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Cited by 101Gut microbiota and healthAntibiotic Resistance in BacteriaInfant Nutrition and Health

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Early-life gut microbiome modulation reduces the abundance of antibiotic-resistant bacteria

Open access
Casaburi, Giorgio, Duar, Rebbeca M., Vance, Daniel P., Mitchell, Ryan, Contreras, Lindsey, Frese, Steven A., Smilowitz, Jennifer T., Underwood, Mark A.·2019·Antimicrobial Resistance & Infection Control
DOI 10.1186/s13756-019-0583-6PMC PMC6693174
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Abstract

Antibiotic-resistant (AR) bacteria are a global threat. AR bacteria can be acquired in early life and have long-term sequelae. Limiting the spread of antibiotic resistance without triggering the development of additional resistance mechanisms is of immense clinical value. Here, we show how the infant gut microbiome can be modified, resulting in a significant reduction of AR genes (ARGs) and the potentially pathogenic bacteria that harbor them. The gut microbiome was characterized using shotgun metagenomics of fecal samples from two groups of healthy, term breastfed infants. One group was fed B. infantis EVC001 in addition to receiving lactation support (n = 29, EVC001-fed), while the other received lactation support alone (n = 31, controls). Coliforms were isolated from fecal samples and genome sequenced, as well as tested for minimal inhibitory concentrations against clinically relevant antibiotics. Infants fed B. infantis EVC001 exhibited a change to the gut microbiome, resulting in a 90% lower level of ARGs compared to controls. ARGs that differed significantly between groups were predicted to confer resistance to beta lactams, fluoroquinolones, or multiple drug classes, the majority of which belonged to Escherichia, Clostridium, and Staphylococcus. Minimal inhibitory concentration assays confirmed the resistance phenotypes among isolates with these genes. Notably, we found extended-spectrum beta lactamases among healthy, vaginally delivered breastfed infants who had never been exposed to antibiotics. Colonization of the gut of breastfed infants by a single strain of B. longum subsp. infantis had a profound impact on the fecal metagenome, including a reduction in ARGs. This highlights the importance of developing novel approaches to limit the spread of these genes among clinically relevant bacteria. Future studies are needed to determine whether colonization with B. infantis EVC001 decreases the incidence of AR infections in breastfed infants. This clinical trial was registered at ClinicalTrials.gov , NCT02457338.

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Fig. 1 Taxonomic classification of metagenomic reads for EVC001-fed infants and controls. a Relative abundance of the top bacterial genera identified between the two groups of infants. b Relative abundance of bacterial species belonging to the Bifidobacterium genus identified among groups. c Hierarchical clustering based on a strain-level analysis of Bifidobacterium longum subspecies. Gene family profiles of a subgroup of reference genomes were selected from a global (n = 38) strain analysis. Each column represents the presence or absence of genes in a sample or a reference genome with respect to the total pangenome. All samples from EVC001-fed infants clustered together with B. longum subsp. infantis ATCC 15697 (B. infantis), whereas the samples from infants in the control group clustered separately with other B. longum subspecies (e.g., B. suis, B. longum DJ01A, and B. longum NCC2705). Functional analysis of gene families confirmed that the EVC001 samples were dominated by B. infantis due to the presence of unique genes (e.g., Blon_2348 in B. infantis), while genes present only in B. longum subsp. longum (e.g., araD; araA), were abundant in the communities from control infants. P-values were computed for each gene via Fisher’s exact test according to group
Fig. 1 Taxonomic classification of metagenomic reads for EVC001-fed infants and controls. a Relative abundance of the top bacterial genera identified between the two groups of infants. b Relative abundance of bacterial species belonging to the Bifidobacterium genus identified among groups. c Hierarchical clustering based on a strain-level analysis of Bifidobacterium longum subspecies. Gene family profiles of a subgroup of reference genomes were selected from a global (n = 38) strain analysis. Each column represents the presence or absence of genes in a sample or a reference genome with respect to the total pangenome. All samples from EVC001-fed infants clustered together with B. longum subsp. infantis ATCC 15697 (B. infantis), whereas the samples from infants in the control group clustered separately with other B. longum subspecies (e.g., B. suis, B. longum DJ01A, and B. longum NCC2705). Functional analysis of gene families confirmed that the EVC001 samples were dominated by B. infantis due to the presence of unique genes (e.g., Blon_2348 in B. infantis), while genes present only in B. longum subsp. longum (e.g., araD; araA), were abundant in the communities from control infants. P-values were computed for each gene via Fisher’s exact test according to groupCC BY · PubMed Central
Fig. 2 Relative abundance of the total resistome profile in each metagenome sample. a Relative abundance of antibiotic resistance genes (ARGs) compared with the overall metagenome for each sample. Each point represents a sample resistome (control, n = 31; EVC001-fed, n = 29). Box plots denote the interquartile range (IQR), with horizontal lines representing the 25th percentile, median, and 75th percentiles. The whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. The asterisks on the top indicate significant P-values (Mann-Whitney test). b Relative abundance of ARGs according to their taxonomic identification. The shade of color represents genera belonging to the same bacterial class. The asterisks on the top indicate significant P-values (Kruskal-Wallis test)
Fig. 2 Relative abundance of the total resistome profile in each metagenome sample. a Relative abundance of antibiotic resistance genes (ARGs) compared with the overall metagenome for each sample. Each point represents a sample resistome (control, n = 31; EVC001-fed, n = 29). Box plots denote the interquartile range (IQR), with horizontal lines representing the 25th percentile, median, and 75th percentiles. The whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. The asterisks on the top indicate significant P-values (Mann-Whitney test). b Relative abundance of ARGs according to their taxonomic identification. The shade of color represents genera belonging to the same bacterial class. The asterisks on the top indicate significant P-values (Kruskal-Wallis test)CC BY · PubMed Central
Fig. 3 Comparison of the most significant antibiotic resistance gene types. a Relative abundance of the most significantly different antibiotic resistance genes (ARGs) identified among EVC001-fed infants and controls (P < 0.02; Bonferroni). Percentages are relative to the overall metagenome. These ARGs confer resistance to different drug classes, including beta-lactams, fluoroquinolones, and macrolides. The ARGs are grouped by gene name, followed by CARD identification entry (ARO). The colored bars represent respective drug class to which the ARG is known to confer resistance to. b Heatmap showing a hierarchical cluster analysis of the total ARGs identified (n = 652). Two groups were identified, one characterized by a lower-ARG carriage, containing most of the samples from infants fed EVC001 and one characterized by a higher overall carriage, containing most samples from infants in the control group. Genes clustered based on similar biological mechanisms implicated in drug resistance (see Results). P-values on the bar were computed using a Kruskal-Wallis test normalized with a Bonferroni correction
Fig. 3 Comparison of the most significant antibiotic resistance gene types. a Relative abundance of the most significantly different antibiotic resistance genes (ARGs) identified among EVC001-fed infants and controls (P < 0.02; Bonferroni). Percentages are relative to the overall metagenome. These ARGs confer resistance to different drug classes, including beta-lactams, fluoroquinolones, and macrolides. The ARGs are grouped by gene name, followed by CARD identification entry (ARO). The colored bars represent respective drug class to which the ARG is known to confer resistance to. b Heatmap showing a hierarchical cluster analysis of the total ARGs identified (n = 652). Two groups were identified, one characterized by a lower-ARG carriage, containing most of the samples from infants fed EVC001 and one characterized by a higher overall carriage, containing most samples from infants in the control group. Genes clustered based on similar biological mechanisms implicated in drug resistance (see Results). P-values on the bar were computed using a Kruskal-Wallis test normalized with a Bonferroni correctionCC BY · PubMed Central
Fig. 4 Quantification of Enterobacteriaceae family by group-specific qPCR. The data are represented as Log10 CFU per μg of genomic DNA extracted from stool samples. Data in boxplots show the median, first, and third quartiles (P < 0.0001, Mann-Whitney Test)
Fig. 4 Quantification of Enterobacteriaceae family by group-specific qPCR. The data are represented as Log10 CFU per μg of genomic DNA extracted from stool samples. Data in boxplots show the median, first, and third quartiles (P < 0.0001, Mann-Whitney Test)CC BY · PubMed Central
Fig. 5 Diversity analyses of infant resistomes according to B. infantis EVC001 colonization. a Rarefaction curves showing the number of unique antibiotic resistance genes (ARGs) identified in relation to the increasing number of sequences. Both EVC001 and the control group presented similar curve trends, suggesting that the sequencing depth is not associated with the diversity of antibiotic resistance. P-values were computed with a nonparametric two-sample t-test using Monte Carlo permutations (n = 999). b Global resistome profiles computed via a principal coordinate analysis (PCoA) based on a Bray-Curtis dissimilarity matrix. The EVC001-fed samples clustered closely, indicating that they shared a similar resistome compared to the controls, which had a more dispersed distribution. The effect of B. infantis EVC001 colonization by itself accounted for 31% of the total explained variation (adonis). The P-value was computed using F-tests based on the sequential sums of squares from permutations of the raw data
Fig. 5 Diversity analyses of infant resistomes according to B. infantis EVC001 colonization. a Rarefaction curves showing the number of unique antibiotic resistance genes (ARGs) identified in relation to the increasing number of sequences. Both EVC001 and the control group presented similar curve trends, suggesting that the sequencing depth is not associated with the diversity of antibiotic resistance. P-values were computed with a nonparametric two-sample t-test using Monte Carlo permutations (n = 999). b Global resistome profiles computed via a principal coordinate analysis (PCoA) based on a Bray-Curtis dissimilarity matrix. The EVC001-fed samples clustered closely, indicating that they shared a similar resistome compared to the controls, which had a more dispersed distribution. The effect of B. infantis EVC001 colonization by itself accounted for 31% of the total explained variation (adonis). The P-value was computed using F-tests based on the sequential sums of squares from permutations of the raw dataCC BY · PubMed Central

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Research works printed but not linked: 2

  1. Andremont A. Commensal flora may play key role in spreading antibiotic resistance. ASM news. 2003;69(12):601–7.
  2. CLSI. Performance Standards for Antimicrobial Susceptibility Testing: CLSI supplement. M100S. 26th ed. Wayne, PA: Clinical and Laboratory Standards Institute; 2016.

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Metadata

Authors
Casaburi, G., Duar, R. M., Vance, D. P., Mitchell, R., Contreras, L., Frese, S. A., Smilowitz, J. T., & Underwood, M. A.
Affiliations
  • Infinant Health Inc. (United States) (US)
  • University of Nebraska–Lincoln (US)
  • University of California, Davis (US)
  • University of California Davis Medical Center (US)
Corresponding author
  • Smilowitz, Jennifer T.
  • Underwood, Mark A.
ORCID
Venue
Antimicrobial Resistance & Infection Control
Publisher
Springer Science and Business Media LLC
Published
2019-08-14
Volume
8
Issue
1
Pages
131-131
ISSN
2047-2994 (ISSN-L)
DOI
10.1186/s13756-019-0583-6
PMC
PMC6693174
OpenAlex
W2967608930
Cited by
101
References
86
Citations by year
2026: 12 · 2025: 6 · 2024: 14 · 2023: 16 · 2022: 20 · 2021: 21 · 2020: 12
FWCI
4.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Antimicrobial Resistance and Infection Control (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
Evolve Biosystems (n/a)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Microbiology (medical) › Antibiotic Resistance in Bacteria
  • Health Sciences › Nursing › Nutrition and Dietetics › Infant Nutrition and Health
Keywords
antibiotic resistance genes, infant gut microbiota, probiotic supplementation, breastfeeding, coliform bacteria, extended-spectrum beta-lactamase, minimum inhibitory concentration, Escherichia, Clostridium, Staphylococcus, vaginal delivery, antibiotic resistance spread
MeSH terms
Gastrointestinal Microbiome, Bifidobacterium longum subspecies infantis, Whole Genome Sequencing, Anti-Bacterial Agents, Bacteria, beta-Lactamases, Breast Feeding, Drug Resistance, Microbial, Feces, Humans, Infant, Newborn, Microbial Sensitivity Tests, Case-Control Studies, Probiotics, Metagenomics, High-Throughput Nucleotide Sequencing

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