). Raw reads from original metagenomic sequencing of the Wild and WildR F2 communities were retrieved from NCBI (BioProject: PRJNA390686) (Rosshart et al., 2017). Source data files contain the numerical data used to generate the figures. All bioinformatic tools used for sequence data analysis were previously published and can be accessed as described in the materials and methods section.

The following data sets were generated
    1. Shen BA
    2. Asfahl KL
    3. Lim B
    4. Bertolli SK
    5. Minot SS
    6. Radey MC
    7. Penewit K
    8. Ngo B
    9. Salipante SJ
    10. Johnston CD
    11. Peterson SB
    12. Goodman AL
    13. Mougous JD
    (2025) NCBI BioProject
    ID PRJNA1367654. Characterization of reconstituted wild gut microbiome through genome assembly, 16S rRNA sequencing, and mobile element identification.
    https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1367654
    1. Shen BA
    2. Asfahl KL
    3. Lim B
    4. Bertolli SK
    5. Minot SS
    6. Radey MC
    7. Penewit K
    8. Ngo B
    9. Salipante SJ
    10. Johnston CD
    11. Peterson SB
    12. Goodman AL
    13. Mougous JD
    (2025) Zenodo
    Characterization of reconstituted wild gut microbiome through genome assembly, 16S rRNA sequencing, and mobile element identification.
    https://doi.org/10.5281/zenodo.17716312
The following previously published data sets were used

References

Article and author information

Author details

  1. Beth A Shen

    Department of Microbiology, University of Washington, Seattle, United States
    Contribution
    Conceptualization, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared

  2. Kyle L Asfahl

    Microbial Interactions & Microbiome Center, University of Washington, Seattle, United States
    Contribution
    Investigation, Visualization, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared

  3. Bentley Lim

    Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, United States
    Contribution
    Resources, Investigation, Methodology
    Competing interests
    No competing interests declared

  4. Savannah K Bertolli

    Department of Microbiology, University of Washington, Seattle, United States
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  5. Samuel S Minot

    Bioinformatics Core, Fred Hutchinson Cancer Center, Seattle, United States
    Contribution
    Software, Methodology
    Competing interests
    No competing interests declared

  6. Matthew C Radey

    Department of Microbiology, University of Washington, Seattle, United States
    Contribution
    Software, Formal analysis, Methodology
    Competing interests
    No competing interests declared

  7. Kelsi M Penewit

    Department of Laboratory Medicine and Pathology, University of Washington, Seattle, United States
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  8. Billy Ngo

    Department of Microbiology, University of Washington, Seattle, United States
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  9. Stephen J Salipante

    Department of Laboratory Medicine and Pathology, University of Washington, Seattle, United States
    Contribution
    Supervision
    Competing interests
    No competing interests declared

  10. Christopher D Johnston

    Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center Houston, Houston, United States
    Contribution
    Funding acquisition, Investigation, Methodology
    Competing interests
    No competing interests declared

  11. S Brook Peterson

    Department of Microbiology, University of Washington, Seattle, United States
    Present address
    Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, United States
    Contribution
    Conceptualization, Formal analysis, Visualization, Methodology, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2648-0965

  12. Andrew L Goodman

    Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, United States
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7599-3471

  13. Joseph D Mougous

    1. Department of Microbiology, University of Washington, Seattle, United States
    2. Microbial Interactions & Microbiome Center, University of Washington, Seattle, United States
    3. Howard Hughes Medical Institute, University of Washington, Seattle, United States
    Present address
    Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Visualization, Methodology, Writing – original draft, Writing – review and editing
    For correspondence
    joseph.mougous@yale.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5417-4861

Funding

National Institutes of Health (R35GM118159)

  • Andrew L Goodman

National Institutes of Health (DE027850)

  • Christopher D Johnston

National Institutes of Health (F32 AI164853)

  • Beth A Shen

The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Ben Ross and members of the Mougous lab for helpful discussions, Stephan Rosshart for providing access to individual wild mouse microbiome data, Natasha Bencivenga-Barry for assistance with preparation of WildR cryopreserved stocks, the Microbial Interactions & Microbiome Center for providing laboratory space and equipment to support animal studies, and the UW Gnotobiotic Animal Core for assistance with gnotobiotic animal work including experimental design, breeding, and technical expertise. This work was supported by NIH grant R35GM118159 (to ALG) and NIH grant R01 DE027850 (to CDJ). BAS was supported by a Ruth R Kirschstein National Research Service Award (F32 AI164853). JDM is a Howard Hughes Medical Institute Investigator and held the Lynn and Michael Garvey Chair in Gastroenterology at the University of Washington. JDM currently holds the John F Enders Professorship at Yale University.

Ethics

This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All animals were handled according to protocols approved by the University of Washington Institutional Animal Care and Use Committee (#4038-04) or the Yale University Institutional Animal Care and Use Committee (#2025-11423).

Version history

  1. Preprint posted:
  2. Sent for peer review:
  3. Reviewed Preprint version 1:
  4. Reviewed Preprint version 2:
  5. Version of Record published:

Cite all versions

You can cite all versions using the DOI https://doi.org/10.7554/eLife.110200. This DOI represents all versions, and will always resolve to the latest one.

Copyright

© 2026, Shen et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 904
    views
  • 58
    downloads
  • 2
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Citations by DOI

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Beth A Shen
  2. Kyle L Asfahl
  3. Bentley Lim
  4. Savannah K Bertolli
  5. Samuel S Minot
  6. Matthew C Radey
  7. Kelsi M Penewit
  8. Billy Ngo
  9. Stephen J Salipante
  10. Christopher D Johnston
  11. S Brook Peterson
  12. Andrew L Goodman
  13. Joseph D Mougous
(2026)
The type VI secretion system governs strain maintenance in a wild mammalian gut microbiome
eLife 15:RP110200.
https://doi.org/10.7554/eLife.110200.3

Share this article

https://doi.org/10.7554/eLife.110200

Categories and tags

Further reading

    1. Microbiology and Infectious Disease

    Gut Microbiome: Bacteria weigh up costs and benefits of mobile weapons

    Zhao Wang, Yang Fu
    Insight

    Gaining the ability to kill rival microbes is not always an advantage for bacteria in complex gut microbiomes.