Niche exclusion of a lung pathogen in mice with designed probiotic communities
- Department of Plant and Microbial Biology, University of California, Berkeley, United States
- Division of Biosciences and Biotechnology, Lawrence Livermore National Laboratory, United States
- Department of Biotechnology and Bioengineering, Sandia National Laboratories, United States
- Department of Systems Biology, Sandia National Laboratories, United States
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, United States
- Department of Biological Engineering, University of California, Berkeley, United States
Figures
Figure 1 with 1 supplement
Characterization of candidate probiotic (CP) activity against Burkholderia thailandensis in vitro.
(A) Phylogenomic tree of CPs (yellow) and model pathogen Bt (red), interspersed amongst publicly available genomes (no color). (B) Schematic of competition assay used to test in vitro inhibitory capabilities. Percent growth of Bt is calculated as the colony-forming unit (CFU) in co-culture at 24 hr divided by the CFU in the Bt monoculture at 24 hr multiplied by 100. Co-culture inhibition was tested for multiple starting densities of CP (see C x-axis). Starting density of Bt and CP at a 1:1 ratio are 3.33×104 CFU/ml per organism. Bt monoculture is inoculated at 3.33×104 CFU/ml. (C) Dose-response curves for CPs against Bt. Relative IC50 is denoted with a vertical dashed-dotted line, and 100% and 50% growth are denoted with horizontal dotted lines. Percent growth at each density is represented as mean ± SEM (N=5-15).
Figure 1—figure supplement 1
Growth curves in lung simulating medium (LSM) and inhibition of candidate probiotics (CPs) by Burkholderia thailandensis.
(A) CPs and Bt were individually inoculated into LSM at 106 colony-forming units (CFU)/ml, and the cultures were incubated at 37 °C with shaking (278 rpm) for 48 hr. (N=3) (B) Co-culture data measuring CFUs of each CP after co-culture with Bt (+) at a 1:1 ratio or each CP grown alone (-) in LSM. Signficance was calulcated using a two-way ANOVA ****p<0.0001; ***p=0.0002; **p=0.0021 (N=3-15).
Figure 2 with 1 supplement
Production of a specialized metabolite plays a role in the antagonistic activities of CP8.
(A) Schematic representation of supernatant inhibition experiment workflow. Supernatant from a Burkholderia thailandensis (Bt) and candidate probiotic (CP) co-culture or from Bt monoculture (supernatant) is mixed 1:1 with 2 x lung simulating medium (LSM). This mixture is used as the growth medium for subsequent Bt growth curves. Fold-change in Bt growth is calculated by dividing the maximum growth of Bt in co-culture supernatant by the maximum growth of Bt grown in supernatant from itself. (B) Left: Heatmap of fold-change in max colony-forming units (CFU) of Bt grown in supernatant from each inhibitory CP and Bt co-culture relative to Bt grown in supernatant from itself. Co-culture supernatant was collected at 72 hr. A fold-change of 1 indicates no difference in growth in co-culture supernatant compared to Bt growth in supernatant from itself. A fold-change less than 1 indicates a reduction in pathogen growth. (N=5) Right: Boxplot of growth inhibition by CP8 supernatant. Data are represented as mean ± SD. Significance was determined by a t-test ****p<0.0001(C) Agar diffusion assays testing the CP8 wild-type strain (CP8 WT) and sfp mutant strain (CP8Δsfp) for inhibition of Bt after 48 hr. (D) Growth curves of CP8 WT (black) and CP8Δsfp (red) (N=5) (E) Dose-response curve of CP8 WT (black) and CP8Δsfp (red) against Bt after 24 hr of co-culture. Percent growth at each density is represented as mean ± SEM (N=5). Statistical signficance was calculated using a t-test with multiple comparisons *p<0.05.
Figure 2—figure supplement 1
Plaque assays to detect phage isolated from candidate probiotics (CPs).
Supernatants from phage-induced CP cultures were serially diluted 1:10 and spotted onto soft agar containing Burkholderia thailandensis (Bt). Supernatant from a phage-induced culture of Bt strain E421, which produces a Bt-targeting phage, generated visible plaques as expected, demonstrating that the phage detection method was effective.
Figure 3 with 1 supplement
Metabolic niche overlap is indicative of pathogen and candidate probiotic (CP) antagonism.
(A) Dose-response curve for CP7 grown in unsupplemented lung simulating medium (LSM) (black) or with additional glucose (red). Percent growth at each density is represented as mean ± SEM. Significance was determined using multiple t-tests (N=5) *p<0.05 (B) Activity of CP7 against Bt at a 1:100 ratio with or without glucose supplementation (red and gray, respectively). Data are summarized as mean ± SD. Significance was determined using a t-test (N=5)***p<0.001. (C) Carbon utilization heatmap for CPs and Bt. (D) Venn diagram of carbon sources utilized by CP7 and Bt. (E) Plot of rank percent Bt growth at a 1:1 ratio after 24 hr vs rank of Niche Index for each CP. Correlation is determined by Spearman rank correlation (r=–0.6367, p<0.0001, 95% CI [-0.7891–0.4261], N=49). (F) Total carbon consumed by CPs grown in combination with Bt at 36 hr (mean ± SD). Activity indicates relative amount of Bt inhibition at a 1:1 ratio from most (+++) to least (+) inhibitory. Signficance was determined by a two-way ANOVA with multiple comparisons *p=0.05; **p<0.01 (N=6). (G) Total electron flux at 24 hr. Red dashed line indicates the estimated abundance of Bt in each co-culture. (H) Summed electron flux of lactate (black), proline (white), and aspartic acid (gray) at 24 hr in different CP co-culture conditions (mean ± SD). Significance was determined by two-way ANOVA (N=5-6) *p<0.05.(I) Receiver operator characteristic curve showing the ability of growth on lactate to distinguish inhibitory CPs from non-inhibitory CPs. An AUROC of 1 indicates perfect distinction between inhibitors and non-inhibitors; an AUROC of 0.5 (dashed red line) indicates no distinction between inhibitors and non-inhibitors.
Figure 3—figure supplement 1
Addition of glucose decreases antagonism between CP19 and Burkholderia thailandensis (Bt).
Dose-response curve of Bt in co-culture with CP19 in standard lung simulating medium (LSM) (5.5 mM glucose) (black) or LSM supplemented to 43 mM glucose (red). Vertical dotted lines indicate the IC50 in the low or high glucose condition. Data are represented as the mean ± SEM. Significance was determined by multiple t-tests (N=5) *p<0.05.
Figure 4 with 2 supplements
Niche overlap aids in identification of efficacious candidate probiotic (CP) combinations.
(A) Venn diagram representation of the Niche Index Fraction (NIF) calculation. Yellow represents the fraction numerator and red the denominator. (B) Heatmap of NIF values for each colonizing CP. (C) Dose-response curve for the CP8/CP19 combination (mean ± SEM). (N=5) (D) Dose-response curve for the CP19/CP13 combination (mean ± SEM). (N=5) (E) Dose-response curve for the CP13/CP8 combination (mean ± SEM). (N=4-5) (F) Lactate consumed (as determined via GC-TOF) for 3 conditions, normalized to colony-forming units (CFU) of each CP inoculated (mean ± SD). Signficance was determined using a one-way ANOVA with multiple comparisons (N = 5-6) ****p<0.0001. (G) Dose-response curve for the CP8/CP19 (red) and CP8sfp/CP19Δsfp (black) combinations. Signficance was determined using multiple t-tests (N=5) *p<0.05(H) Schematic of the proposed mechanism for Bt inhibition by the CP8/CP19 combination. CP8 produces a specialized metabolite that inhibits growth of the Bt. Additionally, increased lactate consumption by CP19 in the presence of CP8 further reduces Bt growth. Overall, minimal niche overlap between the CPs, and high overlap with Bt allows for further inhibition of Bt with minimal inter-CP antagonism.
Figure 4—figure supplement 1
Dose-response curves for pairwise candidate probiotic (CP) combinations with low Niche Index Fractions.
(A) IC50 curve for the CP20/CP17 combination (red diamonds). Single-strain inhibition curves (black) are shown for CP20 (circles) and CP17 (triangles). (N=3-10) (B) IC50 curve for the CP26/CP19 combination (red diamonds). Single-strain inhibition curves (black) are shown for CP26 (circles) and CP19 (triangles). (N=4-10).
Figure 4—figure supplement 2
qPCR generated growth curves for CP8, CP19, and Burkholderia thailandensis (Bt) grown in co-culture.
CP8, CP19, and Bt were co-cultured in lung simulating medium (LSM) for 36 hr at 37 °C and 278 rpm. Samples were periodically taken to quantify their OD using qPCR. Three biological replicates of co-cultures were made and two technical replicates of each co-culture analyzed. All six points for each organism at each timepoint are displayed. Bt growth curve is denoted as black open circles, CP8 as blue closed circles, and CP19 as purple closed circles.
Figure 5 with 3 supplements
Candidate probiotics (CPs) colonize the mouse airway and protect against respiratory Burkholderia thailandensis (Bt) infection.
(A) Schematic of colonization testing for CPs. Each CP (106 colony-forming units, CFU) is administered to the lower airway via oropharyngeal aspiration (OPA). After 7 days, the airway tissues (lungs and trachea) are collected, homogenized, and plated in order to enumerate viable CPs (expressed as CFU per tissue homogenate). (B) Colonization results from airway tissues collected at 7 days following CP administration. The dotted line represents the minimum CFU at which the CP is considered able to colonize in a reliably detectable manner. Data are represented as the mean ± SD (N=3-12). (C) Schematic of the method for survival testing. Each CP (106 CFU) is administered to the lower airway via OPA at 3, 5, or 7 days post-CP a normally lethal dose of Bt (3×104 - 5×105 CFU) is administered to the lower airway via OPA. Survival is measured over the course of 10 days post-Bt. (D) Survival data from mice administered no CP (vehicle control) and challenged with Bt (E) Survival data from mice administered CPs at 3 days (blue), 5 days (orange), or 7 days (red) prior to Bt challenge. The Niche Index value for each CP is listed in the lower-right corner of its associated graph. Comparison of survival rate with versus without CP treatment was accomplished using the Mantel-Cox test (N=10-29) ****p<0.0001, ***p<0.0002, **p<0.01. A summary of the relationship between days surviving and Niche Index value for each dosing schedule is also shown (F) Pathogen loads in airway tissues of mice prophylactically treated with CPs. Each CP or phosphate-buffered saline (PBS) (‘no CP’ negative control) is administered to the lower airway via OPA, 3 days later Bt (3×104 - 5×105 CFU) is similarly administered, and 3 days later (i.e. 3 days post-challenge, 6 days post-treatment) the airway tissues are collected for enumeration of Bt CFU. Mean Bt CFU counts are as follows for each group: CP19 (1.6×103), CP17 (1.7×103), CP20 (2.2×106), CP26 (8.7×106), CP13 (1.3×107), CP8 (3.9×108), No CP (4.6×108). Asterisks indicate significant differences in Bt CFU between treatment versus no treatment groups as determined using Dunn’s multiple comparisons test (N=6-17) ****p<0.0001, ***p<0.0002, **p<0.01. The relationship between the Niche Index values of CPs and the Bt CFU detected in mice treated with the CPs is indicated in the upper left corner.
Figure 5—figure supplement 1
CP8 colonization of the airway is significantly reduced in Burkholderia thailandensis (Bt)-infected mice.
CP8 (106 colony-forming units, CFU) was administered to the airway via oropharyngeal aspiration (OPA) and after 3 days challenged with either phosphate-buffered saline (PBS) (CP8 alone) or Bt (3×104 - 5×105 CFU) (CP8+Bt) via OPA. Airway tissues were recovered at 3 days post-challenge (6 days post-CP8 administration) for enumeration of CP8 load (expressed as CFU per tissue homogenate). Significance was determined using a t-test (N=6-9) **p<0.002.
Figure 5—figure supplement 2
Survival of mice treated with non-viable candidate probiotics (CPs) prior to pathogen challenge.
CPs were rendered non-viable (via UV and heat treatment) and administered to the mouse airway (via oropharyngeal aspiration, OPA) at 3 days (blue), 5 days (orange), or 7 days (red) prior to challenge with Bt (via OPA). Survival was monitored for 10 days following pathogen challenge. For CP20, CP26, CP13, and CP8 treatment at 3 days prior to pathogen challenge was the only dosing regimen investigated because these CPs provided little to no protection when viable bacteria were administered at 5 days or 7 days prior to pathogen challenge (see Figure 5E). Asterisks indicate significant differences between survival of mice treated with phosphate-buffered saline (PBS) (negative control) versus the non-viable CP, whereas plus signs indicate significant differences between survival of mice treated with the non-viable CP versus the viable CP, as calculated using the Holm-Šidák multiple comparisons test (N=10-20) (****or ++++p<0.0001, ***or +++p<0.0002, ** or ++p<0.0021, * or +p<0.0332).
Figure 5—figure supplement 3
CP19 consumption of lactate and inhibition of pathogen growth in mouse airway tissues ex vivo.
(A) Lactate levels in airway tissue homogenates treated with phosphate-buffered saline (PBS) (-CP19) or CP19 (106 colony-forming units, CFU) (+CP19) for 24 hr. Significance was determined using a t-test (N = 5) ****p<0.0001. (B) Growth of Bt in airway tissue homogenates pre-treated with PBS (-CP19) or CP19 (106 CFU) (+CP19) for 24 hr. Pre-treated tissue homogenates were filter sterilized, the filtrates were inoculated with Burkholderia thailandensis (Bt) (106 CFU), and OD600 measurements were taken every 15 min to monitor growth of the pathogen over the course of 12 hr (N=5).
Figure 6
Proposed mechanism of candidate probiotic (CP) protection.
Left: During lower airway infection, bacterial growth elicits inflammation from the host, with concurrent endothelial and epithelial injury. Intra-alveolar oedema introduces additional nutrients from the blood into the alveoli and lung lumen, enabling further growth of the pathogen. This positive feedback loop results in uncontrolled growth of the pathogen, ultimately facilitating its instantiation. Right: Probiotics delivered directly to the lower airway may limit infection by reducing nutrient abundance after oedema, which prevents further growth of the pathogen and thereby breaks the infection-promoting feedback loop.
Tables
Table 1
Summary of pathogen inhibition by candidate probiotics (CPs).
Relative IC50 values and 95% confidence intervals (95% CI) are shown for each inhibitory CP. Not determined (n.d.) indicates that a value could not be measured. CPs are listed in order of decreasing Niche Index (NI) values.
| CP | Species | Relative IC50 | 95% CI | Bt growth at a 1:1 ratio (%) | Niche Index |
|---|---|---|---|---|---|
| CP7 | Pseudomonas stutzeri | 0.001172 | 0.0006442–0.003346 | 1.893 | 0.875 |
| CP4 | Pseudomonas fluorescens | 0.003086 | 0.001791–0.005331 | 3.200 | 0.869 |
| CP19 | Brevibacillus borstelensis | 0.006604 | 0.006484–0.01141 | 3.046 | 0.775 |
| CP17 | Bacillus megaterium | 5738 | 3598 n.d. | 98.99 | 0.704 |
| CP18 | Peribacillus frigoritolerans | 0.0001693 | 0.0001633–0.0001850 | 0.534 | 0.591 |
| CP20 | Bacillus clausii | n.d. | n.d. | 115.2 | 0.457 |
| CP26 | Bacillus licheniformis | n.d. | n.d. | 260.0 | 0.433 |
| CP13 | Bacillus licheniformis | n.d. | n.d. | 913.0 | 0.421 |
| CP9 | Neisseria lactamica | n.d. | n.d. | 157.1 | 0.357 |
| CP8 | Bacillus velenzensis | 2.316 | 0.8280–5.073 | 56.97 | 0.351 |
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Strain, strain background (Burkholderia thailandensis) | Bt-GFP | Daniel J. Hassett | ||
| Strain, strain background (Pseudomonas fluorescens) | CP4 | This paper | SAMN45914816 | NCBI accession number for CP4 genome |
| Strain, strain background (Pseudomonas stutzeri) | CP7 | This paper | SAMN45914812 | NCBI accession number for CP7 genome |
| Strain, strain background (Bacillus velenzensis) | CP8 | This paper | SAMN45914813 | NCBI accession number for CP8 genome |
| Strain, strain background (Neisseria lactamica) | CP9 | This paper | SAMN45914814 | NCBI accession number for CP9 genome |
| Strain, strain background (Bacillus licheniformis) | CP13 | This paper | SAMN39610770 | NCBI accession number for CP13 genome |
| Strain, strain background (Bacillus megaterium) | CP17 | This paper | SAMN45914815 | NCBI accession number for CP17 genome |
| Strain, strain background (Peribacillus frigoritolerans) | CP18 | This paper | SAMN39610774 | NCBI accession number for CP18 genome |
| Strain, strain background (Brevibacillus borstelensis) | CP19 | This paper | SAMN39610771 | NCBI accession number for CP19 genome |
| Strain, strain background (Bacillus clausii) | CP20 | This paper | SAMN39610772 | NCBI accession number for CP20 genome |
| Strain, strain background (Bacillus licheniformis) | CP26 | This paper | SAMN39610773 | NCBI accession number for CP26 genome |
| Recombinant DNA reagent | T2(2)-ori (plasmid) | Qi et al., 2014 | Addgene ID#216627 | Bacillus knockout vector |
| Sequence-based reagent | CP8_probe | This paper | CP8 qPCR probe | /56-FAM/AAAGAGCGA/ZEN/CAGGGAAACAGTGCT/3IABkFQ/ |
| Sequence-based reagent | CP8_F | This paper | qPCR primer | CAGATCTGCCGGATTCATCTT |
| Sequence-based reagent | CP8_R | This paper | qPCR primer | CCGGCATTCTCCATCTCATT |
| Sequence-based reagent | CP19_probe | This paper | CP19 qPCR probe | /5SUN/CCAGATTCG/ZEN/CTTTCTCGACCGGATT/3IABkFQ/ |
| Sequence-based reagent | CP19_F | This paper | qPCR primer | GCAGACATGGGTGAAGAATTTG |
| Sequence-based reagent | CP19_R | This paper | qPCR primer | GGCGATTTCTACCGCTTCAT |
| Sequence-based reagent | Bt_probe | This paper | Bt qPCR probe | /5Cy5/TGTCCGGAAAGAAATCATCCTGGCT/3IAbRQSp/ |
| Sequence-based reagent | Bt_F | This paper | qPCR primer | AGGCCTTCGGGTTGTAAAG |
| Sequence-based reagent | Bt_R | This paper | qPCR primer | GTAGTTAGCCGGTGCTTATTCT |
| Software, algorithm | Canu v2.2 | Koren et al., 2017 | RRID:SCR_015880 | Long read assembly of candidate probiotic genomes was performed using Canu |
| Software, algorithm | speciateIT | RRID:SCR_014615 | For speciation of 16 S sequences, speciateIT was used | |
| Software, algorithm | KBase | Arkin et al., 2018 | RRID:SCR_022162 | The phylogenomic tree was built using KBase |
Additional files
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Supplementary file 1
Representation of candidate probiotic (CP) families, genera and species in mouse airway microbiome profiles.
(A) - Representation of candidate probiotic (CP) families in mouse airway microbiome profiles. Family-level phylogenetic assignments of the CPs were compared to those of mouse airway microbiome constituents previously identified in four independent 16 S rRNA profiling efforts (Barfod et al., 2013; Scheiermann and Klinman, 2017; Kostric et al., 2018; Dickson et al., 2018; O’Dwyer et al., 2019). An identical analysis was performed for ‘background’ (B) strains (contaminants recovered from liver and spleen). For each CP and B family, listed are: (1) The number of times that it is represented in a given airway microbiome profile (‘# Hits’); (2) Its relative abundance in the profile (‘% Hits’); and (3) Its relative rank within the profile, with the most abundant family in the profile designated as ‘Rank’=1. For each profile, the total number of 16 S rRNA sequences placed at the family level, and the total number of families represented, are listed in the headings of the ‘# Hits’ and ‘Rank’ columns, respectively. (B) - Representation of CP genera in mouse airway microbiome profiles. Genus-level phylogenetic assignments of the CPs, and of the B strains, were compared to those of mouse airway microbiome constituents previously identified in four independent 16 S rRNA profiling efforts (Barfod et al., 2013; Scheiermann and Klinman, 2017; Kostric et al., 2018; Dickson et al., 2018; O’Dwyer et al., 2019). For each CP and B genus, listed are: (1) The number of times it is represented in a given airway microbiome profile (‘# Hits’); (2) Its relative abundance in the profile (‘% Hits’); and (3) Its relative rank within the profile, with the most abundant genus in the profile designated as ‘Rank’=1. For each profile, the total number of 16 S rRNA sequences placed at the genus level, and the total number of genera represented, are listed in the headings of the ‘# Hits’ and ‘Rank’ columns, respectively. (C) - Representation of CP species in mouse airway microbiome profiles. Species-level phylogenetic assignments of the CPs, and of the B strains, were compared to those of mouse airway microbiome constituents previously identified in four independent 16 S rRNA profiling efforts (Barfod et al., 2013; Scheiermann and Klinman, 2017; Kostric et al., 2018; Dickson et al., 2018; O’Dwyer et al., 2019). For each CP and B species, listed are: (1) The number of times it is represented in a given airway microbiome profile (‘# Hits’); (2) Its relative abundance in the profile (‘% Hits’); and (3) Its relative rank within the profile, with the most abundant species in the profile designated as ‘Rank’=1. For each profile, the total number of 16 S rRNA sequences placed at the species level, and the total number of species represented, are listed in the headings of the ‘# Hits’ and ‘Rank’ columns, respectively.
- https://cdn.elifesciences.org/articles/108304/elife-108304-supp1-v1.xlsx
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Supplementary file 2
Relative IC50 and Niche Index Fraction values for each candidate probiotic (CP) combination tested.
Relative IC50 values are reported as IC50 (95% confidence interval). Non-inhibitory combinations have relative IC50 values listed as n.a. (not applicable).
- https://cdn.elifesciences.org/articles/108304/elife-108304-supp2-v1.xlsx
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MDAR checklist
- https://cdn.elifesciences.org/articles/108304/elife-108304-mdarchecklist1-v1.pdf
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Niche exclusion of a lung pathogen in mice with designed probiotic communities
eLife 14:RP108304.
https://doi.org/10.7554/eLife.108304.3
