Skip to main content
  • ASM Journals
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems
  • Log in
  • My alerts
  • My Cart

Main menu

  • Home
  • Articles
    • Latest Articles
    • COVID-19 Research and News from ASM Journals
    • mSphere of Influence: Commentaries from Early Career Microbiologists
    • Archive
  • Topics
    • Applied and Environmental Science
    • Clinical Science and Epidemiology
    • Ecological and Evolutionary Science
    • Host-Microbe Biology
    • Molecular Biology and Physiology
    • Therapeutics and Prevention
  • For Authors
    • Getting Started
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About mSphere
    • Editor in Chief
    • Board of Editors
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • ASM Journals
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Eukaryotic Cell
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems

User menu

  • Log in
  • My alerts
  • My Cart

Search

  • Advanced search
mSphere
publisher-logosite-logo

Advanced Search

  • Home
  • Articles
    • Latest Articles
    • COVID-19 Research and News from ASM Journals
    • mSphere of Influence: Commentaries from Early Career Microbiologists
    • Archive
  • Topics
    • Applied and Environmental Science
    • Clinical Science and Epidemiology
    • Ecological and Evolutionary Science
    • Host-Microbe Biology
    • Molecular Biology and Physiology
    • Therapeutics and Prevention
  • For Authors
    • Getting Started
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About mSphere
    • Editor in Chief
    • Board of Editors
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
Research Article | Host-Microbe Biology

Nasal Tissue Extraction Is Essential for Characterization of the Murine Upper Respiratory Tract Microbiota

L. Patrick Schenck, Joshua J. C. McGrath, Daphnée Lamarche, Martin R. Stämpfli, Dawn M. E. Bowdish, Michael G. Surette
Vincent B. Young, Editor
L. Patrick Schenck
aDepartment of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada
bFarncombe Family Digestive Health Research Institute, McMaster University, Hamilton, Ontario, Canada
cMichael G. Degroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada
dMcMaster Immunology Research Centre, McMaster University, Hamilton, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Joshua J. C. McGrath
dMcMaster Immunology Research Centre, McMaster University, Hamilton, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Daphnée Lamarche
aDepartment of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada
bFarncombe Family Digestive Health Research Institute, McMaster University, Hamilton, Ontario, Canada
cMichael G. Degroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Martin R. Stämpfli
dMcMaster Immunology Research Centre, McMaster University, Hamilton, Ontario, Canada
eFirestone Institute for Respiratory Health, McMaster University, Hamilton, Ontario, Canada
fDepartment of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
gDepartment of Medicine, McMaster University, Hamilton, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dawn M. E. Bowdish
cMichael G. Degroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada
dMcMaster Immunology Research Centre, McMaster University, Hamilton, Ontario, Canada
fDepartment of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Dawn M. E. Bowdish
Michael G. Surette
bFarncombe Family Digestive Health Research Institute, McMaster University, Hamilton, Ontario, Canada
cMichael G. Degroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada
gDepartment of Medicine, McMaster University, Hamilton, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Michael G. Surette
Vincent B. Young
University of Michigan—Ann Arbor
Roles: Editor
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1128/mSphere.00562-20
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

ABSTRACT

Respiratory infections are a leading cause of morbidity and mortality worldwide. Bacterial pathogens often colonize the upper respiratory tract (nose or mouth) prior to causing lower respiratory infections or invasive disease. Interactions within the upper respiratory tract between colonizing bacteria and the resident microbiota could contribute to colonization success and subsequent transmission. Human carriage studies have identified associations between pathogens such as Streptococcus pneumoniae and members of the resident microbiota, although few mechanisms of competition and cooperation have been identified and would be aided by the use of animal models. Little is known about the composition of the murine nasal microbiota; thus, we set out to improve assessment, including tissue sampling, composition, and comparison between mouse sources. Nasal washes were efficient in sampling the nasopharyngeal space but barely disrupted the nasal turbinates. Nasal tissue extraction increased the yield of cultivable bacterial compared to nasal washes, revealing distinct community compositions. Experimental pneumococcal colonization led to dominance by the colonizing pathogen in the nasopharynx and nasal turbinates, but the composition of the microbiota, and interactions with resident microbes, differed depending on the sampling method. Importantly, vendor source has a large impact on microbial composition. Bacterial interactions, including cooperation and colonization resistance, depend on the biogeography of the nose and should be considered during research design of experimental colonization with pathogens.

IMPORTANCE The nasal microbiota is composed of species that play a role in the colonization success of pathogens, including Streptococcus pneumoniae and Staphylococcus aureus. Murine models provide the ability to explore disease pathogenesis, but little is known about the natural murine nasal microbiota. This study established techniques to allow the exploration of the bacterial members of the nasal microbiota. The mouse nasal microbiota included traditional respiratory bacteria, including Streptococcus, Staphylococcus, and Moraxella species. Analyses were affected by different sampling methods as well as the commercial source of the mice, which should be included in future research design of infectious disease research.

INTRODUCTION

The upper respiratory tract (URT) is the initial barrier against airway pathogens. Asymptomatic colonization by potential pathogens, including Streptococcus pneumoniae and Staphylococcus aureus, provides a reservoir capable of causing disease within the host or being transmitted to other carriers via respiratory droplets (1). Pathogens could inhibit colonization by other pathogens, as epidemiological studies have identified a negative correlation between S. pneumoniae and S. aureus in children (2, 3). Consistent with this, studies of pneumococcal vaccination have shown that the removal or reduction of S. pneumoniae is associated with increased S. aureus colonization (4). The contribution of the resident microbiota is relatively unknown, although a recent study demonstrated that a nasopharyngeal bacterial composition with high levels of Corynebacterium or Dolosigranulum species was correlated with a reduced risk of lower respiratory infections (5). The antipathogenic activities of Corynebacterium species have been identified in vitro (6, 7). A further understanding of the agonistic and antagonistic interactions between microbial species may explain why certain populations are more susceptible to colonization and infection.

Mechanistic studies involving pneumococcal colonization and the URT microbiota are difficult due to high interindividual variability, low bacterial biomass, and diverse topography. An experimental human pneumococcal colonization model identified increased α-diversity (higher microbial community diversity within a subject) in subjects with successful pneumococcal colonization (8). Identification of the contribution of individual bacterial species was challenging due to distinct microbial compositions between subjects. Mouse models allow for greater control over microbial composition and have been used to assess the alterations of the nasal microbiota during pneumococcal infection (9, 10); however, little is known about the naive URT microbiota composition in mice.

Assessment of murine nasal bacteria is predominated by nasal washes. Cannulation and flushing from trachea to nares, often called a nasal wash, are the most frequently used methods to assess nasal colonization, although tissue extraction is sometimes used to assess adherent or invasive pathogens (11–14). Differences in the duration of colonization and bacterial interactions have been identified using different tissue extraction methods (14–17). No studies have compared these two sampling methods for their efficiency at extracting the native microbiota and their impact on pathogen-microbiota associations. We used culture-dependent and -independent methods to assess the composition of the URT microbiota using nasal washes and complete tissue collection. Nasal washes were sufficient for sampling the nasopharynx but did not disrupt the turbinates. Nasal tissue collection yielded a distinct community with increased bacterial loads compared to those in nasal wash samples. We show that nasal wash may underestimate the presence and interactions of Streptococcus pneumoniae within the URT. Furthermore, the URT microbiota composition differs by the source of the mice. This approach to microbial analysis of the murine URT will improve the study design of host-pathogen and pathogen-commensal interactions during colonization.

RESULTS

Nasal wash does not completely disrupt nasal surfaces.The biogeography affected by a nasal wash is unknown. We performed nasal washes using a gentle buffer (phosphate-buffered saline [PBS]) or a harsh buffer (buffer RLT), followed by histological assessment of the nasal tissue via hematoxylin-and-eosin staining (Fig. 1A and B). PBS does not affect the epithelial architecture of the nasal cavity (Fig. 1C to E), whereas buffer RLT disrupts the epithelial layer within the nasopharyngeal space and septum as well as the nasal-associated lymphoid tissue (Fig. 1G and H) but not the nasal turbinates (Fig. 1F). Overall, nasal washes with harsh buffers were unable to disrupt a large majority of the epithelial layer in the nasal cavity, implying that nasal washes do not accurately sample the complete biogeography of the nasal tissue (Fig. 1A and B).

FIG 1
  • Open in new tab
  • Download powerpoint
FIG 1

Nasal wash does not effectively sample the nasal cavity. (A) Nasal cavities were washed with PBS (n = 3) and buffer RLT (n = 3), and tissues were collected for histological analysis. (B) Hematoxylin-and-eosin-stained cross sections demonstrate that nasal washes with PBS do not disrupt the epithelial layer compared to buffer RLT. (C to E) Specifically, PBS washes do not impact the epithelial architecture in the turbinates (C and D) or the nasopharyngeal space (E). (F to H) Buffer RLT washes greatly disrupt the nasopharyngeal space (G and H) but not the nasal turbinates (F).

Nasal tissue extraction recovers more bacteria than nasal washes.Nasal wash and nasal tissue samples were homogenized, plated on brain heart infusion (BHI) agar and fastidious anaerobic agar (FAA), and incubated aerobically and anaerobically, respectively. Overall, the bacterial load was low in both complete nasal tissue (cNT) and nasal wash samples (∼103 CFU/mouse). Nasal tissue had significantly higher bacterial loads and diversity of colony morphotypes than nasal wash samples (Fig. 2A). Complementary to culture-based analysis, 16S rRNA gene sequencing revealed that cNT and nasal wash samples clustered separately from each other (Fig. 2B) (P < 0.05 by permutational multivariate analysis of variance [PERMANOVA]; R2 = 0.181). Streptococcus species and Staphylococcus species were dominant in nasal tissue and wash samples (Fig. 2C). This difference in microbial composition was driven by nasal tissue containing significantly more Neisseriaceae, Actinomyces, and Bifidobacterium species, while nasal wash samples contained more Erysipelotrichaceae and Cyanobacteria (Fig. 2D) (linear discriminate analysis [LDA] effect size [LEfSe]). No difference was seen in Shannon diversity (P = 0.26) or observed species (P = 0.4181) between nasal wash and nasal tissue samples (see Fig. S1 in the supplemental material).

FIG 2
  • Open in new tab
  • Download powerpoint
FIG 2

Nasal tissue extraction is essential for complete microbiota assessment. Nasal wash samples were collected using PBS, followed by tissue collection from the same mice and V3 16S rRNA gene high-throughput sequencing. (A) Nasal tissue had significantly more bacteria than nasal wash (NW) samples. (B) Nasal tissue microbial communities clustered separately from nasal wash communities (P < 0.05 by Bray-Curtis PERMANOVA). (C and D) Nasal tissue microbiota were enriched in Neisseriaceae, Bifidobacterium, and Actinomyces, while nasal wash samples were enriched in Erysipelotrichaceae and Cyanobacteria (LEfSe).

FIG S1

No difference in α-diversity between nasal tissue and nasal wash microbiota. Nasal wash samples were collected using PBS, followed by tissue collection from the same mice and V3 16S rRNA gene high-throughput sequencing. There was no difference in observed species (P = 0.4181) or Shannon diversity (P = 0.26). Each dot represents one mouse. Data were analyzed by Mann-Whitney tests. Download FIG S1, TIF file, 0.04 MB.
Copyright © 2020 Schenck et al.

This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

The mouse nasal microbiota is distinct from the gut microbiota.It has been reported that a significant amount of the bacterial DNA found in the URT is from environmental contamination rather than being due to resident microbes (18). In mice, contaminating DNA can come from exposure to fecal matter and/or reagent controls. To determine the degree to which microbial profiles are influenced by fecal exposure, we compared the nasal tissue and gut microbiota within a mouse. The nasal microbiota was distinct from the gut microbiota (Fig. S2A) (P < 0.001 by PERMANOVA; R2 = 0.383). The gut microbiota has greatly increased α-diversity compared to the nasal microbiota (Fig. S2B). Additionally, the dominant families in the gut (Muribaculaceae, Lactobacillaceae, Lachnospiraceae, and Erysipelotrichaceae) are different from the dominant families in the nasal tissue (Streptococcaceae, Staphylococcaceae, and Enterococcaceae) microbiota (Fig. S2C).

FIG S2

The murine nasal microbiota is distinct from the gut microbiota. DNA was extracted from nasal and cecal tissues (n = 9 mice), and the V3 region of the 16S rRNA gene was sequenced. (A) The microbial communities were distinct between the nasal and cecal microbiota (P < 0.001 by PERMANOVA). (B) The alpha-diversity metrics demonstrate greatly increased richness in the cecal microbiota compared to the nasal microbiota (P < 0.001 by a Mann-Whitney test). (C) Taxon summary comparing the family-level identifications of cecal and nasal microbiota. Download FIG S2, EPS file, 0.2 MB.
Copyright © 2020 Schenck et al.

This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

The mouse nasal microbiota is distinct from extraction and sequencing controls.Sequencing and extraction controls are essential for low-biomass microbiota analysis as reagents and tissue handling have been shown to influence the community composition of low-biomass communities (19, 20). In this study, negative extraction (surgical tools dipped in PBS and then exposed to the same extraction process as tissues, cage bedding, and drinking water) and PCR negative (elution water used instead of the DNA template) samples were included to determine the impact of contaminating DNA. The negative samples were distinct from the nasal tissue microbiota (Fig. S3A) (P < 0.05 by PERMANOVA; R2 = 0.138). An unweighted pair group method with arithmetic mean (UPGMA) tree based on Bray-Curtis distances demonstrated the separation between negative controls and samples (Fig. S3B). The dominant taxa in the nasal tissue, namely, Streptococcus and Staphylococcus, are not present in the negative samples (Fig. S3C). The inclusion of negative samples with every extraction is still worthwhile to distinguish low-abundance communities from reagent contamination.

FIG S3

Sequencing and extraction negative controls are distinct from the nasal microbiota. DNA was extracted from nasal tissues, bedding material, drinking water, PBS-exposed surgical tools, or water used in place of the template prior to amplification and sequencing of the V3 region of the 16S rRNA gene. (A) The communities were distinct via Bray-Curtis principal-component analysis (PCoA) (P < 0.05 by PERMANOVA; R2 = 0.138). (B) UPGMA tree based on Bray-Curtis distances demonstrating that the negative samples are distinct from the nasal tissue microbiota. (C) Taxonomic summaries of the negative samples contain several different taxa compared to the nasal tissue. Download FIG S3, EPS file, 0.2 MB.
Copyright © 2020 Schenck et al.

This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

Mouse source affects the composition of the nasal microbiota.Differences in the murine gut microbiota between breeding sites have been identified as a source of experimental variability (21). We compared the nasal tissue microbiota from mice bred at McMaster University (n = 32) to those of mice ordered from Jackson Laboratories (JAX) (n = 15). JAX mice have a significantly different nasal microbiota composition compared to in-house-bred mice (Fig. 3A and B) (P < 0.0001 by PERMANOVA; R2 = 0.226). While both groups of mice are dominated by Streptococcaceae, JAX mice have several other dominant taxa (Fig. 3C). Furthermore, JAX mice had increased α-diversity within the nasal tissue microbiota (P < 0.001 by a Mann-Whitney test) (Fig. 4D). LEfSe analysis revealed that 109 genera were significantly different between JAX and in-house-bred mice, including Mycoplasma (Fig. 4E) and Lactobacillus (Fig. 4F).

FIG 3
  • Open in new tab
  • Download powerpoint
FIG 3

Source of mice impacts nasal microbiota composition. The nasal microbiota of C57BL/6J mice ordered directly from Jackson Laboratories were compared to those of C57BL/6J mice bred in-house for several generations. (A) JAX mice had a significantly distinct microbiota composition (P < 0.0001 by PERMANOVA). (B) Bray-Curtis distance tree demonstrating the clustering of mice from Jackson Laboratories compared to mice bred in-house. (C) Taxon summary at the family level comparing the nasal microbiota of in-house-bred mice to those of JAX mice. (D) Alpha-diversity is increased in Jackson Laboratories murine nasal microbiota compared to those of in-house-bred mice, as measured by observed species, Chao1, and Shannon diversity (P < 0.001 by a Mann-Whitney test). LEfSe analysis revealed 109 genera within the nasal microbiota that were significantly different between in-house mice and Jackson Laboratories mice. (E and F) The nasal microbiota of mice from Jackson Laboratories were enriched in Mycoplasma (E) and decreased in Lactobacillus (F) species compared to mice bred in-house.

FIG 4
  • Open in new tab
  • Download powerpoint
FIG 4

Streptococcus pneumoniae dominates the nasal microbiota during colonization. Female C57BL/6J mice were intranasally colonized with 107 CFU of S. pneumoniae and sacrificed 3 days later for collection of PBS nasal wash samples and complete nasal tissues (n = 9). (A) Nasal tissue had significantly higher pneumococcal loads than the nasal wash samples (P = 0.0078 by a Wilcoxon match-paired signed-rank test). (B) The nasal tissue microbiota was distinct from the nasal wash microbiota (P = 0.0002 by PERMANOVA). (C) Summary taxon plot of the nasal tissue microbiota community (dominated by Streptococcaceae and Mycoplasmataceae) and the PBS nasal wash microbiota (dominated by Tannerellaceae, Streptococcaceae, and Staphylococcaceae).

Streptococcus pneumoniae colonization leads to domination of the nasal microbiota.Streptococcus pneumoniae colonizes the upper respiratory tract, a process which disrupts preexisting microbial communities prior to causing respiratory and invasive infections (9, 10). Investigation into microbial interactions between S. pneumoniae and other nasal microbiota members has been primarily performed by analyzing nasal wash samples, which may overlook microbe-microbe interactions occurring deeper in the nasal tissue. Mice were intranasally colonized with Streptococcus pneumoniae, and nasal wash and tissue samples were collected after 3 days (n = 9 mice). The nasal tissue had higher levels of S. pneumoniae than the paired nasal wash sample (Fig. 4A). The cNT and nasal wash microbiota of colonized mice were distinct (Fig. 3B). S. pneumoniae dominated the nasal tissue (Fig. 4B and C). LEfSe analysis revealed 24 significantly different genera between the two sampling methods (Fig. S4). Spearman correlations identified that the relative abundance of Streptococcus sequence reads strongly correlated with cultured S. pneumoniae in the cNT (R = 0.9) and nasal wash (R = 0.95) samples (Fig. S5). Furthermore, nasal tissue S. pneumoniae CFU correlated with nasal wash CFU (R = 0.95), and Streptococcus amplicon sequence variant (ASV) relative abundances were correlated between nasal tissue and wash samples (R = 0.88).

FIG S4

LEfSe results of PBS nasal wash and tissue microbiota differences in S. pneumoniae-colonized mice. Download FIG S4, EPS file, 0.3 MB.
Copyright © 2020 Schenck et al.

This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

FIG S5

Strong Spearman correlations between cultured S. pneumoniae and Streptococcus ASV relative abundances. Mice were colonized with S. pneumoniae, and PBS nasal wash samples and tissues were collected 3 days later. (A and B) S. pneumoniae in the nasal tissue strongly correlated with Streptococcus ASV relative abundances in the nasal tissue (A) and nasal wash (B) samples. (C) The relative abundances of Streptococcus ASVs are strongly correlated between the nasal wash and nasal tissue samples. (D) Cultured S. pneumoniae CFU in the nasal tissue are strongly correlated with cultured S. pneumoniae CFU in the nasal wash samples. Each dot represents one mouse (n = 9). Download FIG S5, EPS file, 0.3 MB.
Copyright © 2020 Schenck et al.

This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

Nasal microbiota correlations are dependent on the tissue extraction methodology.Staphylococcus species decrease during Streptococcus pneumoniae colonization when sampled by nasal wash (9, 10). Staphylococcus and Streptococcus species were negatively correlated in the nasal wash samples of S. pneumoniae-colonized mice (R = −0.72; P = 0.03) (Fig. 5A); however, there was no significant correlation for the nasal tissue microbiota (R = −0.32; P = 0.41) (Fig. 5B). Corynebacterium species are overrepresented in the nasal microbiota of children and adults negative for pneumococcal colonization and have recently been identified to inhibit the growth of S. pneumoniae in vitro (7). No correlation was found between Corynebacterium and Streptococcus species in the nasal wash microbiota of pneumococcus-colonized mice (R = 0.36; P = 0.35) (Fig. 5C); however, a strong negative correlation (R = −0.95; P = 8.8 × 10−5) between Corynebacterium species and Streptococcus species existed in the nasal tissue (Fig. 5D), suggesting that interactions between these species could occur within regions not affected by nasal washes. These correlations imply that both sampling techniques may be necessary to uncover microbial interactions that are site specific. Furthermore, niche-specific interactions may be driving antagonism or cooperation between S. pneumoniae and other bacterial species in the URT.

FIG 5
  • Open in new tab
  • Download powerpoint
FIG 5

Microbiota interactions depend on the nasal sampling method. Spearman correlations of relative abundances of ASVs in nasal wash samples and nasal tissues of S. pneumoniae-colonized mice were determined. (A and B) Staphylococcus and Streptococcus species have a negative correlation in the PBS nasal wash samples (A) but not nasal tissue (B). (C and D) Corynebacterium species have a negative correlation in the nasal tissue (D) but not the nasal wash samples (C). Each dot represents the relative abundance within one animal, from either nasal wash or tissue samples (n = 9).

DISCUSSION

The upper respiratory tract plays an essential role in breathing, trapping inhaled microbes and particles while heating and humidifying air prior to entering the lungs. The topography provides different niches for bacteria to colonize, resulting in protective or deleterious interactions with other microbial species. This study identified that nasal washes do not completely sample the murine nasal microbiota and may overlook some interactions occurring within the turbinates or submucosa of the nasal tissue. Differences in humidity, mucus secretion, and epithelial cell type could contribute to the colonization success of various pathogens and commensals (22, 23). In humans, sampling of different regions of the nasal cavity distinguished the microbial composition of the anterior nares from that of the middle meatus and sphenoethmoidal recess (24). The middle meatus and sphenoethmoidal recess are dominated by Corynebacterium and Staphylococcus species, while anterior nares have a greater abundance of Propionibacterium/Cutibacterium species. In this study, Actinomyces and Neisseria species were increased in the nasal tissue, whereas the nasal wash samples had greater abundances of Erysipelotrichaceae family members. Actinomyces and Neisseria species in the human nasal microbiota have been associated with an increased risk of acute otitis media.

Select bacterial groups, including Corynebacterium, Staphylococcus, Streptococcus, Dolosigranulum, and Moraxella species, are commonly found in the human nose (25, 26). The murine nasal microbiota has a dominant Staphylococcus and Streptococcus population but small Corynebacterium, Dolosigranulum, and Moraxella species populations, similar to mice obtained from Jackson Laboratories and other facilities (9). Mice can be experimentally colonized by Corynebacterium and Moraxella species, indicating that the low abundance in specific-pathogen-free (SPF) mice could be due to a lack of exposure (27, 28). A major determinant of colonization is adherence, requiring selective interactions between host and bacterial factors. Neisseria meningitidis and Streptococcus pyogenes colonization in mice requires the expression of human-specific adherence factors in the olfactory epithelium (12, 29).

The composition of the microbiota differed between mice bred in-house and those delivered by Jackson Laboratories. Vendor-specific microbiota differences have been identified in gut and lung studies and have been implicated in altering the outcomes of disease models (18, 30, 31); however, our study is the first to demonstrate vendor-specific microbiome differences within the nasal tissue. Housing under SPF conditions at different facilities restricts access to many bacteria beyond pathogens, and SPF mice have drastically different respiratory microbiota compositions compared to wild mice (32). Indeed, mice captured from the wild have more, as well as different, bacteria in their lungs, which influences alveolar structure (32). The impact of differential colonization between facilities and sources may impact the baseline physiology or expression of some genes. Krone et al. previously assessed the murine nasal microbiota by nasal wash and found patterns similar to those in our mice, with high levels of Staphylococcaceae, Streptococcaceae, and Erysipelotrichaceae, but failed to detect Actinomycetaceae (9), which were detected in the nasal tissue samples in this study. Interestingly, Weyrich et al. found high levels of Actinomycetaceae (as well as Streptococcaceae and Staphylococcaceae) in nasal tissue samples from their facility (33). Whether these differences are due to different breeding facilities, housing conditions, or sampling techniques is unclear.

Sequencing-based analysis of the URT microbiota is complicated due to the low microbial biomass compared to host DNA (34). Extraction and amplification methods will affect the outcome of sequencing results, and the inclusion of template negative controls is essential for determination of the microbial composition. We demonstrated that the nasal tissue microbiota is distinct from the gut microbiota and negative controls. Furthermore, there was a strong correlation between the cultivable amount of inoculated S. pneumoniae and the ability to detect Streptococcus ASVs in the nasal tissue and wash samples. This strongly suggests that culture-independent analysis of the nasal tissue microbiota is representative of the cultivable microbiota and not contaminating DNA sequences from environmental or extraction sources.

Colonization is essential during bacterial pathogenesis, including adherence prior to invasion or spread to new hosts. Capsule expression by Streptococcus pneumoniae varies depending on nasal location, which alters its ability to adhere, evade killing, or be transmitted to a new host (35–38). As such, the detection of S. pneumoniae in nasal wash or tissue extraction samples has different implications for transmission versus invasive disease. Multiple studies have reported a negative correlation between Staphylococcus and Streptococcus species, potentially due to hydrogen peroxide production (39, 40). We have shown that this negative correlation exists in the nasopharynx of colonized mice but not in the nasal tissue. Conversely, we have shown a negative correlation between Streptococcus and Corynebacterium species in the nasal tissue but not in the nasal wash samples. Corynebacterium species have been demonstrated to liberate host triacylglycerols that kill S. pneumoniae (7). Previous studies have also implicated differences in Haemophilus influenzae and S. pneumoniae antagonism depending on the sampling method (15, 16). Together, these data suggest that multiple sampling methods may be necessary to determine bacterial interactions within the URT. Human experimental colonization models assess pneumococcal colonization, as well as microbial communities, via nasal wash (41) and identify many antagonistic interactions that have also been seen in murine models of experimental colonization (e.g., negative correlation of Corynebacterium and Streptococcus [41, 42]); however, whether there are microbial interactions missed by this sampling method is unclear. The structure of murine nasal tissue is much more complicated than that of human nasal tissue, so species-specific sampling techniques may be needed to study microbial interactions.

Overall, mechanistic investigation of the URT microbiota in infection and immunity requires animal models. Current studies have used mixed methodologies, including different sampling techniques and mouse vendors, to investigate development and disease phenotypes. Proper extraction and assessment of the nasal tissue of mice are essential to reveal reproducible, mechanistic interactions between host cells and microbial members. Our findings demonstrate that assessment of the nasal microbiota is dependent on biogeography and needs to be integrated into research design for evaluation of pathogen and commensal colonization and interactions.

MATERIALS AND METHODS

Animals.C57Bl/6J mice were bred within the McMaster Central Animal Facility, except for the experiments in which we used female C57Bl/6J mice from Jackson Laboratories (Bar Harbor, ME). Mice from Jackson Labs were 6 to 8 weeks old and acclimated to specific pathogen-free conditions for 2 weeks prior to experiments. All mice had access to food and water ad libitum. All mice used in this study were female mice aged 8 to 12 weeks. Mice were anesthetized using isoflurane and euthanized by exsanguination. All experiments were approved by McMaster University’s Animal Research Ethics Board according to the recommendations of the Canadian Council for Animal Care.

Tissue collection.Nasal wash was completed as previously described (43). Briefly, a PE-20 polyethylene tube attached to a 26-gauge needle was inserted through a small incision in the trachea. Lavages were performed with 300 μl of sterilized phosphate-buffered saline (PBS) or buffer RLT (Qiagen), which was flushed through the trachea and collected through the nares in a 1.7-ml microtube. Complete nasal tissue (cNT) was collected from lavaged or naive mice via bisection of the skull with sterilized surgical tools (44). Excised tissues were homogenized in 300 μl PBS in 2-ml screw-top tubes using 2.8-mm ceramic beads for 1 min at 2,000 rpm (MoBio).

Histological analysis.After nasal washes, mouse heads were placed into formalin for 24 h before being placed in a Shandon TBD-2 decalcifier (Thermo Scientific, Kalamazoo, MI) for 4 days. Decalcified heads were placed in formalin for 2 days, followed by twice-daily washes with PBS for an additional 4 days. Samples were washed with and placed in 70% ethanol prior to standard histological processing and embedded in paraffin wax. Cross-sectional slices (5 μm) were mounted on slides and stained with hematoxylin and eosin according to standard protocols. Slides were randomized and scored in a blind fashion. The integrity of the epithelial lining was measured by quantifying the area of intact/disrupted epithelium using ImageJ.

DNA extraction, amplification, and analysis of the 16S rRNA gene.DNA was extracted from PBS nasal wash and cNT homogenates as previously described (10). Samples were mechanically homogenized with 0.2 g of 0.1-mm glass beads and 0.2 g of 2.8-mm glass beads in 800 μl of 200 mM NaPO4 (pH 8) and 100 μl of guanidine thiocyanate-EDTA-N-lauroyl sarcosine. After homogenization, the sample was incubated with 50 μl of lysozyme (100 mg/ml) and 10 μl of RNase A (10 mg/ml) for 1 h at 37°C, followed by incubation with a solution containing 25 μl sodium dodecyl sulfate (25%), 62.5 μl NaCl (5 M), and 25 μl proteinase K (20 mg/ml) for 1 h at 65°C. Samples were centrifuged for 5 min at maximum speed, and the supernatant was transferred to 900 μl of buffered phenol-chloroform-isoamyl alcohol (25:24:1). Samples were vortexed and centrifuged for 10 min at maximum speed prior to transferring the aqueous phase to DNA Clean and Concentrator-25 columns (Zymo) according to the manufacturer’s instructions, except that samples were eluted with 50 μl ultrapure water. Negative controls included PBS-exposed surgical tools, cage bedding, drinking water, and no-template PCR amplicons.

PCR amplification of the 16S rRNA gene (V3 region) involved a two-step, nested PCR, which improves efficiency in the presence of high host DNA levels (45). The first step involved the amplification of the 16S rRNA gene region spanning V1 to V5 using universal primers 8F (AGAGTTTGATCCTGGCTCAG) and 926R (CCGTCAATTCCTTTRAGTTT) for 15 cycles (94°C for 30 s, 56°C for 30 s, and 72°C for 60 s). This product was used as the template in the second reaction for 25 cycles (94°C for 30 s, 47°C for 30 s, and 72°C for 40 s) to amplify the V3 region of the 16S rRNA gene in preparation for MiSeq (Illumina) sequencing. Barcoded primer sequences were adapted similarly to previous work (46). All reactions, including extraction negative and no-template controls, were performed in triplicate to reduce PCR bias, and reaction mixtures were pooled prior to sequencing using the MiSeq sequencing platform (Illumina, Inc., San Diego, CA) at the Farncombe Genomics Facility at McMaster University. Sequences were trimmed using CutAdapt (47) prior to analysis with DADA2 (48) to organize sequences into amplicon sequence variants (ASVs). Taxonomy was assigned using the Silva database (49). Relative abundance, α- and β-diversity, and rarefactions were completed using the Phyloseq package (50) in R version 3.5.2 (51). A dendrogram was constructed based on unweighted pair group method with arithmetic mean (UPGMA) hierarchical clustering using Bray-Curtis distances using the phangorn package (52) and plotted with iTOL (53). Differences between bacterial communities were tested using permutational multivariate analysis of variance (PERMANOVA) within the vegan package (54). Differences in taxon abundances were assessed using linear discriminate analysis (LDA) effect size (LEfSe) (55).

Streptococcus pneumoniae colonization.Mice were intranasally colonized with S. pneumoniae strain P1547 (serotype 6A), obtained from Jeff Weiser (NYU School of Medicine), as previously described (43). S. pneumoniae was grown in tryptic soy broth in a 5% CO2 incubator at 37°C until cultures were in late log phase (optical density at 600 nm [OD600] = 0.5). Cultures were spun down at 15,000 × g for 1 min and resuspended at a concentration of 109 CFU/ml in PBS. Mice were colonized by depositing 10 μl containing 107 CFU of S. pneumoniae directly in the nares. Mice were sacrificed at 3 days postinoculation prior to PBS nasal wash and cNT sample collection.

Bacterial culture.PBS nasal wash and tissue homogenates were incubated overnight on brain heart infusion agar or tryptic soy agar supplemented with 5% sheep’s blood and neomycin (10 μg/ml) or on prereduced fastidious anaerobic agar in an anaerobic chamber. Colonies were counted and collected via the addition of 1 ml BHI medium and scraping the plate surface with a cell scraper. A portion of the collected colonies was frozen at −80°C in 10% glycerol, while the remainder was prepared for genomic extraction.

Statistical analysis.GraphPad Prism 6 and R were used for statistical analysis. Nonparametric tests were used for comparison of histology scoring and bacterial plate counts. Differences with P values of <0.05 were considered statistically significant. Microbial community composition differences were determined using the Adonis function (PERMANOVA) with 10,000 permutations.

Data availability.Data related to this study have been deposited in the NCBI database under BioProject accession number PRJNA679949.

FIG S6

Individual taxon plots of nasal tissue and PBS nasal wash samples from S. pneumoniae-colonized mice. Download FIG S6, EPS file, 0.2 MB.
Copyright © 2020 Schenck et al.

This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

ACKNOWLEDGMENTS

L.P.S. was supported by a scholarship from the Canadian Institutes of Health Research (CIHR). This work was funded by grants from the CIHR to D.M.E.B. and M.G.S. D.M.E.B. and M.G.S. are supported by the CIHR and hold Canada Research Chairs, with further support from the McMaster Immunology Research Centre and the Michael G. Degroote Institute for Infectious Disease Research.

We thank Laura Rossi, Michelle Shah, and the Farncombe Metagenomic facility for DNA sequencing assistance.

FOOTNOTES

    • Received June 11, 2020.
    • Accepted November 11, 2020.
  • Copyright © 2020 Schenck et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

REFERENCES

  1. 1.↵
    1. Bogaert D,
    2. De Groot R,
    3. Hermans PWM
    . 2004. Streptococcus pneumoniae colonisation: the key to pneumococcal disease. Lancet Infect Dis 4:144–154. doi:10.1016/S1473-3099(04)00938-7.
    OpenUrlCrossRefPubMedWeb of Science
  2. 2.↵
    1. Bogaert D,
    2. van Belkum A,
    3. Sluijter M,
    4. Luijendijk A,
    5. de Groot R,
    6. Rümke HC,
    7. Verbrugh HA,
    8. Hermans PWM
    . 2004. Colonisation by Streptococcus pneumoniae and Staphylococcus aureus in healthy children. Lancet 363:1871–1872. doi:10.1016/S0140-6736(04)16357-5.
    OpenUrlCrossRefPubMedWeb of Science
  3. 3.↵
    1. Regev-Yochay G,
    2. Dagan R,
    3. Raz M,
    4. Carmeli Y,
    5. Shainberg B,
    6. Derazne E,
    7. Rahav G,
    8. Rubinstein E
    . 2004. Association between carriage of Streptococcus pneumoniae and Staphylococcus aureus in children. JAMA 292:716–720. doi:10.1001/jama.292.6.716.
    OpenUrlCrossRefPubMedWeb of Science
  4. 4.↵
    1. Bosch AATM,
    2. van Houten MA,
    3. Bruin JP,
    4. Wijmenga-Monsuur AJ,
    5. Trzciński K,
    6. Bogaert D,
    7. Rots NY,
    8. Sanders EAM
    . 2016. Nasopharyngeal carriage of Streptococcus pneumoniae and other bacteria in the 7th year after implementation of the pneumococcal conjugate vaccine in the Netherlands. Vaccine 34:531–539. doi:10.1016/j.vaccine.2015.11.060.
    OpenUrlCrossRef
  5. 5.↵
    1. Biesbroek G,
    2. Tsivtsivadze E,
    3. Sanders EAM,
    4. Montijn R,
    5. Veenhoven RH,
    6. Keijser BJF,
    7. Bogaert D
    . 2014. Early respiratory microbiota composition determines bacterial succession patterns and respiratory health in children. Am J Respir Crit Care Med 190:1283–1292. doi:10.1164/rccm.201407-1240OC.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Hardy BL,
    2. Dickey SW,
    3. Plaut RD,
    4. Riggins DP,
    5. Stibitz S,
    6. Otto M,
    7. Merrell DS
    . 2019. Corynebacterium pseudodiphtheriticum exploits Staphylococcus aureus virulence components in a novel polymicrobial defense strategy. mBio 10:e02491-18. doi:10.1128/mBio.02491-18.
    OpenUrlCrossRef
  7. 7.↵
    1. Bomar L,
    2. Brugger SD,
    3. Yost BH,
    4. Davies SS,
    5. Lemon KP
    . 2016. Corynebacterium accolens releases antipneumococcal free fatty acids from human nostril and skin surface triacylglycerols. mBio 7:e01725-15. doi:10.1128/mBio.01725-15.
    OpenUrlCrossRef
  8. 8.↵
    1. Cremers AJ,
    2. Zomer AL,
    3. Gritzfeld JF,
    4. Ferwerda G,
    5. van Hijum SA,
    6. Ferreira DM,
    7. Shak JR,
    8. Klugman KP,
    9. Boekhorst J,
    10. Timmerman HM,
    11. de Jonge MI,
    12. Gordon SB,
    13. Hermans PW
    . 2014. The adult nasopharyngeal microbiome as a determinant of pneumococcal acquisition. Microbiome 2:44. doi:10.1186/2049-2618-2-44.
    OpenUrlCrossRefPubMed
  9. 9.↵
    1. Krone CL,
    2. Biesbroek G,
    3. Trzciński K,
    4. Sanders EAM,
    5. Bogaert D
    . 2014. Respiratory microbiota dynamics following Streptococcus pneumoniae acquisition in young and elderly mice. Infect Immun 82:1725–1731. doi:10.1128/IAI.01290-13.
    OpenUrlAbstract/FREE Full Text
  10. 10.↵
    1. Thevaranjan N,
    2. Whelan FJ,
    3. Puchta A,
    4. Ashu E,
    5. Rossi L,
    6. Surette MG,
    7. Bowdish DME
    . 2016. Streptococcus pneumoniae colonization disrupts the microbial community within the upper respiratory tract of aging mice. Infect Immun 84:906–916. doi:10.1128/IAI.01275-15.
    OpenUrlAbstract/FREE Full Text
  11. 11.↵
    1. Owen SJ,
    2. Batzloff M,
    3. Chehrehasa F,
    4. Meedeniya A,
    5. Casart Y,
    6. Logue C,
    7. Hirst RG,
    8. Peak IR,
    9. Mackay‐Sim A,
    10. Beacham IR
    . 2009. Nasal‐associated lymphoid tissue and olfactory epithelium as portals of entry for Burkholderia pseudomallei in murine melioidosis. J Infect Dis 199:1761–1770. doi:10.1086/599210.
    OpenUrlCrossRefPubMed
  12. 12.↵
    1. Kasper KJ,
    2. Zeppa JJ,
    3. Wakabayashi AT,
    4. Xu SX,
    5. Mazzuca DM,
    6. Welch I,
    7. Baroja ML,
    8. Kotb M,
    9. Cairns E,
    10. Cleary PP,
    11. Haeryfar SMM,
    12. McCormick JK
    . 2014. Bacterial superantigens promote acute nasopharyngeal infection by Streptococcus pyogenes in a human MHC class II-dependent manner. PLoS Pathog 10:e1004155. doi:10.1371/journal.ppat.1004155.
    OpenUrlCrossRefPubMed
  13. 13.↵
    1. Meyer Sauteur PM,
    2. de Groot RCA,
    3. Estevão SC,
    4. Hoogenboezem T,
    5. de Bruijn ACJM,
    6. Sluijter M,
    7. de Bruijn MJW,
    8. De Kleer IM,
    9. van Haperen R,
    10. van den Brand JMA,
    11. Bogaert D,
    12. Fraaij PLA,
    13. Vink C,
    14. Hendriks RW,
    15. Samsom JN,
    16. Unger WWJ,
    17. van Rossum AMC
    . 2018. The role of B cells in carriage and clearance of Mycoplasma pneumoniae from the respiratory tract of mice. J Infect Dis 217:298–309. doi:10.1093/infdis/jix559.
    OpenUrlCrossRef
  14. 14.↵
    1. Liang B,
    2. Hyland L,
    3. Hou S
    . 2001. Nasal-associated lymphoid tissue is a site of long-term virus-specific antibody production following respiratory virus infection of mice. J Virol 75:5416–5420. doi:10.1128/JVI.75.11.5416-5420.2001.
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    1. Lysenko ES,
    2. Ratner AJ,
    3. Nelson AL,
    4. Weiser JN
    . 2005. The role of innate immune responses in the outcome of interspecies competition for colonization of mucosal surfaces. PLoS Pathog 1:e1. doi:10.1371/journal.ppat.0010001.
    OpenUrlCrossRefPubMed
  16. 16.↵
    1. Margolis E,
    2. Yates A,
    3. Levin BR
    . 2010. The ecology of nasal colonization of Streptococcus pneumoniae, Haemophilus influenzae and Staphylococcus aureus: the role of competition and interactions with host’s immune response. BMC Microbiol 10:59. doi:10.1186/1471-2180-10-59.
    OpenUrlCrossRefPubMed
  17. 17.↵
    1. Briles DE,
    2. Novak L,
    3. Hotomi M,
    4. van Ginkel FW,
    5. King J
    . 2005. Nasal colonization with Streptococcus pneumoniae includes subpopulations of surface and invasive pneumococci. Infect Immun 73:6945–6951. doi:10.1128/IAI.73.10.6945-6951.2005.
    OpenUrlAbstract/FREE Full Text
  18. 18.↵
    1. Dickson RP,
    2. Erb-Downward JR,
    3. Falkowski NR,
    4. Hunter EM,
    5. Ashley SL,
    6. Huffnagle GB
    . 2018. The lung microbiota of healthy mice are highly variable, cluster by environment, and reflect variation in baseline lung innate immunity. Am J Respir Crit Care Med 198:497–508. doi:10.1164/rccm.201711-2180OC.
    OpenUrlCrossRef
  19. 19.↵
    1. de Goffau MC,
    2. Lager S,
    3. Salter SJ,
    4. Wagner J,
    5. Kronbichler A,
    6. Charnock-Jones DS,
    7. Peacock SJ,
    8. Smith GCS,
    9. Parkhill J
    . 2018. Recognizing the reagent microbiome. Nat Microbiol 3:851–853. doi:10.1038/s41564-018-0202-y.
    OpenUrlCrossRef
  20. 20.↵
    1. Salter SJ,
    2. Cox MJ,
    3. Turek EM,
    4. Calus ST,
    5. Cookson WO,
    6. Moffatt MF,
    7. Turner P,
    8. Parkhill J,
    9. Loman NJ,
    10. Walker AW
    . 2014. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87. doi:10.1186/s12915-014-0087-z.
    OpenUrlCrossRefPubMed
  21. 21.↵
    1. Alegre ML
    . 2019. Mouse microbiomes: overlooked culprits of experimental variability. Genome Biol 20:108. doi:10.1186/s13059-019-1723-2.
    OpenUrlCrossRef
  22. 22.↵
    1. Rigottier-Gois L
    . 2013. Dysbiosis in inflammatory bowel diseases: the oxygen hypothesis. ISME J 7:1256–1261. doi:10.1038/ismej.2013.80.
    OpenUrlCrossRefPubMed
  23. 23.↵
    1. Siegel SJ,
    2. Weiser JN
    . 2015. Mechanisms of bacterial colonization of the respiratory tract. Annu Rev Microbiol 69:425–444. doi:10.1146/annurev-micro-091014-104209.
    OpenUrlCrossRefPubMed
  24. 24.↵
    1. Yan M,
    2. Pamp SJ,
    3. Fukuyama J,
    4. Hwang PH,
    5. Cho DY,
    6. Holmes S,
    7. Relman DA
    . 2013. Nasal microenvironments and interspecific interactions influence nasal microbiota complexity and S. aureus carriage. Cell Host Microbe 14:631–640. doi:10.1016/j.chom.2013.11.005.
    OpenUrlCrossRefPubMed
  25. 25.↵
    1. Biesbroek G,
    2. Bosch AATM,
    3. Wang X,
    4. Keijser BJF,
    5. Veenhoven RH,
    6. Sanders EAM,
    7. Bogaert D
    . 2014. The impact of breastfeeding on nasopharyngeal microbial communities in infants. Am J Respir Crit Care Med 190:298–308. doi:10.1164/rccm.201401-0073OC.
    OpenUrlCrossRefPubMed
  26. 26.↵
    1. Stearns JC,
    2. Davidson CJ,
    3. McKeon S,
    4. Whelan FJ,
    5. Fontes ME,
    6. Schryvers AB,
    7. Bowdish DME,
    8. Kellner JD,
    9. Surette MG
    . 2015. Culture and molecular-based profiles show shifts in bacterial communities of the upper respiratory tract that occur with age. ISME J 9:1246–1259. doi:10.1038/ismej.2014.250.
    OpenUrlCrossRefPubMed
  27. 27.↵
    1. Abreu NA,
    2. Nagalingam NA,
    3. Song Y,
    4. Roediger FC,
    5. Pletcher SD,
    6. Goldberg AN,
    7. Lynch SV
    . 2012. Sinus microbiome diversity depletion and Corynebacterium tuberculostearicum enrichment mediates rhinosinusitis. Sci Transl Med 4:151ra124. doi:10.1126/scitranslmed.3003783.
    OpenUrlAbstract/FREE Full Text
  28. 28.↵
    1. Krishnamurthy A,
    2. McGrath J,
    3. Cripps AW,
    4. Kyd JM
    . 2009. The incidence of Streptococcus pneumoniae otitis media is affected by the polymicrobial environment particularly Moraxella catarrhalis in a mouse nasal colonisation model. Microbes Infect 11:545–553. doi:10.1016/j.micinf.2009.03.001.
    OpenUrlCrossRefPubMedWeb of Science
  29. 29.↵
    1. Johswich KO,
    2. McCaw SE,
    3. Islam E,
    4. Sintsova A,
    5. Gu A,
    6. Shively JE,
    7. Gray-Owen SD
    . 2013. In vivo adaptation and persistence of Neisseria meningitidis within the nasopharyngeal mucosa. PLoS Pathog 9:e1003509. doi:10.1371/journal.ppat.1003509.
    OpenUrlCrossRefPubMed
  30. 30.↵
    1. Velazquez EM,
    2. Nguyen H,
    3. Heasley KT,
    4. Saechao CH,
    5. Gil LM,
    6. Rogers AWL,
    7. Miller BM,
    8. Rolston MR,
    9. Lopez CA,
    10. Litvak Y,
    11. Liou MJ,
    12. Faber F,
    13. Bronner DN,
    14. Tiffany CR,
    15. Byndloss MX,
    16. Byndloss AJ,
    17. Bäumler AJ
    . 2019. Endogenous Enterobacteriaceae underlie variation in susceptibility to Salmonella infection. Nat Microbiol 4:1057–1064. doi:10.1038/s41564-019-0407-8.
    OpenUrlCrossRef
  31. 31.↵
    1. Ivanov II,
    2. Frutos RDL,
    3. Manel N,
    4. Yoshinaga K,
    5. Rifkin DB,
    6. Sartor RB,
    7. Finlay BB,
    8. Littman DR
    . 2008. Specific microbiota direct the differentiation of IL-17-producing T-helper cells in the mucosa of the small intestine. Cell Host Microbe 4:337–349. doi:10.1016/j.chom.2008.09.009.
    OpenUrlCrossRefPubMedWeb of Science
  32. 32.↵
    1. Yun Y,
    2. Srinivas G,
    3. Kuenzel S,
    4. Linnenbrink M,
    5. Alnahas S,
    6. Bruce KD,
    7. Steinhoff U,
    8. Baines JF,
    9. Schaible UE
    . 2014. Environmentally determined differences in the murine lung microbiota and their relation to alveolar architecture. PLoS One 9:e0113466. doi:10.1371/journal.pone.0113466.
    OpenUrlCrossRef
  33. 33.↵
    1. Weyrich LS,
    2. Feaga HA,
    3. Park J,
    4. Muse SJ,
    5. Safi CY,
    6. Rolin OY,
    7. Young SE,
    8. Harvill ET
    . 2014. Resident microbiota affect Bordetella pertussis infectious dose and host specificity. J Infect Dis 209:913–921. doi:10.1093/infdis/jit597.
    OpenUrlCrossRefPubMed
  34. 34.↵
    1. Yu G,
    2. Fadrosh D,
    3. Goedert JJ,
    4. Ravel J,
    5. Goldstein AM
    . 2015. Nested PCR biases in interpreting microbial community structure in 16S rRNA gene sequence datasets. PLoS One 10:e0132253. doi:10.1371/journal.pone.0132253.
    OpenUrlCrossRef
  35. 35.↵
    1. Cundell DR,
    2. Gerard NP,
    3. Gerard C,
    4. Idanpaan-Heikkila I,
    5. Tuomanen EI
    . 1995. Streptococcus pneumoniae anchor to activated human cells by the receptor for platelet-activating factor. Nature 377:435–438. doi:10.1038/377435a0.
    OpenUrlCrossRefPubMedWeb of Science
  36. 36.↵
    1. Kietzman CC,
    2. Gao G,
    3. Mann B,
    4. Myers L,
    5. Tuomanen EI
    . 2016. Dynamic capsule restructuring by the main pneumococcal autolysin LytA in response to the epithelium. Nat Commun 7:10859. doi:10.1038/ncomms10859.
    OpenUrlCrossRefPubMed
  37. 37.↵
    1. Weiser JN,
    2. Bae D,
    3. Epino H,
    4. Gordon SB,
    5. Kapoor M,
    6. Zenewicz LA,
    7. Shchepetov M
    . 2001. Changes in availability of oxygen accentuate differences in capsular polysaccharide expression by phenotypic variants and clinical isolates of Streptococcus pneumoniae. Infect Immun 69:5430–5439. doi:10.1128/iai.69.9.5430-5439.2001.
    OpenUrlAbstract/FREE Full Text
  38. 38.↵
    1. Weiser JN,
    2. Austrian R,
    3. Sreenivasan PK,
    4. Masure HR
    . 1994. Phase variation in pneumococcal opacity: relationship between colonial morphology and nasopharyngeal colonization. Infect Immun 62:2582–2589. doi:10.1128/IAI.62.6.2582-2589.1994.
    OpenUrlAbstract/FREE Full Text
  39. 39.↵
    1. Quintero B,
    2. Araque M,
    3. van der Gaast-de Jongh C,
    4. Escalona F,
    5. Correa M,
    6. Morillo-Puente S,
    7. Vielma S,
    8. Hermans PWM
    . 2011. Epidemiology of Streptococcus pneumoniae and Staphylococcus aureus colonization in healthy Venezuelan children. Eur J Clin Microbiol Infect Dis 30:7–19. doi:10.1007/s10096-010-1044-6.
    OpenUrlCrossRefPubMed
  40. 40.↵
    1. Regev-Yochay G,
    2. Trzcinski K,
    3. Thompson CM,
    4. Malley R,
    5. Lipsitch M
    . 2006. Interference between Streptococcus pneumoniae and Staphylococcus aureus: in vitro hydrogen peroxide-mediated killing by Streptococcus pneumoniae. J Bacteriol 188:4996–5001. doi:10.1128/JB.00317-06.
    OpenUrlAbstract/FREE Full Text
  41. 41.↵
    1. de Steenhuijsen Piters WAA,
    2. Jochems SP,
    3. Mitsi E,
    4. Rylance J,
    5. Pojar S,
    6. Nikolaou E,
    7. German EL,
    8. Holloway M,
    9. Carniel BF,
    10. Chu MLJN,
    11. Arp K,
    12. Sanders EAM,
    13. Ferreira DM,
    14. Bogaert D
    . 2019. Interaction between the nasal microbiota and S. pneumoniae in the context of live-attenuated influenza vaccine. Nat Commun 10:2981. doi:10.1038/s41467-019-10814-9.
    OpenUrlCrossRef
  42. 42.↵
    1. Kelly MS,
    2. Surette MG,
    3. Smieja M,
    4. Rossi L,
    5. Luinstra K,
    6. Steenhoff AP,
    7. Goldfarb DM,
    8. Pernica JM,
    9. Arscott-Mills T,
    10. Boiditswe S,
    11. Mazhani T,
    12. Rawls JF,
    13. Cunningham CK,
    14. Shah SS,
    15. Feemster KA,
    16. Seed PC
    . 2018. Pneumococcal colonization and the nasopharyngeal microbiota of children in Botswana. Pediatr Infect Dis J 37:1176–1183. doi:10.1097/INF.0000000000002174.
    OpenUrlCrossRef
  43. 43.↵
    1. Puchta A,
    2. Verschoor CP,
    3. Thurn T,
    4. Bowdish DME
    . 2014. Characterization of inflammatory responses during intranasal colonization with Streptococcus pneumoniae. J Vis Exp 2014:e50490. doi:10.3791/50490.
    OpenUrlCrossRef
  44. 44.↵
    1. Zeppa JJ,
    2. Wakabayashi AT,
    3. Kasper KJ,
    4. Xu SX,
    5. Haeryfar SMM,
    6. McCormick JK
    . 2016. Nasopharyngeal infection of mice with Streptococcus pyogenes and in vivo detection of superantigen activity. Methods Mol Biol 1396:95–107. doi:10.1007/978-1-4939-3344-0_8.
    OpenUrlCrossRef
  45. 45.↵
    1. Stearns JC,
    2. Lynch MDJ,
    3. Senadheera DB,
    4. Tenenbaum HC,
    5. Goldberg MB,
    6. Cvitkovitch DG,
    7. Croitoru K,
    8. Moreno-Hagelsieb G,
    9. Neufeld JD
    . 2011. Bacterial biogeography of the human digestive tract. Sci Rep 1:170. doi:10.1038/srep00170.
    OpenUrlCrossRefPubMed
  46. 46.↵
    1. Bartram AK,
    2. Lynch MDJ,
    3. Stearns JC,
    4. Moreno-Hagelsieb G,
    5. Neufeld JD
    . 2011. Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end Illumina reads. Appl Environ Microbiol 77:3846–3852. doi:10.1128/AEM.02772-10.
    OpenUrlAbstract/FREE Full Text
  47. 47.↵
    1. Martin M
    . 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17:10–12. doi:10.14806/ej.17.1.200.
    OpenUrlCrossRefPubMed
  48. 48.↵
    1. Callahan BJ,
    2. McMurdie PJ,
    3. Rosen MJ,
    4. Han AW,
    5. Johnson AJA,
    6. Holmes SP
    . 2016. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. doi:10.1038/nmeth.3869.
    OpenUrlCrossRefPubMed
  49. 49.↵
    1. Quast C,
    2. Pruesse E,
    3. Yilmaz P,
    4. Gerken J,
    5. Schweer T,
    6. Yarza P,
    7. Peplies J,
    8. Glöckner FO
    . 2013. The SILVA ribosomal RNA gene database project: improved data processing and Web-based tools. Nucleic Acids Res 41:D590–D596. doi:10.1093/nar/gks1219.
    OpenUrlCrossRefPubMedWeb of Science
  50. 50.↵
    1. McMurdie PJ,
    2. Holmes S
    . 2013. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8:e61217. doi:10.1371/journal.pone.0061217.
    OpenUrlCrossRefPubMed
  51. 51.↵
    R Core Team. 2018. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
  52. 52.↵
    1. Schliep KP
    . 2011. phangorn: phylogenetic analysis in R. Bioinformatics 27:592–593. doi:10.1093/bioinformatics/btq706.
    OpenUrlCrossRefPubMedWeb of Science
  53. 53.↵
    1. Letunic I,
    2. Bork P
    . 2016. Interactive Tree of Life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res 44:W242–W245. doi:10.1093/nar/gkw290.
    OpenUrlCrossRefPubMed
  54. 54.↵
    1. Oksanen J,
    2. Blanchet FG,
    3. Friendly M,
    4. Roeland K,
    5. Legendre P,
    6. McGlinn D,
    7. Minchin PR,
    8. O’Hara RB,
    9. Simpson GL,
    10. Solymos P,
    11. Stevens MHH,
    12. Szoecs E,
    13. Wagner H
    . 2019. vegan: community ecology package. R package version 2.5-4.
  55. 55.↵
    1. Segata N,
    2. Izard J,
    3. Waldron L,
    4. Gevers D,
    5. Miropolsky L,
    6. Garrett WS,
    7. Huttenhower C
    . 2011. Metagenomic biomarker discovery and explanation. Genome Biol 12:R60. doi:10.1186/gb-2011-12-6-r60.
    OpenUrlCrossRefPubMed
View Abstract
PreviousNext
Back to top
Download PDF
Citation Tools
Nasal Tissue Extraction Is Essential for Characterization of the Murine Upper Respiratory Tract Microbiota
L. Patrick Schenck, Joshua J. C. McGrath, Daphnée Lamarche, Martin R. Stämpfli, Dawn M. E. Bowdish, Michael G. Surette
mSphere Dec 2020, 5 (6) e00562-20; DOI: 10.1128/mSphere.00562-20

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Print
Alerts
Sign In to Email Alerts with your Email Address
Email

Thank you for sharing this mSphere article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Nasal Tissue Extraction Is Essential for Characterization of the Murine Upper Respiratory Tract Microbiota
(Your Name) has forwarded a page to you from mSphere
(Your Name) thought you would be interested in this article in mSphere.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Nasal Tissue Extraction Is Essential for Characterization of the Murine Upper Respiratory Tract Microbiota
L. Patrick Schenck, Joshua J. C. McGrath, Daphnée Lamarche, Martin R. Stämpfli, Dawn M. E. Bowdish, Michael G. Surette
mSphere Dec 2020, 5 (6) e00562-20; DOI: 10.1128/mSphere.00562-20
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Top
  • Article
    • ABSTRACT
    • INTRODUCTION
    • RESULTS
    • DISCUSSION
    • MATERIALS AND METHODS
    • ACKNOWLEDGMENTS
    • FOOTNOTES
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

KEYWORDS

Streptococcus pneumoniae
colonization
microbiota
upper respiratory tract

Related Articles

Cited By...

About

  • About mSphere
  • Board of Editors
  • Policies
  • For Reviewers
  • For the Media
  • Embargo Policy
  • For Librarians
  • For Advertisers
  • Alerts
  • RSS
  • FAQ
  • Permissions
  • Journal Announcements

Authors

  • ASM Author Center
  • Submit a Manuscript
  • Author Warranty
  • Types of Articles
  • Getting Started
  • Ethics
  • Contact Us

Follow #mSphereJ

@ASMicrobiology

       

 

Website feedback

ASM Journals

ASM journals are the most prominent publications in the field, delivering up-to-date and authoritative coverage of both basic and clinical microbiology.

About ASM | Contact Us | Press Room

 

ASM is a member of

Scientific Society Publisher Alliance

 

American Society for Microbiology
1752 N St. NW
Washington, DC 20036
Phone: (202) 737-3600

Copyright © 2021 American Society for Microbiology | Privacy Policy | Website feedback

Online ISSN: 2379-5042