Pediatric oropharyngeal microbiome: Mapping in chronic tonsillitis and tonsillar hypertrophy

Differences in salivary microbiome among children with tonsillar hypertrophy and/or adenoid hypertrophy

Children diagnosed with severe tonsillar hypertrophy display discernible craniofacial features distinct from those with adenoid hypertrophy, prompting illuminating considerations regarding microbiota regulation in this non-inflammatory condition. The present study aimed to characterize the salivary microbial profile in children with tonsillar hypertrophy and explore the potential functionality therein. A total of 112 children, with a mean age of 7.79 ± 2.41 years, were enrolled and divided into the tonsillar hypertrophy (TH) group (n = 46, 8.4 ± 2.5 years old), adenoid hypertrophy (AH) group (n = 21, 7.6 ± 2.8 years old), adenotonsillar hypertrophy (ATH) group (n = 23, 7.2 ± 2.1 years old), and control group (n = 22, 8.6 ± 2.1 years old). Unstimulated saliva samples were collected, and microbial profiles were analyzed by 16S rRNA sequencing of V3-V4 regions. Diversity and composition of salivary microbiome and the correlation with parameters of overnight polysomnography and complete blood count were investigated. As a result, children with tonsillar hypertrophy had significantly higher α-diversity indices (P＜0.05). β-diversity based on Bray-Curtis distance revealed that the salivary microbiome of the tonsillar hypertrophy group had a slight separation from the other three groups (P＜0.05). The linear discriminant analysis effect size (LEfSe) analysis indicated that Gemella was most closely related to tonsillar hypertrophy, and higher abundance of Gemella, Parvimonas, Dialister, and Lactobacillus may reflect an active state of immune regulation. Meanwhile, children with different degrees of tonsillar hypertrophy shared similar salivary microbiome diversity. This study demonstrated that the salivary microbiome in pediatric tonsillar hypertrophy patients had different signatures, highlighting that the site of upper airway obstruction primarily influences the salivary microbiome rather than hypertrophy severity.IMPORTANCETonsillar hypertrophy is the most frequent cause of upper airway obstruction and one of the primary risk factors for pediatric obstructive sleep apnea (OSA). Studies have discovered that children with isolated tonsillar hypertrophy exhibit different craniofacial morphology features compared with those with isolated adenoid hypertrophy or adenotonsillar hypertrophy. Furthermore, characteristic salivary microbiota from children with OSA compared with healthy children has been identified in our previous research. However, few studies provided insight into the relationship between the different sites of upper airway obstruction resulting from the enlargement of pharyngeal lymphoid tissue at different sites and the alterations in the microbiome. Here, to investigate the differences in the salivary microbiome of children with tonsillar hypertrophy and/or adenoid hypertrophy, we conducted a cross-sectional study and depicted the unique microbiome profile of pediatric tonsillar hypertrophy, which was mainly characterized by a significantly higher abundance of genera belonging to phyla Firmicutes and certain bacteria involving in the immune response in tonsillar hypertrophy, offering novel perspectives for future related research.

Tongue microbiota in relation to the breathing preference in children undergoing orthodontic treatment

BACKGROUND

Mouth breathing (MB), a risk factor of oral dysbiosis and halitosis, is linked with craniofacial anomalies and pediatric obstructive sleep apnea. Here, we aimed to analyze tongue microbiota in children from the perspective of their breathing pattern before/during orthodontic treatment.

METHODS

This prospective case-control study included 30 children with orthodontic anomalies, 15 with MB and 15 with nasal breathing (NB), matched by age, sex, and body mass index. All underwent orthodontic examination and sleep apnea monitoring. Tongue swabs were collected before starting (timepoint M0) and approx. six months into the orthodontic therapy (timepoint M6). Oral candidas and bacteriome were analyzed using mass spectrometry technique and 16S rRNA sequencing, respectively.

RESULTS

MB was associated with higher apnea-hypopnea index. At M0, oral candidas were equally present in both groups. At M6, Candida sp. were found in six children with MB but in none with NB. No significant differences in bacterial diversity were observed between groups and timepoints. However, presence/relative abundance of genus Solobacterium was higher in children with MB than NB at M0.

CONCLUSIONS

Significant links between MB and the presence of genus Solobacterium (M0) as well as Candida sp. (M6) were found in children with orthodontic anomalies, highlighting the risk of halitosis in them.

The association of tonsillar microbiota with biochemical indices based on obesity and tonsillar hypertrophy in children

The correlation between tonsil microbiome and tonsillar hypertrophy has not been well established. Given that oral dysbiosis is related to several metabolic diseases and that tonsillar hypertrophy leads to disordered breathing during sleep and obesity in children, it is necessary to investigate the relationship between the oral microbiome and tonsillar hypertrophy. After 16S rRNA amplicon sequencing of tonsillectomy samples, we evaluated the correlation between the tonsil microbiome and biochemical blood indices in pediatric patients who underwent tonsillectomy. Groups are classified into two categories: based on BMI, and grades 2, 3, and 4 based on tonsil size. Children with obesity and tonsillar hypertrophy have similar microbiome compositions and induce comparable changes in microbiome abundance and composition, confirming the association from a metagenomic perspective. In addition, obesity and tonsillar hypertrophy demonstrated a strong correlation with the Proteobacteria to Firmicutes (P/F) ratio, and among various biochemical indicators, alanine aminotransferase (ALT) levels increase with obesity and tonsillar hypertrophy, indicating a possible association of tonsil microbiome and liver metabolism. These novel findings demonstrate the significance of the tonsil microbiome and suggest the need for tonsil regulation, particularly during childhood.

A Potential Partnership between Genetics and the Oral Microbiome in Children Displaying Periodic Fever/Aphthosis/Pharyngitis/Adenitis Syndrome

Periodic fever/aphthosis/pharyngitis/adenitis (PFAPA) syndrome was initially described in a small cohort of American children [...].

From-Toilet-to-Freezer: A Review on Requirements for an Automatic Protocol to Collect and Store Human Fecal Samples for Research Purposes

The composition, viability and metabolic functionality of intestinal microbiota play an important role in human health and disease. Studies on intestinal microbiota are often based on fecal samples, because these can be sampled in a non-invasive way, although procedures for sampling, processing and storage vary. This review presents factors to consider when developing an automated protocol for sampling, processing and storing fecal samples: donor inclusion criteria, urine-feces separation in smart toilets, homogenization, aliquoting, usage or type of buffer to dissolve and store fecal material, temperature and time for processing and storage and quality control. The lack of standardization and low-throughput of state-of-the-art fecal collection procedures promote a more automated protocol. Based on this review, an automated protocol is proposed. Fecal samples should be collected and immediately processed under anaerobic conditions at either room temperature (RT) for a maximum of 4 h or at 4 °C for no more than 24 h. Upon homogenization, preferably in the absence of added solvent to allow addition of a buffer of choice at a later stage, aliquots obtained should be stored at either -20 °C for up to a few months or -80 °C for a longer period-up to 2 years. Protocols for quality control should characterize microbial composition and viability as well as metabolic functionality.

Changes in the oral and nasal microbiota in pediatric obstructive sleep apnea

Background

Several clinical studies have demonstrated that pediatric obstructive sleep apnea (OSA) is associated with dysbiosis of airway mucosal microbiota. However, how oral and nasal microbial diversity, composition, and structure are altered in pediatric OSA has not been systemically explored.

Methods

30 polysomnography-confirmed OSA patients with adenoid hypertrophy, and 30 controls who did not have adenoid hypertrophy, were enrolled. Swabs from four surface oral tissue sites (tongue base, soft palate, both palatine tonsils, and adenoid) and one nasal swab from both anterior nares were collected. The 16S ribosomal RNA (rRNA) V3-V4 region was sequenced to identify the microbial communities.

Results

The beta diversity and microbial profiles were significantly different between pediatric OSA patients and controls at the five upper airway sites. The abundances of Haemophilus, Fusobacterium, and Porphyromonas were higher at adenoid and tonsils sites of pediatric patients with OSA. Functional analysis revealed that the differential pathway between the pediatric OSA patients and controls involved glycerophospholipids and amino acid metabolism.

Conclusions

In this study, the oral and nasal microbiome of pediatric OSA patients exhibited certain differences in composition compared with the controls. However, the microbiota data could be useful as a reference for studies on the upper airway microbiome.

Respiratory microorganisms in acute pharyngitis patients: Identification, antibiotic prescription patterns and appropriateness, and antibiotic resistance in private primary care, central Malaysia

Acute pharyngitis (AP) is a common reason for private primary care consultations, thus providing an avenue for widespread antibiotic intake among the community. However, there is limited data on the antibiotic prescription appropriateness and resistance information in the Malaysian private primary care setting, therefore, this study aimed to investigate the prevalence of isolated viruses and bacteria, antibiotic resistance patterns, antibiotic prescription patterns and appropriateness by general practitioners (GPs) and factors affecting antibiotic resistance and antibiotic prescription patterns. To investigate, a cross-sectional study was conducted among 205 patients presenting with AP symptoms at private primary care clinics in central Malaysia from 3rd January 2016 to 30th November 2016. Throat swabs were collected from 205 AP patients for two purposes: (i) the detection of four common respiratory viruses associated with AP via reverse-transcription real-time PCR (qRT-PCR); and (ii) bacterial identification using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS). Bacterial isolates were then subjected to antibiotic susceptibility screening and McIsaac scoring was calculated post-prescription based on GP selection of criteria. Generalized estimating equations analysis with multiple logistic regression was conducted to identify factors associated with presence of virus and antibiotic prescription. The results showed that 95.1% (195/205) of patients had at least one of the four viruses, with rhinovirus (88.5%) being the most prevalent, followed by adenovirus (74.9%), influenza A virus (4.6%) and enterovirus (2.1%). A total of 862 non-repetitive colonies were isolated from the culture of throat swabs from 205 patients who were positive for bacteria. From a total of 22 genera, Streptococcus constitutes the most prevalent bacteria genus (40.9%), followed by Neisseria (20%), Rothia (13.0%), Staphylococcus (11%) and Klebsiella (4.9%). Only 5 patients carried group A beta-hemolytic streptococci (GABHS). We also report the presence of vancomycin-resistant S. aureus or VRSA (n = 9, 10.1%) among which one isolate is a multidrug-resistant methicillin-resistant S. aureus (MDR-MRSA), while 54.1% (n = 111) were found to carry at least one antibiotic-resistant bacteria species. Application of the McIsaac scoring system indicated that 87.8% (n = 180) of patients should not be prescribed antibiotics as the majority of AP patients in this study had viral pharyngitis. The antibiotic prescription appropriateness by applying post-prescription McIsaac scoring was able to rule out GABHS pharyngitis in this sample with a GABHS culture-positive sensitivity of 40% (n = 2/5) and specificity of 90% (180/200). In conclusion, antibiotic-resistant throat isolates and over-prescription of antibiotics were observed and McIsaac scoring system is effective in guiding GPs to determine occurrences of viral pharyngitis to reduce unnecessary antibiotic prescription.

Characteristics of salivary microbiota in children with obstructive sleep apnea: A prospective study with polysomnography

Objectives

The present study aimed to investigate the characteristics of salivary microbiota of children with obstructive sleep apnea (OSA) and to assess longitudinal alterations in salivary microbiota before and after adenotonsillectomy.

Methods

A set of cross-sectional samples consisted of 36 OSA children (17 boys and 19 girls, 7.47 ± 2.24 years old) and 22 controls (9 boys and 13 girls, 7.55 ± 2.48 years old) were included in the study, among which eight OSA children (five boys and three girls, 8.8 ± 2.0 years old) who underwent treatment of adenotonsillectomy were followed up after 1 year. Saliva samples were collected, and microbial profiles were analyzed by bioinformatics analysis based on 16S rRNA sequencing.

Results

In cross-sectional samples, the OSA group had higher α-diversity as estimated by Chao1, Shannon, Simpson, Pielou_e, and observed species as compared with the control group (p < 0.05). β-Diversity based on the Bray–Curtis dissimilarities (p = 0.004) and Jaccard distances (p = 0.001) revealed a significant separation between the OSA group and control group. Nested cross-validated random forest classifier identified the 10 most important genera (Lactobacillus, Escherichia, Bifidobacterium, Capnocytophaga, Bacteroidetes_[G-7], Parvimonas, Bacteroides, Klebsiella, Lautropia, and Prevotella) that could differentiate OSA children from controls with an area under the curve (AUC) of 0.94. Linear discriminant analysis effect size (LEfSe) analysis revealed a significantly higher abundance of genera such as Prevotella (p = 0.027), Actinomyces (p = 0.015), Bifidobacterium (p < 0.001), Escherichia (p < 0.001), and Lactobacillus (p < 0.001) in the OSA group, among which Prevotella was further corroborated in longitudinal samples. Prevotella sp_HMT_396 was found to be significantly enriched in the OSA group (p = 0.02) with significantly higher levels as OSA severity increased (p = 0.014), and it had a lower abundance in the post-treatment group (p = 0.003) with a decline in each OSA child 1 year after adenotonsillectomy.

Conclusions

A significantly higher microbial diversity and a significant difference in microbial composition and abundance were identified in salivary microbiota of OSA children compared with controls. Meanwhile, some characteristic genera (Prevotella, Actinomyces, Lactobacillus, Escherichia, and Bifidobacterium) were found in OSA children, among which the relationship between Prevotella spp. and OSA is worth further studies.

A Correlation Study of the Microbiota Between Oral Cavity and Tonsils in Children With Tonsillar Hypertrophy

Tonsillar hypertrophy is a common disease in 3-to-6-year-old children, which may cause serve symptoms like airway obstruction. Microbiological factors play an important role in the etiology of tonsillar hypertrophy. As the starting point of digestive and respiratory tracts, the microbial composition of the oral cavity is not only unique but also closely related to the resident microbiota in other body sites. Here we reported a correlation study of the microbiota between oral cavity and tonsils in children with tonsillar hypertrophy. Saliva, supragingival plaque, and wiped samples from the tonsil surface were collected from both tonsillar hypertrophy patients and participants with healthy tonsils and were then analyzed using Illumina Miseq Sequencing of the 16S rRNA gene. In the tonsillar hypertrophic state, more genera were detected on the tonsil surface than in the tonsil parenchyma, with more intra-microbiota correlations. When tonsillar hypertrophy occurred, both the oral cavity and tonsil surface endured microbiome shift with increased genera category and more active bacterial interactions. Over half of the newly detected genera from the tonsillar hypertrophic state were associated with infection and inflammation process or exhibited antibiotic-resistant characters. Of each individual, the microbial composition and structure of saliva seemed more similar to that of the tonsil surface, compared with the supragingival plaque. In salivary microbiota, genus Johnsonella might be relative with the healthy state of tonsils, while Pseudoxanthomonas might be relative with tonsillar hypertrophy. Our study supported the link between oral microbiota with the healthy and hypertrophic states of tonsils and may provide new directions for future researches in the specific role of oral microbiota in the etiology of tonsil diseases.

Distinct microbial communities colonize tonsillar squamous cell carcinoma

Squamous cell carcinoma of the tonsil is one of the most frequent cancers of the oropharynx. The escalating rate of tonsil cancer during the last decades is associated with the increase of high risk-human papilloma virus (HR-HPV) infections. While the microbiome in oropharyngeal malignant diseases has been characterized to some extent, the microbial colonization of HR-HPV-associated tonsil cancer remains largely unknown. Using 16S rRNA gene amplicon sequencing, we have characterized the microbiome of human palatine tonsil crypts in patients suffering from HR-HPV-associated tonsil cancer in comparison to a control cohort of adult sleep apnea patients. We found an increased abundance of the phyla Firmicutes and Actinobacteria in tumor patients, whereas the abundance of Spirochetes and Synergistetes was significantly higher in the control cohort. Furthermore, the accumulation of several genera such as Veillonella, Streptococcus and Prevotella_7 in tonsillar crypts was associated with tonsil cancer. In contrast, Fusobacterium, Prevotella and Treponema_2 were enriched in sleep apnea patients. Machine learning-based bacterial species analysis indicated that a particular bacterial composition in tonsillar crypts is tumor-predictive. Species-specific PCR-based validation in extended patient cohorts confirmed that differential abundance of Filifactor alocis and Prevotella melaninogenica is a distinct trait of tonsil cancer. This study shows that tonsil cancer patients harbor a characteristic microbiome in the crypt environment that differs from the microbiome of sleep apnea patients on all phylogenetic levels. Moreover, our analysis indicates that profiling of microbial communities in distinct tonsillar niches provides microbiome-based avenues for the diagnosis of tonsil cancer.

The Microbiome in Obstructive Sleep Apnea

Recent evidence has highlighted important associations between obstructive sleep apnea and the microbiome. Although the intricacies of the pathophysiologic mechanisms are not well understood, available evidence suggests a bidirectional relationship between OSA and microbiota composition. Sleep fragmentation, intermittent hypoxia, and intermittent hypercapnia all play significant roles in altering the microbiome, and initial evidence has shown that alterations of the microbiota affect sleep patterns. Animal model evidence strongly supports the idea that the microbiome mediates disease states associated with OSA including hypertension, atherosclerosis, and obesity. The majority of evidence focuses on changes in the gut microbiome, which may result from OSA as well as contribute to sleep pattern changes, OSA-related CVD, and obesity. Meanwhile, a developing body of work suggests changes in the upper airway microbiome may be associated with OSA and periodontitis-related oral cavity microbiome changes may have significance in OSA-related CVD. Lastly, while evidence is limited, several studies suggest there may be a role for treatment of OSA and OSA-related comorbidities through alteration of the microbiome with probiotics, prebiotics, and microbiota transplantation. These early animal and human studies begin to characterize the interrelationships of the microbiome and OSA and may lead to new avenues for treatment.

A Longitudinal Study of the Human Oropharynx Microbiota Over Time Reveals a Common Core and Significant Variations With Self-Reported Disease

Our understanding of human microbial communities, in particular in regard to diseases is advancing, yet the basic understanding of the microbiome in healthy subjects over time remains limited. The oropharynx is a key target for colonization by several important human pathogens. To understand how the oropharyngeal microbiome might limit infections, and how intercurrent infections might be associated with its composition, we characterized the oropharyngeal microbiome of 18 healthy adults, sampled weekly over a 40-weeks using culture-independent molecular techniques. We detected nine phyla, 202 genera and 1438 assignments on OTU level, dominated by Firmicutes, Bacteroidetes, and Proteobacteria on phylum level. Individual microbiomes of participants were characterized by levels of high alpha diversity (mean = 204.55 OTUs, sd = 35.64), evenness (19.83, sd = 9.74) and high temporal stability (mean Pearson's correlation between samples of 0.52, sd = 0.060), with greater differences in microbiome community composition between than within individuals. Significant changes in community composition were associated with disease states, suggesting that it is possible to detect specific changes in OTU abundance and community composition during illness. We defined the common core microbiota by varying occurrence and abundance thresholds showing that individual core microbiomes share a substantial number of OTUs across participants, chiefly Streptococci and Veillonella. Our results provide insights into the microbial communities that characterize the healthy human oropharynx, community structure and variability, and provide new approaches to define individual and shared cores. The wider implications of this result include the potential for modeling the general dynamics of oropharynx microbiota both in health and in response to antimicrobial treatments or probiotics.