Strain-specific galactose utilization by commensal E. coli mitigates Salmonella establishment in the gut

Christopher Schubert; Jana Näf; Lisa Petukhov; Leanid Laganenka; Yassine Cherrak; Wolf-Dietrich Hardt

doi:10.1371/journal.ppat.1013232

Abstract

Salmonella enterica serovar Typhimurium (S. Tm) is a major cause of gastrointestinal diseases worldwide. To date, options for prevention or curative therapy remain limited. The gut microbiota plays a protective role against enteric diseases, particularly in preventing establishment and proliferation of S. Tm. While most research has focused on microbiota-mediated pathogen exclusion during the later, inflammation-dominated stages of infection, little is known about how microbiota members mitigate S. Tm early gut colonization. To address this gap, we conducted 24 h in vivo competitive experiments using S. Tm and different commensal E. coli strains. We observed a significant reduction in pathogen load, which was strain-specific and particularly evident with E. coli 8178. To investigate the underlying molecular mechanisms, we performed an in vivo screen using a rationally designed S. Tm library—which includes a wide range of carbohydrate utilization mutants—both in the absence and presence of E. coli strains. Our findings revealed that E. coli 8178-mediated S. Tm competition was driven by the exploitation of galactose during the early stage of infection. Identifying galactose as a key metabolite in pathogen exclusion by gut microbiota members enhances our mechanistic understanding of microbiota-mediated protection and opens new avenues for developing microbiota- and dietary-based strategies to better control intestinal infections.

Author summary

Salmonella infections remain a major global health problem, and options for preventing or treating them are still limited. Our gut microbiota helps protect against such infections. While most research has focused on how the microbiota acts during later, more severe stages of infection, we wanted to understand how it can stop Salmonella early, before it takes hold. In this study, we looked at how different strains of Escherichia coli, a common gut bacterium, compete with Salmonella Typhimurium. We found that one strain, called 8178, was especially good at restricting Salmonella shortly after infection. We discovered that this competition centers around galactose, a simple sugar. Our findings show that some gut bacteria can effectively starve out invading pathogens by beating them to essential nutrients. This work offers new insights into how our gut microbiota protects us and points to strategies - such as using beneficial bacteria or tailored diets - to help prevent or control gut infections.

Citation: Schubert C, Näf J, Petukhov L, Laganenka L, Cherrak Y, Hardt W-D (2025) Strain-specific galactose utilization by commensal E. coli mitigates Salmonella establishment in the gut. PLoS Pathog 21(6): e1013232. https://doi.org/10.1371/journal.ppat.1013232

Editor: David Skurnik, Universite Paris Descartes Faculte de Medecine, FRANCE

Received: March 10, 2025; Accepted: May 26, 2025; Published: June 27, 2025

Copyright: © 2025 Schubert et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data needed to evaluate the conclusions of this study are presented in the Article and Supporting Information. The amplicon sequencing data for the WISH-barcoded S. Typhimurium mutant pool experiments has been deposited in the European Nucleotide Archive under the accession number: PRJEB85163.

Funding: This work has been funded by grants from the Swiss National Science Foundation: grant 310030_192567, Nr. 10.001.588 and the National Centre of Competence in Research (NCCR) Microbiomes (51NF40_225148) to W.-D.H. Y.C. is supported by an EMBO long-term fellowship (ALTF-234-2020) and a flexibility grant from the SNF/NCCR Microbiome (51NF40_180575). C.S is supported by a German Research Foundation fellowship (SCHU 3606/1-1). L.L. is supported by a grant (LA 4572/1-1) from the German Research Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Foodborne diarrhoea is a widespread disease, affecting 1 in 10 people globally and leading to over 420,000 deaths annually [1]. Bacterial enteric pathogens are among the leading causes of foodborne diseases, with Salmonella responsible for 180 million cases of gastroenteritis each year [2]. Salmonella enterica serovar Typhimurium (S. Tm) is among the most common non-typhoidal serovars that affect humans [3,4]. Research using antibiotic-pretreated specific pathogen free (SPF) C57BL/6J and gnotobiotic mouse models have identified two distinct growth phases for S. Tm in the gut [5]. In these models, S. Tm establishes and grows in the intestinal lumen through monosaccharide-fuelled mixed acid fermentation during the early stage of infection (0–48 hours post-infection) [6–9]. Subsequently, S. Tm employs the type III secretion systems encoded within the pathogenicity island 1 (T3SS-1) and 2 (T3SS-2) to trigger inflammation, creating conditions that favour proliferation, evolution and transmission of the pathogen [6,7,9–18].

Under homeostatic conditions, the gut microbiota plays a variety of functions, including restricting the invasion of enteric pathogens [19]. This phenomenon is referred to as colonization resistance and can often be attributed to specific commensal stains exhibiting pathogen-displacing capabilities [20,21]. This is particularly relevant for S. Tm infections, where several microbiota members were shown to act as protective strains [22–25]. The prevention of pathogen growth by intestinal commensals can occur through interference mechanisms involving the production of toxic compounds. This is exemplified by commensal E. coli or Bacteroides spp. which produce toxins and metabolites directly impacting Salmonella growth in the gastrointestinal tract [26–28]. Alternatively, commensal bacteria can engage in competitive interactions by exploiting available nutrients, thereby reducing the fitness of their competitors – a mechanism known as nutrient exploitation. This holds true for the human probiotic E. coli Nissle strain, which restricts intestinal S. Tm growth by scavenging iron [29]. Besides iron, several electron acceptors such as oxygen, fumarate and nitrate were also shown to be actively used by commensal E. coli strains, thereby limiting Salmonella’s fitness in the gut [7,8,30–32]. While the mechanisms driving S. Tm restriction by commensals are increasingly understood, most of this research focuses on the later stages of infection, particularly when inflammation is already established. In contrast, our understanding of how commensals restrict pathogens during the initial growth phase remains scarce, with galactitol standing as one of the few known carbohydrates exploited by commensal E. coli to limit S. Tm gut invasion [33].

In this study, we aimed to address these gaps by investigating how commensal Enterobacteriaceae restrict S. Tm during the early phase of intestinal growth and identifying the carbohydrates driving this exclusion relationship.

Results

E. coli 8178 limits early S. Tm gut establishment independently of interference mechanisms

E. coli 8178 is a commensal strain, originally isolated from the murine gut and capable of outcompeting S. Tm at the later stages of infection once inflammation is established [14]. This competitive advantage, visible in the severely inflamed gut between 72- and 96-hours post-infection (p.i) is attributed to an interference mechanism involving the synthesis and secretion of siderophore-bound toxins [28,34]. While investigating this phenomenon, we found out that E. coli 8178 was also able to restrict the growth of S. Tm at the early stage of infection (24 h p.i) when administered either prior to or concomitantly with S. Tm [7,28]. To confirm this observation, we inoculated streptomycin-pretreated 129S6/SvEvTac mice harbouring a specific pathogen-free (SPF) microbiota with a 1:1 mixture of E. coli 8178 and S. Tm SL1344. Mice co-inoculated with E. coli 8178 displayed a 50-fold reduction in faecal pathogen loads at 24 hours post-infection compared to mice infected with S. Tm alone (Fig 1A and 1B). This significant reduction during the initial stage of S. Tm infection, which remains uncharacterized, was the focus of our investigation.

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Fig 1. E. coli 8178-mediated S. Tm early growth restriction is independent of interfering competition interactions.

(A) Experimental scheme. Streptomycin-pretreated specific pathogen-free (SPF) 129S6/SvEvTac mice were infected with either S. Tm alone or a 1:1 mixture of S. Tm and the indicated E. coli strain. The E. coli and S. Tm loads were determined by selective plating from faecal samples collected 24 h post-infection (p.i.) prior to euthanasia. Created in BioRender. Cherrak, Y. (2025) https://BioRender.com/n43x499. (B-C) E. coli mitigates the early growth of S. Tm in a strain-dependent manner. The S. Tm loads at 24 h p.i. are plotted and compared between S. Tm mono-infected and S. Tm + E. coli co-infected mice. E. coli 8178 (B) and Z1331 (C) were tested as competitors. (D) E. coli loads at 24 h p.i from Fig 1B and 1C are shown. (E) E. coli 8178 restricts S. Tm establishment independently of interference mechanisms. The faecal load of S. Tm collected 24 h p.i. is plotted and compared between S. Tm mono-infected and S. Tm + E. coli 8178 co-infected mice. The E. coli 8178 mutant strains tested are listed and categorized based on the nature of the interference system disrupted. (F) Inflammation does not trigger E. coli 8178-mediated S. Tm competition 24 h p.i. E. coli 8178 competitiveness was tested against an avirulent S. Tm mutant (ΔinvG/ΔssaV). (B-F) All competitive experiments are presented in a box-and-whiskers plot, showing the minimum to maximum values, median, and interquartile range (25^th to 75^th percentiles). The bar plots show the median. Two-tailed Mann–Whitney U tests to compare 2 groups in each panel. P ≥ 0.05 not significant (ns), p < 0.05 (*), p < 0.01 (**). A minimum of 5 mice (n ≥ 5) were used for each experimental group. CFU: colony forming units.

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First, we aimed to determine whether S. Tm growth attenuation at 24 h p.i was specific to E. coli 8178 or if it was a common effect among other commensal E. coli strains. To explore this, we co-inoculated streptomycin-pretreated 129S6/SvEvTac mice with a mixture of S. Tm and a different E. coli strain. We selected E. coli Z1331, a recent and genetically tractable isolate from a healthy human volunteer [35]. This strain has previously been used to study autoinducer-2-mediated chemotaxis in both interspecies and intraspecies signalling [36,37]. Interestingly, in this context, the competitive elimination of S. Tm at 24 h p.i was not observed (Figs 1C and S1 A) despite E. coli Z1331 shedding at similar levels as E. coli 8178 at 24 h p.i (Fig 1D). This indicated that S. Tm growth attenuation by E. coli 8178 is a strain-specific feature. Given the variety of antimicrobial systems encoded by E. coli 8178, we next hypothesized that S. Tm competition at 24 hours was driven by an interference mechanism, similar to what occurs during the late-stage infection, when inflammation peaks [28,34]. To test this, we systematically mutated each known interference factor in the E. coli 8178 genome, including both diffusible and contact-dependent toxin delivery machineries. We then assessed the ability of each E. coli 8178 mutant to displace S. Tm using streptomycin-pretreated SPF 129S6/SvEvTac mice and found that all strains remain effective in reducing S. Tm early gut establishment (Fig 1E). Finally, considering the variety of antagonistic relationships triggered during inflammation [14,27–29,31], we examined whether E. coli 8178-mediated exclusion of S. Tm was dependent on an inflammatory response. To investigate this, we infected streptomycin-pretreated SPF 129S6/SvEvTac mice with E. coli 8178 and an isogenic S. Tm strain lacking both type three secretion systems (T3SS-1, ΔinvG and T3SS-2 ΔssaV), thus unable to trigger a severe gut inflammation [11]. Notably, the faecal loads of the S. Tm ΔinvG ΔssaV at 24 h p.i were consistently reduced by the presence of E. coli 8178 (Fig 1F). Overall, we concluded that E. coli 8178-mediated inhibition of S. Tm during the initial growth phase was independent of inflammation and did not rely on any known interference mechanisms.

Impact of E. coli 8178 on S. Tm sugar metabolism during initial growth phase

Since exclusion of S. Tm by E. coli 8178 at 24 h post-infection is likely not due to an interference mechanism, we hypothesized that this effect may be explained by nutrient exploitation. Recently, hexoses have been identified as the primary nutrient source driving S. Tm colonization during the initial growth phase [6,8,9], making them a potential prime target for nutrient exploitation. To explore this further, we employed a targeted library of 35 S. Tm mutants, each defective in specific carbohydrate-utilizing enzymes [8] and uniquely labelled with a chromosomal, fitness-neutral DNA barcode (WISH tag, [38]) (Fig 2A and 2B). We screened for metabolic-deficient S. Tm strains and tested whether mutant fitness was impacted by the presence of E. coli 8178. We also included E. coli Z1331 for comparison to highlight specific E. coli 8178-driven changes (Fig 2B). To control the quality of the generated pool data, seven wildtype (WT) strains carrying distinct WISH tags were included. This allowed to assess the bottleneck severity by calculating the Shannon evenness score, with mice scoring below 0.9 being excluded from the competitive index analysis [8,39]. Furthermore, two control S. Tm mutants (ΔdcuABC, Δfrd), which are deficient in fumarate respiration and exhibit an initial growth defect, were included as internal standards to validate our findings [7,8]. Streptomycin-pretreated 129S6/SvEvTac mice were infected with the targeted S. Tm carbohydrate-mutant pool, both in the absence and presence of E. coli 8178 or E. coli Z1331. The raw fitness data for each S. Tm metabolic mutants across these 3 conditions are presented in the S1 Data file. The Shannon evenness score and the fitness of the S. Tm control mutants for each dataset are presented in S2A and S2B Fig. As previously reported, mutants deficient in fumarate respiration are already attenuated by day 1 post-infection [8], further validating the reliability of our downstream analysis.

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Fig 2. Evaluation of S. Tm metabolic requirement in presence of E. coli strains.

(A) Schematic representation of the S. Tm metabolic mutant pool, illustrating the targeted carbohydrate utilization pathways, adapted from [8] (https://www.nature.com/articles/s41467-025-56890-y#Fig1). The mutants affect key enzymatic steps, including dehydratases, kinases, and isomerases, positioned between transport reactions and central metabolic intermediates in glycolysis, the Entner-Doudoroff pathway, and the pentose phosphate pathway. Each circle represents an enzymatic step. Abbreviations are listed in S4 Table PG, peptidoglycan. (B) Experimental scheme. A WISH-barcoded S. Tm mutant pool library comprising 7 SL1344 wild type (WT), 2 control mutants (Δfrd and ΔdcuABC) and 35 deficient strains in carbohydrate utilization was pooled and used in this study. Streptomycin-pretreated SPF 129S6/SvEvTac mice were infected with the S. Tm pool alone or in combination with an E. coli strain (8178 or Z1331). The fitness of each S. Tm mutant was assessed by WISH-barcode sequencing from faecal samples. Created in BioRender. Cherrak, Y. (2025) https://BioRender.com/c18e944. (C) Effect of E. coli strains on S. Tm carbohydrate mutant fitness in vivo. The competitive index for each S. Tm mutant (listed on the left) is calculated relative to the WT and depicted as a heat map, across 3 different conditions: without E. coli (/), in presence of E. coli 8178 (+ E. coli 8178) in presence of E. coli Z1331 (+ E. coli Z1331). Median values from a minimum of 6 mice (n ≥ 6) are shown. Two-tailed Mann–Whitney U tests to compare 2 groups (S. Tm library alone vs S. Tm library + E. coli 8178 or S. Tm library alone vs S. Tm library + E. coli Z1331). P ≥ 0.05 not significant (ns), p < 0.05 (*), p < 0.01 (**), p < 0.005 (***), p < 0.001 (****).

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Consistent with earlier findings, we found that in absence of competing strains, S. Tm relies on multiple carbohydrates to efficiently grow in the murine gut [8] (Fig 2C, left column). Specifically, the Δpgm, ΔpgI, and ΔpfkA mutants, responsible for catalysing the sequential conversion of D-glucose 1-phosphate to D-glucose 6-phosphate (pgm), then to D-fructose 6-phosphate (pgi), and finally to D-fructose 1,6-bisphosphate (pfkA)—exhibited a fitness disadvantage compared to the WT control. This was reflected in competitive index (C.I) values below 1, underscoring the essential role of glycolysis under these conditions. Additionally, mutants deficient in metabolizing arabinose (ΔaraB), galactose (ΔgalK), fructose (ΔfruK), and mannose (ΔmanA) also displayed reduced fitness (Fig 2C). This suggests that S. Tm primarily depends on these metabolites and targeting one of these carbohydrates could potentially impede early gut establishment of the pathogen. Interestingly, the presence of additional E. coli competitor strains significantly alters the fitness of S. Tm carbohydrate mutants in vivo (Fig 2C). This was particularly true for the fitness of the S. Tm glycerol (ΔglpD) and mannose (ΔmanA) metabolic mutants which were affected by both E. coli 8178 and E. coli Z1331. While these effects were consistent across both E. coli strains, we also observed strain-specific changes. Particularly, the fitness of the S. Tm ΔfruK mutant, while relatively unchanged by E. coli 8178 (C.I from 0.632 to 0.588), decreased significantly in the presence of E. coli Z1331 (C.I = 0.117). More interestingly, the addition of E. coli 8178 significantly impaired the fitness of the S. Tm ΔgalK mutant, as evidenced by an almost 50% reduction in the competitive index, from 0.501 to 0.261—an effect not observed in the presence of E. coli Z1331 (Fig 2C). Given the competitive interaction between S. Tm and E. coli 8178 (but not E. coli Z1331, Fig 1B and 1C), we decided to focus on S. Tm metabolic genes that were exclusively affected by E. coli 8178 while remaining unaffected by E. coli Z1331. This highlighted galK, and broadly, galactose metabolism as a strong candidate governing E. coli 8178-mediated competition against S. Tm, which we selected for further investigation.

E. coli 8178`s restrictions of S. Tm early establishment is centred on galactose

Galactose metabolism is widely conserved across Enterobacteriaceae and is considered a core component of their metabolic repertoire [8,40]. This is particularly evident in E. coli 8178 and E. coli Z1331 strains which we tested and confirmed were capable of using galactose as a carbon source in vitro (S3A Fig). However, it remains unclear whether galactose consumption enhances intestinal colonization of these strains. To evaluate the role of galactose metabolism in E. coli within an in vivo context, we generated ΔgalK mutants in both E. coli 8178 and E. coli Z1331 backgrounds and assessed their fitness in streptomycin-pretreated 129S6/SvEvTac mice. When inoculated with a 1:1 mixture of WT and galK-deficient E. coli 8178, the WT strain demonstrated a growth advantage over the ΔgalK mutant (C.I < 1), indicating that galactose metabolism is important for E. coli 8178 colonization of the gut (Fig 3A). In contrast, E. coli Z1331 did not show a similar dependency on galactose for intestinal colonization, despite both strains metabolizing galactose in vitro. We next explored how the galactose utilization of these E. coli strains changes in the presence of S. Tm. Under these conditions, the E. coli 8178 ΔgalK mutant showed an even greater fitness disadvantage compared to the condition without S. Tm, underscoring the importance of galactose for E. coli 8178 growth, especially when S. Tm is present (Fig 3A). In contrast, the fitness of the E. coli Z1331 ΔgalK mutant remained neutral and unchanged in the presence of S. Tm. To further confirm the capacity of E. coli 8178 to actively utilize galactose, we measured and compared S. Tm galactose-associated fitness in the presence of either the WT or galK-deficient E. coli 8178 strain. We hypothesized that co-inoculation with an E. coli strain incapable of using galactose in vivo would deplete other carbohydrates (besides galactose) even more efficiently that the WT E. coli 8178 and thereby accentuate the reliance of S. Tm on galactose. This in turn, should further exacerbate the competitive attenuation of the S. Tm galK mutant compared to WT S. Tm. Consistent with this hypothesis, S. Tm exhibited a significantly greater dependence on galactose when co-inoculated with a galK-deficient E. coli 8178 strain. This was shown by a S. Tm galK competitive index of approximately 0.01, which is 26 times lower than in the presence of the WT E. coli 8178 strain (C.I = 0.26) (Figs 3B and S3B). Together, these findings demonstrate that galactose metabolism is essential for the gut luminal growth of E. coli 8178, suggesting that it may be selectively exploited by this strain during intestinal colonization.

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Fig 3. Galactose utilization by E. coli 8178 is strain-specific and facilitates the early inhibition of S. Tm growth in the gut.

(A) Fitness of the galK-deficient E. coli strain in vivo. Streptomycin-pretreated 129S6/SvEvTac mice were infected with both the E. coli WT and ΔgalK strains, either in the presence or absence of the WT S. Tm (+ S. Tm). The competitive index of the ΔgalK mutant in E. coli 8178 (left) and Z1331 (right) at 24 h post-infection (p.i.) are plotted. (B) Effect of E. coli 8178 on the fitness of galK-deficient S. Tm in vivo. Streptomycin-pretreated 129S6/SvEvTac mice were infected with both the S. Tm WT and ΔgalK strains, in the presence of either the WT or galK-deficient E. coli 8178. The competitive indexes at 24 h p.i. of the S. Tm ΔgalK mutant are plotted across these two conditions. (C) Competitiveness of the E. coli 8178 ΔgalK mutant against S. Tm. The S. Tm load at 24 h p.i. is plotted and compared between S. Tm mono-infected and S. Tm + E. coli co-infected mice. The strains tested are indicated. (A-B) Dotted line: Fitness expected for a fitness-neutral mutation. (A-C) All experiments are presented in a box-and-whiskers plot, showing the minimum to maximum values, median, and interquartile range (25^th to 75^th percentiles). The bar plots show the median. Two-tailed Mann–Whitney U tests to compare 2 groups in each panel. P ≥ 0.05 not significant (ns), p < 0.05 (*), p < 0.01 (**). A minimum of 5 mice (n ≥ 5) were used for each experimental group. CFU: colony forming units.

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Based on these findings, we hypothesized that E. coli 8178 exploits galactose and consequently attenuates the early gut establishment of S. Tm. To test this, we assessed the ability of the E. coli 8178 ΔgalK mutant to restrict S. Tm growth in streptomycin-pretreated 129S6/SvEvTac mice. In contrast to the E. coli 8178 WT, S. Tm colonization was partially restored in mice co-infected with the E. coli 8178 galK mutant (Figs 3C and S3C). Similar observations were made when substituting our Salmonella model organism SL1344 by a different strain (ATCC 14028) (S3D Fig). This effect was not due to variations in colonization efficacy, as both the E. coli 8178 WT and galK mutant colonize the gut to a similar extent when competing against S. Tm (S3E Fig). While our complementation attempts were unsuccessful, this phenotype remained consistent across multiple galK-deficient E. coli 8178 clones. We also employed a whole genome sequencing approach that ruled out the presence of background mutations in genes other than the galK locus. Combined, this indicates that utilization of galactose by E. coli 8178 limits S. Tm establishment through competitive nutrient exploitation.

Discussion

Here we report that galactose is a key metabolite in mitigating early gut establishment of S. Tm by the mouse commensal E. coli 8178. This observation is strain-dependent, as a different E. coli isolate, Z1331, did not exhibit this effect.

Characterization of the S. Tm growth mitigation was achieved using a previously published, quality-controlled, and rationally designed WISH-barcoded S. Tm mutant pool representing the metabolic capacity of Salmonella [8]. This allowed to highlight how the presence of an additional strain affects S. Tm metabolic requirements during gut-luminal growth. Simultaneous testing of multiple mutants within a single animal can efficiently identify important metabolic pathways, reducing costs and the number of animals needed for a comprehensive analysis [41]. There are two main methodologies for assessing mutant fitness in high-throughput scenarios: randomly barcoded transposon insertion sequencing (RB-TnSeq, [42]) and rationally designed libraries, as used in our study. The latter has technical advantages, utilizing smaller strain libraries for robust mutant representation in niches like the mouse gut (which is often characterized by S. Tm population bottlenecks) and enabling simpler bioinformatics, as each mutant is WISH-barcoded for a specific gene inactivation. Testing the S. Tm mutant pool in competition with different E. coli isolates allowed us to report the strain-specific exploitation of galactose as a novel strategy employed by commensal E. coli to mitigate S. Tm’s early gut invasion.

Freter’s nutrient niche theory suggests that for a bacterium to successfully colonize a niche, it must be the most efficient at metabolizing at least one specific nutrient within that environment [43,44]. In recent years, galactitol has been identified as an important substrate for Enterobacteriaceae, specifically for Klebsiella spp., E. coli spp., and S. Tm [33,45–47]. As a result, galactitol was shown to drive metabolic competition between S. Tm and other Enterobacteriaceae strains [33,47]. In the current study, we identified galactose as an additional carbohydrate that mediates colonization resistance against S. Tm SL1344. Galactitol is a sugar alcohol and the reduction product of galactose. This circumstance requires bacterial oxidation of galactitol before it can be degraded via glycolysis, increasing the metabolic cost of galactitol utilization compared to galactose. Unlike galactitol, which is less common, galactose is relatively abundant in the diet [48–50] and in the cecum contents of mice with a complex microbiota and gnotobiotic models [6,8]. This is also relevant for the caecal contents of streptomycin-pretreated mice, such as those used in the present study, which were shown to exhibit approximately 2 mM galactose [6]. Taking this information into consideration, we propose that galactose is a key nutrient that can mediate Enterobacteriaceae-Enterobacteriaceae competition in the gut. In line with this, galactose was shown to act as an important nutrient that promotes S. Tm growth in the gut [51]. Furthermore, galactose degradation genes in Enterobacteriaceae have been identified as part of the core genome, underscoring the significance of galactose as a specific niche for Enterobacteriaceae [8]. While these observations support the idea of a galactose-rich diet as mediator for S. Tm elimination by commensal Enterobacteriaceae, it is important to note that galactose supplementation experiments have only partially, but not fully, rescued S. Tm survival against E. coli 8178. This might be attributable to the host’s relatively high efficiency in absorbing galactose or to the already sufficient levels of galactose in the caecal contents of our mice, making galactose supplementation ineffective. Despite both E. coli 8178 and E. coli Z1331 having similar in vitro growth on galactose as the sole carbon source, only E. coli 8178 was able to exploit it and attenuate S. Tm growth in the gut. This suggests that the metabolic repertoire of a given bacterial strain alone is insufficient to predict colonization or competitive interactions in vivo. The challenge of defining bacterial nutrient preferences in vivo stems not only from our limited understanding of the bacterial factors that drive the hierarchical consumption of carbon substrates [52] but also from the highly complex and dynamic environment that bacteria encounter within the gut microbiota [53]. Although both E. coli 8178 and Z1331 can metabolize galactose under defined in vitro conditions—where D-galactose is the sole and abundant carbon source—translating this into the gastrointestinal setting may reveal differential requirements for galactose metabolism and other growth-fuelling metabolites. Metabolic exploitation can also be influenced by the sequence of the transcriptional regulator which may differ at the strain level. In some E. coli serovars, the start codon of the transcriptional regulator LacI for lactose metabolism is GTG, leading to lower expression of the repressor. This results in higher basal expression of the lactose-utilizing genes, giving these strains a metabolic advantage over isogenic strains with the ATG start codon in the lacI gene [54]. A similar observation was made in Clostridioides difficile, in which the transcriptional regulator for trehalose in some epidemic ribotypes has acquired a mutation that allows them to metabolize trehalose at lower concentrations [55]. Both adaptations provide a competitive advantage in colonization and highlight the extent of strain adaptation required to efficiently utilize a specific niche. Understanding nutrient preferences at the strain-specific level could introduce novel concepts in basic microbiology while also providing optimized strategies for enhancing probiotic efficiency. Taken together, our data indicate that galactose is a crucial nutrient niche for the establishment of S. Tm and its exploitation can be affected by the presence of endogenous and specific E. coli strains. Similar observations will guide the design of optimized microbiota-based strategies aimed at limiting these nutrients to inhibit or even prevent pathogen invasion.

Methods

Animals and ethic statements

Male and female 8–12 weeks old 129S6/SvEvTac (Jackson Laboratory) mice were randomly assigned to experimental groups and used in this study. The mice were housed under SPF conditions in individually ventilated cages at the EPIC mouse facility, ETH Zurich. All animal experiments were conducted in accordance with Swiss and cantonal regulations and were reviewed and approved by the Tierversuchskommission, Kantonales Veterinäramt Zürich under license ZH158/2019, ZH108/2022, and ZH109/2022, in compliance with the cantonal and Swiss legislation.

Strains, media, and chemicals

All strains, plasmids and oligonucleotides used in this study are listed in S1–S3 Tables. Custom oligonucleotides were synthetized by Microsynth AG (Balgach, Switzerland). E. coli 8178 and Z1331 strains originate from previous work [14,35]. The S. Tm mutant pool was designed in [8]. Bacterial strains were routinely cultured in lysogeny broth (LB) with or without 1% agar-agar. Mutant selection was carried out using antibiotics: streptomycin (100 μg/ml), carbenicillin (100 μg/ml), kanamycin (50 μg/ml), and chloramphenicol (30 μg/ml). Gene deletions in E. coli 8178 and Z1331 were performed using a modified lambda red recombinase one-step inactivation method [56]. In brief, kanamycin resistance cassettes (kanamycin for deletions, were PCR-amplified (Phusion DNA Polymerase, Sigma-Aldrich)) with primers containing 50-nucleotide homologous regions flanking the target site. Electroporation of these PCR products into E. coli cells expressing lambda red recombinase from the pSIM5 plasmid allowed for mutant generation, which were then selected on antibiotic plates [57]. Gene deletions were confirmed by colony PCR and whole-genome sequencing, with a particular focus on the E. coli 8178 ΔgalK mutant (PRJEB85163).

Mouse infection experiments

The 8- to 12-week-old mice were orally pretreated with streptomycin (25 mg) 24 h before inoculation [58]. S. Tm and E. coli cultures were individually grown in LB at 37°C for 4 h and washed twice with a phosphate-buffered saline solution (PBS: 137 mM NaCl, 2.7 mM KCl, 10 mM Na₂HPO_4, and 1.8 mM KH₂PO). The S. Tm pool was cultured in a similar fashion from pre-mixed cryo stocks. Prior to colonization experiments, E. coli strains were electroporated with the pRSF1010 (P3) plasmid from Salmonella enterica serovar Typhimurium SL1344 which confers streptomycin resistance [59]. Each mouse received a single oral dose of 50 μl containing approximately 5 x 10⁷ colony forming units (cfu) of an inoculum mixture consisting of equal ratios of the indicated strains. Faecal samples were collected 24 hours post-infection, and animals were euthanized via CO₂ asphyxiation on day 1 post-infection. Faecal samples were then suspended in 1 ml of PBS and homogenized using a TissueLyser (Qiagen). Bacterial loads were quantified by plating the homogenized suspension on selective MacConkey or LB agar plates. In competition assays involving two bacterial strains (WT and mutant), the mutant’s bacterial load was directly quantified by plating on antibiotic-containing agar. Conversely, the bacterial load of the WT strain was derived from the total colony count on antibiotic-free plates using the formula: cfu_WT = cfu_total − cfu_mutant. The load of each mutant strain was then normalized to its initial inoculum, and this value was used to calculate the normalized competitive index (C.I.) to assess its fitness relative to the WT strain. The C.I. for each mutant was determined by taking the ratio of cfu_mutant to cfu_WT, divided by the ratio of the mutant and WT strains in the inoculum.

Evaluation of S. Tm metabolic mutant fitness via barcode counting

Preparation and analysis of in vivo samples containing the S. Tm WISH barcoded mutant pool was achieved as previously reported [8]. Specifically, faecal S. Tm cells were cultivated in LB medium supplemented with carbenicillin to select for WISH-barcoded strains. Following enrichment, cells were pelleted and stored at -20°C. DNA was extracted from the thawed pellets using the Qiagen Mini DNA kit, following the manufacturer’s protocol. Amplification of WISH barcodes via PCR was performed using the DreamTaq MasterMix (Thermo Fisher Scientific) under the following cycling conditions: (1) initial denaturation at 95°C for 3 min, (2) denaturation at 95°C for 30 sec, (3) annealing at 55°C for 30 sec, (4) extension at 72°C for 20 sec, repeated for 25 cycles, followed by (5) a final extension at 72°C for 10 min. The resulting PCR products were purified (Macherey-Nagel) and subsequently indexed by a second PCR with unique dual index primers using the following program: (1) 95°C for 3 min, (2) 95°C for 30 sec, (3) 55°C for 30 sec, (4) 72°C for 20 sec, repeated for 10 cycles, with a (5) final extension at 72°C for 3 min. The indexed products were checked by gel electrophoresis (1% w/v agarose in Tris, acetate, EDTA buffer: 40 mM tris-acetate, 1 mM EDTA), pooled based on band intensity, and purified using AMPure beads (Beckman Coulter) for library preparation. Amplicon sequencing was carried out by BMKGENE (Münster, Germany) using the Novaseq platform, with 150 bp paired-end reads at a target output of 1 G per sample. Following sequencing, reads were demultiplexed and WISH-barcodes were counted using the mBARq software [60]. Misreads or mutations of up to five bases were assigned to the closest matching WISH-tag sequence. WISH-barcode counts for each mouse are provided in S1 Data file. These counts were then used to calculate competitive fitness and Shannon evenness scores across seven wild-type strains. WISH counts ≤ 10 were excluded from further analysis, setting the detection limit as previously described by [38].

In vitro galactose utilization assay

Biolog PM1 MicroPlates (BIOLOG; [61]) were used for metabolic profiling of S. Tm and E. coli strains according to the manufacturer’s protocol. Bacteria were grown overnight in M9 minimal medium with 25 mM pyruvate as the sole carbon source at 37°C with shaking. They were then washed and resuspended in M9 medium without pyruvate to an OD₆₀₀ of 0.056. 100 μl of this suspension was added to each well of the microplate. Plates were sealed with parafilm and incubated at 37°C. OD₆₀₀ was measured every 10 minutes for 12 hours with orbital shaking at 282 rpm using a BioTek Synergy H1 Microplate spectrophotometer (Agilent).

Statistical analysis

Statistical analyses and data visualization were conducted using GraphPad Prism version 9.2.0 for Windows (GraphPad Software, La Jolla, CA, USA). For comparisons between two groups, the unpaired Mann–Whitney U-test was employed to evaluate statistical significance, based on rank comparison. P values < 0.05 were considered to indicate statistical significance.

Materials availability

Mouse lines used in this study can be obtained from Jackson laboratories.

Supporting information

S1 Fig. E. coli 8178 and Z1331 loads in co-infected mice.

(A). The competitive index between S. Tm and E. coli from Fig 1B and 1C are shown. The box-and-whiskers plot represent the minimum to maximum values, median, and interquartile range (25^th to 75^th percentiles). Two-tailed Mann–Whitney U tests to compare 2 groups in each panel. P < 0.01 (**).

https://doi.org/10.1371/journal.ppat.1013232.s001

(TIFF)

S2 Fig. Quality-control of the S. Tm mutant pool analysis in vivo.

(A) The Shannon evenness score at 24 h post-infection (p.i) is presented for each condition tested. A score close to 1 signifies an even distribution of the 7 S. Tm wild-type strains, reflecting the absence of a bottleneck effect. The median and standard deviation are shown, with the dotted line representing the threshold (0.9) below which samples were excluded from analysis. (B) Fitness of the internal S. Tm metabolic mutant controls. The competitive index of the S. Tm ΔdcuABC (left) and Δfrd (mutant) at 24 h p.i is plotted for each condition tested. Data are presented in a box-and-whiskers plot, showing the minimum to maximum values, median, and interquartile range (25^th to 75^th percentiles). The bar plots show the median. Dotted line: competitive index expected for a fitness-neutral mutation. (A-B) A minimum of 6 mice (n ≥ 6) were used for each condition tested.

https://doi.org/10.1371/journal.ppat.1013232.s002

(TIFF)

S3 Fig. E. coli 8178 and Z1331 grow on galactose as the sole carbon source.

(A) In vitro growth on galactose as the sole carbon source was assessed for E. coli 8178 and Z1331 strains. Growth was measured in a Biolog PM1 microplate, with data plotted as ΔOD_600nm for 3 hours and 12 hours for each bacterium as indicated. (B) Bacterial loads of the WT and galK-deficient S. Tm strains in presence of the WT (left) or ΔgalK (right) E. coli 8178 are plotted as CFU per gram of feces at 24 h p.i (from Fig 3B). (C) Competitive index at 24 h p.i between S. Tm and E. coli (from Fig 3C). (D) The S. Tm ATCC 14028 loads at 24 h p.i. are plotted and compared between S. Tm mono-infected and S. Tm + E. coli 8178 co-infected mice. (E) E. coli 8178 loads in S. Tm + E. coli co-infected mice (from Figs 3C and S3D). (B-E) Data are presented in a box-and-whiskers plot, showing the minimum to maximum values, median, and interquartile range (25^th to 75^th percentiles). The bar plots show the median. Two-tailed Mann–Whitney U tests to compare 2 groups in each panel. P ≥ 0.05 not significant (ns), p < 0.01 (**).

https://doi.org/10.1371/journal.ppat.1013232.s003

(TIFF)

S1 Table. Bacterial strains used in this study.

https://doi.org/10.1371/journal.ppat.1013232.s004

(XLSX)

S2 Table. Plasmid used in this study.

https://doi.org/10.1371/journal.ppat.1013232.s005

(XLSX)

S3 Table. Oligonucleotides used in this study.

https://doi.org/10.1371/journal.ppat.1013232.s006

(XLSX)

S4 Table. List of abbreviations.

https://doi.org/10.1371/journal.ppat.1013232.s007

(XLSX)

S1 Data. Raw data from this study.

https://doi.org/10.1371/journal.ppat.1013232.s008

(XLSX)

Acknowledgments

We would like to thank members of the Hardt group for their comments on the paper. We also thank the EPIC RCHCI staff for support with the animal work.

References

1. WHO U. WHO estimates of the global burden of foodborne diseases: foodborne diseases burden epidemiology reference group 2007-2015. World Health Organization; Geneva, Switzerland: 2015.
2. Besser JM. Salmonella epidemiology: A whirlwind of change. Food Microbiol. 2018;71:55–9. pmid:29366469
- View Article
- PubMed/NCBI
- Google Scholar
3. Herzog MK-M, Peters A, Shayya N, Cazzaniga M, Kaka Bra K, Arora T, et al. Comparing Campylobacter jejuni to three other enteric pathogens in OligoMM12 mice reveals pathogen-specific host and microbiota responses. Gut Microbes. 2025;17(1):2447832. pmid:39835346
- View Article
- PubMed/NCBI
- Google Scholar
4. EFSA. The European Union One Health 2021 Zoonoses Report. EFSA J. 2022;20(12):e07666.
- View Article
- Google Scholar
5. Wotzka SY, Nguyen BD, Hardt W-D. Salmonella Typhimurium diarrhea reveals basic principles of enteropathogen infection and disease-promoted DNA exchange. Cell Host Microbe. 2017;21(4):443–54. pmid:28407482
- View Article
- PubMed/NCBI
- Google Scholar
6. Nguyen BD, Sintsova A, Schubert C, Sichert A, Scheidegger C, Näf J, et al. Salmonella Typhimurium screen identifies shifts in mixed-acid fermentation during gut colonization. Cell Host Microbe. 2024;32(10):1758–1773.e4. pmid:39293436
- View Article
- PubMed/NCBI
- Google Scholar
7. Nguyen BD, Cuenca V M, Hartl J, Gül E, Bauer R, Meile S, et al. Import of aspartate and malate by DcuABC Drives H2/fumarate respiration to promote initial Salmonella Gut-Lumen Colonization in Mice. Cell Host Microbe. 2020;27(6):922–936.e6. pmid:32416061
- View Article
- PubMed/NCBI
- Google Scholar
8. Schubert C, Nguyen BD, Sichert A, Näpflin N, Sintsova A, Feer L, et al. Monosaccharides drive Salmonella gut colonization in a context-dependent or -independent manner. Nat Commun. 2025;16(1):1735. pmid:39966379
- View Article
- PubMed/NCBI
- Google Scholar
9. Rogers AWL, Radlinski LC, Nguyen H, Tiffany CR, Carvalho TP, Masson HLP, et al. Salmonella re-engineers the intestinal environment to break colonization resistance in the presence of a compositionally intact microbiota. Cell Host Microbe. 2024;32(10):1774–1786.e9. pmid:39181125
- View Article
- PubMed/NCBI
- Google Scholar
10. Lupp C, Robertson ML, Wickham ME, Sekirov I, Champion OL, Gaynor EC, et al. Host-mediated inflammation disrupts the intestinal microbiota and promotes the overgrowth of Enterobacteriaceae. Cell Host Microbe. 2007;2(2):119–29. pmid:18005726
- View Article
- PubMed/NCBI
- Google Scholar
11. Stecher B, Robbiani R, Walker AW, Westendorf AM, Barthel M, Kremer M, et al. Salmonella enterica serovar typhimurium exploits inflammation to compete with the intestinal microbiota. PLoS Biol. 2007;5(10):2177–89. pmid:17760501
- View Article
- PubMed/NCBI
- Google Scholar
12. Winter SE, Thiennimitr P, Winter MG, Butler BP, Huseby DL, Crawford RW, et al. Gut inflammation provides a respiratory electron acceptor for Salmonella. Nature. 2010;467(7314):426–9. pmid:20864996
- View Article
- PubMed/NCBI
- Google Scholar
13. Thiennimitr P, Winter SE, Winter MG, Xavier MN, Tolstikov V, Huseby DL, et al. Intestinal inflammation allows Salmonella to use ethanolamine to compete with the microbiota. Proc Natl Acad Sci U S A. 2011;108(42):17480–5. pmid:21969563
- View Article
- PubMed/NCBI
- Google Scholar
14. Stecher B, Denzler R, Maier L, Bernet F, Sanders MJ, Pickard DJ, et al. Gut inflammation can boost horizontal gene transfer between pathogenic and commensal Enterobacteriaceae. Proc Natl Acad Sci U S A. 2012;109(4):1269–74. pmid:22232693
- View Article
- PubMed/NCBI
- Google Scholar
15. Maier L, Vyas R, Cordova CD, Lindsay H, Schmidt TSB, Brugiroux S, et al. Microbiota-derived hydrogen fuels Salmonella typhimurium invasion of the gut ecosystem. Cell Host Microbe. 2013;14(6):641–51. pmid:24331462
- View Article
- PubMed/NCBI
- Google Scholar
16. Faber F, Thiennimitr P, Spiga L, Byndloss MX, Litvak Y, Lawhon S, et al. Respiration of microbiota-derived 1,2-propanediol drives Salmonella expansion during Colitis. PLoS Pathog. 2017;13(1):e1006129. pmid:28056091
- View Article
- PubMed/NCBI
- Google Scholar
17. Gillis CC, Hughes ER, Spiga L, Winter MG, Zhu W, Furtado de Carvalho T, et al. Dysbiosis-associated change in host metabolism generates lactate to support Salmonella growth. Cell Host Microbe. 2018;23(4):570. pmid:29649446
- View Article
- PubMed/NCBI
- Google Scholar
18. Fattinger SA, Geiser P, Samperio Ventayol P, Di Martino ML, Furter M, Felmy B, et al. Epithelium-autonomous NAIP/NLRC4 prevents TNF-driven inflammatory destruction of the gut epithelial barrier in Salmonella-infected mice. Mucosal Immunol. 2021;14(3):615–29. pmid:33731826
- View Article
- PubMed/NCBI
- Google Scholar
19. Bohnhoff M, Miller CP. Enhanced susceptibility to Salmonella infection in streptomycin-treated mice. J Infect Dis. 1962;111:117–27. pmid:13968487
- View Article
- PubMed/NCBI
- Google Scholar
20. Buffie CG, Pamer EG. Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol. 2013;13(11):790–801. pmid:24096337
- View Article
- PubMed/NCBI
- Google Scholar
21. Caballero-Flores G, Pickard JM, Núñez G. Microbiota-mediated colonization resistance: mechanisms and regulation. Nat Rev Microbiol. 2023;21(6):347–60. pmid:36539611
- View Article
- PubMed/NCBI
- Google Scholar
22. Brugiroux S, Beutler M, Pfann C, Garzetti D, Ruscheweyh H-J, Ring D, et al. Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium. Nat Microbiol. 2016;2:16215. pmid:27869789
- View Article
- PubMed/NCBI
- Google Scholar
23. Sorbara MT, Pamer EG. Interbacterial mechanisms of colonization resistance and the strategies pathogens use to overcome them. Mucosal Immunol. 2019;12(1):1–9. pmid:29988120
- View Article
- PubMed/NCBI
- Google Scholar
24. Rogers AWL, Tsolis RM, Bäumler AJ. Salmonella versus the Microbiome. Microbiol Mol Biol Rev. 2020;85(1):e00027–19. pmid:33361269
- View Article
- PubMed/NCBI
- Google Scholar
25. Spragge F, Bakkeren E, Jahn MT, B N Araujo E, Pearson CF, Wang X, et al. Microbiome diversity protects against pathogens by nutrient blocking. Science. 2023;382(6676):eadj3502. pmid:38096285
- View Article
- PubMed/NCBI
- Google Scholar
26. Jacobson A, Lam L, Rajendram M, Tamburini F, Honeycutt J, Pham T, et al. A gut commensal-produced metabolite mediates colonization resistance to Salmonella infection. Cell Host Microbe. 2018;24(2):296-307.e7. pmid:30057174
- View Article
- PubMed/NCBI
- Google Scholar
27. Sassone-Corsi M, Nuccio S-P, Liu H, Hernandez D, Vu CT, Takahashi AA, et al. Microcins mediate competition among Enterobacteriaceae in the inflamed gut. Nature. 2016;540(7632):280–3. pmid:27798599
- View Article
- PubMed/NCBI
- Google Scholar
28. Cherrak Y, Salazar MA, Yilmaz K, Kreuzer M, Hardt W-D. Commensal E. coli limits Salmonella gut invasion during inflammation by producing toxin-bound siderophores in a tonB-dependent manner. PLoS Biol. 2024;22(6):e3002616. pmid:38865418
- View Article
- PubMed/NCBI
- Google Scholar
29. Deriu E, Liu JZ, Pezeshki M, Edwards RA, Ochoa RJ, Contreras H, et al. Probiotic bacteria reduce salmonella typhimurium intestinal colonization by competing for iron. Cell Host Microbe. 2013;14(1):26–37. pmid:23870311
- View Article
- PubMed/NCBI
- Google Scholar
30. Litvak Y, Mon KKZ, Nguyen H, Chanthavixay G, Liou M, Velazquez EM, et al. Commensal Enterobacteriaceae protect against Salmonella Colonization through oxygen competition. Cell Host Microbe. 2019;25(1):128–139.e5. pmid:30629913
- View Article
- PubMed/NCBI
- Google Scholar
31. Velazquez EM, Nguyen H, Heasley KT, Saechao CH, Gil LM, Rogers AWL, et al. Endogenous Enterobacteriaceae underlie variation in susceptibility to Salmonella infection. Nat Microbiol. 2019;4(6):1057–64. pmid:30911125
- View Article
- PubMed/NCBI
- Google Scholar
32. Liou MJ, Miller BM, Litvak Y, Nguyen H, Natwick DE, Savage HP, et al. Host cells subdivide nutrient niches into discrete biogeographical microhabitats for gut microbes. Cell Host Microbe. 2022;30(6):836–847.e6. pmid:35568027
- View Article
- PubMed/NCBI
- Google Scholar
33. Eberl C, Weiss AS, Jochum LM, Durai Raj AC, Ring D, Hussain S, et al. E. coli enhance colonization resistance against Salmonella Typhimurium by competing for galactitol, a context-dependent limiting carbon source. Cell Host Microbe. 2021;29(11):1680–92
- View Article
- Google Scholar
34. Cherrak Y, Younes AA, Perez-Molphe-Montoya E, Maurer L, Yilmaz K, Enz U, et al. Neutrophil recruitment during intestinal inflammation primes Salmonella elimination by commensal E. coli in a context-dependent manner. Cell Host Microbe. 2025;33(3):358–72.
- View Article
- Google Scholar
35. Wotzka SY, Kreuzer M, Maier L, Zünd M, Schlumberger M, Nguyen B, et al. Microbiota stability in healthy individuals after single-dose lactulose challenge-A randomized controlled study. PLoS One. 2018;13(10):e0206214. pmid:30359438
- View Article
- PubMed/NCBI
- Google Scholar
36. Laganenka L, Lee J-W, Malfertheiner L, Dieterich CL, Fuchs L, Piel J, et al. Chemotaxis and autoinducer-2 signalling mediate colonization and contribute to co-existence of Escherichia coli strains in the murine gut. Nat Microbiol. 2023;8(2):204–17. pmid:36624229
- View Article
- PubMed/NCBI
- Google Scholar
37. Laganenka L, Schubert C, Sichert A, Kalita I, Barthel M, Nguyen BD, et al. Interplay between chemotaxis, quorum sensing, and metabolism regulates Escherichia coli-Salmonella Typhimurium interactions in vivo. PLoS Pathog. 2025;21(5):e1013156. pmid:40315408
- View Article
- PubMed/NCBI
- Google Scholar
38. Daniel BBJ, Steiger Y, Sintsova A, Field CM, Nguyen BD, Schubert C, et al. Assessing microbiome population dynamics using wild-type isogenic standardized hybrid (WISH)-tags. Nat Microbiol. 2024;9(4):1103–16. pmid:38503975
- View Article
- PubMed/NCBI
- Google Scholar
39. Maier L, Diard M, Sellin ME, Chouffane E-S, Trautwein-Weidner K, Periaswamy B, et al. Granulocytes impose a tight bottleneck upon the gut luminal pathogen population during Salmonella typhimurium colitis. PLoS Pathog. 2014;10(12):e1004557. pmid:25522364
- View Article
- PubMed/NCBI
- Google Scholar
40. Näpflin N, Schubert C, Malfertheiner L, Hardt W-D, von Mering C. Unravelling the Core and Accessory Genome Diversity of Enterobacteriaceaein Carbon Metabolism. bioRxiv. 2025.
- View Article
- Google Scholar
41. Cain AK, Barquist L, Goodman AL, Paulsen IT, Parkhill J, van Opijnen T. A decade of advances in transposon-insertion sequencing. Nat Rev Genet. 2020;21(9):526–40. pmid:32533119
- View Article
- PubMed/NCBI
- Google Scholar
42. van Opijnen T, Bodi KL, Camilli A. Tn-seq: high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms. Nat Methods. 2009;6(10):767–72. pmid:19767758
- View Article
- PubMed/NCBI
- Google Scholar
43. Freter R, Brickner H, Fekete J, Vickerman MM, Carey KE. Survival and implantation of Escherichia coli in the intestinal tract. Infect Immun. 1983;39(2):686–703. pmid:6339389
- View Article
- PubMed/NCBI
- Google Scholar
44. Freter R, Brickner H, Botney M, Cleven D, Aranki A. Mechanisms that control bacterial populations in continuous-flow culture models of mouse large intestinal flora. Infect Immun. 1983;39(2):676–85. pmid:6339388
- View Article
- PubMed/NCBI
- Google Scholar
45. Oliveira RA, Ng KM, Correia MB, Cabral V, Shi H, Sonnenburg JL, et al. Klebsiella michiganensis transmission enhances resistance to Enterobacteriaceae gut invasion by nutrition competition. Nat Microbiol. 2020;5(4):630–41. pmid:31959968
- View Article
- PubMed/NCBI
- Google Scholar
46. Gül E, Abi Younes A, Huuskonen J, Diawara C, Nguyen BD, Maurer L, et al. Differences in carbon metabolic capacity fuel co-existence and plasmid transfer between Salmonella strains in the mouse gut. Cell Host Microbe. 2023;31(7):1140–1153.e3. pmid:37348498
- View Article
- PubMed/NCBI
- Google Scholar
47. Osbelt L, Almási ÉDH, Wende M, Kienesberger S, Voltz A, Lesker TR, et al. Klebsiella oxytoca inhibits Salmonella infection through multiple microbiota-context-dependent mechanisms. Nat Microbiol. 2024;9(7):1792–811. pmid:38862602
- View Article
- PubMed/NCBI
- Google Scholar
48. Englyst KN, Liu S, Englyst HN. Nutritional characterization and measurement of dietary carbohydrates. Eur J Clin Nutr. 2007;61 Suppl 1:S19–39. pmid:17992185
- View Article
- PubMed/NCBI
- Google Scholar
49. Castillo JJ, Couture G, Bacalzo NP Jr, Chen Y, Chin EL, Blecksmith SE, et al. The development of the davis food glycopedia-a glycan encyclopedia of food. Nutrients. 2022;14(8):1639. pmid:35458202
- View Article
- PubMed/NCBI
- Google Scholar
50. Larke JA, Bacalzo N, Castillo JJ, Couture G, Chen Y, Xue Z, et al. Dietary intake of monosaccharides from foods is associated with characteristics of the gut microbiota and gastrointestinal inflammation in healthy US adults. J Nutr. 2023;153(1):106–19. pmid:36913444
- View Article
- PubMed/NCBI
- Google Scholar
51. Stecher B, Barthel M, Schlumberger MC, Haberli L, Rabsch W, Kremer M, et al. Motility allows S. Typhimurium to benefit from the mucosal defence. Cell Microbiol. 2008;10(5):1166–80. pmid:18241212
- View Article
- PubMed/NCBI
- Google Scholar
52. Okano H, Hermsen R, Kochanowski K, Hwa T. Regulation underlying hierarchical and simultaneous utilization of carbon substrates by flux sensors in Escherichia coli. Nat Microbiol. 2020;5(1):206–15. pmid:31819215
- View Article
- PubMed/NCBI
- Google Scholar
53. Zeng X, Xing X, Gupta M, Keber FC, Lopez JG, Lee Y-CJ, et al. Gut bacterial nutrient preferences quantified in vivo. Cell. 2022;185(18):3441–56.e19.
- View Article
- Google Scholar
54. Cherrak Y, Salazar MA, Näpflin N, Malfertheiner L, Herzog MK-M, Schubert C, et al. Non-canonical start codons confer context-dependent advantages in carbohydrate utilization for commensal E. coli in the murine gut. Nat Microbiol. 2024;9(10):2696–709. pmid:39160293
- View Article
- PubMed/NCBI
- Google Scholar
55. Collins J, Robinson C, Danhof H, Knetsch CW, van Leeuwen HC, Lawley TD, et al. Dietary trehalose enhances virulence of epidemic Clostridium difficile. Nature. 2018;553(7688):291–4. pmid:29310122
- View Article
- PubMed/NCBI
- Google Scholar
56. Datsenko KA, Wanner BL. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc Natl Acad Sci U S A. 2000;97(12):6640–5. pmid:10829079
- View Article
- PubMed/NCBI
- Google Scholar
57. Diner EJ, Garza-Sánchez F, Hayes CS. Genome engineering using targeted oligonucleotide libraries and functional selection. Strain Engineering: Methods and Protocols. 2011. pp. 71–82.
58. Barthel M, Hapfelmeier S, Quintanilla-Martínez L, Kremer M, Rohde M, Hogardt M, et al. Pretreatment of mice with streptomycin provides a Salmonella enterica serovar Typhimurium colitis model that allows analysis of both pathogen and host. Infect Immun. 2003;71(5):2839–58. pmid:12704158
- View Article
- PubMed/NCBI
- Google Scholar
59. Guerry P, van Embden J, Falkow S. Molecular nature of two nonconjugative plasmids carrying drug resistance genes. J Bacteriol. 1974;117(2):619–30. pmid:4590480
- View Article
- PubMed/NCBI
- Google Scholar
60. Sintsova A, Ruscheweyh H-J, Field CM, Feer L, Nguyen BD, Daniel B, et al. mBARq: a versatile and user-friendly framework for the analysis of DNA barcodes from transposon insertion libraries, knockout mutants, and isogenic strain populations. Bioinformatics. 2024;40(2):btae078. pmid:38341646
- View Article
- PubMed/NCBI
- Google Scholar
61. Bochner BR, Gadzinski P, Panomitros E. Phenotype microarrays for high-throughput phenotypic testing and assay of gene function. Genome Res. 2001;11(7):1246–55. pmid:11435407
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. WHO U. WHO estimates of the global burden of foodborne diseases: foodborne diseases burden epidemiology reference group 2007-2015. World Health Organization; Geneva, Switzerland: 2015.

[ref2] 2. Besser JM. Salmonella epidemiology: A whirlwind of change. Food Microbiol. 2018;71:55–9. pmid:29366469
View Article
PubMed/NCBI
Google Scholar

[3] View Article

[4] PubMed/NCBI

[5] Google Scholar

[ref3] 3. Herzog MK-M, Peters A, Shayya N, Cazzaniga M, Kaka Bra K, Arora T, et al. Comparing Campylobacter jejuni to three other enteric pathogens in OligoMM12 mice reveals pathogen-specific host and microbiota responses. Gut Microbes. 2025;17(1):2447832. pmid:39835346
View Article
PubMed/NCBI
Google Scholar

[7] View Article

[8] PubMed/NCBI

[9] Google Scholar

[ref4] 4. EFSA. The European Union One Health 2021 Zoonoses Report. EFSA J. 2022;20(12):e07666.
View Article
Google Scholar

[11] View Article

[12] Google Scholar

[ref5] 5. Wotzka SY, Nguyen BD, Hardt W-D. Salmonella Typhimurium diarrhea reveals basic principles of enteropathogen infection and disease-promoted DNA exchange. Cell Host Microbe. 2017;21(4):443–54. pmid:28407482
View Article
PubMed/NCBI
Google Scholar

[14] View Article

[15] PubMed/NCBI

[16] Google Scholar

[ref6] 6. Nguyen BD, Sintsova A, Schubert C, Sichert A, Scheidegger C, Näf J, et al. Salmonella Typhimurium screen identifies shifts in mixed-acid fermentation during gut colonization. Cell Host Microbe. 2024;32(10):1758–1773.e4. pmid:39293436
View Article
PubMed/NCBI
Google Scholar

[18] View Article

[19] PubMed/NCBI

[20] Google Scholar

[ref7] 7. Nguyen BD, Cuenca V M, Hartl J, Gül E, Bauer R, Meile S, et al. Import of aspartate and malate by DcuABC Drives H2/fumarate respiration to promote initial Salmonella Gut-Lumen Colonization in Mice. Cell Host Microbe. 2020;27(6):922–936.e6. pmid:32416061
View Article
PubMed/NCBI
Google Scholar

[22] View Article

[23] PubMed/NCBI

[24] Google Scholar

[ref8] 8. Schubert C, Nguyen BD, Sichert A, Näpflin N, Sintsova A, Feer L, et al. Monosaccharides drive Salmonella gut colonization in a context-dependent or -independent manner. Nat Commun. 2025;16(1):1735. pmid:39966379
View Article
PubMed/NCBI
Google Scholar

[26] View Article

[27] PubMed/NCBI

[28] Google Scholar

[ref9] 9. Rogers AWL, Radlinski LC, Nguyen H, Tiffany CR, Carvalho TP, Masson HLP, et al. Salmonella re-engineers the intestinal environment to break colonization resistance in the presence of a compositionally intact microbiota. Cell Host Microbe. 2024;32(10):1774–1786.e9. pmid:39181125
View Article
PubMed/NCBI
Google Scholar

[30] View Article

[31] PubMed/NCBI

[32] Google Scholar

[ref10] 10. Lupp C, Robertson ML, Wickham ME, Sekirov I, Champion OL, Gaynor EC, et al. Host-mediated inflammation disrupts the intestinal microbiota and promotes the overgrowth of Enterobacteriaceae. Cell Host Microbe. 2007;2(2):119–29. pmid:18005726
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref11] 11. Stecher B, Robbiani R, Walker AW, Westendorf AM, Barthel M, Kremer M, et al. Salmonella enterica serovar typhimurium exploits inflammation to compete with the intestinal microbiota. PLoS Biol. 2007;5(10):2177–89. pmid:17760501
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref12] 12. Winter SE, Thiennimitr P, Winter MG, Butler BP, Huseby DL, Crawford RW, et al. Gut inflammation provides a respiratory electron acceptor for Salmonella. Nature. 2010;467(7314):426–9. pmid:20864996
View Article
PubMed/NCBI
Google Scholar

[42] View Article

[43] PubMed/NCBI

[44] Google Scholar

[ref13] 13. Thiennimitr P, Winter SE, Winter MG, Xavier MN, Tolstikov V, Huseby DL, et al. Intestinal inflammation allows Salmonella to use ethanolamine to compete with the microbiota. Proc Natl Acad Sci U S A. 2011;108(42):17480–5. pmid:21969563
View Article
PubMed/NCBI
Google Scholar

[46] View Article

[47] PubMed/NCBI

[48] Google Scholar

[ref14] 14. Stecher B, Denzler R, Maier L, Bernet F, Sanders MJ, Pickard DJ, et al. Gut inflammation can boost horizontal gene transfer between pathogenic and commensal Enterobacteriaceae. Proc Natl Acad Sci U S A. 2012;109(4):1269–74. pmid:22232693
View Article
PubMed/NCBI
Google Scholar

[50] View Article

[51] PubMed/NCBI

[52] Google Scholar

[ref15] 15. Maier L, Vyas R, Cordova CD, Lindsay H, Schmidt TSB, Brugiroux S, et al. Microbiota-derived hydrogen fuels Salmonella typhimurium invasion of the gut ecosystem. Cell Host Microbe. 2013;14(6):641–51. pmid:24331462
View Article
PubMed/NCBI
Google Scholar

[54] View Article

[55] PubMed/NCBI

[56] Google Scholar

[ref16] 16. Faber F, Thiennimitr P, Spiga L, Byndloss MX, Litvak Y, Lawhon S, et al. Respiration of microbiota-derived 1,2-propanediol drives Salmonella expansion during Colitis. PLoS Pathog. 2017;13(1):e1006129. pmid:28056091
View Article
PubMed/NCBI
Google Scholar

[58] View Article

[59] PubMed/NCBI

[60] Google Scholar

[ref17] 17. Gillis CC, Hughes ER, Spiga L, Winter MG, Zhu W, Furtado de Carvalho T, et al. Dysbiosis-associated change in host metabolism generates lactate to support Salmonella growth. Cell Host Microbe. 2018;23(4):570. pmid:29649446
View Article
PubMed/NCBI
Google Scholar

[62] View Article

[63] PubMed/NCBI

[64] Google Scholar

[ref18] 18. Fattinger SA, Geiser P, Samperio Ventayol P, Di Martino ML, Furter M, Felmy B, et al. Epithelium-autonomous NAIP/NLRC4 prevents TNF-driven inflammatory destruction of the gut epithelial barrier in Salmonella-infected mice. Mucosal Immunol. 2021;14(3):615–29. pmid:33731826
View Article
PubMed/NCBI
Google Scholar

[66] View Article

[67] PubMed/NCBI

[68] Google Scholar

[ref19] 19. Bohnhoff M, Miller CP. Enhanced susceptibility to Salmonella infection in streptomycin-treated mice. J Infect Dis. 1962;111:117–27. pmid:13968487
View Article
PubMed/NCBI
Google Scholar

[70] View Article

[71] PubMed/NCBI

[72] Google Scholar

[ref20] 20. Buffie CG, Pamer EG. Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol. 2013;13(11):790–801. pmid:24096337
View Article
PubMed/NCBI
Google Scholar

[74] View Article

[75] PubMed/NCBI

[76] Google Scholar

[ref21] 21. Caballero-Flores G, Pickard JM, Núñez G. Microbiota-mediated colonization resistance: mechanisms and regulation. Nat Rev Microbiol. 2023;21(6):347–60. pmid:36539611
View Article
PubMed/NCBI
Google Scholar

[78] View Article

[79] PubMed/NCBI

[80] Google Scholar

[ref22] 22. Brugiroux S, Beutler M, Pfann C, Garzetti D, Ruscheweyh H-J, Ring D, et al. Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium. Nat Microbiol. 2016;2:16215. pmid:27869789
View Article
PubMed/NCBI
Google Scholar

[82] View Article

[83] PubMed/NCBI

[84] Google Scholar

[ref23] 23. Sorbara MT, Pamer EG. Interbacterial mechanisms of colonization resistance and the strategies pathogens use to overcome them. Mucosal Immunol. 2019;12(1):1–9. pmid:29988120
View Article
PubMed/NCBI
Google Scholar

[86] View Article

[87] PubMed/NCBI

[88] Google Scholar

[ref24] 24. Rogers AWL, Tsolis RM, Bäumler AJ. Salmonella versus the Microbiome. Microbiol Mol Biol Rev. 2020;85(1):e00027–19. pmid:33361269
View Article
PubMed/NCBI
Google Scholar

[90] View Article

[91] PubMed/NCBI

[92] Google Scholar

[ref25] 25. Spragge F, Bakkeren E, Jahn MT, B N Araujo E, Pearson CF, Wang X, et al. Microbiome diversity protects against pathogens by nutrient blocking. Science. 2023;382(6676):eadj3502. pmid:38096285
View Article
PubMed/NCBI
Google Scholar

[94] View Article

[95] PubMed/NCBI

[96] Google Scholar

[ref26] 26. Jacobson A, Lam L, Rajendram M, Tamburini F, Honeycutt J, Pham T, et al. A gut commensal-produced metabolite mediates colonization resistance to Salmonella infection. Cell Host Microbe. 2018;24(2):296-307.e7. pmid:30057174
View Article
PubMed/NCBI
Google Scholar

[98] View Article

[99] PubMed/NCBI

[100] Google Scholar

[ref27] 27. Sassone-Corsi M, Nuccio S-P, Liu H, Hernandez D, Vu CT, Takahashi AA, et al. Microcins mediate competition among Enterobacteriaceae in the inflamed gut. Nature. 2016;540(7632):280–3. pmid:27798599
View Article
PubMed/NCBI
Google Scholar

[102] View Article

[103] PubMed/NCBI

[104] Google Scholar

[ref28] 28. Cherrak Y, Salazar MA, Yilmaz K, Kreuzer M, Hardt W-D. Commensal E. coli limits Salmonella gut invasion during inflammation by producing toxin-bound siderophores in a tonB-dependent manner. PLoS Biol. 2024;22(6):e3002616. pmid:38865418
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref29] 29. Deriu E, Liu JZ, Pezeshki M, Edwards RA, Ochoa RJ, Contreras H, et al. Probiotic bacteria reduce salmonella typhimurium intestinal colonization by competing for iron. Cell Host Microbe. 2013;14(1):26–37. pmid:23870311
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref30] 30. Litvak Y, Mon KKZ, Nguyen H, Chanthavixay G, Liou M, Velazquez EM, et al. Commensal Enterobacteriaceae protect against Salmonella Colonization through oxygen competition. Cell Host Microbe. 2019;25(1):128–139.e5. pmid:30629913
View Article
PubMed/NCBI
Google Scholar

[114] View Article

[115] PubMed/NCBI

[116] Google Scholar

[ref31] 31. Velazquez EM, Nguyen H, Heasley KT, Saechao CH, Gil LM, Rogers AWL, et al. Endogenous Enterobacteriaceae underlie variation in susceptibility to Salmonella infection. Nat Microbiol. 2019;4(6):1057–64. pmid:30911125
View Article
PubMed/NCBI
Google Scholar

[118] View Article

[119] PubMed/NCBI

[120] Google Scholar

[ref32] 32. Liou MJ, Miller BM, Litvak Y, Nguyen H, Natwick DE, Savage HP, et al. Host cells subdivide nutrient niches into discrete biogeographical microhabitats for gut microbes. Cell Host Microbe. 2022;30(6):836–847.e6. pmid:35568027
View Article
PubMed/NCBI
Google Scholar

[122] View Article

[123] PubMed/NCBI

[124] Google Scholar

[ref33] 33. Eberl C, Weiss AS, Jochum LM, Durai Raj AC, Ring D, Hussain S, et al. E. coli enhance colonization resistance against Salmonella Typhimurium by competing for galactitol, a context-dependent limiting carbon source. Cell Host Microbe. 2021;29(11):1680–92
View Article
Google Scholar

[126] View Article

[127] Google Scholar

[ref34] 34. Cherrak Y, Younes AA, Perez-Molphe-Montoya E, Maurer L, Yilmaz K, Enz U, et al. Neutrophil recruitment during intestinal inflammation primes Salmonella elimination by commensal E. coli in a context-dependent manner. Cell Host Microbe. 2025;33(3):358–72.
View Article
Google Scholar

[129] View Article

[130] Google Scholar

[ref35] 35. Wotzka SY, Kreuzer M, Maier L, Zünd M, Schlumberger M, Nguyen B, et al. Microbiota stability in healthy individuals after single-dose lactulose challenge-A randomized controlled study. PLoS One. 2018;13(10):e0206214. pmid:30359438
View Article
PubMed/NCBI
Google Scholar

[132] View Article

[133] PubMed/NCBI

[134] Google Scholar

[ref36] 36. Laganenka L, Lee J-W, Malfertheiner L, Dieterich CL, Fuchs L, Piel J, et al. Chemotaxis and autoinducer-2 signalling mediate colonization and contribute to co-existence of Escherichia coli strains in the murine gut. Nat Microbiol. 2023;8(2):204–17. pmid:36624229
View Article
PubMed/NCBI
Google Scholar

[136] View Article

[137] PubMed/NCBI

[138] Google Scholar

[ref37] 37. Laganenka L, Schubert C, Sichert A, Kalita I, Barthel M, Nguyen BD, et al. Interplay between chemotaxis, quorum sensing, and metabolism regulates Escherichia coli-Salmonella Typhimurium interactions in vivo. PLoS Pathog. 2025;21(5):e1013156. pmid:40315408
View Article
PubMed/NCBI
Google Scholar

[140] View Article

[141] PubMed/NCBI

[142] Google Scholar

[ref38] 38. Daniel BBJ, Steiger Y, Sintsova A, Field CM, Nguyen BD, Schubert C, et al. Assessing microbiome population dynamics using wild-type isogenic standardized hybrid (WISH)-tags. Nat Microbiol. 2024;9(4):1103–16. pmid:38503975
View Article
PubMed/NCBI
Google Scholar

[144] View Article

[145] PubMed/NCBI

[146] Google Scholar

[ref39] 39. Maier L, Diard M, Sellin ME, Chouffane E-S, Trautwein-Weidner K, Periaswamy B, et al. Granulocytes impose a tight bottleneck upon the gut luminal pathogen population during Salmonella typhimurium colitis. PLoS Pathog. 2014;10(12):e1004557. pmid:25522364
View Article
PubMed/NCBI
Google Scholar

[148] View Article

[149] PubMed/NCBI

[150] Google Scholar

[ref40] 40. Näpflin N, Schubert C, Malfertheiner L, Hardt W-D, von Mering C. Unravelling the Core and Accessory Genome Diversity of Enterobacteriaceaein Carbon Metabolism. bioRxiv. 2025.
View Article
Google Scholar

[152] View Article

[153] Google Scholar

[ref41] 41. Cain AK, Barquist L, Goodman AL, Paulsen IT, Parkhill J, van Opijnen T. A decade of advances in transposon-insertion sequencing. Nat Rev Genet. 2020;21(9):526–40. pmid:32533119
View Article
PubMed/NCBI
Google Scholar

[155] View Article

[156] PubMed/NCBI

[157] Google Scholar

[ref42] 42. van Opijnen T, Bodi KL, Camilli A. Tn-seq: high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms. Nat Methods. 2009;6(10):767–72. pmid:19767758
View Article
PubMed/NCBI
Google Scholar

[159] View Article

[160] PubMed/NCBI

[161] Google Scholar

[ref43] 43. Freter R, Brickner H, Fekete J, Vickerman MM, Carey KE. Survival and implantation of Escherichia coli in the intestinal tract. Infect Immun. 1983;39(2):686–703. pmid:6339389
View Article
PubMed/NCBI
Google Scholar

[163] View Article

[164] PubMed/NCBI

[165] Google Scholar

[ref44] 44. Freter R, Brickner H, Botney M, Cleven D, Aranki A. Mechanisms that control bacterial populations in continuous-flow culture models of mouse large intestinal flora. Infect Immun. 1983;39(2):676–85. pmid:6339388
View Article
PubMed/NCBI
Google Scholar

[167] View Article

[168] PubMed/NCBI

[169] Google Scholar

[ref45] 45. Oliveira RA, Ng KM, Correia MB, Cabral V, Shi H, Sonnenburg JL, et al. Klebsiella michiganensis transmission enhances resistance to Enterobacteriaceae gut invasion by nutrition competition. Nat Microbiol. 2020;5(4):630–41. pmid:31959968
View Article
PubMed/NCBI
Google Scholar

[171] View Article

[172] PubMed/NCBI

[173] Google Scholar

[ref46] 46. Gül E, Abi Younes A, Huuskonen J, Diawara C, Nguyen BD, Maurer L, et al. Differences in carbon metabolic capacity fuel co-existence and plasmid transfer between Salmonella strains in the mouse gut. Cell Host Microbe. 2023;31(7):1140–1153.e3. pmid:37348498
View Article
PubMed/NCBI
Google Scholar

[175] View Article

[176] PubMed/NCBI

[177] Google Scholar

[ref47] 47. Osbelt L, Almási ÉDH, Wende M, Kienesberger S, Voltz A, Lesker TR, et al. Klebsiella oxytoca inhibits Salmonella infection through multiple microbiota-context-dependent mechanisms. Nat Microbiol. 2024;9(7):1792–811. pmid:38862602
View Article
PubMed/NCBI
Google Scholar

[179] View Article

[180] PubMed/NCBI

[181] Google Scholar

[ref48] 48. Englyst KN, Liu S, Englyst HN. Nutritional characterization and measurement of dietary carbohydrates. Eur J Clin Nutr. 2007;61 Suppl 1:S19–39. pmid:17992185
View Article
PubMed/NCBI
Google Scholar

[183] View Article

[184] PubMed/NCBI

[185] Google Scholar

[ref49] 49. Castillo JJ, Couture G, Bacalzo NP Jr, Chen Y, Chin EL, Blecksmith SE, et al. The development of the davis food glycopedia-a glycan encyclopedia of food. Nutrients. 2022;14(8):1639. pmid:35458202
View Article
PubMed/NCBI
Google Scholar

[187] View Article

[188] PubMed/NCBI

[189] Google Scholar

[ref50] 50. Larke JA, Bacalzo N, Castillo JJ, Couture G, Chen Y, Xue Z, et al. Dietary intake of monosaccharides from foods is associated with characteristics of the gut microbiota and gastrointestinal inflammation in healthy US adults. J Nutr. 2023;153(1):106–19. pmid:36913444
View Article
PubMed/NCBI
Google Scholar

[191] View Article

[192] PubMed/NCBI

[193] Google Scholar

[ref51] 51. Stecher B, Barthel M, Schlumberger MC, Haberli L, Rabsch W, Kremer M, et al. Motility allows S. Typhimurium to benefit from the mucosal defence. Cell Microbiol. 2008;10(5):1166–80. pmid:18241212
View Article
PubMed/NCBI
Google Scholar

[195] View Article

[196] PubMed/NCBI

[197] Google Scholar

[ref52] 52. Okano H, Hermsen R, Kochanowski K, Hwa T. Regulation underlying hierarchical and simultaneous utilization of carbon substrates by flux sensors in Escherichia coli. Nat Microbiol. 2020;5(1):206–15. pmid:31819215
View Article
PubMed/NCBI
Google Scholar

[199] View Article

[200] PubMed/NCBI

[201] Google Scholar

[ref53] 53. Zeng X, Xing X, Gupta M, Keber FC, Lopez JG, Lee Y-CJ, et al. Gut bacterial nutrient preferences quantified in vivo. Cell. 2022;185(18):3441–56.e19.
View Article
Google Scholar

[203] View Article

[204] Google Scholar

[ref54] 54. Cherrak Y, Salazar MA, Näpflin N, Malfertheiner L, Herzog MK-M, Schubert C, et al. Non-canonical start codons confer context-dependent advantages in carbohydrate utilization for commensal E. coli in the murine gut. Nat Microbiol. 2024;9(10):2696–709. pmid:39160293
View Article
PubMed/NCBI
Google Scholar

[206] View Article

[207] PubMed/NCBI

[208] Google Scholar

[ref55] 55. Collins J, Robinson C, Danhof H, Knetsch CW, van Leeuwen HC, Lawley TD, et al. Dietary trehalose enhances virulence of epidemic Clostridium difficile. Nature. 2018;553(7688):291–4. pmid:29310122
View Article
PubMed/NCBI
Google Scholar

[210] View Article

[211] PubMed/NCBI

[212] Google Scholar

[ref56] 56. Datsenko KA, Wanner BL. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc Natl Acad Sci U S A. 2000;97(12):6640–5. pmid:10829079
View Article
PubMed/NCBI
Google Scholar

[214] View Article

[215] PubMed/NCBI

[216] Google Scholar

[ref57] 57. Diner EJ, Garza-Sánchez F, Hayes CS. Genome engineering using targeted oligonucleotide libraries and functional selection. Strain Engineering: Methods and Protocols. 2011. pp. 71–82.

[ref58] 58. Barthel M, Hapfelmeier S, Quintanilla-Martínez L, Kremer M, Rohde M, Hogardt M, et al. Pretreatment of mice with streptomycin provides a Salmonella enterica serovar Typhimurium colitis model that allows analysis of both pathogen and host. Infect Immun. 2003;71(5):2839–58. pmid:12704158
View Article
PubMed/NCBI
Google Scholar

[219] View Article

[220] PubMed/NCBI

[221] Google Scholar

[ref59] 59. Guerry P, van Embden J, Falkow S. Molecular nature of two nonconjugative plasmids carrying drug resistance genes. J Bacteriol. 1974;117(2):619–30. pmid:4590480
View Article
PubMed/NCBI
Google Scholar

[223] View Article

[224] PubMed/NCBI

[225] Google Scholar

[ref60] 60. Sintsova A, Ruscheweyh H-J, Field CM, Feer L, Nguyen BD, Daniel B, et al. mBARq: a versatile and user-friendly framework for the analysis of DNA barcodes from transposon insertion libraries, knockout mutants, and isogenic strain populations. Bioinformatics. 2024;40(2):btae078. pmid:38341646
View Article
PubMed/NCBI
Google Scholar

[227] View Article

[228] PubMed/NCBI

[229] Google Scholar

[ref61] 61. Bochner BR, Gadzinski P, Panomitros E. Phenotype microarrays for high-throughput phenotypic testing and assay of gene function. Genome Res. 2001;11(7):1246–55. pmid:11435407
View Article
PubMed/NCBI
Google Scholar

[231] View Article

[232] PubMed/NCBI

[233] Google Scholar

Figures

Abstract

Author summary

Introduction

Results

E. coli 8178 limits early S. Tm gut establishment independently of interference mechanisms

Impact of E. coli 8178 on S. Tm sugar metabolism during initial growth phase

E. coli 8178`s restrictions of S. Tm early establishment is centred on galactose

Discussion

Methods

Animals and ethic statements

Strains, media, and chemicals

Mouse infection experiments

Evaluation of S. Tm metabolic mutant fitness via barcode counting

In vitro galactose utilization assay

Statistical analysis

Materials availability

Supporting information

S1 Fig. E. coli 8178 and Z1331 loads in co-infected mice.

S2 Fig. Quality-control of the S. Tm mutant pool analysis in vivo.

S3 Fig. E. coli 8178 and Z1331 grow on galactose as the sole carbon source.

S1 Table. Bacterial strains used in this study.

S2 Table. Plasmid used in this study.

S3 Table. Oligonucleotides used in this study.

S4 Table. List of abbreviations.

S1 Data. Raw data from this study.

Acknowledgments

References