Structural and functional changes in the oral microbiome of the patients with craniofacial microsomia

Structural and functional changes in the oral microbiome of the patients with craniofacial microsomia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Structural and functional changes in the oral microbiome of the patients with craniofacial microsomia TIANYING ZANG, XIAOJUN TANG, Zhiyong ZHANG, WEI LIU, LIN YIN, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4673616/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Feb, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background Craniofacial microsomia (CFM), the second most common congenital craniofacial deformity, has manifold clinical manifestations and treatments that may interact with oral bacteria dysbiosis (OBD). However, studies exploring the relationship between CFM and OBD are scanty. Methods Saliva samples of 20 patients with CFM and 24 controls were collected, and oral microflora and gene function annotation were compared using 16S ribosomal RNA and metagenomics. The correlation between clinical phenotypes of CFM and microbiota community structure was also evaluated. Results The oral microflora of CFM patients exhibited higher richness and evenness. The dominant genera in CFM were mainly pathogenic and included Actinomyces , Fusobacterium , and Prevotella . The severity of CFM was significantly positively correlated with the abundance of Neisseria and Porphyromonas . The upregulated pathways were primarily enriched in biotin and amino acid metabolism, including Tryptophan metabolism, which positively correlated with the abundance of Neisseria. Conclusion This study suggests for the first time that patients with CFM exhibit distinct oral bacterial dysbiosis, characterized by an elevated prevalence of opportunistic pathogens and upregulated pathways associated with oral and systemic health. These findings provide evidence for corresponding preventions and therapeutic interventions of CFM. craniofacial microsomia microflora oral cavity 16S rRNA metagenomics Figures Figure 1 Figure 2 Figure 3 Introduction During embryogenesis, the craniomaxillofacial region is developed from frontonasal prominence, maxillary prominence, mandibular prominence, median nasal prominence, and lateral nasal prominence. Disturbances in the development of the first and second pharyngeal arches during the first 6 weeks of the embryonic stage may lead to a series of deformations and craniofacial microsomia (CFM). CFM, the second most common congenital craniofacial malformation after cleft lip and palate, manifests as mandible, maxilla, ear, facial nerve, and muscle underdevelopment. CFM is characterized by dental anomalies resulting from first pharyngeal arch dysplasia 1,2,3 . Children born with craniofacial deformity are susceptible to poor oral health 4 , often caused by oral structural deficiencies (OSD). The deformed oral structure may result in poor oral hygiene and disorderly oral microenvironment homeostasis, further inhibiting alveolar bone homeostasis, masseter dysfunction, delayed development of permanent teeth, and even the disruption of orthodontic and orthognathic treatment planning 5, 6, 7, 8 . In CFM patients, OSD includes abnormal maxilla and mandible, dental agenesis, delayed dental development, tooth size anomalies, abnormal tooth morphology, and enamel defects 9 . Meanwhile, obstructive sleep apnea syndrome (OSAS), one of the manifestations of CFM, and typical treatments of CFM, including mandibular distraction osteogenesis, orthodontics, or orthognathic surgery, have been associated with oral bacteria dysbiosis (OBD). However, the oral health status of patients with CFM remains to be fully elucidated. Oral microenvironment homeostasis comprises oral anatomy, microbiota, mucosal immune system, epithelial barrier, and other factors. All the elements interact with each other in a complex, diverse, and dynamic way. The oral microbiota, an essential part of oral homeostasis, is the second largest microbiota in humans and encompasses bacteria, fungi, viruses, and some low-abundance microbiota. Among these, bacteria constitute the main component of the oral microbiota because of their rich types and quantities. Various endogenous and exogenous factors, such as anatomical structure, oral hygiene habits, and OSAS, interact with the oral bacteria. Then, the interaction and balance of oral bacteria further affect oral health and even systemic diseases. Therefore, change in the abundance, structure, and function of oral bacteria is a vital evaluation indicator of oral health status 10, 11,12, 13 . Multiple clinical manifestations and treatments have been shown to influence and interact with oral health in patients with CFM. Therefore, exploring the potential structural and functional changes in the oral microbiota of CFM patients is imperative to establish a basis for the inclusion of oral hygiene therapies in future treatment regimens for CFM. However, there is currently no comparative analysis of the oral flora between CFM patients and normal controls. Thus, the present study sought to compare the characteristics and changes in oral bacteria of CFM patients using 16S ribosomal RNA (rRNA) and evaluate potential corresponding functional molecular change using metagenomics. Combined multi-omics approaches were utilized to preliminarily characterize the oral microbiota of CFM and assess whether changes in the microbiota of CFM patients mediate functional changes. Materials and Methods Subject selection CFM patients were recruited from Maxillo-facial Surgery Center, XXXXXX, from November 2022 to April 2023. Healthy controls diagnosed with hypertrophic scarring were recruited from the Department of Scar & Wound Treatment of Plastic Surgery Hospital from October 2022 to April 2023. Inclusion criteria were as follows: (1) patients diagnosed with CFM and classified according to the Pruzansky-Kaban Classification and healthy controls diagnosed with hypertrophic scarring; (2) aged 6–12 years old (the mixed dentition stage); (3) parents or guardians signed the informed consent form. Exclusion criteria were as follows: (1) no other systemic diseases reported except for CFM or hypertrophic scarring; (2) those who had not taken probiotics, fluoride, or antibiotics for at least 3 months; (3) those who had not received periodontal and/or OSAS treatment in the last 1 month; (4) particular dietary preference such as vegetarianism; (5) pet feeding; (6) those without discomfort or symptoms on the day of sampling; (7) females who were not in the physiological period. All Subjects understood the nature of the experiment and provided informed consent before participating in the study. This study was approved by the ethical review board of the Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College (approval no. 2021 − 199) on Month 12, 2021. All methods were performed in accordance with the relevant guidelines and regulations. Sample Collection Non-stimulated saliva samples were collected from CFM patients and healthy controls. All participants were instructed not to brush their teeth for 24 hours and eat or drink for 1 hour before sampling. After rinsing their mouths with 20 ml of physiological saline for 1 minute, eight sterile cotton swabs were put into the participant’s mouth for 2 minutes to absorb saliva and then into the 5 ml sterilized Cryogenic Storage Tube. The tubes were frozen with liquid nitrogen and stored in the refrigerator at -80℃. The demographic data of each participant were recorded, including age, gender, and body mass index (BMI). All patients underwent sleep monitoring with respiratory polysomnography (RP), and the obstructive apnea-hypopnea index (OAHI) and blood oxygen saturation (SpO 2 ) levels were recorded. 16S rRNA Diversity Sequencing DNA extraction and amplification Genomic DNA was extracted from saliva samples using the MagPure Soil DNA KF Kit and DNA concentrations and integrity were measured using the NanoDrop 2000 (Thermo Fisher Scientific, USA). Polymerase chain reaction (PCR) amplification of bacterial 16S rRNA genes was performed using barcoded primers and Takara Ex Taq (Takara) using extracted DNA stored in a -20°C refrigerator. V3-V4 regions of 16S rRNA genes were amplified using primers 343F (5’-TACGGRAGGCAGCAG-3’) and 798R (5’-AGGGTATCTAATCCT-3’) 14 . Library Construction and Sequencing PCR products were purified with AMPure XP beads (Agencourt) and re-amplified for quality assessment using agarose gel electrophoresis. AMPure XP beads were used to purify the final amplicon, and the Qubit dsDNA Assay Kit (Thermo Fisher Scientific, USA) was used to measure the DNA concentration of samples for sequencing using an Illumina NovaSeq 6000 platform with 250 base pairs (bp) paired-end reads (Illumina Inc.; OE Biotech Company, Shanghai, China). Bioinformatic Analysis Sequencing and data processing were performed by OE Biotech Co., Ltd. (Shanghai, China). Raw sequencing data were in the FASTQ format. Preprocessing was then carried out using Cutadapt software to detect and remove adapters from the paired-end reads. DADA2 3 with QIIME2 4 (2020.11) default parameters were used to filter low-quality reads, denoise, merge, detect, and cut off the chimera reads after trimming paired-end reads. The QIIME2 package was used to select the representative read of each amplicon sequence variant and output the abundance table. With default parameters, a q2-feature classifier was used to classify all representative reads against the Silva database (Version 138). A MagPure Soil DNA KF Kit was used to isolate total DNA from the sample. An agarose gel electrophoresis and NanoDrop2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) were used to measure DNA concentration and integrity. DNA was fragmented using an S220 Focused-ultrasonicator (Covaris, USA) and cleansed using Agencourt AMPure XP beads (Beckman Coulter Co., USA). Subsequently, libraries were constructed using the TruSeq Nano DNA LT Sample Preparation Kit (Illumina, San Diego, CA, USA) following the manufacturer’s instructions. The Metagenome was sequenced and analyzed by OE Biotech Co., Ltd. (Shanghai, China). Meanwhile,150 bp paired-end reads were generated from the libraries on an Illumina Novaseq 6000 platform. Sequences in the FastQ file were trimmed and filtered using Fastp (v 0.20.1) 15 , low-quality primary groups were filtered out, and reads containing N bases were removed. The host pollution was controlled by aligning the post-filtered pair-end reads against the human genome using bowtie2 (v 2.2.9) and discarding the aligned reads. MEGAHIT (v 1.1.2) was used for genome assembly after obtaining valid reads 16,17 . Gaps inside the scaffold were used to break the scaffold into new contigs (Scaftigs), and new Scaftigs with a length > 500 bp were retained. Using Prodigal (v 2.6.3), open reading frames (ORFs) were predicted on assembled scaffolds and translated into amino acid sequences 18 . CDHIT (v 4.5.7) was used to construct non-redundant gene sets from all predicted genes. The clustering parameters had a 95% identity and 90% coverage. The longest gene represented each gene set. Then, clean reads of each sample were aligned against the non-redundant gene set (95% identity) using bowtie2 (v 2.2.9), and the abundant information of the gene in the corresponding gene set was analyzed. The species’ taxonomy was determined using the Non Redundant Protein (NR) database, and gene abundance was used to calculate the abundance of the species. Abundance statistics were performed at Domain, Kingdom, Phylum, Class, Order, Family, Genus, and Species levels to construct abundance profiles on the corresponding taxonomy level. The amino acid sequence representing the gene set was compared and annotated using DIAMOND (v 0.9.7) with NR, Kyoto Encyclopaedia of Genes and Genomes (KEGG), eggNOG, SWISS-PROT, and GO databases at an e-value of 1e-5 19,20,21 . Gene sets were compared with the CAZy database using hmmscan (v 3.1) to obtain the carbohydrate-active enzyme corresponding to the gene. The carbohydrate activity was calculated by summing the gene abundances corresponding to the carbohydrate-active enzyme abundance 22 . Statistical Analysis Normally distributed data were compared using the independent samples t-test; otherwise, the Wilcoxon rank-sum test was adopted. In 16S rRNA sequencing, QIIME2 software was used to analyze alpha and beta diversity. The Shannon index was used to estimate microbial diversity in samples 23, 24 . Principal coordinate analysis (PCoA) was performed to estimate beta diversity using an unweighted Unifrac distance matrix. A T-test was used to analyze the differences in diversity and taxonomic composition between the two groups. Spearman correlation analysis was applied to measure the correlation between the clinical characteristics of patients and microbial structure. In metagenome sequencing, the taxonomic or functional abundance spectrum was analyzed using R software (version 3.2.0), and an equidistant matrix of PCoA was calculated and analyzed. The Student’s t-test was used to analyze significant differences between groups. Taxonomic and functional abundance spectra were compared using linear discriminant analysis effect size (LEfSe). All data were analyzed using R software. P < 0.05 was considered statistically significant. Results Baseline Demographic and Clinical Characteristics Forty-four participants were recruited, of whom 20 cases belonged to the CFM group (CFM) and 24 to the healthy control group (Ctrl). The baseline demographic and clinical characteristics of different groups are shown in Table 1 . No significant difference was found between CFM and Ctrl groups in terms of age, gender, and BMI (P = 0.446, 0.876, and 0.229, respectively). According to the Pruzansky-Kaban classification, 1, 6, 9, and 4 CFM patients were classified as Type I, Type IIa, Type IIb, and Type III, respectively. Sixteen patients were diagnosed with OSAS, accounting for 80% of all patients. The average OAHI was 2.8 and the average SpO2 was 74.2% (65.4–83.0%). 16S rRNA gene sequencing of 44 samples yielded 3,518,300 raw reads. The average number of sequences per sample was 79,961. After preprocessing the sequencing data, 2,969,017 high-quality sequences were obtained, averaging 67,477 sequences per sample. Among the 44 samples, 2,789 amplicon sequence variants were detected. The sequences were categorized based on their taxonomic group using the Human Oral Microbiome Database (HOMD). There were 15 Phyla, 26 classes, 73 orders, 126 families, 247 genera, and 479 species in the saliva sample of 44 participants. Meanwhile, metagenomics sequencing was further performed on samples from 6 patients and 6 healthy controls. The effective data size distribution of each sample was between 11.96 and 15.93 G, and the N50 statistical distribution of Contigs was between 454 and 938 bp. After removing redundancy, 1,499,952 ORFs were identified in the gene catalog (non-redundant gene set). Compared with KEGG, NR, and CAZy databases, the annotation rates of non-redundant genes were 94.15, 51.21, and 1.69%, respectively. Table 1 Baseline demographic and clinical characteristics of two groups. Characteristic Patients Controls P-value No. of Patients 20 24 Gender, male, n% 12 (60%) 15 (62.5%) 0.876 Age 8.1 (7.1–9.1) 7.7 (6.8–8.7) 0.446 BMI (kg/m 2 ) 16.4 ± 2.2 15.9 ± 1.3 0.299 Pruzansky-Kaban I 1 IIa 6 IIb 9 III 4 OAHI 2.8 ± 2.3 SpO 2 (%) 74.2 (65.4–83.0) Normally distributed data were expressed as mean ± SD (standard deviations) and non-normally distributed data were expressed as median interquartile range. P<0.05 was considered statistically significant. BMI: Body Mass Index; OHAI: obstructive apnea/hypopnea index; SpO 2 : oxygen saturation Diversity, Composition, and Comparison of the Salivary Microbiome According to the rarefaction curve, the plateauing stage had been reached (Supplementary Fig. 1), indicating that all samples were sequenced to a reasonable depth and the results reflected microbial information of saliva samples. The Shannon index differed significantly between the CFM group and the Ctrl group (P = 0.024) (Fig. 1 A). PCoA was performed to assess the variation of salivary microbial community structure using the unweighted UniFrac distance, with axis 1 (PC1) explaining 9.56% of the variability and axis 2 (PC2) explaining 9.23%. Salivary microbial communities differed significantly between the CFM group and the Ctrl group (P = 0.001), indicating significant differences in the phylogenetic structure (Fig. 1 B). The relative abundance of the top 10 phyla is summarized in Fig. 1 C. Proteobacteria (36.46%), Firmicutes (31.34%), and Bacteroidota (20.07%) were the three most abundant phyla in the Ctrl group. Proteobacteria (31.82%), Bacteroidota (23.34%), Firmicutes (20.82%), Actinobacteriota (11.35%), and Fusobacteriota (10.34%) were the five most abundant phyla in the CFM group. Detailed statistics are presented in Supplementary Table 1. Actinobacteriota (Ctrl = 0.04, CFM = 0.11, P < 0.001), Campilobacterota (Ctrl = 0.006, CFM = 0.02, P = 0.013); Firmicutes (Ctrl = 0.31, CFM = 0.21, P = 0.012), and Desulfobacterota (Ctrl = 0.0007, CFM = 0.0002, P = 0.002) differed significantly between the two groups (Fig. 2 A). The top 15 most abundant taxa are shown in Fig. 1 D. Streptococcus (24.20%), Haemophilus (18.23%), and Neisseria (11.63%) were significantly enriched in the Ctrl group. Neisseria (18.07%) and Streptococcus (14.34%) were highly abundant in the CFM group. Detailed statistics are shown in Supplementary Table 2. The top 10 most abundant genera are shown in Fig. 2 B. Corynebacterium (Ctrl = 0.01, CFM = 0.05, P < 0.001), Capnocytophaga (Ctrl = 0.03, CFM = 0.07, P = 0.002), Rothia (Ctrl = 0.01, CFM = 0.03, P = 0.021), Campylobacter (Ctrl = 0.01, CFM = 0.02, P = 0.013), Actinomyces (Ctrl = 0.02, CFM = 0.04, P = 0.022), and Prevotella (Ctrl = 0.05, CFM = 0.09, P = 0.048) were the most predominant genera in the CFM group. Haemophilus (Ctrl = 0.18, CFM = 0.07, P < 0.001), Gemella (Ctrl = 0.03, CFM = 0.01, P < 0.001), Streptococcus (Ctrl = 0.24, CFM = 0.14, P = 0.008), and Porphyromonas (Ctrl = 0.06, CFM = 0.03, P = 0.04) were the most abundant genera in the Ctrl group. Based on the relative abundance of community structure, the correlations between patient clinical phenotype and microbial community structure were determined using Spearman analysis. Neisseria and Porphyromonas were positively correlated with the Pruzansky-Kaban classification, with a Spearman’s rank correlation coefficient (rs) of 0.66 (P = 0.0016) and 0.52 (P = 0.019), respectively. Prevotella and Kingella were negatively correlated with the Pruzansky-Kaban classification, with an rs of -0.57 (P = 0.009) and − 0.45 (P = 0.046), respectively. Campylobacter , Leptotrichia , and Kingella were positively correlated with SpO2, with an rs of 0.54 (P = 0.014), 0.53 (P = 0.03), and 0.48 (P = 0.016), respectively. Staphylococcus significantly negatively correlated with SpO2, with an rs of 0.46 (P = 0.04). Meanwhile, no correlation was found between microbial community structure and BMI and OAHI (Fig. 2 C). To identify potential biomarkers, the LEfSe method was used to analyze differences in the composition of the microbial communities between the two groups. The cladogram of salivary microbial structure and dominant bacteria was generated based on a linear discriminant analysis (LDA) threshold of 3, which indicated the most significant differences between CFM and Ctrl groups. Neisseriaceae was the most predominant at the family level and Prevotella , Capnocytophaga , Corynebacterium , Leptotrichia , Actinomyces , Fusobacterium , Campylobacter , Rothia , and Kingella were the most predominant at the genus level in the CFM group. Gemellaceae was the most predominant at the family level and Pelomonas , Gemella , Porphyromonas , and Streptococcus were dominant at the genus level in the Ctrl group (Fig. 2 D-E). According to the Pruzansky-Kaban classification, CFM patients were divided into Type I-IIA and Type IIB-III groups, patients with or without temporomandibular joint (TMJ) dysfunction. The difference in the salivary microbiome of both groups was compared to explore the relationship between the disease severity and microbial community structure. The top three genera with the highest average abundance were Prevotella (0.16), Neisseria (0.09), and Leptotrichia (0.07) in Type I-IIA and Neisseria (0.23), Haemophilus (0.09), and Prevotella (0.06) in Type IIB-III. The top 3 statistically significantly differential genera between the two groups included Faecalibacterium (0.0001, 0.0006, P = 0.001), Neisseria (0.09, 0.23, P = 0.004), and Porphyromonas (0.01, 0.05, P = 0.009) (Fig. 2 F-G). Functional Comparison of the Salivary Microbiome Between CFM and Ctrl Groups The distribution of gene numbers between the two groups is displayed in Fig. S2-A, which revealed a significant difference between CFM and Ctrl (P = 0.016). Hierarchical clustering analysis was performed to evaluate the similarities and differences in gene abundances of all samples and the results showed that CFM and Ctrl groups had a high intra-group similarity (Fig. S2-B). KEGG annotations of amino acid sequences obtained from the two groups are shown in Fig S2-C, with metabolism-associated genes accounting for the most significant proportion. Carbohydrate metabolism was annotated to 77,286 genes, making it the most functionally rich category, followed by amino acid metabolism, with 63,843 annotated genes, and Metabolism of cofactors and vitamins, Energy metabolism, Nucleotide metabolism, and Glycan biosynthesis and metabolism, with relatively abundant genes. Other metabolic pathways with relatively abundant genes included Genetic Information Processing, Environmental Information Processing, and Cellular Processes. Based on the annotation of differentially-expressed KEGG ORTHOLOGY (KO) between CFM and Ctrl groups at level 3, the top 30 KO relative abundances were selected for clustering information based on the P-value to draw their functional heatmaps (Fig. 3 A), revealing significant differences in functional abundance between the two groups. Thirty-four functional pathways differed significantly between the two groups, and the top 10 functional pathways with the highest abundance were selected to generate the boxplots (Fig. 3 B). Functional pathways with significant differences in the CFM group were Porphyrin and chlorophyll metabolism (0.013), Sulfur metabolism (0.003), Biotin metabolism (0.042), Histidine metabolism (0.040), Plant-pathogen interaction (0.019), Lysine degradation (0.005), Tryptophan metabolism (0.031), Salmonella infection (0.015), and Fluid shear stress and atherosclerosis (0.034). Biofilm formation-Escherichia coli (0.003) had a higher functional abundance and statistical significance in the Ctrl group. Functional biomarkers with significant differences between groups based on an LDA score of 2 are shown in Fig. 3 C. A correlation analysis was conducted to determine the relationship between high abundance bacteria and functions (Fig. 3 D). Leptotrichia was significantly negatively correlated with Histidine metabolism (rs = -0.94, P = 0.017) and Tryptophan metabolism (rs = -0.94, P = 0.017). Neisseria was positively correlated with Tryptophan metabolism (rs = 0.71, P = 0.136), Lysine degradation (rs = 0.77, P = 0.103), and Histidine metabolism (rs = 0.49, P = 0.356) and negatively correlated with Sulfur metabolism (rs = -0.66, P = 0.175). Discussion CFM is the second most common craniofacial malformation after cleft lip and palate, with an incidence rate ranging from 1 in 3,500 to 1 in 5,600 live births 25, 26 . Based on CFM characteristics, including abnormal oral anatomical structure, underdeveloped mandible, oblique occlusal plane, and frequent co-occurrence with OSAS 27, 28 , we hypothesized that these patients are at a higher risk of oral microbial dysbiosis (OMD). According to previous literature, OMD is associated with alveolar bone resorption, tooth loosening 29,30 , chewing dysfunction, and aggravating occlusal plane tilt and can affect long-term orthodontic or orthognathic treatment, all of which may affect the treatment and improvement of CFM patients 31,32 . However, there are no reports on the distribution characteristics of the oral microbiota in CFM patients. Therefore, the present study employed 16S rRNA sequencing to compare and investigate the structural features of the oral microbiota in CFM patients and healthy controls and identified numerous bacterial taxa with statistical differences. Furthermore, metagenomic sequencing identified functional abundance and differences in the oral microbiome in CFM samples. These data allowed a comprehensive analysis of bacterial diversity in CFM samples. The standard oral microbiota protects against potential pathogens by occupying distinct ecological niches without causing harm 33 . A disruption in microbial homeostasis leads to the transformation of the original microbial community structure into a dysbiotic pathogenic state, decreasing pH in the oral cavity. Consequently, the acidic environment exacerbates the proliferation of pathogenic bacteria, leading to inflammation and tissue damage 34 . The observed pathogenicity is not only caused by individual bacterial species but also by alterations in community structure that are closely linked to various systemic and oral diseases. Some systemic diseases related to microbiota dysbiosis include osteoporosis, cancer, cardiovascular diseases, gastrointestinal diseases, and diabetes 35,36,37, 38 . For oral diseases, an alteration in microbial composition results in elevated levels of pathogenic bacteria, thereby worsening immune-mediated inflammatory responses. Moreover, this leads to elevated levels of specific cytokines and inflammatory mediators, which contribute to the degradation of alveolar bone and periodontal tissues, resulting in alveolar bone resorption, ultimately impacting masticatory function and aesthetic appearance. Microbiota dysbiosis in the oral cavity can result in dental caries, pulpitis, periodontitis, and head and neck tumors 39, 40,41, 42, 43,38 . Individuals with craniofacial disorders at birth, which impact the growth and function of teeth and jaws, are frequently at a heightened risk of experiencing poor oral health conditions 44 . This heightened risk can be attributed to challenges in effectively cleaning structurally abnormal oral cavities and the continuous exposure of dental enamel and gum tissue to the oral environment due to deformities. Consequently, these factors may facilitate the formation and accumulation of plaque, ultimately increasing the vulnerability to oral diseases. The clinical manifestations and treatment methods of CFM may have a potential mutual influence on OMD. The clinical manifestations include an underdeveloped mandible and an inclined occlusal plane. Additionally, patients with CFM exhibit a higher incidence of poorly developed teeth (ranging from 6.7–33.3%) and delayed tooth eruption (ranging from 20.5–54.3%) compared with normal individuals, whose respective incidence rates are 4.5–13.3% and 3.4–4.3%. Variations in tooth morphology and increased interdental spacing are frequently in CFM 45,46,28 . The above-mentioned anatomical abnormalities have been recognized as potential factors contributing to OMD and demonstrate interconnected relationships 47 . Furthermore, a previous study found that the prevalence of OSAS among patients with CFM ranged from 7–67% 48 . Other studies reported notable alterations in the composition and metabolomic features of the oral microbiota in pediatric patients with OSAS 49,50,51 . This phenomenon was attributed to recurrent episodes of upper airway collapse, reduced nasal airflow, snoring, and mouth breathing during sleep 52 , which resulted in compromised oral self-cleaning capabilities, salivary gland dysfunction 53, 54,55,56 , reduced blood oxygen content, and alterations in airway humidity, temperature, and pH due to diminished nasal airflow 57 . Additionally, the oral cavity of patients with OSAS was directly exposed to dust, particles, and various airborne microorganisms, ultimately disrupting the microbial balance, leading to increased secretion of pro-inflammatory cytokines, mediating respiratory inflammation and edema, and inducing or exacerbating the occurrence of OSAS 58 . In addition to clinical manifestations, various factors during the treatment process of CFM may interact with OMD. Surgery is the most widely accepted treatment for characteristic deformity in CFM to enhance both aesthetic and functional outcomes, mainly through mandibular elongation and dental functional improvement 59 . The most significant surgeries include mandibular distraction osteogenesis (MDO) and orthodontics or orthognathic surgery. MDO is usually performed during the mixed dentition period, during which children have more significant potential for skeletal growth. MDO helps lengthen the affected mandible, create the space of an open bite, induce the descent of the maxillary occlusal plane, and improve the occlusal plane and facial symmetry of the patient 60, 61 . During the MDO process, the active growth of the alveolar bone on the affected side is a significant determinant in the downward movement of the maxillary occlusal plane, thereby significantly influencing the maintenance of occlusal plane stability 62, 63, 64, 65, 66 . Orthodontics or orthognathic surgery is usually performed as a supplementary treatment for patients with poor occlusion and appearance in the permanent dentition stage 67 . At this stage of treatment, oral anatomical factors, particularly the alveolar bone, are critical in dental implantation, orthodontic procedures, periodontal therapy, and oral functional restoration 68, 69, 70,71, 72,73 . In summary, many factors may interact with OMD in patients with CFM. However, whether CFM is associated with OMD remains elusive, An association between the two is necessary to optimize the current treatment sequence. The current study compared the oral microbiota structure and function between CFM patients and normal individuals and confirmed the existence of OMD in patients with CFM. Regarding the selection of samples and sampling time points, previous studies have shown that saliva is the most suitable sample for analyzing the composition of oral biofilm microbiota, with minimal harm to the host 74,74,75 . The oral microbiota in young children exhibits notable alterations in composition and diversity, ultimately stabilizing around the age of 2 76 . Therefore, children in the mixed dentition period were selected as the study subjects, and saliva was used as the study sample. The Shannon dilution curve demonstrated the rationality of the amount of sequenced data, excellent sequencing quality, and reliable research results. The CFM group exhibited more extraordinary species richness and evenness than the Ctrl group. Beta diversity analysis indicated significant differences in microbial community structure between the two groups; between-group differences were more significant than within-group differences. The phyla with statistical differences and high relative abundance were Actinobacteriota and Firmicutes in the CFM and Ctrl groups, respectively. These are resident bacteria in the oral cavity, with some genera classified as opportunistic pathogenic bacteria 77,78 . The dominant differential species in the CFM group included Corynebacterium , Capnocytophaga , Rothia , Actinomyces , Prevotella , Campylobacter , Leptotrichia , and Fusobacterium , which are resident microbial communities in the oral cavity and play crucial roles in maintaining microecological balance. Certain species may exhibit pathogenicity when their abundance increase or the host’s immune system is compromised. Capnocytophaga , a genus of facultative anaerobic bacteria, includes certain species identified as opportunistic pathogens in the human subgingival sulcus and dental plaque 79,80 . Previous studies reported a correlation between the increased abundance of Capnocytophaga and prepubertal periodontitis 81,82 , gingivitis 83 , and oral cancer 84, 85 . Corynebacterium is primarily aerobic and typically non-pathogenic but sometimes opportunistically invades tissues (through wounds) or leads to infections such as granulomatous lymphadenitis, pneumonia, pharyngitis, skin infections, and endocarditis in immunocompromised hosts 86, 87, 88 . An increased abundance of Corynebacterium is also linked to a reduced likelihood of developing head and neck squamous cell carcinoma, suggesting potential implications for cancer prevention strategies 89 . Actinomyces are facultative anaerobes that exhibit optimal growth in anaerobic environments, serve as opportunistic pathogens in the oral cavity, and are particularly prevalent in the gingiva. The metabolic activities of Actinomyces , contributing significantly to acid-base equilibrium, include metabolizing sugar into acid and amino acids into acid and ammonia. Additionally, Actinomyces are implicated in the generation of hydrogen sulfide and methyl mercaptan, which have been linked to oral malodor, dental caries, and periodontal disease 90, 91 . Besides, excessive abundance of Actinomyces can lead to various complications, such as dental surgery infection, oral abscess 92 , and oral tumors 93 . Fusobacterium , a genus of obligate anaerobic bacteria, has been associated with various human diseases, including periodontal disease, oral, head, and neck infections, colorectal cancer, and localized skin ulcers 94, 95, 96, 97 . Identical to Prevotella and Porphyromonas , Fusobacterium can degrade nitrogenous compounds into short-chain fatty acids, sulfide compounds, and ammonia, which are cytotoxic and can induce tissue inflammation by modulating immune responses 98 and even promote cell apoptosis 99 . These processes all contribute to the initiation and progression of periodontal diseases. Prevotella can grow under anaerobic conditions and cause acidification. An increased abundance of Prevotella is related to the development of periodontal disease, abscesses, and oral tumors 100, 101,102 . Our data showed that Porphyromonas was highly abundant in the Ctrl group and Type IIB-III patients. Leptotrichia is an anaerobic Gram-negative bacteria that forms part of the bacterial biofilm of the oral cavity. Its increased abundance has been reported to be associated with inflammatory bowel disease, cancer, and adenomatous polyps 103,104 . Campylobacter grows best in microaerobic environments and can cause gastrointestinal infections 105 . Certain species of Rothia , a Gram-positive bacterium, are opportunistic pathogens in the oral cavity and pharynx that sometimes cause septicemia, endocarditis, and other severe infections 106, 107, 108 . Prior research has demonstrated that elevated abundance of Streptococcus mutans and Porphyromonas gingivalis is implicated in periodontal disease, dental caries, and certain systemic illnesses. S . mutans is a Gram-positive and anaerobic acid-producing microorganism that can synthesize extracellular polymers of glucan. It also produces acid and thrives in acidic environments, ultimately causing tooth decay and the dissolution of hydroxyapatite in the enamel and dentin. P . gingivalis can ferment sugar and produce acid, which facilitates microbial adhesion to tooth surfaces and enamel demineralization 109,110,111,112,113 . Furthermore, P . gingivalis and S . mutans have been sporadically detected in the saliva of individuals with good oral health, suggesting that they may also form part of the resident oral flora. The present study found that the average abundance of S . mutans in CFM and Ctrl groups was 0.002 and 0.0002, respectively, with no statistical significance. The average abundance of P . gingivalis was higher in the Ctrl group than in the CFM group, with no statistical significance. Alterations in in oral bacterial composition have been demonstrated in patients with OSAS and obesity 114, 115 . To determine whether OBD in CFM patients is mainly affected by OSAS, we performed a Spearman correlation analysis to ensure the relationship between CFM Pruzansky-Kaban type, OAHI, SpO2, BMI, and oral microbial structure 116 . The results showed that the relative abundance of Neisseria and Porphyromonas increased with the severity of CFM deformity. Excessively high levels of Neisseria may lead to abnormal activation of the immune system causing cellular inflammation; the inflammatory state of the oral cavity further promotes the colonization of Neisseria 117,118 . Porphyromonas is a strictly anaerobic Gram-negative rod bacteria that has been shown to be a cause of periodontitis and pulpitis. In this study, the abundance of Staphylococcus increased with the decrease of SpO2, suggesting that it is a facultative anaerobic organism. Partial species such as S. aureus and S. epidermidis are opportunistic pathogens resident in the oral cavity and known to cause oral mucositis and gingivitis. In addition, there was no relevance between OAHI, BMI, and bacteria structure. Collectively, our correlation analysis results and those of previous studies suggest a decrease in the diversity of the oral microbiota in individuals with moderate to severe OSAS 119 . In contrast, our study found a significant increase in the richness and evenness of the oral microbiota in patients with CFM, suggesting a potential link between oral microbiome diversity and CFM. The relationship between CFM severity and specific genera and corresponding species needs to be further studied. There were on significant differences between the CFM and Ctrl groups in Cellular Processes, Environmental Information Processing, Genetic Information Processing, Human Diseases, Metabolism, and Organismal Systems. At level 3, pathway activity of Porphyrin and chlorophyll metabolism, Sulfur metabolism, Biotin metabolism, Histidine metabolism, Plant − pathogen interaction, Lysine degradation, Tryptophan metabolism, Salmonella infection, Fluid shear stress, and atherosclerosis was significantly increased in the CFM group than in the Ctrl group. Tryptophan, an essential amino acid absorbed through the intestinal epithelium, is utilized for protein synthesis, and approximately 10–20% of it is further metabolized by bacteria 120, 121, 122 . The metabolism of free tryptophan in the oral cavity involves three pathways: (1) Indole pathway: This pathway involves the direct conversion of tryptophan into indole and its derivatives by periodontal plaque microorganisms, including Fusobacterium, Prevotella , and Porphyromonas . These metabolites form part of the developmental mechanisms of periodontitis and halitosis 123 . (2) 5-Hydroxytryptamine (5-HT) pathway: Tryptophan is converted into 5-hydroxytryptophan (5-HTP) via the catalysis of tryptophan hydroxylase (TPH), and then metabolized to generate 5-hydroxytryptamine (5-HT) 124 . 5-HT is a key neurotransmitter involved in regulating central nervous system functions. Moreover, 5-HT interacts with receptors on various immune cells, such as T cells, macrophages, and dendritic cells, triggering inflammatory and immune regulatory responses 125,126 . (3) Kynurenine metabolic pathway: More than 95% of free tryptophan is metabolized via this pathway. This pathway is driven by indoleamine 2,3-dioxygenase 1 (IDO) and tryptophan 2,3-dioxygenase (TDO), and leads to the production of kynurenine (Kyn) and the associated downstream products such as quinolinic acid, niacin, nicotinamide adenine dinucleotide, and kynurenic acid 127 . IDO, a key rate-limiting enzyme involved in this pathway, contributes to the formation of inflammation and immunosuppression. The activation of IDO can enhance the establishment of an immunosuppressive microenvironment, thereby inhibiting the progression of the anti-tumor immune response. IDO expression is significantly elevated in melanoma, colon cancer, and lung cancer tissues, and this high expression is inversely related to tumor prognosis 128, 129,130 . Furthermore, several tryptophan metabolites may also modulate diverse biological processes 131 . In the study by Balci et al. (2021), we discovered that patients with stage III grade B periodontitis have elevated levels of tryptophan in their saliva compared to healthy controls. Moreover, the level of tryptophan can be used for probing bleeding and serve as a plaque index 132 . Furthermore, 5-HT, another metabolite of tryptophan, and its precursor 5-HTP, regulate bone metabolism 133,134 . Evidence from animal studies have demonstrated that 5-HTP can promote osteoclastogenesis and aggravate alveolar bone resorption 135 . Sulfur metabolism has been implicated in the regulation of energy metabolism in humans. Sulfur, one of the most prevalent bio-elements, is involved in diverse processes including cell signaling, free radical detoxification, enhancement of structural support, and energy production 136, 137, 138, 139, 140 . The organic and inorganic sulfur levels in the body are primarily influenced by the consumption of amino acids such as methionine, B-complex vitamins, and trace elements 141,142 . Sulfur-metabolizing bacteria have been shown to modulate sulfur metabolism. Representative ones include Streptococcus, Prevotella , and Fusobacterium 143,144,145,146,147,148,149 . Hydrogen sulfide (H 2 S), sulfite, thiosulfate, and sulfate are the main sulfur metabolism products. As an essential product, physiological levels of H 2 S induce anti-inflammatory effects, inhibit invasive pathogens, and help alleviate tissue damage 150,151,152,153,154 . In contrast, excessively high concentrations of H 2 S cause toxicity in animals are, mainly in the cardiovascular system, the central nervous system, and the energy metabolism process. Specifically, in the energy metabolism process, H 2 S inhibits cytochrome c oxidase (COX) activity within the mitochondrial electron transport chain (ETC) 155 . This triggers DNA damage, disrupts the intestinal mucus bilayer, promotes inflammation, and contributes to colorectal cancer 156 . Biotin, also known as vitamin B7, vitamin H, or coenzyme R, plays a crucial role in metabolism by acting as a cofactor for various enzymes. The levels of biotin are influenced bydietary intake and bacterial activity. It has been suggested that deficiencies in the bacterial production of biotin affected the microbial community dynamics, host metabolic processes, and inflammatory responses 157, 158,159 . Most Bacteroidetes and Proteobacteria phyla organisms are responsible for biotin biosynthesis 160,161 . This essential micronutrient, biotin, serves as a cofactor for a range of enzymes, including biotin-dependent carboxylases, decarboxylases, and transcarboxylases 162 . For instance, it participates in various metabolic processes, including fatty acid synthesis, amino acid metabolism, and gluconeogenesis, by forming covalent bonds with lysine residues 163, 164 . Biotin exerts anti-inflammatory effects by inhibiting NF-κB activation, and its deficiency can lead to inflammation by stimulating the secretion of pro-inflammatory cytokines 165, 166 . In the human digestive tract, histidine (His), an essential amino acid, plays a vital role for various gut bacteria. These bacteria break down histidine and use it as a nutrient source. This breakdown process produces several byproducts, including histamine, uric acid, glutamate, and imidazole propionate (IMP) 167,168 . Previous research has demonstrated that His and its metabolites exert diverse physiological effects on the human body. Increased levels of His have been associated with the inhibition of inflammation and oxidative stress. Overexpression of His decreases taste and olfactory sensitivity, ellicits symptoms such as headaches, weakness, drowsiness, nausea, and cognitive impairment 169 . Moreover, His and His-containing dipeptides (HIS-cd) were linked to the occurrence of inflammatory bowel diseases and ocular disorders 170,171, 172, 173 . Histamine, a significant immune modulator, affects the hypersensitivity reactions and chronic inflammatory processes 174,175 , as well as intestinal diseases, anxiety, and immune responses induced by dysbiosis of the gut microbiota 176,177 . Research in animals suggests that glutamate might help heal damage in the intestinal barrier by regulating the release of corticotropin-releasing factor (CRF) 178 . Excessive IMP damages the gut barrier and alters the levels of inflammatory cytokines 179,180 , disrupts insulin signaling via the mammalian target of rapamycin complex 1 (mTORC1) 168 . Lysine is an essential amino acid which is degradated via two distinct pathways. The primary pathway involves the formation of saccharopine via ε-deamination within liver mitochondria, leading to the formation of acetyl-CoA 181, 182 . Another pathway entails α-deamination or transamination to produce pipecolic acid (PA). Fusobacterium nucleatum , which is increased in CFM, has been demonstrated to ferment lysine 183 . Intestinal bacteria normally produce very low amounts of precursor molecules for protein-bound uremic toxins (PBUTs) like indole, para-cresol, and phenol. On the other hand, lysine acts as a diuretic, helping to flush out toxins from the body. Therefore, the marked elevation in lysine degradation hinders the effective removal of toxins 184, 185 . In this research, the saliva microbiome of patients with CFM was compared with that from controls by 16S rRNA and metagenomics sequencing. The results revealed significant differences in the diversity, composition, and functional profiles of oral microbial communities between CFM patients and controls in the mixed dentition stage. The increased abundance of bacterial genera in CFM patients primarily consists of opportunistic pathogens in the oral cavity. Previous research has linked the abnormal growth of these bacteria to various oral diseases, including halitosis, dental caries, periodontitis, pulpitis, oral infections, periodontal abscesses, and oral tumors. Furthermore, specific genera have been linked to occurrence of systemic diseases, including gastrointestinal infections, gastrointestinal tumors, pneumonia, pharyngitis, skin infections, sepsis, and endocarditis. Notably, Neisseria and Porphyromonas , were positively correlated with the severity of CFM, could stimulate cellular inflammation especially when their abundance was high, ultimately enhancing the development of oral inflammation. Pathogenic bacteria such as Prevotella and S. mutans were enriched in the CFM group. In contrast, P. gingivalis , a pathogenic bacteria, displayed higher abundance in the Ctrl. group, probably due to failure to exclude individuals with oral diseases in the Ctrl group. Several functional pathways were upregulated in patients with CFM compared to controls, particularly those related to the metabolism of amino acids and biotin. Notably, tryptophan metabolism, which significantly affects oral health, was also upregulated in the CFM group. Furthermore, pathways such as sulfur metabolism, biotin metabolism, and histidine metabolism were upregulated, which may increase the risk of various diseases. This study has some limitations that should be discussed. The enrolled sample size was small primarily due to the rarity of CFM in craniofacial disease, with an incidence rate ranging from 1 in 3,500 to 1 in 5,600. In addition, variables such as dietary habits and geographical location were unaccounted for due to the small sample size, potentially limiting the generalizability of the study findings to other regions or ethnic groups. Moreover, since the 16S rRNA sequencing used in this study accurately detects bacteria at the genus level, species-level oral bacteria were not further discussed. Subsequent research should investigate the potential effects and mechanisms of the identified microbial biomarkers and to develop appropriate treatment strategies. Future investigations should also incorporate intervention strategies or explore metabolites to improve the efficacy. Conclusion CFMs significantly impact facial structure and function. Due to the complexity of these conditions, patients with CFM benefit most from a multidisciplinary treatment approach. This comprehensive care, involving a team of specialists, aims to restore both facial appearance and function. By analyzing the clinical manifestations and treatment strategies that may be related to OMD in CFM, we found that several genera were significantly increased, including Corynebacterium, Capnocytophaga, Rothia, Actinomyces, Prevotella, Campylobacter, Leptotrichia , and Fusobacterium in CFM patients. Neisseria and Porphyromona were positively correlated with the severity of CFM, whereas pathways that were upregulated predominantly included Tryptophan metabolism, Sulfur metabolism, Biotin metabolism, Histidine metabolism, and Lysine degradation. Nesseria promotes Tryptophan metabolism and Lysine degradation, while Leptotrichia decreases Histidine metabolism and Tryptophan metabolism. This study identified the key bacterial genera and functional changes associated with CFM. Furthermore, researchers should address the dysbiosis of oral microbiota in CFM patients to mitigate the persistence of pathogenic bacteria and their impact on oral health and long-term treatment outcomes. Declarations Acknowledgments The authors thank the patients diagnosed with CFM and control group volunteers who participated in our study. They also thank Ouyi Biotechnology Company Limited for its technical services and valuable suggestions for bioinformatics analysis. Ethics approval and consent to participate This study was approved by the ethical review board of the Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College (approval no. 2021-199) on Month 12, 2021. All participants voluntarily consented to participate in the study, providing informed consent. Their decision did not impact the treatment protocol. Competing interests The authors declare no competing interest. Raw data: The datasets supporting the conclusions of this article are available in the Bioproject database repository. [unique persistent identifier and hyperlink to datasets of macrogenomic sequencing in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1118211 ]. [unique persistent identifier and hyperlink to datasets of 16s rRNA sequencing in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1118189 ]. References Elsten EECM, Caron CJJM, Dunaway DJ, Padwa BL, Forrest C, Koudstaal MJ. Dental anomalies in craniofacial microsomia: A systematic review. Orthod Craniofacial Res . 2020;23(1):16-26. doi:10.1111/ocr.12351 Maruko E, Hayes C, Evans CA, Padwa B, Mulliken JB. Hypodontia in hemifacial microsomia. Cleft Palate Craniofac J . 2001;38(1):15-19. Ongkosuwito EM, De Gijt P, Wattel E, Carels CEL, Kuijpers-Jagtman AM. Dental Development in Hemifacial Microsomia. J Dent Res . 2010;89(12):1368-1372. doi:10.1177/0022034510378425 Cheng LL, Moor SL, Ho CTC. Predisposing Factors to Dental Caries in Children with Cleft Lip and Palate: A Review and Strategies for Early Prevention. The Cleft Palate-Craniofacial Journal . 2007;44(1):67-72. doi:10.1597/05-112 Meaney S, Anweigi L, Ziada H, Allen F. The impact of hypodontia: a qualitative study on the experiences of patients. Eur J Orthod . 2012;34(5):547-552. Rakhshan V. Congenitally missing teeth (hypodontia): A review of the literature concerning the etiology, prevalence, risk factors, patterns and treatment. Dent Res J (Isfahan) . 2015;12(1). https://pubmed.ncbi.nlm.nih.gov/25709668 Park MK, Shin MK, Kim SO, et al. Prevalence of delayed tooth development and its relation to tooth agenesis in Korean children. Arch Oral Biol . 2017;73:243-247. doi:10.1016/j.archoralbio.2016.10.024 Badrov J, Lauc T, Nakaš E, Galić I. Dental Age and Tooth Development in Orthodontic Patients with Agenesis of Permanent Teeth. Biomed Res Int . 2017;2017:8683970. doi:10.1155/2017/8683970 Elsten EECM, Caron CJJM, Dunaway DJ, Padwa BL, Forrest C, Koudstaal MJ. Dental anomalies in craniofacial microsomia: A systematic review. Orthod Craniofac Res . 2020;23(1):16-26. doi:10.1111/ocr.12351 Mark Welch JL, Ramírez-Puebla ST, Borisy GG. Oral Microbiome Geography: Micron-Scale Habitat and Niche. Cell Host & Microbe . 2020;28(2):160-168. doi:10.1016/j.chom.2020.07.009 Zhang Y, Wang X, Li H, Ni C, Du Z, Yan F. Human oral microbiota and its modulation for oral health. Biomed Pharmacother . 2018;99:883-893. doi:10.1016/j.biopha.2018.01.146 Lamont RJ, Koo H, Hajishengallis G. The oral microbiota: dynamic communities and host interactions. Nat Rev Microbiol . 2018;16(12):745-759. doi:10.1038/s41579-018-0089-x Chhaliyil P, Fischer KF, Schoel B, Chhalliyil P. A Novel, Simple, Frequent Oral Cleaning Method Reduces Damaging Bacteria in the Dental Microbiota. J Int Soc Prev Community Dent . 2020;10(4):511-519. doi:10.4103/jispcd.JISPCD_31_20 Nossa CW. Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome. WJG . 2010;16(33):4135. doi:10.3748/wjg.v16.i33.4135 Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics . 2018;34(17):i884-i890. doi:10.1093/bioinformatics/bty560 Li D, Luo R, Liu CM, et al. MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods . 2016;102. doi:10.1016/j.ymeth.2016.02.020 Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics . 2015;31(10):1674-1676. doi:10.1093/bioinformatics/btv033 Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics . 2010;11:119. doi:10.1186/1471-2105-11-119 Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods . 2015;12(1):59-60. doi:10.1038/nmeth.3176 Powell S, Forslund K, Szklarczyk D, et al. eggNOG v4.0: nested orthology inference across 3686 organisms. Nucleic Acids Res . 2014;42(Database issue):D231-D239. doi:10.1093/nar/gkt1253 Kanehisa M, Goto S, Hattori M, et al. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res . 2006;34(Database issue):D354-D357. Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics. Nucleic Acids Res . 2009;37(Database issue):D233-D238. doi:10.1093/nar/gkn663 Hill TCJ, Walsh KA, Harris JA, Moffett BF. Using ecological diversity measures with bacterial communities. FEMS Microbiol Ecol . 2003;43(1). doi:10.1111/j.1574-6941.2003.tb01040.x Chao A, Bunge J. Estimating the number of species in a stochastic abundance model. Biometrics . 2002;58(3):531-539. Chen Q, Zhao Y, Shen G, Dai J. Etiology and Pathogenesis of Hemifacial Microsomia. J Dent Res . 2018;97(12):1297-1305. doi:10.1177/0022034518795609 Hartsfield JK. Review of the etiologic heterogeneity of the oculo-auriculo-vertebral spectrum (Hemifacial Microsomia). Orthod Craniofac Res . 2007;10(3):121-128. Caron CJJM, Pluijmers BI, Wolvius EB, et al. Craniofacial and extracraniofacial anomalies in craniofacial microsomia: a multicenter study of 755 patients’. J Craniomaxillofac Surg . 2017;45(8):1302-1310. doi:10.1016/j.jcms.2017.06.001 Elsten EECM, Caron CJJM, Dunaway DJ, Padwa BL, Forrest C, Koudstaal MJ. Dental anomalies in craniofacial microsomia: A systematic review. Orthod Craniofacial Res . 2020;23(1):16-26. doi:10.1111/ocr.12351 Irie K, Novince CM, Darveau RP. Impact of the Oral Commensal Flora on Alveolar Bone Homeostasis. J Dent Res . 2014;93(8):801-806. doi:10.1177/0022034514540173 Hathaway-Schrader JD, Novince CM. Maintaining homeostatic control of periodontal bone tissue. Periodontol 2000 . 2021;86(1):157-187. doi:10.1111/prd.12368 Li Y, Ling J, Jiang Q. Inflammasomes in Alveolar Bone Loss. Front Immunol . 2021;12:691013. doi:10.3389/fimmu.2021.691013 Shibazaki-Yorozuya R, Yamada A, Nagata S, Ueda K, Miller AJ, Maki K. Three-dimensional longitudinal changes in craniofacial growth in untreated hemifacial microsomia patients with cone-beam computed tomography. American Journal of Orthodontics and Dentofacial Orthopedics . 2014;145(5):579-594. doi:10.1016/j.ajodo.2013.09.015 Bowen WH, Burne RA, Wu H, Koo H. Oral Biofilms: Pathogens, Matrix, and Polymicrobial Interactions in Microenvironments. Trends Microbiol . 2018;26(3):229-242. doi:10.1016/j.tim.2017.09.008 Chimenos-Küstner E, Giovannoni ML, Schemel-Suárez M. Dysbiosis as a determinant factor of systemic and oral pathology: importance of microbiome. Med Clin (Barc) . 2017;149(7):305-309. doi:10.1016/j.medcli.2017.05.036 Mark Welch JL, Ramírez-Puebla ST, Borisy GG. Oral Microbiome Geography: Micron-Scale Habitat and Niche. Cell Host & Microbe . 2020;28(2):160-168. doi:10.1016/j.chom.2020.07.009 Tuganbaev T, Yoshida K, Honda K. The effects of oral microbiota on health. Science . 2022;376(6596):934-936. doi:10.1126/science.abn1890 Tonelli A, Lumngwena EN, Ntusi NAB. The oral microbiome in the pathophysiology of cardiovascular disease. Nat Rev Cardiol . 2023;20(6):386-403. doi:10.1038/s41569-022-00825-3 Radaic A. The oralome and its dysbiosis: New insights into oral microbiome-host interactions. Computational and Structural Biotechnology Journal . Published online 2021. Santos AL, Siqueira JF, Rôças IN, Jesus EC, Rosado AS, Tiedje JM. Comparing the bacterial diversity of acute and chronic dental root canal infections. PLoS One . 2011;6(11):e28088. doi:10.1371/journal.pone.0028088 Schulze-Schweifing K, Banerjee A, Wade WG. Comparison of bacterial culture and 16S rRNA community profiling by clonal analysis and pyrosequencing for the characterization of the dentine caries-associated microbiome. Front Cell Infect Microbiol . 2014;4:164. doi:10.3389/fcimb.2014.00164 Hathaway-Schrader JD, Novince CM. Maintaining homeostatic control of periodontal bone tissue. Periodontol 2000 . 2021;86(1):157-187. doi:10.1111/prd.12368 Yang F, Zeng X, Ning K, et al. Saliva microbiomes distinguish caries-active from healthy human populations. ISME J . 2012;6(1). doi:10.1038/ismej.2011.71 Antiabong JF, Boardman W, Moore RB, Brown MH, Ball AS. The oral microbial community of gingivitis and lumpy jaw in captive macropods. Res Vet Sci . 2013;95(3). doi:10.1016/j.rvsc.2013.08.010 Cheng LL, Moor SL, Ho CTC. Predisposing factors to dental caries in children with cleft lip and palate: a review and strategies for early prevention. Cleft Palate Craniofac J . 2007;44(1):67-72. Ongkosuwito EM, de Gijt P, Wattel E, Carels CEL, Kuijpers-Jagtman AM. Dental development in hemifacial microsomia. J Dent Res . 2010;89(12):1368-1372. doi:10.1177/0022034510378425 Silvestri A, Natali G, Fadda MT. Dental agenesis in hemifacial microsomia. Pediatr Dent . 1996;18(1):48-51. Li X, Liu Y, Yang X, Li C, Song Z. The Oral Microbiota: Community Composition, Influencing Factors, Pathogenesis, and Interventions. Front Microbiol . 2022;13:895537. doi:10.3389/fmicb.2022.895537 Caron CJJM, Pluijmers BI, Maas BDPJ, et al. Obstructive sleep apnoea in craniofacial microsomia: analysis of 755 patients. Int J Oral Maxillofac Surg . 2017;46(10):1330-1337. doi:10.1016/j.ijom.2017.05.020 Xu H, Li X, Zheng X, et al. Pediatric Obstructive Sleep Apnea is Associated With Changes in the Oral Microbiome and Urinary Metabolomics Profile: A Pilot Study. J Clin Sleep Med . 2018;14(9):1559-1567. doi:10.5664/jcsm.7336 Jia P, Zou J, Yin S, Chen F, Yi H, Zhang Q. Analysis of the Salivary Microbiome in Obstructive Sleep Apnea Syndrome Patients. Chen T, ed. Canadian Journal of Infectious Diseases and Medical Microbiology . 2020;2020:1-7. doi:10.1155/2020/6682020 Nizam N, Basoglu OK, Tasbakan MS, Lappin DF, Buduneli N. Is there an association between obstructive sleep apnea syndrome and periodontal inflammation? Clin Oral Invest . 2016;20(4):659-668. doi:10.1007/s00784-015-1544-y Oksenberg A, Froom P, Melamed S. Dry mouth upon awakening in obstructive sleep apnea. J Sleep Res . 2006;15(3):317-320. Boink MA, Roffel S, Nazmi K, Bolscher JGM, Veerman ECI, Gibbs S. Saliva-Derived Host Defense Peptides Histatin1 and LL-37 Increase Secretion of Antimicrobial Skin and Oral Mucosa Chemokine CCL20 in an IL-1α-Independent Manner. J Immunol Res . 2017;2017:3078194. doi:10.1155/2017/3078194 Frenkel ES, Ribbeck K. Salivary mucins in host defense and disease prevention. J Oral Microbiol . 2015;7:29759. doi:10.3402/jom.v7.29759 Ginsburg I, Kohen R, Koren E. Saliva: a “solubilizer” of lipophilic antioxidant polyphenols. Oral Dis . 2013;19(3):321-322. doi:10.1111/odi.12038 Frenkel ES, Ribbeck K. Salivary mucins promote the coexistence of competing oral bacterial species. ISME J . 2017;11(5):1286-1290. doi:10.1038/ismej.2016.200 Man WH, de Steenhuijsen Piters WAA, Bogaert D. The microbiota of the respiratory tract: gatekeeper to respiratory health. Nat Rev Microbiol . 2017;15(5):259-270. doi:10.1038/nrmicro.2017.14 Zhang X, Wang S, Xu H, Yi H, Guan J, Yin S. Metabolomics and microbiome profiling as biomarkers in obstructive sleep apnoea: a comprehensive review. Eur Respir Rev . 2021;30(160). doi:10.1183/16000617.0220-2020 Efunkoya AA, Bamgbose BO, Adebola RA, Adeoye JB, Akpasa IO. Maxillomandibular distraction osteogenesis. J Craniofac Surg . 2014;25(5):1787-1792. doi:10.1097/SCS.0000000000000907 Weichman KE, Jacobs J, Patel P, et al. Early Distraction for Mild to Moderate Unilateral Craniofacial Microsomia: Long-Term Follow-Up, Outcomes, and Recommendations. Plast Reconstr Surg . 2017;139(4):941e-953e. doi:10.1097/PRS.0000000000003223 Zhang RS, Lin LO, Hoppe IC, Swanson JW, Taylor JA, Bartlett SP. Early Mandibular Distraction in Craniofacial Microsomia and Need for Orthognathic Correction at Skeletal Maturity: A Comparative Long-Term Follow-Up Study. Plast Reconstr Surg . 2018;142(5):1285-1293. doi:10.1097/PRS.0000000000004842 Melsen B, Bjerregaard J, Bundgaard M. The effect of treatment with functional appliance on a pathologic growth pattern of the condyle. Am J Orthod Dentofacial Orthop . 1986;90(6):503-512. Shibazaki-Yorozuya R, Yamada A, Nagata S, Ueda K, Miller AJ, Maki K. Three-dimensional longitudinal changes in craniofacial growth in untreated hemifacial microsomia patients with cone-beam computed tomography. Am J Orthod Dentofacial Orthop . 2014;145(5):579-594. doi:10.1016/j.ajodo.2013.09.015 Chow A, Lee HF, Trahar M, Kawamoto H, Vastardis H, Ting K. Cephalometric evaluation of the craniofacial complex in patients treated with an intraoral distraction osteogenesis device: a long-term study. Am J Orthod Dentofacial Orthop . 2008;134(6):724-731. doi:10.1016/j.ajodo.2007.01.029 Ko EWC, Chen PKT, Lo LJ. Comparison of the adult three-dimensional craniofacial features of patients with unilateral craniofacial microsomia with and without early mandible distraction. Int J Oral Maxillofac Surg . 2017;46(7):811-818. doi:10.1016/j.ijom.2017.03.002 Meazzini MC, Mazzoleni F, Gabriele C, Bozzetti A. Mandibular distraction osteogenesis in hemifacial microsomia: long-term follow-up. J Craniomaxillofac Surg . 2005;33(6):370-376. Aiyar A, Pedersen TK, Resnick CM, Nørholt SE, Verna C, Stoustrup PB. Management of unilateral craniofacial microsomia with orthopaedic functional appliances: A systematic literature review. Orthod Craniofac Res . Published online November 2023. doi:10.1111/ocr.12729 Li Y, Ling J, Jiang Q. Inflammasomes in Alveolar Bone Loss. Front Immunol . 2021;12:691013. doi:10.3389/fimmu.2021.691013 Hathaway‐Schrader JD, Novince CM. Maintaining homeostatic control of periodontal bone tissue. Periodontology 2000 . 2021;86(1):157-187. doi:10.1111/prd.12368 Shibazaki-Yorozuya R, Yamada A, Nagata S, Ueda K, Miller AJ, Maki K. Three-dimensional longitudinal changes in craniofacial growth in untreated hemifacial microsomia patients with cone-beam computed tomography. American Journal of Orthodontics and Dentofacial Orthopedics . 2014;145(5):579-594. doi:10.1016/j.ajodo.2013.09.015 Lee KM, Kim YI, Park SB, Son WS. Alveolar bone loss around lower incisors during surgical orthodontic treatment in mandibular prognathism. Angle Orthod . 2012;82(4):637-644. doi:10.2319/081711-526.1 Ona M, Wakabayashi N. Influence of alveolar support on stress in periodontal structures. J Dent Res . 2006;85(12):1087-1091. Irie K, Novince CM, Darveau RP. Impact of the Oral Commensal Flora on Alveolar Bone Homeostasis. J Dent Res . 2014;93(8):801-806. doi:10.1177/0022034514540173 Bonne NJ, Wong DT. Salivary biomarker development using genomic, proteomic and metabolomic approaches. Genome Med . 2012;4(10):82. doi:10.1186/gm383 Yoshizawa JM, Schafer CA, Schafer JJ, Farrell JJ, Paster BJ, Wong DTW. Salivary biomarkers: toward future clinical and diagnostic utilities. Clin Microbiol Rev . 2013;26(4):781-791. doi:10.1128/CMR.00021-13 Gomez A, Nelson KE. The Oral Microbiome of Children: Development, Disease, and Implications Beyond Oral Health. Microb Ecol . 2017;73(2):492-503. doi:10.1007/s00248-016-0854-1 Pathak JL, Yan Y, Zhang Q, Wang L, Ge L. The role of oral microbiome in respiratory health and diseases. Respir Med . 2021;185:106475. doi:10.1016/j.rmed.2021.106475 Varoni EM, Rimondini L. Oral Microbiome, Oral Health and Systemic Health: A Multidirectional Link. Biomedicines . 2022;10(1). doi:10.3390/biomedicines10010186 Zaura E, Keijser BJF, Huse SM, Crielaard W. Defining the healthy “core microbiome” of oral microbial communities. BMC Microbiol . 2009;9:259. doi:10.1186/1471-2180-9-259 Takeshita T, Yasui M, Shibata Y, et al. Dental plaque development on a hydroxyapatite disk in young adults observed by using a barcoded pyrosequencing approach. Sci Rep . 2015;5:8136. doi:10.1038/srep08136 Page RC, Vandesteen GE, Ebersole JL, Williams BL, Dixon IL, Altman LC. Clinical and laboratory studies of a family with a high prevalence of juvenile periodontitis. J Periodontol . 1985;56(10):602-610. Watanabe K. Prepubertal periodontitis: a review of diagnostic criteria, pathogenesis, and differential diagnosis. J Periodontal Res . 1990;25(1):31-48. Page RC. Gingivitis. J Clin Periodontol . 1986;13(5):345-359. Zhu W, Shen W, Wang J, et al. Capnocytophaga gingivalis is a potential tumor promotor in oral cancer. Oral Dis . 2024;30(2):353-362. doi:10.1111/odi.14376 Hayes RB, Ahn J, Fan X, et al. Association of Oral Microbiome With Risk for Incident Head and Neck Squamous Cell Cancer. JAMA Oncol . 2018;4(3):358-365. doi:10.1001/jamaoncol.2017.4777 Kinoshita S, Udaka S, Shimono M. Studies on the amino acid fermentation. Part 1. Production of L-glutamic acid by various microorganisms. J Gen Appl Microbiol . 2004;50(6):331-343. Poetsch A, Haussmann U, Burkovski A. Proteomics of corynebacteria: From biotechnology workhorses to pathogens. Proteomics . 2011;11(15):3244-3255. doi:10.1002/pmic.201000786 Costa JJ, Michel JL, Rappuoli R, Murphy JR. Restriction map of corynebacteriophages beta c and beta vir and physical localization of the diphtheria tox operon. J Bacteriol . 1981;148(1):124-130. Hayes RB, Ahn J, Fan X, et al. Association of Oral Microbiome With Risk for Incident Head and Neck Squamous Cell Cancer. JAMA Oncol . 2018;4(3):358. doi:10.1001/jamaoncol.2017.4777 Kurita-Ochiai T, Seto S, Suzuki N, et al. Butyric acid induces apoptosis in inflamed fibroblasts. J Dent Res . 2008;87(1):51-55. Washio J, Sato T, Koseki T, Takahashi N. Hydrogen sulfide-producing bacteria in tongue biofilm and their relationship with oral malodour. J Med Microbiol . 2005;54(Pt 9):889-895. doi:10.1099/jmm.0.46118-0 Gross EL, Beall CJ, Kutsch SR, Firestone ND, Leys EJ, Griffen AL. Beyond Streptococcus mutans: dental caries onset linked to multiple species by 16S rRNA community analysis. PLoS One . 2012;7(10):e47722. doi:10.1371/journal.pone.0047722 Hayes RB, Ahn J, Fan X, et al. Association of Oral Microbiome With Risk for Incident Head and Neck Squamous Cell Cancer. JAMA Oncol . 2018;4(3):358-365. doi:10.1001/jamaoncol.2017.4777 Brook I. Fusobacterial infections in children. J Infect . 1994;28(2):155-165. Ehlers Klug T, Rusan M, Fuursted K, Ovesen T. Fusobacterium necrophorum: most prevalent pathogen in peritonsillar abscess in Denmark. Clin Infect Dis . 2009;49(10):1467-1472. doi:10.1086/644616 Shang FM, Liu HL. Fusobacterium nucleatum and colorectal cancer: A review. World J Gastrointest Oncol . 2018;10(3):71-81. doi:10.4251/wjgo.v10.i3.71 Citron DM. Update on the taxonomy and clinical aspects of the genus fusobacterium. Clin Infect Dis . 2002;35(Suppl 1):S22-S27. Niederman R, Zhang J, Kashket S. Short-chain carboxylic-acid-stimulated, PMN-mediated gingival inflammation. Crit Rev Oral Biol Med . 1997;8(3):269-290. Kurita-Ochiai T, Seto S, Suzuki N, et al. Butyric acid induces apoptosis in inflamed fibroblasts. J Dent Res . 2008;87(1):51-55. Tanaka S, Yoshida M, Murakami Y, et al. The relationship of Prevotella intermedia, Prevotella nigrescens and Prevotella melaninogenica in the supragingival plaque of children, caries and oral malodor. J Clin Pediatr Dent . 2008;32(3):195-200. Thomas RM, Jobin C. The Microbiome and Cancer: Is the “Oncobiome” Mirage Real? Trends Cancer . 2015;1(1):24-35. Schwabe RF, Jobin C. The microbiome and cancer. Nat Rev Cancer . 2013;13(11):800-812. doi:10.1038/nrc3610 Senthakumaran T, Moen AEF, Tannæs TM, et al. Microbial dynamics with CRC progression: a study of the mucosal microbiota at multiple sites in cancers, adenomatous polyps, and healthy controls. Eur J Clin Microbiol Infect Dis . 2023;42(3):305-322. doi:10.1007/s10096-023-04551-7 Qi Y, Zang SQ, Wei J, et al. High-throughput sequencing provides insights into oral microbiota dysbiosis in association with inflammatory bowel disease. Genomics . 2021;113(1 Pt 2):664-676. doi:10.1016/j.ygeno.2020.09.063 Zilbauer M, Dorrell N, Wren BW, Bajaj-Elliott M. Campylobacter jejuni-mediated disease pathogenesis: an update. Trans R Soc Trop Med Hyg . 2008;102(2):123-129. Kaasch AJ, Saxler G, Seifert H. Septic arthritis due to Rothia mucilaginosa. Infection . 2011;39(1):81-82. doi:10.1007/s15010-010-0065-5 Uchibori S, Tsudukibashi O, Goto H, Kobayashi T, Aida M. A novel selective medium for the isolation and distribution of Rothia dentocariosa in oral cavities. J Microbiol Methods . 2012;91(1):205-207. doi:10.1016/j.mimet.2012.07.004 Kobayashi T, Uchibori S, Tsuzukibashi O, Goto H, Aida M. A selective medium for Rothia mucilaginosa and its distribution in oral cavities. J Microbiol Methods . 2012;91(3):364-365. doi:10.1016/j.mimet.2012.09.011 Takahashi N, Nyvad B. The role of bacteria in the caries process: ecological perspectives. J Dent Res . 2011;90(3):294-303. doi:10.1177/0022034510379602 Torlakovic L, Klepac-Ceraj V, Ogaard B, Cotton SL, Paster BJ, Olsen I. Microbial community succession on developing lesions on human enamel. J Oral Microbiol . 2012;4. doi:10.3402/jom.v4i0.16125 Belstrøm D, Paster BJ, Fiehn NE, Bardow A, Holmstrup P. Salivary bacterial fingerprints of established oral disease revealed by the Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS) technique. J Oral Microbiol . 2016;8:30170. doi:10.3402/jom.v8.30170 Paju S, Pussinen PJ, Suominen-Taipale L, Hyvönen M, Knuuttila M, Könönen E. Detection of multiple pathogenic species in saliva is associated with periodontal infection in adults. J Clin Microbiol . 2009;47(1):235-238. doi:10.1128/JCM.01824-08 Lemos JA, Palmer SR, Zeng L, et al. The Biology of Streptococcus mutans. Microbiol Spectr . 2019;7(1). doi:10.1128/microbiolspec.GPP3-0051-2018 Wu Y, Chi X, Zhang Q, Chen F, Deng X. Characterization of the salivary microbiome in people with obesity. PeerJ . 2018;6:e4458. doi:10.7717/peerj.4458 Ma T, Wu Z, Lin J, Shan C, Abasijiang A, Zhao J. Characterization of the oral and gut microbiome in children with obesity aged 3 to 5 years. Front Cell Infect Microbiol . 2023;13:1102650. doi:10.3389/fcimb.2023.1102650 Saito T, Shimazaki Y, Sakamoto M. Obesity and periodontitis. N Engl J Med . 1998;339(7):482-483. Iaffaldano L, Granata I, Pagliuca C, et al. Oropharyngeal microbiome evaluation highlights Neisseria abundance in active celiac patients. Sci Rep . 2018;8(1):11047. doi:10.1038/s41598-018-29443-1 D’Argenio V, Casaburi G, Precone V, et al. Metagenomics Reveals Dysbiosis and a Potentially Pathogenic N. flavescens Strain in Duodenum of Adult Celiac Patients. Am J Gastroenterol . 2016;111(6):879-890. doi:10.1038/ajg.2016.95 Shamriz O, Mizrahi H, Werbner M, Shoenfeld Y, Avni O, Koren O. Microbiota at the crossroads of autoimmunity. Autoimmun Rev . 2016;15(9):859-869. doi:10.1016/j.autrev.2016.07.012 Dong F, Perdew GH. The aryl hydrocarbon receptor as a mediator of host-microbiota interplay. Gut Microbes . 2020;12(1):1859812. doi:10.1080/19490976.2020.1859812 Barik S. The Uniqueness of Tryptophan in Biology: Properties, Metabolism, Interactions and Localization in Proteins. Int J Mol Sci . 2020;21(22). doi:10.3390/ijms21228776 Palego L, Betti L, Rossi A, Giannaccini G. Tryptophan Biochemistry: Structural, Nutritional, Metabolic, and Medical Aspects in Humans. J Amino Acids . 2016;2016:8952520. doi:10.1155/2016/8952520 Takahashi N. Oral Microbiome Metabolism: From “Who Are They?” to “What Are They Doing?”. J Dent Res . 2015;94(12):1628-1637. doi:10.1177/0022034515606045 Grifka-Walk HM, Jenkins BR, Kominsky DJ. Amino Acid Trp: The Far Out Impacts of Host and Commensal Tryptophan Metabolism. Front Immunol . 2021;12:653208. doi:10.3389/fimmu.2021.653208 Wu H, Denna TH, Storkersen JN, Gerriets VA. Beyond a neurotransmitter: The role of serotonin in inflammation and immunity. Pharmacol Res . 2019;140:100-114. doi:10.1016/j.phrs.2018.06.015 Shajib MS, Khan WI. The role of serotonin and its receptors in activation of immune responses and inflammation. Acta Physiol (Oxf) . 2015;213(3):561-574. doi:10.1111/apha.12430 Liu XH, Zhai XY. Role of tryptophan metabolism in cancers and therapeutic implications. Biochimie . 2021;182:131-139. doi:10.1016/j.biochi.2021.01.005 Rubel F, Kern JS, Technau-Hafsi K, et al. Indoleamine 2,3-Dioxygenase Expression in Primary Cutaneous Melanoma Correlates with Breslow Thickness and Is of Significant Prognostic Value for Progression-Free Survival. J Invest Dermatol . 2018;138(3):679-687. doi:10.1016/j.jid.2017.09.036 Suzuki Y, Suda T, Furuhashi K, et al. Increased serum kynurenine/tryptophan ratio correlates with disease progression in lung cancer. Lung Cancer . 2010;67(3):361-365. doi:10.1016/j.lungcan.2009.05.001 Brandacher G, Perathoner A, Ladurner R, et al. Prognostic value of indoleamine 2,3-dioxygenase expression in colorectal cancer: effect on tumor-infiltrating T cells. Clin Cancer Res . 2006;12(4):1144-1151. Neavin DR, Liu D, Ray B, Weinshilboum RM. The Role of the Aryl Hydrocarbon Receptor (AHR) in Immune and Inflammatory Diseases. Int J Mol Sci . 2018;19(12). doi:10.3390/ijms19123851 Balci N, Kurgan Ş, Çekici A, Çakır T, Serdar MA. Free amino acid composition of saliva in patients with healthy periodontium and periodontitis. Clin Oral Investig . 2021;25(6):4175-4183. doi:10.1007/s00784-021-03977-7 Li X, Ma Y, Wu X, et al. Serotonin acts as a novel regulator of interleukin-6 secretion in osteocytes through the activation of the 5-HT(2B) receptor and the ERK1/2 signalling pathway. Biochem Biophys Res Commun . 2013;441(4):809-814. doi:10.1016/j.bbrc.2013.10.141 Chabbi-Achengli Y, Coudert AE, Callebert J, et al. Decreased osteoclastogenesis in serotonin-deficient mice. Proc Natl Acad Sci U S A . 2012;109(7):2567-2572. doi:10.1073/pnas.1117792109 Li X, Wu X, Ma Y, et al. Oral administration of 5-hydroxytryptophan aggravated periodontitis-induced alveolar bone loss in rats. Arch Oral Biol . 2015;60(5):789-798. doi:10.1016/j.archoralbio.2015.01.015 Kabil O, Banerjee R. Redox biochemistry of hydrogen sulfide. J Biol Chem . 2010;285(29):21903-21907. doi:10.1074/jbc.R110.128363 Miller CG, Schmidt EE. Sulfur Metabolism Under Stress. Antioxid Redox Signal . 2020;33(16):1158-1173. doi:10.1089/ars.2020.8151 Kumar R, Landry AP, Guha A, et al. A redox cycle with complex II prioritizes sulfide quinone oxidoreductase-dependent H2S oxidation. J Biol Chem . 2022;298(1):101435. doi:10.1016/j.jbc.2021.101435 Olson KR. A Case for Hydrogen Sulfide Metabolism as an Oxygen Sensing Mechanism. Antioxidants (Basel) . 2021;10(11). doi:10.3390/antiox10111650 Bouillaud F. Sulfide Oxidation Evidences the Immediate Cellular Response to a Decrease in the Mitochondrial ATP/O2 Ratio. Biomolecules . 2022;12(3). doi:10.3390/biom12030361 Stipanuk MH. Sulfur amino acid metabolism: pathways for production and removal of homocysteine and cysteine. Annu Rev Nutr . 2004;24:539-577. Miller CG, Holmgren A, Arnér ESJ, Schmidt EE. NADPH-dependent and -independent disulfide reductase systems. Free Radic Biol Med . 2018;127:248-261. doi:10.1016/j.freeradbiomed.2018.03.051 Yoshida Y, Ito S, Kamo M, et al. Production of hydrogen sulfide by two enzymes associated with biosynthesis of homocysteine and lanthionine in Fusobacterium nucleatum subsp. nucleatum ATCC 25586. Microbiology (Reading) . 2010;156(Pt 7):2260-2269. doi:10.1099/mic.0.039180-0 Marciano D, Santana M, Mantilla BS, Silber AM, Marino-Buslje C, Nowicki C. Biochemical characterization of serine acetyltransferase and cysteine desulfhydrase from Leishmania major. Mol Biochem Parasitol . 2010;173(2):170-174. doi:10.1016/j.molbiopara.2010.06.004 Dharmani P, Strauss J, Ambrose C, Allen-Vercoe E, Chadee K. Fusobacterium nucleatum infection of colonic cells stimulates MUC2 mucin and tumor necrosis factor alpha. Infect Immun . 2011;79(7):2597-2607. doi:10.1128/IAI.05118-11 Takahashi Y, Yoshida A, Nagata E, et al. Streptococcus anginosus l-cysteine desulfhydrase gene expression is associated with abscess formation in BALB/c mice. Mol Oral Microbiol . 2011;26(3):221-227. doi:10.1111/j.2041-1014.2010.00599.x Strauss J, Kaplan GG, Beck PL, et al. Invasive potential of gut mucosa-derived Fusobacterium nucleatum positively correlates with IBD status of the host. Inflamm Bowel Dis . 2011;17(9):1971-1978. doi:10.1002/ibd.21606 Castellarin M, Warren RL, Freeman JD, et al. Fusobacterium nucleatum infection is prevalent in human colorectal carcinoma. Genome Res . 2012;22(2):299-306. doi:10.1101/gr.126516.111 Kostic AD, Gevers D, Pedamallu CS, et al. Genomic analysis identifies association of Fusobacterium with colorectal carcinoma. Genome Res . 2012;22(2):292-298. doi:10.1101/gr.126573.111 Módis K, Bos EM, Calzia E, et al. Regulation of mitochondrial bioenergetic function by hydrogen sulfide. Part II. Pathophysiological and therapeutic aspects. Br J Pharmacol . 2014;171(8):2123-2146. doi:10.1111/bph.12368 Bos EM, van Goor H, Joles JA, Whiteman M, Leuvenink HGD. Hydrogen sulfide: physiological properties and therapeutic potential in ischaemia. Br J Pharmacol . 2015;172(6):1479-1493. doi:10.1111/bph.12869 Wallace JL, Wang R. Hydrogen sulfide-based therapeutics: exploiting a unique but ubiquitous gasotransmitter. Nat Rev Drug Discov . 2015;14(5):329-345. doi:10.1038/nrd4433 Ijssennagger N, van der Meer R, van Mil SWC. Sulfide as a Mucus Barrier-Breaker in Inflammatory Bowel Disease? Trends Mol Med . 2016;22(3):190-199. doi:10.1016/j.molmed.2016.01.002 Zaorska E, Tomasova L, Koszelewski D, Ostaszewski R, Ufnal M. Hydrogen Sulfide in Pharmacotherapy, Beyond the Hydrogen Sulfide-Donors. Biomolecules . 2020;10(2). doi:10.3390/biom10020323 Wang R. Physiological implications of hydrogen sulfide: a whiff exploration that blossomed. Physiol Rev . 2012;92(2):791-896. doi:10.1152/physrev.00017.2011 Wang Y, Nguyen LH, Mehta RS, Song M, Huttenhower C, Chan AT. Association Between the Sulfur Microbial Diet and Risk of Colorectal Cancer. JAMA Netw Open . 2021;4(11):e2134308. doi:10.1001/jamanetworkopen.2021.34308 Yoshii K, Hosomi K, Sawane K, Kunisawa J. Metabolism of Dietary and Microbial Vitamin B Family in the Regulation of Host Immunity. Front Nutr . 2019;6:48. doi:10.3389/fnut.2019.00048 Hayashi A, Mikami Y, Miyamoto K, et al. Intestinal Dysbiosis and Biotin Deprivation Induce Alopecia through Overgrowth of Lactobacillus murinus in Mice. Cell Reports . 2017;20(7):1513-1524. doi:10.1016/j.celrep.2017.07.057 Magnúsdóttir S, Ravcheev D, De Crécy-Lagard V, Thiele I. Systematic genome assessment of B-vitamin biosynthesis suggests co-operation among gut microbes. Front Genet . 2015;6. doi:10.3389/fgene.2015.00148 MetaHIT Consortium (additional members), Arumugam M, Raes J, et al. Enterotypes of the human gut microbiome. Nature . 2011;473(7346):174-180. doi:10.1038/nature09944 Magnúsdóttir S, Ravcheev D, de Crécy-Lagard V, Thiele I. Systematic genome assessment of B-vitamin biosynthesis suggests co-operation among gut microbes. Front Genet . 2015;6:148. doi:10.3389/fgene.2015.00148 León-Del-Río A. Biotin in metabolism, gene expression, and human disease. J Inherit Metab Dis . 2019;42(4):647-654. doi:10.1002/jimd.12073 Lin S, Cronan JE. Closing in on complete pathways of biotin biosynthesis. Mol Biosyst . 2011;7(6):1811-1821. doi:10.1039/c1mb05022b Cronan JE. Advances in synthesis of biotin and assembly of lipoic acid. Curr Opin Chem Biol . 2018;47:60-66. doi:10.1016/j.cbpa.2018.08.004 Agrawal S, Agrawal A, Said HM. Biotin deficiency enhances the inflammatory response of human dendritic cells. Am J Physiol Cell Physiol . 2016;311(3):C386-C391. doi:10.1152/ajpcell.00141.2016 Elahi A, Sabui S, Narasappa NN, et al. Biotin Deficiency Induces Th1- and Th17-Mediated Proinflammatory Responses in Human CD4+ T Lymphocytes via Activation of the mTOR Signaling Pathway. J Immunol . 2018;200(8):2563-2570. doi:10.4049/jimmunol.1701200 Oliphant K, Allen-Vercoe E. Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health. Microbiome . 2019;7(1):91. doi:10.1186/s40168-019-0704-8 Koh A, Molinaro A, Ståhlman M, et al. Microbially Produced Imidazole Propionate Impairs Insulin Signaling through mTORC1. Cell . 2018;175(4). doi:10.1016/j.cell.2018.09.055 Moro J, Tomé D, Schmidely P, Demersay TC, Azzout-Marniche D. Histidine: A Systematic Review on Metabolism and Physiological Effects in Human and Different Animal Species. Nutrients . 2020;12(5). doi:10.3390/nu12051414 Babizhayev MA, Guiotto A, Kasus-Jacobi A. N-Acetylcarnosine and histidyl-hydrazide are potent agents for multitargeted ophthalmic therapy of senile cataracts and diabetic ocular complications. J Drug Target . 2009;17(1):36-63. doi:10.1080/10611860802438736 Hisatsune T, Kaneko J, Kurashige H, et al. Effect of Anserine/Carnosine Supplementation on Verbal Episodic Memory in Elderly People. J Alzheimers Dis . 2016;50(1):149-159. doi:10.3233/JAD-150767 Tan SP, Brown SB, Griffiths CE, Weller RB, Gibbs NK. Feeding filaggrin: effects of l-histidine supplementation in atopic dermatitis. Clin Cosmet Investig Dermatol . 2017;10:403-411. doi:10.2147/CCID.S146760 DiNicolantonio JJ, McCarty MF, OKeefe JH. Role of dietary histidine in the prevention of obesity and metabolic syndrome. Open Heart . 2018;5(2):e000676. doi:10.1136/openhrt-2017-000676 Wunschel EJ, Schirmer B, Seifert R, Neumann D. Lack of Histamine H4-Receptor Expression Aggravates TNBS-Induced Acute Colitis Symptoms in Mice. Front Pharmacol . 2017;8:642. doi:10.3389/fphar.2017.00642 Dy M, Schneider E. Histamine-cytokine connection in immunity and hematopoiesis. Cytokine Growth Factor Rev . 2004;15(5):393-410. Cacabelos R, Torrellas C, Fernández-Novoa L, López-Muñoz F. Histamine and Immune Biomarkers in CNS Disorders. Mediators of Inflammation . 2016;2016:1-10. doi:10.1155/2016/1924603 Smolinska S, Winiarska E, Globinska A, Jutel M. Histamine: A Mediator of Intestinal Disorders—A Review. Metabolites . 2022;12(10):895. doi:10.3390/metabo12100895 Guo J, Liang T, Chen H, et al. Glutamate attenuates lipopolysaccharide induced intestinal barrier injury by regulating corticotropin-releasing factor pathway in weaned pigs. Anim Biosci . 2022;35(8):1235-1249. doi:10.5713/ab.21.0476 Yamamoto M, Pinto-Sanchez MI, Bercik P, Britz-McKibbin P. Metabolomics reveals elevated urinary excretion of collagen degradation and epithelial cell turnover products in irritable bowel syndrome patients. Metabolomics . 2019;15(6):82. doi:10.1007/s11306-019-1543-0 Wu J, Wu Y, Feng W, et al. Role of Microbial Metabolites of Histidine in the Development of Colitis. Molecular Nutrition Food Res . 2022;66(14):2101175. doi:10.1002/mnfr.202101175 Yuan H, Wu X, Wu Q, et al. Lysine catabolism reprograms tumour immunity through histone crotonylation. Nature . 2023;617(7962):818-826. doi:10.1038/s41586-023-06061-0 Leandro J, Houten SM. Saccharopine, a lysine degradation intermediate, is a mitochondrial toxin. J Cell Biol . 2019;218(2):391-392. doi:10.1083/jcb.201901033 Loesche WJ, Gibbons RJ. Amino acid fermentation by Fusobacterium nucleatum. Arch Oral Biol . 1968;13(2):191-202. Wang X, Yang S, Li S, et al. Aberrant gut microbiota alters host metabolome and impacts renal failure in humans and rodents. Gut . 2020;69(12):2131-2142. doi:10.1136/gutjnl-2019-319766 RUBIN AL, SPRITZ N, MEAD AW, HERRMANN RA, BRAVEMAN WS, LUCKEY EH. The use of L-lysine monomydrochloride in combination with mercurial diuretics in the treatment of refractory fluid retention. Circulation . 1960;21:332-336. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4673616","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":333335607,"identity":"5e7f9596-43b7-4264-9fbe-90cd4ef4df9a","order_by":0,"name":"TIANYING ZANG","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"TIANYING","middleName":"","lastName":"ZANG","suffix":""},{"id":333335608,"identity":"86b390bc-47b6-4cc8-81a7-f47774d27f9d","order_by":1,"name":"XIAOJUN TANG","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYBAC9gYGBsYPBjY8/CAWUYDnAAMDs0RFmoxkzwEStDDwnDlsY3DDgVgt0ocPv5BsO8/DcAPowI85xGjhS0uzKGy7zcM4u4FZcuY2IrTY8/CYGUgCtTDLHGBj5iVGCw9IC2/bOR42iQTitRg/4DlzgIeHBC1sacBATuaR4DnYTJxfeHiYD3/8YGBnb3+8+eCHj8RoAQI2CQjN2ECceiBg/kC00lEwCkbBKBiZAABTBS//ZI+mrwAAAABJRU5ErkJggg==","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":true,"prefix":"","firstName":"XIAOJUN","middleName":"","lastName":"TANG","suffix":""},{"id":333335610,"identity":"92b4d231-9910-4bbe-a552-601360b2fdda","order_by":2,"name":"Zhiyong ZHANG","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Zhiyong","middleName":"","lastName":"ZHANG","suffix":""},{"id":333335611,"identity":"42a46f9e-cb5c-4135-9d97-b1f224f5456b","order_by":3,"name":"WEI LIU","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"WEI","middleName":"","lastName":"LIU","suffix":""},{"id":333335612,"identity":"bc46e0bd-e45b-4b92-8728-e954cb2924ae","order_by":4,"name":"LIN YIN","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"LIN","middleName":"","lastName":"YIN","suffix":""},{"id":333335613,"identity":"fffe9942-3ceb-49e0-b97a-2d8eea7ce50d","order_by":5,"name":"Shanbaga Zhao Zhao","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Shanbaga","middleName":"Zhao","lastName":"Zhao","suffix":""},{"id":333335614,"identity":"9b7885ce-b496-4c68-b9cf-34c6943562e6","order_by":6,"name":"Bingyang Liu","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Bingyang","middleName":"","lastName":"Liu","suffix":""},{"id":333335615,"identity":"19e65de2-e000-4cd0-8d6e-8e8df0907298","order_by":7,"name":"LUNKUN Ma","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"LUNKUN","middleName":"","lastName":"Ma","suffix":""},{"id":333335616,"identity":"2549755a-6b1d-43a2-903e-4859644fd25f","order_by":8,"name":"ZHIFENG LI","email":"","orcid":"","institution":"Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"ZHIFENG","middleName":"","lastName":"LI","suffix":""}],"badges":[],"createdAt":"2024-07-02 10:47:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4673616/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4673616/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-86537-3","type":"published","date":"2025-02-13T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62135685,"identity":"adfd2eff-65db-4489-8b75-cc350194f15c","added_by":"auto","created_at":"2024-08-09 16:20:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":357110,"visible":true,"origin":"","legend":"\u003cp\u003eComparative analysis of salivary bacterial composition in individuals diagnosed with CFM and Ctrl. group. \u003cstrong\u003eA\u003c/strong\u003e Boxplot diagram of alpha-diversity. \u003cstrong\u003eB\u003c/strong\u003eComparison of beta diversity (PCoA). \u003cstrong\u003eC,D \u003c/strong\u003eThe top 15 higher relative abundance of salivary bacteria at the phylum (C) and genus (D) level.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4673616/v1/6e329c9f234c6950681cfbfe.png"},{"id":62134317,"identity":"1023e4ac-26a4-4217-939c-d7ceb818d12c","added_by":"auto","created_at":"2024-08-09 16:04:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":622504,"visible":true,"origin":"","legend":"\u003cp\u003eThe diversity, abundance, and distribution of salivary bacteria were compared between the CFM and Ctrl. groups. \u003cstrong\u003eA\u003c/strong\u003eBoxplot of the differential phyla between the CFM and Ctrl. groups. \u003cstrong\u003eB\u003c/strong\u003eBoxplot of the top 10 differential genera between the CFM and Ctrl. groups. \u003cstrong\u003eC\u003c/strong\u003e Heat map matrix of Spearman correlation between high-abundance genera and clinical characterization of CFM patients. \u003cstrong\u003eD\u003c/strong\u003e The contribution of different species to differences between group CFM and Ctrl. \u003cstrong\u003eE\u003c/strong\u003e The differential species annotation analysis between group CFM and Ctrl. \u003cstrong\u003eF\u003c/strong\u003e The contribution of different species to differences between group TypeI-IIA and TypeIIB-III in CFM. \u003cstrong\u003eG\u003c/strong\u003eThe contribution of different species to differences between group TypeI-IIA and TypeIIB-III in CFM.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4673616/v1/68bc827ed865126058b510c4.png"},{"id":62134319,"identity":"6b12f7e0-3eaf-42b5-98f0-fbf0c6357519","added_by":"auto","created_at":"2024-08-09 16:04:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":503390,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional annotation and difference analysis between the CFM and Ctrl. groups. \u003cstrong\u003eA\u003c/strong\u003e Heatmap of differentiated functions between group CFM and Ctrl. \u003cstrong\u003eB\u003c/strong\u003e Boxplot of significant difference function between group CFM and Ctrl. \u003cstrong\u003eC \u003c/strong\u003eFunctional biomarkers with significant differences between group CFM and Ctrl. \u003cstrong\u003eD\u003c/strong\u003e Heatmap of correlation between functional pathways and bacterial genera\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4673616/v1/a1f8f30cc08298c95b651ecb.png"},{"id":76487717,"identity":"74dc1a4d-a0a5-473c-a92d-0c72b429b01b","added_by":"auto","created_at":"2025-02-17 16:11:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2679944,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4673616/v1/de1166d2-a7f5-46fa-a59a-db88bf868a46.pdf"},{"id":62135686,"identity":"d4219166-38ac-4ae7-82d0-1ffd43462e9c","added_by":"auto","created_at":"2024-08-09 16:20:07","extension":"xls","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":750,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xls","url":"https://assets-eu.researchsquare.com/files/rs-4673616/v1/10d2f815e25630c0a648f325.xls"},{"id":62134323,"identity":"6930d772-1e16-4285-81c9-ab4484be46e5","added_by":"auto","created_at":"2024-08-09 16:04:07","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11690,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.xls","url":"https://assets-eu.researchsquare.com/files/rs-4673616/v1/146730f905be31dd08c23fd7.xls"},{"id":62134810,"identity":"e829241a-ae5d-4f72-b6f1-534e75b1df66","added_by":"auto","created_at":"2024-08-09 16:12:07","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":323283,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-4673616/v1/67ce1bc087a02b4566331517.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Structural and functional changes in the oral microbiome of the patients with craniofacial microsomia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDuring embryogenesis, the craniomaxillofacial region is developed from frontonasal prominence, maxillary prominence, mandibular prominence, median nasal prominence, and lateral nasal prominence. Disturbances in the development of the first and second pharyngeal arches during the first 6 weeks of the embryonic stage may lead to a series of deformations and craniofacial microsomia (CFM). CFM, the second most common congenital craniofacial malformation after cleft lip and palate, manifests as mandible, maxilla, ear, facial nerve, and muscle underdevelopment. CFM is characterized by dental anomalies resulting from first pharyngeal arch dysplasia \u003csup\u003e1,2,3\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eChildren born with craniofacial deformity are susceptible to poor oral health \u003csup\u003e4\u003c/sup\u003e, often caused by oral structural deficiencies (OSD). The deformed oral structure may result in poor oral hygiene and disorderly oral microenvironment homeostasis, further inhibiting alveolar bone homeostasis, masseter dysfunction, delayed development of permanent teeth, and even the disruption of orthodontic and orthognathic treatment planning \u003csup\u003e5, 6, 7, 8\u003c/sup\u003e. In CFM patients, OSD includes abnormal maxilla and mandible, dental agenesis, delayed dental development, tooth size anomalies, abnormal tooth morphology, and enamel defects \u003csup\u003e9\u003c/sup\u003e. Meanwhile, obstructive sleep apnea syndrome (OSAS), one of the manifestations of CFM, and typical treatments of CFM, including mandibular distraction osteogenesis, orthodontics, or orthognathic surgery, have been associated with oral bacteria dysbiosis (OBD). However, the oral health status of patients with CFM remains to be fully elucidated.\u003c/p\u003e \u003cp\u003eOral microenvironment homeostasis comprises oral anatomy, microbiota, mucosal immune system, epithelial barrier, and other factors. All the elements interact with each other in a complex, diverse, and dynamic way. The oral microbiota, an essential part of oral homeostasis, is the second largest microbiota in humans and encompasses bacteria, fungi, viruses, and some low-abundance microbiota. Among these, bacteria constitute the main component of the oral microbiota because of their rich types and quantities. Various endogenous and exogenous factors, such as anatomical structure, oral hygiene habits, and OSAS, interact with the oral bacteria. Then, the interaction and balance of oral bacteria further affect oral health and even systemic diseases. Therefore, change in the abundance, structure, and function of oral bacteria is a vital evaluation indicator of oral health status \u003csup\u003e10, 11,12, 13\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e Multiple clinical manifestations and treatments have been shown to influence and interact with oral health in patients with CFM. Therefore, exploring the potential structural and functional changes in the oral microbiota of CFM patients is imperative to establish a basis for the inclusion of oral hygiene therapies in future treatment regimens for CFM. However, there is currently no comparative analysis of the oral flora between CFM patients and normal controls. Thus, the present study sought to compare the characteristics and changes in oral bacteria of CFM patients using 16S ribosomal RNA (rRNA) and evaluate potential corresponding functional molecular change using metagenomics. Combined multi-omics approaches were utilized to preliminarily characterize the oral microbiota of CFM and assess whether changes in the microbiota of CFM patients mediate functional changes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubject selection\u003c/h2\u003e \u003cp\u003eCFM patients were recruited from Maxillo-facial Surgery Center, XXXXXX, from November 2022 to April 2023. Healthy controls diagnosed with hypertrophic scarring were recruited from the Department of Scar \u0026amp; Wound Treatment of Plastic Surgery Hospital from October 2022 to April 2023.\u003c/p\u003e \u003cp\u003eInclusion criteria were as follows: (1) patients diagnosed with CFM and classified according to the Pruzansky-Kaban Classification and healthy controls diagnosed with hypertrophic scarring; (2) aged 6\u0026ndash;12 years old (the mixed dentition stage); (3) parents or guardians signed the informed consent form.\u003c/p\u003e \u003cp\u003eExclusion criteria were as follows: (1) no other systemic diseases reported except for CFM or hypertrophic scarring; (2) those who had not taken probiotics, fluoride, or antibiotics for at least 3 months; (3) those who had not received periodontal and/or OSAS treatment in the last 1 month; (4) particular dietary preference such as vegetarianism; (5) pet feeding; (6) those without discomfort or symptoms on the day of sampling; (7) females who were not in the physiological period.\u003c/p\u003e \u003cp\u003e All Subjects understood the nature of the experiment and provided informed consent before participating in the study. This study was approved by the ethical review board of the Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College (approval no. 2021\u0026thinsp;\u0026minus;\u0026thinsp;199) on Month 12, 2021. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSample Collection\u003c/h2\u003e \u003cp\u003eNon-stimulated saliva samples were collected from CFM patients and healthy controls. All participants were instructed not to brush their teeth for 24 hours and eat or drink for 1 hour before sampling. After rinsing their mouths with 20 ml of physiological saline for 1 minute, eight sterile cotton swabs were put into the participant\u0026rsquo;s mouth for 2 minutes to absorb saliva and then into the 5 ml sterilized Cryogenic Storage Tube. The tubes were frozen with liquid nitrogen and stored in the refrigerator at -80℃.\u003c/p\u003e \u003cp\u003eThe demographic data of each participant were recorded, including age, gender, and body mass index (BMI). All patients underwent sleep monitoring with respiratory polysomnography (RP), and the obstructive apnea-hypopnea index (OAHI) and blood oxygen saturation (SpO\u003csub\u003e2\u003c/sub\u003e) levels were recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e16S rRNA Diversity Sequencing\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eDNA extraction and amplification\u003c/h2\u003e \u003cp\u003eGenomic DNA was extracted from saliva samples using the MagPure Soil DNA KF Kit and DNA concentrations and integrity were measured using the NanoDrop 2000 (Thermo Fisher Scientific, USA). Polymerase chain reaction (PCR) amplification of bacterial 16S rRNA genes was performed using barcoded primers and Takara Ex Taq (Takara) using extracted DNA stored in a -20\u0026deg;C refrigerator. V3-V4 regions of 16S rRNA genes were amplified using primers 343F (5\u0026rsquo;-TACGGRAGGCAGCAG-3\u0026rsquo;) and 798R (5\u0026rsquo;-AGGGTATCTAATCCT-3\u0026rsquo;) \u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eLibrary Construction and Sequencing\u003c/h2\u003e \u003cp\u003ePCR products were purified with AMPure XP beads (Agencourt) and re-amplified for quality assessment using agarose gel electrophoresis. AMPure XP beads were used to purify the final amplicon, and the Qubit dsDNA Assay Kit (Thermo Fisher Scientific, USA) was used to measure the DNA concentration of samples for sequencing using an Illumina NovaSeq 6000 platform with 250 base pairs (bp) paired-end reads (Illumina Inc.; OE Biotech Company, Shanghai, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatic Analysis\u003c/h2\u003e \u003cp\u003eSequencing and data processing were performed by OE Biotech Co., Ltd. (Shanghai, China). Raw sequencing data were in the FASTQ format. Preprocessing was then carried out using Cutadapt software to detect and remove adapters from the paired-end reads. DADA2 \u003csup\u003e3\u003c/sup\u003e with QIIME2 \u003csup\u003e4\u003c/sup\u003e (2020.11) default parameters were used to filter low-quality reads, denoise, merge, detect, and cut off the chimera reads after trimming paired-end reads. The QIIME2 package was used to select the representative read of each amplicon sequence variant and output the abundance table. With default parameters, a q2-feature classifier was used to classify all representative reads against the Silva database (Version 138).\u003c/p\u003e \u003cp\u003eA MagPure Soil DNA KF Kit was used to isolate total DNA from the sample. An agarose gel electrophoresis and NanoDrop2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) were used to measure DNA concentration and integrity. DNA was fragmented using an S220 Focused-ultrasonicator (Covaris, USA) and cleansed using Agencourt AMPure XP beads (Beckman Coulter Co., USA). Subsequently, libraries were constructed using the TruSeq Nano DNA LT Sample Preparation Kit (Illumina, San Diego, CA, USA) following the manufacturer\u0026rsquo;s instructions. The Metagenome was sequenced and analyzed by OE Biotech Co., Ltd. (Shanghai, China).\u003c/p\u003e \u003cp\u003eMeanwhile,150 bp paired-end reads were generated from the libraries on an Illumina Novaseq 6000 platform. Sequences in the FastQ file were trimmed and filtered using Fastp (v 0.20.1) \u003csup\u003e15\u003c/sup\u003e, low-quality primary groups were filtered out, and reads containing N bases were removed. The host pollution was controlled by aligning the post-filtered pair-end reads against the human genome using bowtie2 (v 2.2.9) and discarding the aligned reads. MEGAHIT (v 1.1.2) was used for genome assembly after obtaining valid reads \u003csup\u003e16,17\u003c/sup\u003e. Gaps inside the scaffold were used to break the scaffold into new contigs (Scaftigs), and new Scaftigs with a length\u0026thinsp;\u0026gt;\u0026thinsp;500 bp were retained. Using Prodigal (v 2.6.3), open reading frames (ORFs) were predicted on assembled scaffolds and translated into amino acid sequences \u003csup\u003e18\u003c/sup\u003e. CDHIT (v 4.5.7) was used to construct non-redundant gene sets from all predicted genes. The clustering parameters had a 95% identity and 90% coverage. The longest gene represented each gene set. Then, clean reads of each sample were aligned against the non-redundant gene set (95% identity) using bowtie2 (v 2.2.9), and the abundant information of the gene in the corresponding gene set was analyzed. The species\u0026rsquo; taxonomy was determined using the Non Redundant Protein (NR) database, and gene abundance was used to calculate the abundance of the species. Abundance statistics were performed at Domain, Kingdom, Phylum, Class, Order, Family, Genus, and Species levels to construct abundance profiles on the corresponding taxonomy level. The amino acid sequence representing the gene set was compared and annotated using DIAMOND (v 0.9.7) with NR, Kyoto Encyclopaedia\u0026emsp;of\u0026emsp;Genes\u0026emsp;and\u0026emsp;Genomes (KEGG), eggNOG, SWISS-PROT, and GO databases at an e-value of 1e-5 \u003csup\u003e19,20,21\u003c/sup\u003e. Gene sets were compared with the CAZy database using hmmscan (v 3.1) to obtain the carbohydrate-active enzyme corresponding to the gene. The carbohydrate activity was calculated by summing the gene abundances corresponding to the carbohydrate-active enzyme abundance \u003csup\u003e22\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eNormally distributed data were compared using the independent samples t-test; otherwise, the Wilcoxon rank-sum test was adopted. In 16S rRNA sequencing, QIIME2 software was used to analyze alpha and beta diversity. The Shannon index was used to estimate microbial diversity in samples \u003csup\u003e23, 24\u003c/sup\u003e. Principal coordinate analysis (PCoA) was performed to estimate beta diversity using an unweighted Unifrac distance matrix. A T-test was used to analyze the differences in diversity and taxonomic composition between the two groups. Spearman correlation analysis was applied to measure the correlation between the clinical characteristics of patients and microbial structure. In metagenome sequencing, the taxonomic or functional abundance spectrum was analyzed using R software (version 3.2.0), and an equidistant matrix of PCoA was calculated and analyzed. The Student\u0026rsquo;s t-test was used to analyze significant differences between groups. Taxonomic and functional abundance spectra were compared using linear discriminant analysis effect size (LEfSe). All data were analyzed using R software. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Demographic and Clinical Characteristics\u003c/h2\u003e \u003cp\u003eForty-four participants were recruited, of whom 20 cases belonged to the CFM group (CFM) and 24 to the healthy control group (Ctrl). The baseline demographic and clinical characteristics of different groups are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. No significant difference was found between CFM and Ctrl groups in terms of age, gender, and BMI (P\u0026thinsp;=\u0026thinsp;0.446, 0.876, and 0.229, respectively). According to the Pruzansky-Kaban classification, 1, 6, 9, and 4 CFM patients were classified as Type I, Type IIa, Type IIb, and Type III, respectively. Sixteen patients were diagnosed with OSAS, accounting for 80% of all patients. The average OAHI was 2.8 and the average SpO2 was 74.2% (65.4\u0026ndash;83.0%).\u003c/p\u003e \u003cp\u003e16S rRNA gene sequencing of 44 samples yielded 3,518,300 raw reads. The average number of sequences per sample was 79,961. After preprocessing the sequencing data, 2,969,017 high-quality sequences were obtained, averaging 67,477 sequences per sample. Among the 44 samples, 2,789 amplicon sequence variants were detected. The sequences were categorized based on their taxonomic group using the Human Oral Microbiome Database (HOMD). There were 15 Phyla, 26 classes, 73 orders, 126 families, 247 genera, and 479 species in the saliva sample of 44 participants.\u003c/p\u003e \u003cp\u003eMeanwhile, metagenomics sequencing was further performed on samples from 6 patients and 6 healthy controls. The effective data size distribution of each sample was between 11.96 and 15.93 G, and the N50 statistical distribution of Contigs was between 454 and 938 bp. After removing redundancy, 1,499,952 ORFs were identified in the gene catalog (non-redundant gene set). Compared with KEGG, NR, and CAZy databases, the annotation rates of non-redundant genes were 94.15, 51.21, and 1.69%, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographic and clinical characteristics of two groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of Patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, male, n%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.1 (7.1\u0026ndash;9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.7 (6.8\u0026ndash;8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.446\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePruzansky-Kaban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIIa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIIb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOAHI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.2 (65.4\u0026ndash;83.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNormally distributed data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (standard deviations) and non-normally distributed data were expressed as median interquartile range. P\u0026lt;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eBMI: Body Mass Index; OHAI: obstructive apnea/hypopnea index; SpO\u003csub\u003e2\u003c/sub\u003e: oxygen saturation\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDiversity, Composition, and Comparison of the Salivary Microbiome\u003c/h2\u003e \u003cp\u003eAccording to the rarefaction curve, the plateauing stage had been reached (Supplementary Fig.\u0026nbsp;1), indicating that all samples were sequenced to a reasonable depth and the results reflected microbial information of saliva samples.\u003c/p\u003e \u003cp\u003eThe Shannon index differed significantly between the CFM group and the Ctrl group (P\u0026thinsp;=\u0026thinsp;0.024) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). PCoA was performed to assess the variation of salivary microbial community structure using the unweighted UniFrac distance, with axis 1 (PC1) explaining 9.56% of the variability and axis 2 (PC2) explaining 9.23%. Salivary microbial communities differed significantly between the CFM group and the Ctrl group (P\u0026thinsp;=\u0026thinsp;0.001), indicating significant differences in the phylogenetic structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe relative abundance of the top 10 phyla is summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC. Proteobacteria (36.46%), Firmicutes (31.34%), and Bacteroidota (20.07%) were the three most abundant phyla in the Ctrl group. Proteobacteria (31.82%), Bacteroidota (23.34%), Firmicutes (20.82%), Actinobacteriota (11.35%), and Fusobacteriota (10.34%) were the five most abundant phyla in the CFM group. Detailed statistics are presented in Supplementary Table\u0026nbsp;1. Actinobacteriota (Ctrl\u0026thinsp;=\u0026thinsp;0.04, CFM\u0026thinsp;=\u0026thinsp;0.11, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Campilobacterota (Ctrl\u0026thinsp;=\u0026thinsp;0.006, CFM\u0026thinsp;=\u0026thinsp;0.02, P\u0026thinsp;=\u0026thinsp;0.013); Firmicutes (Ctrl\u0026thinsp;=\u0026thinsp;0.31, CFM\u0026thinsp;=\u0026thinsp;0.21, P\u0026thinsp;=\u0026thinsp;0.012), and Desulfobacterota (Ctrl\u0026thinsp;=\u0026thinsp;0.0007, CFM\u0026thinsp;=\u0026thinsp;0.0002, P\u0026thinsp;=\u0026thinsp;0.002) differed significantly between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe top 15 most abundant taxa are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD. Streptococcus (24.20%),\u003c/p\u003e \u003cp\u003eHaemophilus (18.23%), and Neisseria (11.63%) were significantly enriched in the Ctrl group. Neisseria (18.07%) and Streptococcus (14.34%) were highly abundant in the CFM group. Detailed statistics are shown in Supplementary Table\u0026nbsp;2. The top 10 most abundant genera are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB. \u003cem\u003eCorynebacterium\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.01, CFM\u0026thinsp;=\u0026thinsp;0.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003eCapnocytophaga\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.03, CFM\u0026thinsp;=\u0026thinsp;0.07, P\u0026thinsp;=\u0026thinsp;0.002), \u003cem\u003eRothia\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.01, CFM\u0026thinsp;=\u0026thinsp;0.03, P\u0026thinsp;=\u0026thinsp;0.021), \u003cem\u003eCampylobacter\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.01, CFM\u0026thinsp;=\u0026thinsp;0.02, P\u0026thinsp;=\u0026thinsp;0.013), \u003cem\u003eActinomyces\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.02, CFM\u0026thinsp;=\u0026thinsp;0.04, P\u0026thinsp;=\u0026thinsp;0.022), and \u003cem\u003ePrevotella\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.05, CFM\u0026thinsp;=\u0026thinsp;0.09, P\u0026thinsp;=\u0026thinsp;0.048) were the most predominant genera in the CFM group. \u003cem\u003eHaemophilus\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.18, CFM\u0026thinsp;=\u0026thinsp;0.07, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003eGemella\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.03, CFM\u0026thinsp;=\u0026thinsp;0.01, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003eStreptococcus\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.24, CFM\u0026thinsp;=\u0026thinsp;0.14, P\u0026thinsp;=\u0026thinsp;0.008), and \u003cem\u003ePorphyromonas\u003c/em\u003e (Ctrl\u0026thinsp;=\u0026thinsp;0.06, CFM\u0026thinsp;=\u0026thinsp;0.03, P\u0026thinsp;=\u0026thinsp;0.04) were the most abundant genera in the Ctrl group.\u003c/p\u003e \u003cp\u003eBased on the relative abundance of community structure, the correlations between patient clinical phenotype and microbial community structure were determined using Spearman analysis. \u003cem\u003eNeisseria\u003c/em\u003e and \u003cem\u003ePorphyromonas\u003c/em\u003e were positively correlated with the Pruzansky-Kaban classification, with a Spearman\u0026rsquo;s rank correlation coefficient (rs) of 0.66 (P\u0026thinsp;=\u0026thinsp;0.0016) and 0.52 (P\u0026thinsp;=\u0026thinsp;0.019), respectively. \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003eKingella\u003c/em\u003e were negatively correlated with the Pruzansky-Kaban classification, with an rs of -0.57 (P\u0026thinsp;=\u0026thinsp;0.009) and \u0026minus;\u0026thinsp;0.45 (P\u0026thinsp;=\u0026thinsp;0.046), respectively. \u003cem\u003eCampylobacter\u003c/em\u003e, \u003cem\u003eLeptotrichia\u003c/em\u003e, and \u003cem\u003eKingella\u003c/em\u003e were positively correlated with SpO2, with an rs of 0.54 (P\u0026thinsp;=\u0026thinsp;0.014), 0.53 (P\u0026thinsp;=\u0026thinsp;0.03), and 0.48 (P\u0026thinsp;=\u0026thinsp;0.016), respectively. \u003cem\u003eStaphylococcus\u003c/em\u003e significantly negatively correlated with SpO2, with an rs of 0.46 (P\u0026thinsp;=\u0026thinsp;0.04). Meanwhile, no correlation was found between microbial community structure and BMI and OAHI (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eTo identify potential biomarkers, the LEfSe method was used to analyze differences in the composition of the microbial communities between the two groups. The cladogram of salivary microbial structure and dominant bacteria was generated based on a linear discriminant analysis (LDA) threshold of 3, which indicated the most significant differences between CFM and Ctrl groups. Neisseriaceae was the most predominant at the family level and \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eCapnocytophaga\u003c/em\u003e, \u003cem\u003eCorynebacterium\u003c/em\u003e, \u003cem\u003eLeptotrichia\u003c/em\u003e, \u003cem\u003eActinomyces\u003c/em\u003e, \u003cem\u003eFusobacterium\u003c/em\u003e, \u003cem\u003eCampylobacter\u003c/em\u003e, \u003cem\u003eRothia\u003c/em\u003e, and \u003cem\u003eKingella\u003c/em\u003e were the most predominant at the genus level in the CFM group. Gemellaceae was the most predominant at the family level and \u003cem\u003ePelomonas\u003c/em\u003e, \u003cem\u003eGemella\u003c/em\u003e, \u003cem\u003ePorphyromonas\u003c/em\u003e, and \u003cem\u003eStreptococcus\u003c/em\u003e were dominant at the genus level in the Ctrl group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-E).\u003c/p\u003e \u003cp\u003eAccording to the Pruzansky-Kaban classification, CFM patients were divided into Type I-IIA and Type IIB-III groups, patients with or without temporomandibular joint (TMJ) dysfunction. The difference in the salivary microbiome of both groups was compared to explore the relationship between the disease severity and microbial community structure. The top three genera with the highest average abundance were \u003cem\u003ePrevotella\u003c/em\u003e (0.16), \u003cem\u003eNeisseria\u003c/em\u003e (0.09), and \u003cem\u003eLeptotrichia\u003c/em\u003e (0.07) in Type I-IIA and \u003cem\u003eNeisseria\u003c/em\u003e (0.23), \u003cem\u003eHaemophilus\u003c/em\u003e (0.09), and \u003cem\u003ePrevotella\u003c/em\u003e (0.06) in Type IIB-III. The top 3 statistically significantly differential genera between the two groups included \u003cem\u003eFaecalibacterium\u003c/em\u003e (0.0001, 0.0006, P\u0026thinsp;=\u0026thinsp;0.001), \u003cem\u003eNeisseria\u003c/em\u003e (0.09, 0.23, P\u0026thinsp;=\u0026thinsp;0.004), and \u003cem\u003ePorphyromonas\u003c/em\u003e (0.01, 0.05, P\u0026thinsp;=\u0026thinsp;0.009) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF-G).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFunctional Comparison of the Salivary Microbiome Between CFM and Ctrl Groups\u003c/h2\u003e \u003cp\u003eThe distribution of gene numbers between the two groups is displayed in Fig. S2-A, which revealed a significant difference between CFM and Ctrl (P\u0026thinsp;=\u0026thinsp;0.016). Hierarchical clustering analysis was performed to evaluate the similarities and differences in gene abundances of all samples and the results showed that CFM and Ctrl groups had a high intra-group similarity (Fig. S2-B).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKEGG annotations of amino acid sequences obtained from the two groups are shown in Fig S2-C, with metabolism-associated genes accounting for the most significant proportion. Carbohydrate metabolism was annotated to 77,286 genes, making it the most functionally rich category, followed by amino acid metabolism, with 63,843 annotated genes, and Metabolism of cofactors and vitamins, Energy metabolism, Nucleotide metabolism, and Glycan biosynthesis and metabolism, with relatively abundant genes. Other metabolic pathways with relatively abundant genes included Genetic Information Processing, Environmental Information Processing, and Cellular Processes.\u003c/p\u003e \u003cp\u003eBased on the annotation of differentially-expressed KEGG ORTHOLOGY (KO) between CFM and Ctrl groups at level 3, the top 30 KO relative abundances were selected for clustering information based on the P-value to draw their functional heatmaps (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), revealing significant differences in functional abundance between the two groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThirty-four functional pathways differed significantly between the two groups, and the top 10 functional pathways with the highest abundance were selected to generate the boxplots (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Functional pathways with significant differences in the CFM group were Porphyrin and chlorophyll metabolism (0.013), Sulfur metabolism (0.003), Biotin metabolism (0.042), Histidine metabolism (0.040), Plant-pathogen interaction (0.019), Lysine degradation (0.005), Tryptophan metabolism (0.031), Salmonella infection (0.015), and Fluid shear stress and atherosclerosis (0.034). Biofilm formation-Escherichia coli (0.003) had a higher functional abundance and statistical significance in the Ctrl group. Functional biomarkers with significant differences between groups based on an LDA score of 2 are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eC.\u003c/p\u003e \u003cp\u003eA correlation analysis was conducted to determine the relationship between high abundance bacteria and functions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). \u003cem\u003eLeptotrichia\u003c/em\u003e was significantly negatively correlated with Histidine metabolism (rs = -0.94, P\u0026thinsp;=\u0026thinsp;0.017) and Tryptophan metabolism (rs = -0.94, P\u0026thinsp;=\u0026thinsp;0.017). \u003cem\u003eNeisseria\u003c/em\u003e was positively correlated with Tryptophan metabolism (rs\u0026thinsp;=\u0026thinsp;0.71, P\u0026thinsp;=\u0026thinsp;0.136), Lysine degradation (rs\u0026thinsp;=\u0026thinsp;0.77, P\u0026thinsp;=\u0026thinsp;0.103), and Histidine metabolism (rs\u0026thinsp;=\u0026thinsp;0.49, P\u0026thinsp;=\u0026thinsp;0.356) and negatively correlated with Sulfur metabolism (rs = -0.66, P\u0026thinsp;=\u0026thinsp;0.175).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCFM is the second most common craniofacial malformation after cleft lip and palate, with an incidence rate ranging from 1 in 3,500 to 1 in 5,600 live births \u003csup\u003e25, 26\u003c/sup\u003e. Based on CFM characteristics, including abnormal oral anatomical structure, underdeveloped mandible, oblique occlusal plane, and frequent co-occurrence with OSAS \u003csup\u003e27, 28\u003c/sup\u003e, we hypothesized that these patients are at a higher risk of oral microbial dysbiosis (OMD). According to previous literature, OMD is associated with alveolar bone resorption, tooth loosening \u003csup\u003e29,30\u003c/sup\u003e, chewing dysfunction, and aggravating occlusal plane tilt and can affect long-term orthodontic or orthognathic treatment, all of which may affect the treatment and improvement of CFM patients \u003csup\u003e31,32\u003c/sup\u003e. However, there are no reports on the distribution characteristics of the oral microbiota in CFM patients. Therefore, the present study employed 16S rRNA sequencing to compare and investigate the structural features of the oral microbiota in CFM patients and healthy controls and identified numerous bacterial taxa with statistical differences. Furthermore, metagenomic sequencing identified functional abundance and differences in the oral microbiome in CFM samples. These data allowed a comprehensive analysis of bacterial diversity in CFM samples.\u003c/p\u003e \u003cp\u003eThe standard oral microbiota protects against potential pathogens by occupying distinct ecological niches without causing harm \u003csup\u003e33\u003c/sup\u003e. A disruption in microbial homeostasis leads to the transformation of the original microbial community structure into a dysbiotic pathogenic state, decreasing pH in the oral cavity. Consequently, the acidic environment exacerbates the proliferation of pathogenic bacteria, leading to inflammation and tissue damage \u003csup\u003e34\u003c/sup\u003e. The observed pathogenicity is not only caused by individual bacterial species but also by alterations in community structure that are closely linked to various systemic and oral diseases. Some systemic diseases related to microbiota dysbiosis include osteoporosis, cancer, cardiovascular diseases, gastrointestinal diseases, and diabetes \u003csup\u003e35,36,37, 38\u003c/sup\u003e. For oral diseases, an alteration in microbial composition results in elevated levels of pathogenic bacteria, thereby worsening immune-mediated inflammatory responses. Moreover, this leads to elevated levels of specific cytokines and inflammatory mediators, which contribute to the degradation of alveolar bone and periodontal tissues, resulting in alveolar bone resorption, ultimately impacting masticatory function and aesthetic appearance. Microbiota dysbiosis in the oral cavity can result in dental caries, pulpitis, periodontitis, and head and neck tumors \u003csup\u003e39, 40,41, 42, 43,38\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIndividuals with craniofacial disorders at birth, which impact the growth and function of teeth and jaws, are frequently at a heightened risk of experiencing poor oral health conditions \u003csup\u003e44\u003c/sup\u003e. This heightened risk can be attributed to challenges in effectively cleaning structurally abnormal oral cavities and the continuous exposure of dental enamel and gum tissue to the oral environment due to deformities. Consequently, these factors may facilitate the formation and accumulation of plaque, ultimately increasing the vulnerability to oral diseases.\u003c/p\u003e \u003cp\u003eThe clinical manifestations and treatment methods of CFM may have a potential mutual influence on OMD. The clinical manifestations include an underdeveloped mandible and an inclined occlusal plane. Additionally, patients with CFM exhibit a higher incidence of poorly developed teeth (ranging from 6.7\u0026ndash;33.3%) and delayed tooth eruption (ranging from 20.5\u0026ndash;54.3%) compared with normal individuals, whose respective incidence rates are 4.5\u0026ndash;13.3% and 3.4\u0026ndash;4.3%. Variations in tooth morphology and increased interdental spacing are frequently in CFM \u003csup\u003e45,46,28\u003c/sup\u003e. The above-mentioned anatomical abnormalities have been recognized as potential factors contributing to OMD and demonstrate interconnected relationships \u003csup\u003e47\u003c/sup\u003e. Furthermore, a previous study found that the prevalence of OSAS among patients with CFM ranged from 7\u0026ndash;67% \u003csup\u003e48\u003c/sup\u003e. Other studies reported notable alterations in the composition and metabolomic features of the oral microbiota in pediatric patients with OSAS \u003csup\u003e49,50,51\u003c/sup\u003e. This phenomenon was attributed to recurrent episodes of upper airway collapse, reduced nasal airflow, snoring, and mouth breathing during sleep \u003csup\u003e52\u003c/sup\u003e, which resulted in compromised oral self-cleaning capabilities, salivary gland dysfunction \u003csup\u003e53, 54,55,56\u003c/sup\u003e, reduced blood oxygen content, and alterations in airway humidity, temperature, and pH due to diminished nasal airflow \u003csup\u003e57\u003c/sup\u003e. Additionally, the oral cavity of patients with OSAS was directly exposed to dust, particles, and various airborne microorganisms, ultimately disrupting the microbial balance, leading to increased secretion of pro-inflammatory cytokines, mediating respiratory inflammation and edema, and inducing or exacerbating the occurrence of OSAS \u003csup\u003e58\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition to clinical manifestations, various factors during the treatment process of CFM may interact with OMD. Surgery is the most widely accepted treatment for characteristic deformity in CFM to enhance both aesthetic and functional outcomes, mainly through mandibular elongation and dental functional improvement \u003csup\u003e59\u003c/sup\u003e. The most significant surgeries include mandibular distraction osteogenesis (MDO) and orthodontics or orthognathic surgery. MDO is usually performed during the mixed dentition period, during which children have more significant potential for skeletal growth. MDO helps lengthen the affected mandible, create the space of an open bite, induce the descent of the maxillary occlusal plane, and improve the occlusal plane and facial symmetry of the patient \u003csup\u003e60, 61\u003c/sup\u003e. During the MDO process, the active growth of the alveolar bone on the affected side is a significant determinant in the downward movement of the maxillary occlusal plane, thereby significantly influencing the maintenance of occlusal plane stability \u003csup\u003e62, 63, 64, 65, 66\u003c/sup\u003e. Orthodontics or orthognathic surgery is usually performed as a supplementary treatment for patients with poor occlusion and appearance in the permanent dentition stage \u003csup\u003e67\u003c/sup\u003e. At this stage of treatment, oral anatomical factors, particularly the alveolar bone, are critical in dental implantation, orthodontic procedures, periodontal therapy, and oral functional restoration \u003csup\u003e68, 69, 70,71, 72,73\u003c/sup\u003e. In summary, many factors may interact with OMD in patients with CFM. However, whether CFM is associated with OMD remains elusive, An association between the two is necessary to optimize the current treatment sequence. The current study compared the oral microbiota structure and function between CFM patients and normal individuals and confirmed the existence of OMD in patients with CFM.\u003c/p\u003e \u003cp\u003eRegarding the selection of samples and sampling time points, previous studies have shown that saliva is the most suitable sample for analyzing the composition of oral biofilm microbiota, with minimal harm to the host \u003csup\u003e74,74,75\u003c/sup\u003e. The oral microbiota in young children exhibits notable alterations in composition and diversity, ultimately stabilizing around the age of 2 \u003csup\u003e76\u003c/sup\u003e. Therefore, children in the mixed dentition period were selected as the study subjects, and saliva was used as the study sample.\u003c/p\u003e \u003cp\u003eThe Shannon dilution curve demonstrated the rationality of the amount of sequenced data, excellent sequencing quality, and reliable research results. The CFM group exhibited more extraordinary species richness and evenness than the Ctrl group. Beta diversity analysis indicated significant differences in microbial community structure between the two groups; between-group differences were more significant than within-group differences. The phyla with statistical differences and high relative abundance were \u003cem\u003eActinobacteriota\u003c/em\u003e and \u003cem\u003eFirmicutes\u003c/em\u003e in the CFM and Ctrl groups, respectively. These are resident bacteria in the oral cavity, with some genera classified as opportunistic pathogenic bacteria \u003csup\u003e77,78\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe dominant differential species in the CFM group included \u003cem\u003eCorynebacterium\u003c/em\u003e, \u003cem\u003eCapnocytophaga\u003c/em\u003e, \u003cem\u003eRothia\u003c/em\u003e, \u003cem\u003eActinomyces\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eCampylobacter\u003c/em\u003e, \u003cem\u003eLeptotrichia\u003c/em\u003e, and \u003cem\u003eFusobacterium\u003c/em\u003e, which are resident microbial communities in the oral cavity and play crucial roles in maintaining microecological balance. Certain species may exhibit pathogenicity when their abundance increase or the host\u0026rsquo;s immune system is compromised.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCapnocytophaga\u003c/em\u003e, a genus of facultative anaerobic bacteria, includes certain species identified as opportunistic pathogens in the human subgingival sulcus and dental plaque \u003csup\u003e79,80\u003c/sup\u003e. Previous studies reported a correlation between the increased abundance of \u003cem\u003eCapnocytophaga\u003c/em\u003e and prepubertal periodontitis \u003csup\u003e81,82\u003c/sup\u003e, gingivitis \u003csup\u003e83\u003c/sup\u003e, and oral cancer \u003csup\u003e84, 85\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCorynebacterium\u003c/em\u003e is primarily aerobic and typically non-pathogenic but sometimes opportunistically invades tissues (through wounds) or leads to infections such as granulomatous lymphadenitis, pneumonia, pharyngitis, skin infections, and endocarditis in immunocompromised hosts \u003csup\u003e86, 87, 88\u003c/sup\u003e. An increased abundance of \u003cem\u003eCorynebacterium\u003c/em\u003e is also linked to a reduced likelihood of developing head and neck squamous cell carcinoma, suggesting potential implications for cancer prevention strategies \u003csup\u003e89\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eActinomyces\u003c/em\u003e are facultative anaerobes that exhibit optimal growth in anaerobic environments, serve as opportunistic pathogens in the oral cavity, and are particularly prevalent in the gingiva. The metabolic activities of \u003cem\u003eActinomyces\u003c/em\u003e, contributing significantly to acid-base equilibrium, include metabolizing sugar into acid and amino acids into acid and ammonia. Additionally, \u003cem\u003eActinomyces\u003c/em\u003e are implicated in the generation of hydrogen sulfide and methyl mercaptan, which have been linked to oral malodor, dental caries, and periodontal disease \u003csup\u003e90, 91\u003c/sup\u003e. Besides, excessive abundance of \u003cem\u003eActinomyces\u003c/em\u003e can lead to various complications, such as dental surgery infection, oral abscess \u003csup\u003e92\u003c/sup\u003e, and oral tumors \u003csup\u003e93\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eFusobacterium\u003c/em\u003e, a genus of obligate anaerobic bacteria, has been associated with various human diseases, including periodontal disease, oral, head, and neck infections, colorectal cancer, and localized skin ulcers \u003csup\u003e94, 95, 96, 97\u003c/sup\u003e. Identical to \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003ePorphyromonas\u003c/em\u003e, \u003cem\u003eFusobacterium\u003c/em\u003e can degrade nitrogenous compounds into short-chain fatty acids, sulfide compounds, and ammonia, which are cytotoxic and can induce tissue inflammation by modulating immune responses \u003csup\u003e98\u003c/sup\u003e and even promote cell apoptosis \u003csup\u003e99\u003c/sup\u003e. These processes all contribute to the initiation and progression of periodontal diseases. \u003cem\u003ePrevotella\u003c/em\u003e can grow under anaerobic conditions and cause acidification. An increased abundance of \u003cem\u003ePrevotella\u003c/em\u003e is related to the development of periodontal disease, abscesses, and oral tumors \u003csup\u003e100, 101,102\u003c/sup\u003e. Our data showed that \u003cem\u003ePorphyromonas\u003c/em\u003e was highly abundant in the Ctrl group and Type IIB-III patients.\u003c/p\u003e \u003cp\u003e \u003cem\u003eLeptotrichia\u003c/em\u003e is an anaerobic Gram-negative bacteria that forms part of the bacterial biofilm of the oral cavity. Its increased abundance has been reported to be associated with inflammatory bowel disease, cancer, and adenomatous polyps \u003csup\u003e103,104\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCampylobacter\u003c/em\u003e grows best in microaerobic environments and can cause gastrointestinal infections \u003csup\u003e105\u003c/sup\u003e. Certain species of \u003cem\u003eRothia\u003c/em\u003e, a Gram-positive bacterium, are opportunistic pathogens in the oral cavity and pharynx that sometimes cause septicemia, endocarditis, and other severe infections \u003csup\u003e106, 107, 108\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrior research has demonstrated that elevated abundance of \u003cem\u003eStreptococcus mutans\u003c/em\u003e and \u003cem\u003ePorphyromonas gingivalis\u003c/em\u003e is implicated in periodontal disease, dental caries, and certain systemic illnesses. \u003cem\u003eS\u003c/em\u003e. \u003cem\u003emutans\u003c/em\u003e is a Gram-positive and anaerobic acid-producing microorganism that can synthesize extracellular polymers of glucan. It also produces acid and thrives in acidic environments, ultimately causing tooth decay and the dissolution of hydroxyapatite in the enamel and dentin. \u003cem\u003eP\u003c/em\u003e. \u003cem\u003egingivalis\u003c/em\u003e can ferment sugar and produce acid, which facilitates microbial adhesion to tooth surfaces and enamel demineralization \u003csup\u003e109,110,111,112,113\u003c/sup\u003e. Furthermore, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003egingivalis\u003c/em\u003e and \u003cem\u003eS\u003c/em\u003e. \u003cem\u003emutans\u003c/em\u003e have been sporadically detected in the saliva of individuals with good oral health, suggesting that they may also form part of the resident oral flora. The present study found that the average abundance of \u003cem\u003eS\u003c/em\u003e. \u003cem\u003emutans\u003c/em\u003e in CFM and Ctrl groups was 0.002 and 0.0002, respectively, with no statistical significance. The average abundance of \u003cem\u003eP\u003c/em\u003e. \u003cem\u003egingivalis\u003c/em\u003e was higher in the Ctrl group than in the CFM group, with no statistical significance.\u003c/p\u003e \u003cp\u003eAlterations in in oral bacterial composition have been demonstrated in patients with OSAS and obesity \u003csup\u003e114, 115\u003c/sup\u003e. To determine whether OBD in CFM patients is mainly affected by OSAS, we performed a Spearman correlation analysis to ensure the relationship between CFM Pruzansky-Kaban type, OAHI, SpO2, BMI, and oral microbial structure\u003csup\u003e116\u003c/sup\u003e. The results showed that the relative abundance of \u003cem\u003eNeisseria\u003c/em\u003e and \u003cem\u003ePorphyromonas\u003c/em\u003e increased with the severity of CFM deformity. Excessively high levels of \u003cem\u003eNeisseria\u003c/em\u003e may lead to abnormal activation of the immune system causing cellular inflammation; the inflammatory state of the oral cavity further promotes the colonization of \u003cem\u003eNeisseria\u003c/em\u003e\u003csup\u003e117,118\u003c/sup\u003e. \u003cem\u003ePorphyromonas\u003c/em\u003e is a strictly anaerobic Gram-negative rod bacteria that has been shown to be a cause of periodontitis and pulpitis. In this study, the abundance of \u003cem\u003eStaphylococcus\u003c/em\u003e increased with the decrease of SpO2, suggesting that it is a facultative anaerobic organism. Partial species such as \u003cem\u003eS. aureus\u003c/em\u003e and \u003cem\u003eS. epidermidis\u003c/em\u003e are opportunistic pathogens resident in the oral cavity and known to cause oral mucositis and gingivitis. In addition, there was no relevance between OAHI, BMI, and bacteria structure. Collectively, our correlation analysis results and those of previous studies suggest a decrease in the diversity of the oral microbiota in individuals with moderate to severe OSAS\u003csup\u003e119\u003c/sup\u003e. In contrast, our study found a significant increase in the richness and evenness of the oral microbiota in patients with CFM, suggesting a potential link between oral microbiome diversity and CFM. The relationship between CFM severity and specific genera and corresponding species needs to be further studied.\u003c/p\u003e \u003cp\u003eThere were on significant differences between the CFM and Ctrl groups in Cellular Processes, Environmental Information Processing, Genetic Information Processing, Human Diseases, Metabolism, and Organismal Systems. At level 3, pathway activity of Porphyrin and chlorophyll metabolism, Sulfur metabolism, Biotin metabolism, Histidine metabolism, Plant\u0026thinsp;\u0026minus;\u0026thinsp;pathogen interaction, Lysine degradation, Tryptophan metabolism, Salmonella infection, Fluid shear stress, and atherosclerosis was significantly increased in the CFM group than in the Ctrl group.\u003c/p\u003e \u003cp\u003eTryptophan, an essential amino acid absorbed through the intestinal epithelium, is utilized for protein synthesis, and approximately 10\u0026ndash;20% of it is further metabolized by bacteria \u003csup\u003e120, 121, 122\u003c/sup\u003e. The metabolism of free tryptophan in the oral cavity involves three pathways: (1) Indole pathway: This pathway involves the direct conversion of tryptophan into indole and its derivatives by periodontal plaque microorganisms, including \u003cem\u003eFusobacterium, Prevotella\u003c/em\u003e, and \u003cem\u003ePorphyromonas\u003c/em\u003e. These metabolites form part of the developmental mechanisms of periodontitis and halitosis\u003csup\u003e123\u003c/sup\u003e. (2) 5-Hydroxytryptamine (5-HT) pathway: Tryptophan is converted into 5-hydroxytryptophan (5-HTP) via the catalysis of tryptophan hydroxylase (TPH), and then metabolized to generate 5-hydroxytryptamine (5-HT) \u003csup\u003e124\u003c/sup\u003e. 5-HT is a key neurotransmitter involved in regulating central nervous system functions. Moreover, 5-HT interacts with receptors on various immune cells, such as T cells, macrophages, and dendritic cells, triggering inflammatory and immune regulatory responses\u003csup\u003e125,126\u003c/sup\u003e. (3) Kynurenine metabolic pathway: More than 95% of free tryptophan is metabolized via this pathway. This pathway is driven by indoleamine 2,3-dioxygenase 1 (IDO) and tryptophan 2,3-dioxygenase (TDO), and leads to the production of kynurenine (Kyn) and the associated downstream products such as quinolinic acid, niacin, nicotinamide adenine dinucleotide, and kynurenic acid \u003csup\u003e127\u003c/sup\u003e. IDO, a key rate-limiting enzyme involved in this pathway, contributes to the formation of inflammation and immunosuppression. The activation of IDO can enhance the establishment of an immunosuppressive microenvironment, thereby inhibiting the progression of the anti-tumor immune response. IDO expression is significantly elevated in melanoma, colon cancer, and lung cancer tissues, and this high expression is inversely related to tumor prognosis\u003csup\u003e128, 129,130\u003c/sup\u003e. Furthermore, several tryptophan metabolites may also modulate diverse biological processes \u003csup\u003e131\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the study by Balci et al. (2021), we discovered that patients with stage III grade B periodontitis have elevated levels of tryptophan in their saliva compared to healthy controls. Moreover, the level of tryptophan can be used for probing bleeding and serve as a plaque index\u003csup\u003e132\u003c/sup\u003e. Furthermore, 5-HT, another metabolite of tryptophan, and its precursor 5-HTP, regulate bone metabolism \u003csup\u003e133,134\u003c/sup\u003e. Evidence from animal studies have demonstrated that 5-HTP can promote osteoclastogenesis and aggravate alveolar bone resorption \u003csup\u003e135\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSulfur metabolism has been implicated in the regulation of energy metabolism in humans. Sulfur, one of the most prevalent bio-elements, is involved in diverse processes including cell signaling, free radical detoxification, enhancement of structural support, and energy production\u003csup\u003e136, 137, 138, 139, 140\u003c/sup\u003e. The organic and inorganic sulfur levels in the body are primarily influenced by the consumption of amino acids such as methionine, B-complex vitamins, and trace elements \u003csup\u003e141,142\u003c/sup\u003e. Sulfur-metabolizing bacteria have been shown to modulate sulfur metabolism. Representative ones include \u003cem\u003eStreptococcus, Prevotella\u003c/em\u003e, and \u003cem\u003eFusobacterium\u003c/em\u003e \u003csup\u003e143,144,145,146,147,148,149\u003c/sup\u003e. Hydrogen sulfide (H\u003csub\u003e2\u003c/sub\u003eS), sulfite, thiosulfate, and sulfate are the main sulfur metabolism products. As an essential product, physiological levels of H\u003csub\u003e2\u003c/sub\u003eS induce anti-inflammatory effects, inhibit invasive pathogens, and help alleviate tissue damage\u003csup\u003e150,151,152,153,154\u003c/sup\u003e. In contrast, excessively high concentrations of H\u003csub\u003e2\u003c/sub\u003eS cause toxicity in animals are, mainly in the cardiovascular system, the central nervous system, and the energy metabolism process. Specifically, in the energy metabolism process, H\u003csub\u003e2\u003c/sub\u003eS inhibits cytochrome c oxidase (COX) activity within the mitochondrial electron transport chain (ETC)\u003csup\u003e155\u003c/sup\u003e. This triggers DNA damage, disrupts the intestinal mucus bilayer, promotes inflammation, and contributes to colorectal cancer \u003csup\u003e156\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBiotin, also known as vitamin B7, vitamin H, or coenzyme R, plays a crucial role in metabolism by acting as a cofactor for various enzymes. The levels of biotin are influenced bydietary intake and bacterial activity. It has been suggested that deficiencies in the bacterial production of biotin affected the microbial community dynamics, host metabolic processes, and inflammatory responses\u003csup\u003e157, 158,159\u003c/sup\u003e. Most \u003cem\u003eBacteroidetes\u003c/em\u003e and \u003cem\u003eProteobacteria phyla\u003c/em\u003e organisms are responsible for biotin biosynthesis \u003csup\u003e160,161\u003c/sup\u003e. This essential micronutrient, biotin, serves as a cofactor for a range of enzymes, including biotin-dependent carboxylases, decarboxylases, and transcarboxylases \u003csup\u003e162\u003c/sup\u003e. For instance, it participates in various metabolic processes, including fatty acid synthesis, amino acid metabolism, and gluconeogenesis, by forming covalent bonds with lysine residues \u003csup\u003e163, 164\u003c/sup\u003e. Biotin exerts anti-inflammatory effects by inhibiting NF-κB activation, and its deficiency can lead to inflammation by stimulating the secretion of pro-inflammatory cytokines \u003csup\u003e165, 166\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the human digestive tract, histidine (His), an essential amino acid, plays a vital role for various gut bacteria. These bacteria break down histidine and use it as a nutrient source. This breakdown process produces several byproducts, including histamine, uric acid, glutamate, and imidazole propionate (IMP) \u003csup\u003e167,168\u003c/sup\u003e. Previous research has demonstrated that His and its metabolites exert diverse physiological effects on the human body. Increased levels of His have been associated with the inhibition of inflammation and oxidative stress. Overexpression of His decreases taste and olfactory sensitivity, ellicits symptoms such as headaches, weakness, drowsiness, nausea, and cognitive impairment \u003csup\u003e169\u003c/sup\u003e. Moreover, His and His-containing dipeptides (HIS-cd) were linked to the occurrence of inflammatory bowel diseases and ocular disorders \u003csup\u003e170,171, 172, 173\u003c/sup\u003e. Histamine, a significant immune modulator, affects the hypersensitivity reactions and chronic inflammatory processes \u003csup\u003e174,175\u003c/sup\u003e, as well as intestinal diseases, anxiety, and immune responses induced by dysbiosis of the gut microbiota \u003csup\u003e176,177\u003c/sup\u003e. Research in animals suggests that glutamate might help heal damage in the intestinal barrier by regulating the release of corticotropin-releasing factor (CRF) \u003csup\u003e178\u003c/sup\u003e. Excessive IMP damages the gut barrier and alters the levels of inflammatory cytokines \u003csup\u003e179,180\u003c/sup\u003e, disrupts insulin signaling via the mammalian target of rapamycin complex 1 (mTORC1) \u003csup\u003e168\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLysine is an essential amino acid which is degradated via two distinct pathways. The primary pathway involves the formation of saccharopine via ε-deamination within liver mitochondria, leading to the formation of acetyl-CoA\u003csup\u003e181, 182\u003c/sup\u003e. Another pathway entails α-deamination or transamination to produce pipecolic acid (PA). \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e, which is increased in CFM, has been demonstrated to ferment lysine \u003csup\u003e183\u003c/sup\u003e. Intestinal bacteria normally produce very low amounts of precursor molecules for protein-bound uremic toxins (PBUTs) like indole, para-cresol, and phenol. On the other hand, lysine acts as a diuretic, helping to flush out toxins from the body. Therefore, the marked elevation in lysine degradation hinders the effective removal of toxins\u003csup\u003e184, 185\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this research, the saliva microbiome of patients with CFM was compared with that from controls by 16S rRNA and metagenomics sequencing. The results revealed significant differences in the diversity, composition, and functional profiles of oral microbial communities between CFM patients and controls in the mixed dentition stage. The increased abundance of bacterial genera in CFM patients primarily consists of opportunistic pathogens in the oral cavity. Previous research has linked the abnormal growth of these bacteria to various oral diseases, including halitosis, dental caries, periodontitis, pulpitis, oral infections, periodontal abscesses, and oral tumors. Furthermore, specific genera have been linked to occurrence of systemic diseases, including gastrointestinal infections, gastrointestinal tumors, pneumonia, pharyngitis, skin infections, sepsis, and endocarditis. Notably, \u003cem\u003eNeisseria\u003c/em\u003e and \u003cem\u003ePorphyromonas\u003c/em\u003e, were positively correlated with the severity of CFM, could stimulate cellular inflammation especially when their abundance was high, ultimately enhancing the development of oral inflammation. Pathogenic bacteria such as \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003eS. mutans\u003c/em\u003e were enriched in the CFM group. In contrast, \u003cem\u003eP. gingivalis\u003c/em\u003e, a pathogenic bacteria, displayed higher abundance in the Ctrl. group, probably due to failure to exclude individuals with oral diseases in the Ctrl group. Several functional pathways were upregulated in patients with CFM compared to controls, particularly those related to the metabolism of amino acids and biotin. Notably, tryptophan metabolism, which significantly affects oral health, was also upregulated in the CFM group. Furthermore, pathways such as sulfur metabolism, biotin metabolism, and histidine metabolism were upregulated, which may increase the risk of various diseases.\u003c/p\u003e \u003cp\u003eThis study has some limitations that should be discussed. The enrolled sample size was small primarily due to the rarity of CFM in craniofacial disease, with an incidence rate ranging from 1 in 3,500 to 1 in 5,600. In addition, variables such as dietary habits and geographical location were unaccounted for due to the small sample size, potentially limiting the generalizability of the study findings to other regions or ethnic groups. Moreover, since the 16S rRNA sequencing used in this study accurately detects bacteria at the genus level, species-level oral bacteria were not further discussed. Subsequent research should investigate the potential effects and mechanisms of the identified microbial biomarkers and to develop appropriate treatment strategies. Future investigations should also incorporate intervention strategies or explore metabolites to improve the efficacy.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCFMs significantly impact facial structure and function. Due to the complexity of these conditions, patients with CFM benefit most from a multidisciplinary treatment approach. This comprehensive care, involving a team of specialists, aims to restore both facial appearance and function. By analyzing the clinical manifestations and treatment strategies that may be related to OMD in CFM, we found that several genera were significantly increased, including \u003cem\u003eCorynebacterium, Capnocytophaga, Rothia, Actinomyces, Prevotella, Campylobacter, Leptotrichia\u003c/em\u003e, and \u003cem\u003eFusobacterium\u003c/em\u003e in CFM patients. \u003cem\u003eNeisseria\u003c/em\u003e and \u003cem\u003ePorphyromona\u003c/em\u003e were positively correlated with the severity of CFM, whereas pathways that were upregulated predominantly included Tryptophan metabolism, Sulfur metabolism, Biotin metabolism, Histidine metabolism, and Lysine degradation. \u003cem\u003eNesseria\u003c/em\u003e promotes Tryptophan metabolism and Lysine degradation, while \u003cem\u003eLeptotrichia\u003c/em\u003e decreases Histidine metabolism and Tryptophan metabolism. This study identified the key bacterial genera and functional changes associated with CFM. Furthermore, researchers should address the dysbiosis of oral microbiota in CFM patients to mitigate the persistence of pathogenic bacteria and their impact on oral health and long-term treatment outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the patients diagnosed with CFM and control group volunteers who participated in our study. They also thank Ouyi Biotechnology Company Limited for its technical services and valuable suggestions for bioinformatics analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethical review board of the Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College (approval no. 2021-199) on Month 12, 2021. All participants voluntarily consented to participate in the study, providing informed consent. Their decision did not impact the treatment protocol.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRaw data:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets supporting the conclusions of this article are available in the Bioproject database repository.\u003c/p\u003e\n\u003cp\u003e[unique persistent identifier and hyperlink to datasets of macrogenomic sequencing in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1118211\u003cu\u003e].\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e[unique persistent identifier and hyperlink to datasets of 16s rRNA sequencing in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1118189\u003cu\u003e].\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eElsten EECM, Caron CJJM, Dunaway DJ, Padwa BL, Forrest C, Koudstaal MJ. Dental anomalies in craniofacial microsomia: A systematic review. \u003cem\u003eOrthod Craniofacial Res\u003c/em\u003e. 2020;23(1):16-26. doi:10.1111/ocr.12351\u003c/li\u003e\n\u003cli\u003eMaruko E, Hayes C, Evans CA, Padwa B, Mulliken JB. Hypodontia in hemifacial microsomia. \u003cem\u003eCleft Palate Craniofac J\u003c/em\u003e. 2001;38(1):15-19.\u003c/li\u003e\n\u003cli\u003eOngkosuwito EM, De Gijt P, Wattel E, Carels CEL, Kuijpers-Jagtman AM. Dental Development in Hemifacial Microsomia. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2010;89(12):1368-1372. doi:10.1177/0022034510378425\u003c/li\u003e\n\u003cli\u003eCheng LL, Moor SL, Ho CTC. Predisposing Factors to Dental Caries in Children with Cleft Lip and Palate: A Review and Strategies for Early Prevention. \u003cem\u003eThe Cleft Palate-Craniofacial Journal\u003c/em\u003e. 2007;44(1):67-72. doi:10.1597/05-112\u003c/li\u003e\n\u003cli\u003eMeaney S, Anweigi L, Ziada H, Allen F. The impact of hypodontia: a qualitative study on the experiences of patients. \u003cem\u003eEur J Orthod\u003c/em\u003e. 2012;34(5):547-552.\u003c/li\u003e\n\u003cli\u003eRakhshan V. Congenitally missing teeth (hypodontia): A review of the literature concerning the etiology, prevalence, risk factors, patterns and treatment. \u003cem\u003eDent Res J (Isfahan)\u003c/em\u003e. 2015;12(1). https://pubmed.ncbi.nlm.nih.gov/25709668\u003c/li\u003e\n\u003cli\u003ePark MK, Shin MK, Kim SO, et al. Prevalence of delayed tooth development and its relation to tooth agenesis in Korean children. \u003cem\u003eArch Oral Biol\u003c/em\u003e. 2017;73:243-247. doi:10.1016/j.archoralbio.2016.10.024\u003c/li\u003e\n\u003cli\u003eBadrov J, Lauc T, Naka\u0026scaron; E, Galić I. Dental Age and Tooth Development in Orthodontic Patients with Agenesis of Permanent Teeth. \u003cem\u003eBiomed Res Int\u003c/em\u003e. 2017;2017:8683970. doi:10.1155/2017/8683970\u003c/li\u003e\n\u003cli\u003eElsten EECM, Caron CJJM, Dunaway DJ, Padwa BL, Forrest C, Koudstaal MJ. Dental anomalies in craniofacial microsomia: A systematic review. \u003cem\u003eOrthod Craniofac Res\u003c/em\u003e. 2020;23(1):16-26. doi:10.1111/ocr.12351\u003c/li\u003e\n\u003cli\u003eMark Welch JL, Ram\u0026iacute;rez-Puebla ST, Borisy GG. Oral Microbiome Geography: Micron-Scale Habitat and Niche. \u003cem\u003eCell Host \u0026amp; Microbe\u003c/em\u003e. 2020;28(2):160-168. doi:10.1016/j.chom.2020.07.009\u003c/li\u003e\n\u003cli\u003eZhang Y, Wang X, Li H, Ni C, Du Z, Yan F. Human oral microbiota and its modulation for oral health. \u003cem\u003eBiomed Pharmacother\u003c/em\u003e. 2018;99:883-893. doi:10.1016/j.biopha.2018.01.146\u003c/li\u003e\n\u003cli\u003eLamont RJ, Koo H, Hajishengallis G. The oral microbiota: dynamic communities and host interactions. \u003cem\u003eNat Rev Microbiol\u003c/em\u003e. 2018;16(12):745-759. doi:10.1038/s41579-018-0089-x\u003c/li\u003e\n\u003cli\u003eChhaliyil P, Fischer KF, Schoel B, Chhalliyil P. A Novel, Simple, Frequent Oral Cleaning Method Reduces Damaging Bacteria in the Dental Microbiota. \u003cem\u003eJ Int Soc Prev Community Dent\u003c/em\u003e. 2020;10(4):511-519. doi:10.4103/jispcd.JISPCD_31_20\u003c/li\u003e\n\u003cli\u003eNossa CW. Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome. \u003cem\u003eWJG\u003c/em\u003e. 2010;16(33):4135. doi:10.3748/wjg.v16.i33.4135\u003c/li\u003e\n\u003cli\u003eChen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. \u003cem\u003eBioinformatics\u003c/em\u003e. 2018;34(17):i884-i890. doi:10.1093/bioinformatics/bty560\u003c/li\u003e\n\u003cli\u003eLi D, Luo R, Liu CM, et al. MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices. \u003cem\u003eMethods\u003c/em\u003e. 2016;102. doi:10.1016/j.ymeth.2016.02.020\u003c/li\u003e\n\u003cli\u003eLi D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. \u003cem\u003eBioinformatics\u003c/em\u003e. 2015;31(10):1674-1676. doi:10.1093/bioinformatics/btv033\u003c/li\u003e\n\u003cli\u003eHyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. \u003cem\u003eBMC Bioinformatics\u003c/em\u003e. 2010;11:119. doi:10.1186/1471-2105-11-119\u003c/li\u003e\n\u003cli\u003eBuchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. \u003cem\u003eNat Methods\u003c/em\u003e. 2015;12(1):59-60. doi:10.1038/nmeth.3176\u003c/li\u003e\n\u003cli\u003ePowell S, Forslund K, Szklarczyk D, et al. eggNOG v4.0: nested orthology inference across 3686 organisms. \u003cem\u003eNucleic Acids Res\u003c/em\u003e. 2014;42(Database issue):D231-D239. doi:10.1093/nar/gkt1253\u003c/li\u003e\n\u003cli\u003eKanehisa M, Goto S, Hattori M, et al. From genomics to chemical genomics: new developments in KEGG. \u003cem\u003eNucleic Acids Res\u003c/em\u003e. 2006;34(Database issue):D354-D357.\u003c/li\u003e\n\u003cli\u003eCantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics. \u003cem\u003eNucleic Acids Res\u003c/em\u003e. 2009;37(Database issue):D233-D238. doi:10.1093/nar/gkn663\u003c/li\u003e\n\u003cli\u003eHill TCJ, Walsh KA, Harris JA, Moffett BF. Using ecological diversity measures with bacterial communities. \u003cem\u003eFEMS Microbiol Ecol\u003c/em\u003e. 2003;43(1). doi:10.1111/j.1574-6941.2003.tb01040.x\u003c/li\u003e\n\u003cli\u003eChao A, Bunge J. Estimating the number of species in a stochastic abundance model. \u003cem\u003eBiometrics\u003c/em\u003e. 2002;58(3):531-539.\u003c/li\u003e\n\u003cli\u003eChen Q, Zhao Y, Shen G, Dai J. Etiology and Pathogenesis of Hemifacial Microsomia. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2018;97(12):1297-1305. doi:10.1177/0022034518795609\u003c/li\u003e\n\u003cli\u003eHartsfield JK. Review of the etiologic heterogeneity of the oculo-auriculo-vertebral spectrum (Hemifacial Microsomia). \u003cem\u003eOrthod Craniofac Res\u003c/em\u003e. 2007;10(3):121-128.\u003c/li\u003e\n\u003cli\u003eCaron CJJM, Pluijmers BI, Wolvius EB, et al. Craniofacial and extracraniofacial anomalies in craniofacial microsomia: a multicenter study of 755 patients\u0026rsquo;. \u003cem\u003eJ Craniomaxillofac Surg\u003c/em\u003e. 2017;45(8):1302-1310. doi:10.1016/j.jcms.2017.06.001\u003c/li\u003e\n\u003cli\u003eElsten EECM, Caron CJJM, Dunaway DJ, Padwa BL, Forrest C, Koudstaal MJ. Dental anomalies in craniofacial microsomia: A systematic review. \u003cem\u003eOrthod Craniofacial Res\u003c/em\u003e. 2020;23(1):16-26. doi:10.1111/ocr.12351\u003c/li\u003e\n\u003cli\u003eIrie K, Novince CM, Darveau RP. Impact of the Oral Commensal Flora on Alveolar Bone Homeostasis. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2014;93(8):801-806. doi:10.1177/0022034514540173\u003c/li\u003e\n\u003cli\u003eHathaway-Schrader JD, Novince CM. Maintaining homeostatic control of periodontal bone tissue. \u003cem\u003ePeriodontol 2000\u003c/em\u003e. 2021;86(1):157-187. doi:10.1111/prd.12368\u003c/li\u003e\n\u003cli\u003eLi Y, Ling J, Jiang Q. Inflammasomes in Alveolar Bone Loss. \u003cem\u003eFront Immunol\u003c/em\u003e. 2021;12:691013. doi:10.3389/fimmu.2021.691013\u003c/li\u003e\n\u003cli\u003eShibazaki-Yorozuya R, Yamada A, Nagata S, Ueda K, Miller AJ, Maki K. Three-dimensional longitudinal changes in craniofacial growth in untreated hemifacial microsomia patients with cone-beam computed tomography. \u003cem\u003eAmerican Journal of Orthodontics and Dentofacial Orthopedics\u003c/em\u003e. 2014;145(5):579-594. doi:10.1016/j.ajodo.2013.09.015\u003c/li\u003e\n\u003cli\u003eBowen WH, Burne RA, Wu H, Koo H. Oral Biofilms: Pathogens, Matrix, and Polymicrobial Interactions in Microenvironments. \u003cem\u003eTrends Microbiol\u003c/em\u003e. 2018;26(3):229-242. doi:10.1016/j.tim.2017.09.008\u003c/li\u003e\n\u003cli\u003eChimenos-K\u0026uuml;stner E, Giovannoni ML, Schemel-Su\u0026aacute;rez M. Dysbiosis as a determinant factor of systemic and oral pathology: importance of microbiome. \u003cem\u003eMed Clin (Barc)\u003c/em\u003e. 2017;149(7):305-309. doi:10.1016/j.medcli.2017.05.036\u003c/li\u003e\n\u003cli\u003eMark Welch JL, Ram\u0026iacute;rez-Puebla ST, Borisy GG. Oral Microbiome Geography: Micron-Scale Habitat and Niche. \u003cem\u003eCell Host \u0026amp; Microbe\u003c/em\u003e. 2020;28(2):160-168. doi:10.1016/j.chom.2020.07.009\u003c/li\u003e\n\u003cli\u003eTuganbaev T, Yoshida K, Honda K. The effects of oral microbiota on health. \u003cem\u003eScience\u003c/em\u003e. 2022;376(6596):934-936. doi:10.1126/science.abn1890\u003c/li\u003e\n\u003cli\u003eTonelli A, Lumngwena EN, Ntusi NAB. The oral microbiome in the pathophysiology of cardiovascular disease. \u003cem\u003eNat Rev Cardiol\u003c/em\u003e. 2023;20(6):386-403. doi:10.1038/s41569-022-00825-3\u003c/li\u003e\n\u003cli\u003eRadaic A. The oralome and its dysbiosis: New insights into oral microbiome-host interactions. \u003cem\u003eComputational and Structural Biotechnology Journal\u003c/em\u003e. Published online 2021.\u003c/li\u003e\n\u003cli\u003eSantos AL, Siqueira JF, R\u0026ocirc;\u0026ccedil;as IN, Jesus EC, Rosado AS, Tiedje JM. Comparing the bacterial diversity of acute and chronic dental root canal infections. \u003cem\u003ePLoS One\u003c/em\u003e. 2011;6(11):e28088. doi:10.1371/journal.pone.0028088\u003c/li\u003e\n\u003cli\u003eSchulze-Schweifing K, Banerjee A, Wade WG. Comparison of bacterial culture and 16S rRNA community profiling by clonal analysis and pyrosequencing for the characterization of the dentine caries-associated microbiome. \u003cem\u003eFront Cell Infect Microbiol\u003c/em\u003e. 2014;4:164. doi:10.3389/fcimb.2014.00164\u003c/li\u003e\n\u003cli\u003eHathaway-Schrader JD, Novince CM. Maintaining homeostatic control of periodontal bone tissue. \u003cem\u003ePeriodontol 2000\u003c/em\u003e. 2021;86(1):157-187. doi:10.1111/prd.12368\u003c/li\u003e\n\u003cli\u003eYang F, Zeng X, Ning K, et al. Saliva microbiomes distinguish caries-active from healthy human populations. \u003cem\u003eISME J\u003c/em\u003e. 2012;6(1). doi:10.1038/ismej.2011.71\u003c/li\u003e\n\u003cli\u003eAntiabong JF, Boardman W, Moore RB, Brown MH, Ball AS. The oral microbial community of gingivitis and lumpy jaw in captive macropods. \u003cem\u003eRes Vet Sci\u003c/em\u003e. 2013;95(3). doi:10.1016/j.rvsc.2013.08.010\u003c/li\u003e\n\u003cli\u003eCheng LL, Moor SL, Ho CTC. Predisposing factors to dental caries in children with cleft lip and palate: a review and strategies for early prevention. \u003cem\u003eCleft Palate Craniofac J\u003c/em\u003e. 2007;44(1):67-72.\u003c/li\u003e\n\u003cli\u003eOngkosuwito EM, de Gijt P, Wattel E, Carels CEL, Kuijpers-Jagtman AM. Dental development in hemifacial microsomia. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2010;89(12):1368-1372. doi:10.1177/0022034510378425\u003c/li\u003e\n\u003cli\u003eSilvestri A, Natali G, Fadda MT. Dental agenesis in hemifacial microsomia. \u003cem\u003ePediatr Dent\u003c/em\u003e. 1996;18(1):48-51.\u003c/li\u003e\n\u003cli\u003eLi X, Liu Y, Yang X, Li C, Song Z. The Oral Microbiota: Community Composition, Influencing Factors, Pathogenesis, and Interventions. \u003cem\u003eFront Microbiol\u003c/em\u003e. 2022;13:895537. doi:10.3389/fmicb.2022.895537\u003c/li\u003e\n\u003cli\u003eCaron CJJM, Pluijmers BI, Maas BDPJ, et al. Obstructive sleep apnoea in craniofacial microsomia: analysis of 755 patients. \u003cem\u003eInt J Oral Maxillofac Surg\u003c/em\u003e. 2017;46(10):1330-1337. doi:10.1016/j.ijom.2017.05.020\u003c/li\u003e\n\u003cli\u003eXu H, Li X, Zheng X, et al. Pediatric Obstructive Sleep Apnea is Associated With Changes in the Oral Microbiome and Urinary Metabolomics Profile: A Pilot Study. \u003cem\u003eJ Clin Sleep Med\u003c/em\u003e. 2018;14(9):1559-1567. doi:10.5664/jcsm.7336\u003c/li\u003e\n\u003cli\u003eJia P, Zou J, Yin S, Chen F, Yi H, Zhang Q. Analysis of the Salivary Microbiome in Obstructive Sleep Apnea Syndrome Patients. Chen T, ed. \u003cem\u003eCanadian Journal of Infectious Diseases and Medical Microbiology\u003c/em\u003e. 2020;2020:1-7. doi:10.1155/2020/6682020\u003c/li\u003e\n\u003cli\u003eNizam N, Basoglu OK, Tasbakan MS, Lappin DF, Buduneli N. Is there an association between obstructive sleep apnea syndrome and periodontal inflammation? \u003cem\u003eClin Oral Invest\u003c/em\u003e. 2016;20(4):659-668. doi:10.1007/s00784-015-1544-y\u003c/li\u003e\n\u003cli\u003eOksenberg A, Froom P, Melamed S. Dry mouth upon awakening in obstructive sleep apnea. \u003cem\u003eJ Sleep Res\u003c/em\u003e. 2006;15(3):317-320.\u003c/li\u003e\n\u003cli\u003eBoink MA, Roffel S, Nazmi K, Bolscher JGM, Veerman ECI, Gibbs S. Saliva-Derived Host Defense Peptides Histatin1 and LL-37 Increase Secretion of Antimicrobial Skin and Oral Mucosa Chemokine CCL20 in an IL-1\u0026alpha;-Independent Manner. \u003cem\u003eJ Immunol Res\u003c/em\u003e. 2017;2017:3078194. doi:10.1155/2017/3078194\u003c/li\u003e\n\u003cli\u003eFrenkel ES, Ribbeck K. Salivary mucins in host defense and disease prevention. \u003cem\u003eJ Oral Microbiol\u003c/em\u003e. 2015;7:29759. doi:10.3402/jom.v7.29759\u003c/li\u003e\n\u003cli\u003eGinsburg I, Kohen R, Koren E. Saliva: a \u0026ldquo;solubilizer\u0026rdquo; of lipophilic antioxidant polyphenols. \u003cem\u003eOral Dis\u003c/em\u003e. 2013;19(3):321-322. doi:10.1111/odi.12038\u003c/li\u003e\n\u003cli\u003eFrenkel ES, Ribbeck K. Salivary mucins promote the coexistence of competing oral bacterial species. \u003cem\u003eISME J\u003c/em\u003e. 2017;11(5):1286-1290. doi:10.1038/ismej.2016.200\u003c/li\u003e\n\u003cli\u003eMan WH, de Steenhuijsen Piters WAA, Bogaert D. The microbiota of the respiratory tract: gatekeeper to respiratory health. \u003cem\u003eNat Rev Microbiol\u003c/em\u003e. 2017;15(5):259-270. doi:10.1038/nrmicro.2017.14\u003c/li\u003e\n\u003cli\u003eZhang X, Wang S, Xu H, Yi H, Guan J, Yin S. Metabolomics and microbiome profiling as biomarkers in obstructive sleep apnoea: a comprehensive review. \u003cem\u003eEur Respir Rev\u003c/em\u003e. 2021;30(160). doi:10.1183/16000617.0220-2020\u003c/li\u003e\n\u003cli\u003eEfunkoya AA, Bamgbose BO, Adebola RA, Adeoye JB, Akpasa IO. Maxillomandibular distraction osteogenesis. \u003cem\u003eJ Craniofac Surg\u003c/em\u003e. 2014;25(5):1787-1792. doi:10.1097/SCS.0000000000000907\u003c/li\u003e\n\u003cli\u003eWeichman KE, Jacobs J, Patel P, et al. Early Distraction for Mild to Moderate Unilateral Craniofacial Microsomia: Long-Term Follow-Up, Outcomes, and Recommendations. \u003cem\u003ePlast Reconstr Surg\u003c/em\u003e. 2017;139(4):941e-953e. doi:10.1097/PRS.0000000000003223\u003c/li\u003e\n\u003cli\u003eZhang RS, Lin LO, Hoppe IC, Swanson JW, Taylor JA, Bartlett SP. Early Mandibular Distraction in Craniofacial Microsomia and Need for Orthognathic Correction at Skeletal Maturity: A Comparative Long-Term Follow-Up Study. \u003cem\u003ePlast Reconstr Surg\u003c/em\u003e. 2018;142(5):1285-1293. doi:10.1097/PRS.0000000000004842\u003c/li\u003e\n\u003cli\u003eMelsen B, Bjerregaard J, Bundgaard M. The effect of treatment with functional appliance on a pathologic growth pattern of the condyle. \u003cem\u003eAm J Orthod Dentofacial Orthop\u003c/em\u003e. 1986;90(6):503-512.\u003c/li\u003e\n\u003cli\u003eShibazaki-Yorozuya R, Yamada A, Nagata S, Ueda K, Miller AJ, Maki K. Three-dimensional longitudinal changes in craniofacial growth in untreated hemifacial microsomia patients with cone-beam computed tomography. \u003cem\u003eAm J Orthod Dentofacial Orthop\u003c/em\u003e. 2014;145(5):579-594. doi:10.1016/j.ajodo.2013.09.015\u003c/li\u003e\n\u003cli\u003eChow A, Lee HF, Trahar M, Kawamoto H, Vastardis H, Ting K. Cephalometric evaluation of the craniofacial complex in patients treated with an intraoral distraction osteogenesis device: a long-term study. \u003cem\u003eAm J Orthod Dentofacial Orthop\u003c/em\u003e. 2008;134(6):724-731. doi:10.1016/j.ajodo.2007.01.029\u003c/li\u003e\n\u003cli\u003eKo EWC, Chen PKT, Lo LJ. Comparison of the adult three-dimensional craniofacial features of patients with unilateral craniofacial microsomia with and without early mandible distraction. \u003cem\u003eInt J Oral Maxillofac Surg\u003c/em\u003e. 2017;46(7):811-818. doi:10.1016/j.ijom.2017.03.002\u003c/li\u003e\n\u003cli\u003eMeazzini MC, Mazzoleni F, Gabriele C, Bozzetti A. Mandibular distraction osteogenesis in hemifacial microsomia: long-term follow-up. \u003cem\u003eJ Craniomaxillofac Surg\u003c/em\u003e. 2005;33(6):370-376.\u003c/li\u003e\n\u003cli\u003eAiyar A, Pedersen TK, Resnick CM, N\u0026oslash;rholt SE, Verna C, Stoustrup PB. Management of unilateral craniofacial microsomia with orthopaedic functional appliances: A systematic literature review. \u003cem\u003eOrthod Craniofac Res\u003c/em\u003e. Published online November 2023. doi:10.1111/ocr.12729\u003c/li\u003e\n\u003cli\u003eLi Y, Ling J, Jiang Q. Inflammasomes in Alveolar Bone Loss. \u003cem\u003eFront Immunol\u003c/em\u003e. 2021;12:691013. doi:10.3389/fimmu.2021.691013\u003c/li\u003e\n\u003cli\u003eHathaway‐Schrader JD, Novince CM. Maintaining homeostatic control of periodontal bone tissue. \u003cem\u003ePeriodontology 2000\u003c/em\u003e. 2021;86(1):157-187. doi:10.1111/prd.12368\u003c/li\u003e\n\u003cli\u003eShibazaki-Yorozuya R, Yamada A, Nagata S, Ueda K, Miller AJ, Maki K. Three-dimensional longitudinal changes in craniofacial growth in untreated hemifacial microsomia patients with cone-beam computed tomography. \u003cem\u003eAmerican Journal of Orthodontics and Dentofacial Orthopedics\u003c/em\u003e. 2014;145(5):579-594. doi:10.1016/j.ajodo.2013.09.015\u003c/li\u003e\n\u003cli\u003eLee KM, Kim YI, Park SB, Son WS. Alveolar bone loss around lower incisors during surgical orthodontic treatment in mandibular prognathism. \u003cem\u003eAngle Orthod\u003c/em\u003e. 2012;82(4):637-644. doi:10.2319/081711-526.1\u003c/li\u003e\n\u003cli\u003eOna M, Wakabayashi N. Influence of alveolar support on stress in periodontal structures. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2006;85(12):1087-1091.\u003c/li\u003e\n\u003cli\u003eIrie K, Novince CM, Darveau RP. Impact of the Oral Commensal Flora on Alveolar Bone Homeostasis. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2014;93(8):801-806. doi:10.1177/0022034514540173\u003c/li\u003e\n\u003cli\u003eBonne NJ, Wong DT. Salivary biomarker development using genomic, proteomic and metabolomic approaches. \u003cem\u003eGenome Med\u003c/em\u003e. 2012;4(10):82. doi:10.1186/gm383\u003c/li\u003e\n\u003cli\u003eYoshizawa JM, Schafer CA, Schafer JJ, Farrell JJ, Paster BJ, Wong DTW. Salivary biomarkers: toward future clinical and diagnostic utilities. \u003cem\u003eClin Microbiol Rev\u003c/em\u003e. 2013;26(4):781-791. doi:10.1128/CMR.00021-13\u003c/li\u003e\n\u003cli\u003eGomez A, Nelson KE. The Oral Microbiome of Children: Development, Disease, and Implications Beyond Oral Health. \u003cem\u003eMicrob Ecol\u003c/em\u003e. 2017;73(2):492-503. doi:10.1007/s00248-016-0854-1\u003c/li\u003e\n\u003cli\u003ePathak JL, Yan Y, Zhang Q, Wang L, Ge L. The role of oral microbiome in respiratory health and diseases. \u003cem\u003eRespir Med\u003c/em\u003e. 2021;185:106475. doi:10.1016/j.rmed.2021.106475\u003c/li\u003e\n\u003cli\u003eVaroni EM, Rimondini L. Oral Microbiome, Oral Health and Systemic Health: A Multidirectional Link. \u003cem\u003eBiomedicines\u003c/em\u003e. 2022;10(1). doi:10.3390/biomedicines10010186\u003c/li\u003e\n\u003cli\u003eZaura E, Keijser BJF, Huse SM, Crielaard W. Defining the healthy \u0026ldquo;core microbiome\u0026rdquo; of oral microbial communities. \u003cem\u003eBMC Microbiol\u003c/em\u003e. 2009;9:259. doi:10.1186/1471-2180-9-259\u003c/li\u003e\n\u003cli\u003eTakeshita T, Yasui M, Shibata Y, et al. Dental plaque development on a hydroxyapatite disk in young adults observed by using a barcoded pyrosequencing approach. \u003cem\u003eSci Rep\u003c/em\u003e. 2015;5:8136. doi:10.1038/srep08136\u003c/li\u003e\n\u003cli\u003ePage RC, Vandesteen GE, Ebersole JL, Williams BL, Dixon IL, Altman LC. Clinical and laboratory studies of a family with a high prevalence of juvenile periodontitis. \u003cem\u003eJ Periodontol\u003c/em\u003e. 1985;56(10):602-610.\u003c/li\u003e\n\u003cli\u003eWatanabe K. Prepubertal periodontitis: a review of diagnostic criteria, pathogenesis, and differential diagnosis. \u003cem\u003eJ Periodontal Res\u003c/em\u003e. 1990;25(1):31-48.\u003c/li\u003e\n\u003cli\u003ePage RC. Gingivitis. \u003cem\u003eJ Clin Periodontol\u003c/em\u003e. 1986;13(5):345-359.\u003c/li\u003e\n\u003cli\u003eZhu W, Shen W, Wang J, et al. Capnocytophaga gingivalis is a potential tumor promotor in oral cancer. \u003cem\u003eOral Dis\u003c/em\u003e. 2024;30(2):353-362. doi:10.1111/odi.14376\u003c/li\u003e\n\u003cli\u003eHayes RB, Ahn J, Fan X, et al. Association of Oral Microbiome With Risk for Incident Head and Neck Squamous Cell Cancer. \u003cem\u003eJAMA Oncol\u003c/em\u003e. 2018;4(3):358-365. doi:10.1001/jamaoncol.2017.4777\u003c/li\u003e\n\u003cli\u003eKinoshita S, Udaka S, Shimono M. Studies on the amino acid fermentation. Part 1. Production of L-glutamic acid by various microorganisms. \u003cem\u003eJ Gen Appl Microbiol\u003c/em\u003e. 2004;50(6):331-343.\u003c/li\u003e\n\u003cli\u003ePoetsch A, Haussmann U, Burkovski A. Proteomics of corynebacteria: From biotechnology workhorses to pathogens. \u003cem\u003eProteomics\u003c/em\u003e. 2011;11(15):3244-3255. doi:10.1002/pmic.201000786\u003c/li\u003e\n\u003cli\u003eCosta JJ, Michel JL, Rappuoli R, Murphy JR. Restriction map of corynebacteriophages beta c and beta vir and physical localization of the diphtheria tox operon. \u003cem\u003eJ Bacteriol\u003c/em\u003e. 1981;148(1):124-130.\u003c/li\u003e\n\u003cli\u003eHayes RB, Ahn J, Fan X, et al. Association of Oral Microbiome With Risk for Incident Head and Neck Squamous Cell Cancer. \u003cem\u003eJAMA Oncol\u003c/em\u003e. 2018;4(3):358. doi:10.1001/jamaoncol.2017.4777\u003c/li\u003e\n\u003cli\u003eKurita-Ochiai T, Seto S, Suzuki N, et al. Butyric acid induces apoptosis in inflamed fibroblasts. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2008;87(1):51-55.\u003c/li\u003e\n\u003cli\u003eWashio J, Sato T, Koseki T, Takahashi N. Hydrogen sulfide-producing bacteria in tongue biofilm and their relationship with oral malodour. \u003cem\u003eJ Med Microbiol\u003c/em\u003e. 2005;54(Pt 9):889-895. doi:10.1099/jmm.0.46118-0\u003c/li\u003e\n\u003cli\u003eGross EL, Beall CJ, Kutsch SR, Firestone ND, Leys EJ, Griffen AL. Beyond Streptococcus mutans: dental caries onset linked to multiple species by 16S rRNA community analysis. \u003cem\u003ePLoS One\u003c/em\u003e. 2012;7(10):e47722. doi:10.1371/journal.pone.0047722\u003c/li\u003e\n\u003cli\u003eHayes RB, Ahn J, Fan X, et al. Association of Oral Microbiome With Risk for Incident Head and Neck Squamous Cell Cancer. \u003cem\u003eJAMA Oncol\u003c/em\u003e. 2018;4(3):358-365. doi:10.1001/jamaoncol.2017.4777\u003c/li\u003e\n\u003cli\u003eBrook I. Fusobacterial infections in children. \u003cem\u003eJ Infect\u003c/em\u003e. 1994;28(2):155-165.\u003c/li\u003e\n\u003cli\u003eEhlers Klug T, Rusan M, Fuursted K, Ovesen T. Fusobacterium necrophorum: most prevalent pathogen in peritonsillar abscess in Denmark. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 2009;49(10):1467-1472. doi:10.1086/644616\u003c/li\u003e\n\u003cli\u003eShang FM, Liu HL. Fusobacterium nucleatum and colorectal cancer: A review. \u003cem\u003eWorld J Gastrointest Oncol\u003c/em\u003e. 2018;10(3):71-81. doi:10.4251/wjgo.v10.i3.71\u003c/li\u003e\n\u003cli\u003eCitron DM. Update on the taxonomy and clinical aspects of the genus fusobacterium. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 2002;35(Suppl 1):S22-S27.\u003c/li\u003e\n\u003cli\u003eNiederman R, Zhang J, Kashket S. Short-chain carboxylic-acid-stimulated, PMN-mediated gingival inflammation. \u003cem\u003eCrit Rev Oral Biol Med\u003c/em\u003e. 1997;8(3):269-290.\u003c/li\u003e\n\u003cli\u003eKurita-Ochiai T, Seto S, Suzuki N, et al. Butyric acid induces apoptosis in inflamed fibroblasts. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2008;87(1):51-55.\u003c/li\u003e\n\u003cli\u003eTanaka S, Yoshida M, Murakami Y, et al. The relationship of Prevotella intermedia, Prevotella nigrescens and Prevotella melaninogenica in the supragingival plaque of children, caries and oral malodor. \u003cem\u003eJ Clin Pediatr Dent\u003c/em\u003e. 2008;32(3):195-200.\u003c/li\u003e\n\u003cli\u003eThomas RM, Jobin C. The Microbiome and Cancer: Is the \u0026ldquo;Oncobiome\u0026rdquo; Mirage Real? \u003cem\u003eTrends Cancer\u003c/em\u003e. 2015;1(1):24-35.\u003c/li\u003e\n\u003cli\u003eSchwabe RF, Jobin C. The microbiome and cancer. \u003cem\u003eNat Rev Cancer\u003c/em\u003e. 2013;13(11):800-812. doi:10.1038/nrc3610\u003c/li\u003e\n\u003cli\u003eSenthakumaran T, Moen AEF, Tann\u0026aelig;s TM, et al. Microbial dynamics with CRC progression: a study of the mucosal microbiota at multiple sites in cancers, adenomatous polyps, and healthy controls. \u003cem\u003eEur J Clin Microbiol Infect Dis\u003c/em\u003e. 2023;42(3):305-322. doi:10.1007/s10096-023-04551-7\u003c/li\u003e\n\u003cli\u003eQi Y, Zang SQ, Wei J, et al. High-throughput sequencing provides insights into oral microbiota dysbiosis in association with inflammatory bowel disease. \u003cem\u003eGenomics\u003c/em\u003e. 2021;113(1 Pt 2):664-676. doi:10.1016/j.ygeno.2020.09.063\u003c/li\u003e\n\u003cli\u003eZilbauer M, Dorrell N, Wren BW, Bajaj-Elliott M. Campylobacter jejuni-mediated disease pathogenesis: an update. \u003cem\u003eTrans R Soc Trop Med Hyg\u003c/em\u003e. 2008;102(2):123-129.\u003c/li\u003e\n\u003cli\u003eKaasch AJ, Saxler G, Seifert H. Septic arthritis due to Rothia mucilaginosa. \u003cem\u003eInfection\u003c/em\u003e. 2011;39(1):81-82. doi:10.1007/s15010-010-0065-5\u003c/li\u003e\n\u003cli\u003eUchibori S, Tsudukibashi O, Goto H, Kobayashi T, Aida M. A novel selective medium for the isolation and distribution of Rothia dentocariosa in oral cavities. \u003cem\u003eJ Microbiol Methods\u003c/em\u003e. 2012;91(1):205-207. doi:10.1016/j.mimet.2012.07.004\u003c/li\u003e\n\u003cli\u003eKobayashi T, Uchibori S, Tsuzukibashi O, Goto H, Aida M. A selective medium for Rothia mucilaginosa and its distribution in oral cavities. \u003cem\u003eJ Microbiol Methods\u003c/em\u003e. 2012;91(3):364-365. doi:10.1016/j.mimet.2012.09.011\u003c/li\u003e\n\u003cli\u003eTakahashi N, Nyvad B. The role of bacteria in the caries process: ecological perspectives. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2011;90(3):294-303. doi:10.1177/0022034510379602\u003c/li\u003e\n\u003cli\u003eTorlakovic L, Klepac-Ceraj V, Ogaard B, Cotton SL, Paster BJ, Olsen I. Microbial community succession on developing lesions on human enamel. \u003cem\u003eJ Oral Microbiol\u003c/em\u003e. 2012;4. doi:10.3402/jom.v4i0.16125\u003c/li\u003e\n\u003cli\u003eBelstr\u0026oslash;m D, Paster BJ, Fiehn NE, Bardow A, Holmstrup P. Salivary bacterial fingerprints of established oral disease revealed by the Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS) technique. \u003cem\u003eJ Oral Microbiol\u003c/em\u003e. 2016;8:30170. doi:10.3402/jom.v8.30170\u003c/li\u003e\n\u003cli\u003ePaju S, Pussinen PJ, Suominen-Taipale L, Hyv\u0026ouml;nen M, Knuuttila M, K\u0026ouml;n\u0026ouml;nen E. Detection of multiple pathogenic species in saliva is associated with periodontal infection in adults. \u003cem\u003eJ Clin Microbiol\u003c/em\u003e. 2009;47(1):235-238. doi:10.1128/JCM.01824-08\u003c/li\u003e\n\u003cli\u003eLemos JA, Palmer SR, Zeng L, et al. The Biology of Streptococcus mutans. \u003cem\u003eMicrobiol Spectr\u003c/em\u003e. 2019;7(1). doi:10.1128/microbiolspec.GPP3-0051-2018\u003c/li\u003e\n\u003cli\u003eWu Y, Chi X, Zhang Q, Chen F, Deng X. Characterization of the salivary microbiome in people with obesity. \u003cem\u003ePeerJ\u003c/em\u003e. 2018;6:e4458. doi:10.7717/peerj.4458\u003c/li\u003e\n\u003cli\u003eMa T, Wu Z, Lin J, Shan C, Abasijiang A, Zhao J. Characterization of the oral and gut microbiome in children with obesity aged 3 to 5 years. \u003cem\u003eFront Cell Infect Microbiol\u003c/em\u003e. 2023;13:1102650. doi:10.3389/fcimb.2023.1102650\u003c/li\u003e\n\u003cli\u003eSaito T, Shimazaki Y, Sakamoto M. Obesity and periodontitis. \u003cem\u003eN Engl J Med\u003c/em\u003e. 1998;339(7):482-483.\u003c/li\u003e\n\u003cli\u003eIaffaldano L, Granata I, Pagliuca C, et al. Oropharyngeal microbiome evaluation highlights Neisseria abundance in active celiac patients. \u003cem\u003eSci Rep\u003c/em\u003e. 2018;8(1):11047. doi:10.1038/s41598-018-29443-1\u003c/li\u003e\n\u003cli\u003eD\u0026rsquo;Argenio V, Casaburi G, Precone V, et al. Metagenomics Reveals Dysbiosis and a Potentially Pathogenic N. flavescens Strain in Duodenum of Adult Celiac Patients. \u003cem\u003eAm J Gastroenterol\u003c/em\u003e. 2016;111(6):879-890. doi:10.1038/ajg.2016.95\u003c/li\u003e\n\u003cli\u003eShamriz O, Mizrahi H, Werbner M, Shoenfeld Y, Avni O, Koren O. Microbiota at the crossroads of autoimmunity. \u003cem\u003eAutoimmun Rev\u003c/em\u003e. 2016;15(9):859-869. doi:10.1016/j.autrev.2016.07.012\u003c/li\u003e\n\u003cli\u003eDong F, Perdew GH. The aryl hydrocarbon receptor as a mediator of host-microbiota interplay. \u003cem\u003eGut Microbes\u003c/em\u003e. 2020;12(1):1859812. doi:10.1080/19490976.2020.1859812\u003c/li\u003e\n\u003cli\u003eBarik S. The Uniqueness of Tryptophan in Biology: Properties, Metabolism, Interactions and Localization in Proteins. \u003cem\u003eInt J Mol Sci\u003c/em\u003e. 2020;21(22). doi:10.3390/ijms21228776\u003c/li\u003e\n\u003cli\u003ePalego L, Betti L, Rossi A, Giannaccini G. Tryptophan Biochemistry: Structural, Nutritional, Metabolic, and Medical Aspects in Humans. \u003cem\u003eJ Amino Acids\u003c/em\u003e. 2016;2016:8952520. doi:10.1155/2016/8952520\u003c/li\u003e\n\u003cli\u003eTakahashi N. Oral Microbiome Metabolism: From \u0026ldquo;Who Are They?\u0026rdquo; to \u0026ldquo;What Are They Doing?\u0026rdquo;. \u003cem\u003eJ Dent Res\u003c/em\u003e. 2015;94(12):1628-1637. doi:10.1177/0022034515606045\u003c/li\u003e\n\u003cli\u003eGrifka-Walk HM, Jenkins BR, Kominsky DJ. Amino Acid Trp: The Far Out Impacts of Host and Commensal Tryptophan Metabolism. \u003cem\u003eFront Immunol\u003c/em\u003e. 2021;12:653208. doi:10.3389/fimmu.2021.653208\u003c/li\u003e\n\u003cli\u003eWu H, Denna TH, Storkersen JN, Gerriets VA. Beyond a neurotransmitter: The role of serotonin in inflammation and immunity. \u003cem\u003ePharmacol Res\u003c/em\u003e. 2019;140:100-114. doi:10.1016/j.phrs.2018.06.015\u003c/li\u003e\n\u003cli\u003eShajib MS, Khan WI. The role of serotonin and its receptors in activation of immune responses and inflammation. \u003cem\u003eActa Physiol (Oxf)\u003c/em\u003e. 2015;213(3):561-574. doi:10.1111/apha.12430\u003c/li\u003e\n\u003cli\u003eLiu XH, Zhai XY. Role of tryptophan metabolism in cancers and therapeutic implications. \u003cem\u003eBiochimie\u003c/em\u003e. 2021;182:131-139. doi:10.1016/j.biochi.2021.01.005\u003c/li\u003e\n\u003cli\u003eRubel F, Kern JS, Technau-Hafsi K, et al. Indoleamine 2,3-Dioxygenase Expression in Primary Cutaneous Melanoma Correlates with Breslow Thickness and Is of Significant Prognostic Value for Progression-Free Survival. \u003cem\u003eJ Invest Dermatol\u003c/em\u003e. 2018;138(3):679-687. doi:10.1016/j.jid.2017.09.036\u003c/li\u003e\n\u003cli\u003eSuzuki Y, Suda T, Furuhashi K, et al. Increased serum kynurenine/tryptophan ratio correlates with disease progression in lung cancer. \u003cem\u003eLung Cancer\u003c/em\u003e. 2010;67(3):361-365. doi:10.1016/j.lungcan.2009.05.001\u003c/li\u003e\n\u003cli\u003eBrandacher G, Perathoner A, Ladurner R, et al. Prognostic value of indoleamine 2,3-dioxygenase expression in colorectal cancer: effect on tumor-infiltrating T cells. \u003cem\u003eClin Cancer Res\u003c/em\u003e. 2006;12(4):1144-1151.\u003c/li\u003e\n\u003cli\u003eNeavin DR, Liu D, Ray B, Weinshilboum RM. The Role of the Aryl Hydrocarbon Receptor (AHR) in Immune and Inflammatory Diseases. \u003cem\u003eInt J Mol Sci\u003c/em\u003e. 2018;19(12). doi:10.3390/ijms19123851\u003c/li\u003e\n\u003cli\u003eBalci N, Kurgan Ş, \u0026Ccedil;ekici A, \u0026Ccedil;akır T, Serdar MA. Free amino acid composition of saliva in patients with healthy periodontium and periodontitis. \u003cem\u003eClin Oral Investig\u003c/em\u003e. 2021;25(6):4175-4183. doi:10.1007/s00784-021-03977-7\u003c/li\u003e\n\u003cli\u003eLi X, Ma Y, Wu X, et al. Serotonin acts as a novel regulator of interleukin-6 secretion in osteocytes through the activation of the 5-HT(2B) receptor and the ERK1/2 signalling pathway. \u003cem\u003eBiochem Biophys Res Commun\u003c/em\u003e. 2013;441(4):809-814. doi:10.1016/j.bbrc.2013.10.141\u003c/li\u003e\n\u003cli\u003eChabbi-Achengli Y, Coudert AE, Callebert J, et al. Decreased osteoclastogenesis in serotonin-deficient mice. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e. 2012;109(7):2567-2572. doi:10.1073/pnas.1117792109\u003c/li\u003e\n\u003cli\u003eLi X, Wu X, Ma Y, et al. Oral administration of 5-hydroxytryptophan aggravated periodontitis-induced alveolar bone loss in rats. \u003cem\u003eArch Oral Biol\u003c/em\u003e. 2015;60(5):789-798. doi:10.1016/j.archoralbio.2015.01.015\u003c/li\u003e\n\u003cli\u003eKabil O, Banerjee R. Redox biochemistry of hydrogen sulfide. \u003cem\u003eJ Biol Chem\u003c/em\u003e. 2010;285(29):21903-21907. doi:10.1074/jbc.R110.128363\u003c/li\u003e\n\u003cli\u003eMiller CG, Schmidt EE. Sulfur Metabolism Under Stress. \u003cem\u003eAntioxid Redox Signal\u003c/em\u003e. 2020;33(16):1158-1173. doi:10.1089/ars.2020.8151\u003c/li\u003e\n\u003cli\u003eKumar R, Landry AP, Guha A, et al. A redox cycle with complex II prioritizes sulfide quinone oxidoreductase-dependent H2S oxidation. \u003cem\u003eJ Biol Chem\u003c/em\u003e. 2022;298(1):101435. doi:10.1016/j.jbc.2021.101435\u003c/li\u003e\n\u003cli\u003eOlson KR. A Case for Hydrogen Sulfide Metabolism as an Oxygen Sensing Mechanism. \u003cem\u003eAntioxidants (Basel)\u003c/em\u003e. 2021;10(11). doi:10.3390/antiox10111650\u003c/li\u003e\n\u003cli\u003eBouillaud F. Sulfide Oxidation Evidences the Immediate Cellular Response to a Decrease in the Mitochondrial ATP/O2 Ratio. \u003cem\u003eBiomolecules\u003c/em\u003e. 2022;12(3). doi:10.3390/biom12030361\u003c/li\u003e\n\u003cli\u003eStipanuk MH. Sulfur amino acid metabolism: pathways for production and removal of homocysteine and cysteine. \u003cem\u003eAnnu Rev Nutr\u003c/em\u003e. 2004;24:539-577.\u003c/li\u003e\n\u003cli\u003eMiller CG, Holmgren A, Arn\u0026eacute;r ESJ, Schmidt EE. NADPH-dependent and -independent disulfide reductase systems. \u003cem\u003eFree Radic Biol Med\u003c/em\u003e. 2018;127:248-261. doi:10.1016/j.freeradbiomed.2018.03.051\u003c/li\u003e\n\u003cli\u003eYoshida Y, Ito S, Kamo M, et al. Production of hydrogen sulfide by two enzymes associated with biosynthesis of homocysteine and lanthionine in Fusobacterium nucleatum subsp. nucleatum ATCC 25586. \u003cem\u003eMicrobiology (Reading)\u003c/em\u003e. 2010;156(Pt 7):2260-2269. doi:10.1099/mic.0.039180-0\u003c/li\u003e\n\u003cli\u003eMarciano D, Santana M, Mantilla BS, Silber AM, Marino-Buslje C, Nowicki C. Biochemical characterization of serine acetyltransferase and cysteine desulfhydrase from Leishmania major. \u003cem\u003eMol Biochem Parasitol\u003c/em\u003e. 2010;173(2):170-174. doi:10.1016/j.molbiopara.2010.06.004\u003c/li\u003e\n\u003cli\u003eDharmani P, Strauss J, Ambrose C, Allen-Vercoe E, Chadee K. Fusobacterium nucleatum infection of colonic cells stimulates MUC2 mucin and tumor necrosis factor alpha. \u003cem\u003eInfect Immun\u003c/em\u003e. 2011;79(7):2597-2607. doi:10.1128/IAI.05118-11\u003c/li\u003e\n\u003cli\u003eTakahashi Y, Yoshida A, Nagata E, et al. Streptococcus anginosus l-cysteine desulfhydrase gene expression is associated with abscess formation in BALB/c mice. \u003cem\u003eMol Oral Microbiol\u003c/em\u003e. 2011;26(3):221-227. doi:10.1111/j.2041-1014.2010.00599.x\u003c/li\u003e\n\u003cli\u003eStrauss J, Kaplan GG, Beck PL, et al. Invasive potential of gut mucosa-derived Fusobacterium nucleatum positively correlates with IBD status of the host. \u003cem\u003eInflamm Bowel Dis\u003c/em\u003e. 2011;17(9):1971-1978. doi:10.1002/ibd.21606\u003c/li\u003e\n\u003cli\u003eCastellarin M, Warren RL, Freeman JD, et al. Fusobacterium nucleatum infection is prevalent in human colorectal carcinoma. \u003cem\u003eGenome Res\u003c/em\u003e. 2012;22(2):299-306. doi:10.1101/gr.126516.111\u003c/li\u003e\n\u003cli\u003eKostic AD, Gevers D, Pedamallu CS, et al. Genomic analysis identifies association of Fusobacterium with colorectal carcinoma. \u003cem\u003eGenome Res\u003c/em\u003e. 2012;22(2):292-298. doi:10.1101/gr.126573.111\u003c/li\u003e\n\u003cli\u003eM\u0026oacute;dis K, Bos EM, Calzia E, et al. Regulation of mitochondrial bioenergetic function by hydrogen sulfide. Part II. Pathophysiological and therapeutic aspects. \u003cem\u003eBr J Pharmacol\u003c/em\u003e. 2014;171(8):2123-2146. doi:10.1111/bph.12368\u003c/li\u003e\n\u003cli\u003eBos EM, van Goor H, Joles JA, Whiteman M, Leuvenink HGD. Hydrogen sulfide: physiological properties and therapeutic potential in ischaemia. \u003cem\u003eBr J Pharmacol\u003c/em\u003e. 2015;172(6):1479-1493. doi:10.1111/bph.12869\u003c/li\u003e\n\u003cli\u003eWallace JL, Wang R. Hydrogen sulfide-based therapeutics: exploiting a unique but ubiquitous gasotransmitter. \u003cem\u003eNat Rev Drug Discov\u003c/em\u003e. 2015;14(5):329-345. doi:10.1038/nrd4433\u003c/li\u003e\n\u003cli\u003eIjssennagger N, van der Meer R, van Mil SWC. Sulfide as a Mucus Barrier-Breaker in Inflammatory Bowel Disease? \u003cem\u003eTrends Mol Med\u003c/em\u003e. 2016;22(3):190-199. doi:10.1016/j.molmed.2016.01.002\u003c/li\u003e\n\u003cli\u003eZaorska E, Tomasova L, Koszelewski D, Ostaszewski R, Ufnal M. Hydrogen Sulfide in Pharmacotherapy, Beyond the Hydrogen Sulfide-Donors. \u003cem\u003eBiomolecules\u003c/em\u003e. 2020;10(2). doi:10.3390/biom10020323\u003c/li\u003e\n\u003cli\u003eWang R. Physiological implications of hydrogen sulfide: a whiff exploration that blossomed. \u003cem\u003ePhysiol Rev\u003c/em\u003e. 2012;92(2):791-896. doi:10.1152/physrev.00017.2011\u003c/li\u003e\n\u003cli\u003eWang Y, Nguyen LH, Mehta RS, Song M, Huttenhower C, Chan AT. Association Between the Sulfur Microbial Diet and Risk of Colorectal Cancer. \u003cem\u003eJAMA Netw Open\u003c/em\u003e. 2021;4(11):e2134308. doi:10.1001/jamanetworkopen.2021.34308\u003c/li\u003e\n\u003cli\u003eYoshii K, Hosomi K, Sawane K, Kunisawa J. Metabolism of Dietary and Microbial Vitamin B Family in the Regulation of Host Immunity. \u003cem\u003eFront Nutr\u003c/em\u003e. 2019;6:48. doi:10.3389/fnut.2019.00048\u003c/li\u003e\n\u003cli\u003eHayashi A, Mikami Y, Miyamoto K, et al. Intestinal Dysbiosis and Biotin Deprivation Induce Alopecia through Overgrowth of Lactobacillus murinus in Mice. \u003cem\u003eCell Reports\u003c/em\u003e. 2017;20(7):1513-1524. doi:10.1016/j.celrep.2017.07.057\u003c/li\u003e\n\u003cli\u003eMagn\u0026uacute;sd\u0026oacute;ttir S, Ravcheev D, De Cr\u0026eacute;cy-Lagard V, Thiele I. Systematic genome assessment of B-vitamin biosynthesis suggests co-operation among gut microbes. \u003cem\u003eFront Genet\u003c/em\u003e. 2015;6. doi:10.3389/fgene.2015.00148\u003c/li\u003e\n\u003cli\u003eMetaHIT Consortium (additional members), Arumugam M, Raes J, et al. Enterotypes of the human gut microbiome. \u003cem\u003eNature\u003c/em\u003e. 2011;473(7346):174-180. doi:10.1038/nature09944\u003c/li\u003e\n\u003cli\u003eMagn\u0026uacute;sd\u0026oacute;ttir S, Ravcheev D, de Cr\u0026eacute;cy-Lagard V, Thiele I. Systematic genome assessment of B-vitamin biosynthesis suggests co-operation among gut microbes. \u003cem\u003eFront Genet\u003c/em\u003e. 2015;6:148. doi:10.3389/fgene.2015.00148\u003c/li\u003e\n\u003cli\u003eLe\u0026oacute;n-Del-R\u0026iacute;o A. Biotin in metabolism, gene expression, and human disease. \u003cem\u003eJ Inherit Metab Dis\u003c/em\u003e. 2019;42(4):647-654. doi:10.1002/jimd.12073\u003c/li\u003e\n\u003cli\u003eLin S, Cronan JE. Closing in on complete pathways of biotin biosynthesis. \u003cem\u003eMol Biosyst\u003c/em\u003e. 2011;7(6):1811-1821. doi:10.1039/c1mb05022b\u003c/li\u003e\n\u003cli\u003eCronan JE. Advances in synthesis of biotin and assembly of lipoic acid. \u003cem\u003eCurr Opin Chem Biol\u003c/em\u003e. 2018;47:60-66. doi:10.1016/j.cbpa.2018.08.004\u003c/li\u003e\n\u003cli\u003eAgrawal S, Agrawal A, Said HM. Biotin deficiency enhances the inflammatory response of human dendritic cells. \u003cem\u003eAm J Physiol Cell Physiol\u003c/em\u003e. 2016;311(3):C386-C391. doi:10.1152/ajpcell.00141.2016\u003c/li\u003e\n\u003cli\u003eElahi A, Sabui S, Narasappa NN, et al. Biotin Deficiency Induces Th1- and Th17-Mediated Proinflammatory Responses in Human CD4+ T Lymphocytes via Activation of the mTOR Signaling Pathway. \u003cem\u003eJ Immunol\u003c/em\u003e. 2018;200(8):2563-2570. doi:10.4049/jimmunol.1701200\u003c/li\u003e\n\u003cli\u003eOliphant K, Allen-Vercoe E. Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health. \u003cem\u003eMicrobiome\u003c/em\u003e. 2019;7(1):91. doi:10.1186/s40168-019-0704-8\u003c/li\u003e\n\u003cli\u003eKoh A, Molinaro A, St\u0026aring;hlman M, et al. Microbially Produced Imidazole Propionate Impairs Insulin Signaling through mTORC1. \u003cem\u003eCell\u003c/em\u003e. 2018;175(4). doi:10.1016/j.cell.2018.09.055\u003c/li\u003e\n\u003cli\u003eMoro J, Tom\u0026eacute; D, Schmidely P, Demersay TC, Azzout-Marniche D. Histidine: A Systematic Review on Metabolism and Physiological Effects in Human and Different Animal Species. \u003cem\u003eNutrients\u003c/em\u003e. 2020;12(5). doi:10.3390/nu12051414\u003c/li\u003e\n\u003cli\u003eBabizhayev MA, Guiotto A, Kasus-Jacobi A. N-Acetylcarnosine and histidyl-hydrazide are potent agents for multitargeted ophthalmic therapy of senile cataracts and diabetic ocular complications. \u003cem\u003eJ Drug Target\u003c/em\u003e. 2009;17(1):36-63. doi:10.1080/10611860802438736\u003c/li\u003e\n\u003cli\u003eHisatsune T, Kaneko J, Kurashige H, et al. Effect of Anserine/Carnosine Supplementation on Verbal Episodic Memory in Elderly People. \u003cem\u003eJ Alzheimers Dis\u003c/em\u003e. 2016;50(1):149-159. doi:10.3233/JAD-150767\u003c/li\u003e\n\u003cli\u003eTan SP, Brown SB, Griffiths CE, Weller RB, Gibbs NK. Feeding filaggrin: effects of l-histidine supplementation in atopic dermatitis. \u003cem\u003eClin Cosmet Investig Dermatol\u003c/em\u003e. 2017;10:403-411. doi:10.2147/CCID.S146760\u003c/li\u003e\n\u003cli\u003eDiNicolantonio JJ, McCarty MF, OKeefe JH. Role of dietary histidine in the prevention of obesity and metabolic syndrome. \u003cem\u003eOpen Heart\u003c/em\u003e. 2018;5(2):e000676. doi:10.1136/openhrt-2017-000676\u003c/li\u003e\n\u003cli\u003eWunschel EJ, Schirmer B, Seifert R, Neumann D. Lack of Histamine H4-Receptor Expression Aggravates TNBS-Induced Acute Colitis Symptoms in Mice. \u003cem\u003eFront Pharmacol\u003c/em\u003e. 2017;8:642. doi:10.3389/fphar.2017.00642\u003c/li\u003e\n\u003cli\u003eDy M, Schneider E. Histamine-cytokine connection in immunity and hematopoiesis. \u003cem\u003eCytokine Growth Factor Rev\u003c/em\u003e. 2004;15(5):393-410.\u003c/li\u003e\n\u003cli\u003eCacabelos R, Torrellas C, Fern\u0026aacute;ndez-Novoa L, L\u0026oacute;pez-Mu\u0026ntilde;oz F. Histamine and Immune Biomarkers in CNS Disorders. \u003cem\u003eMediators of Inflammation\u003c/em\u003e. 2016;2016:1-10. doi:10.1155/2016/1924603\u003c/li\u003e\n\u003cli\u003eSmolinska S, Winiarska E, Globinska A, Jutel M. Histamine: A Mediator of Intestinal Disorders\u0026mdash;A Review. \u003cem\u003eMetabolites\u003c/em\u003e. 2022;12(10):895. doi:10.3390/metabo12100895\u003c/li\u003e\n\u003cli\u003eGuo J, Liang T, Chen H, et al. Glutamate attenuates lipopolysaccharide induced intestinal barrier injury by regulating corticotropin-releasing factor pathway in weaned pigs. \u003cem\u003eAnim Biosci\u003c/em\u003e. 2022;35(8):1235-1249. doi:10.5713/ab.21.0476\u003c/li\u003e\n\u003cli\u003eYamamoto M, Pinto-Sanchez MI, Bercik P, Britz-McKibbin P. Metabolomics reveals elevated urinary excretion of collagen degradation and epithelial cell turnover products in irritable bowel syndrome patients. \u003cem\u003eMetabolomics\u003c/em\u003e. 2019;15(6):82. doi:10.1007/s11306-019-1543-0\u003c/li\u003e\n\u003cli\u003eWu J, Wu Y, Feng W, et al. Role of Microbial Metabolites of Histidine in the Development of Colitis. \u003cem\u003eMolecular Nutrition Food Res\u003c/em\u003e. 2022;66(14):2101175. doi:10.1002/mnfr.202101175\u003c/li\u003e\n\u003cli\u003eYuan H, Wu X, Wu Q, et al. Lysine catabolism reprograms tumour immunity through histone crotonylation. \u003cem\u003eNature\u003c/em\u003e. 2023;617(7962):818-826. doi:10.1038/s41586-023-06061-0\u003c/li\u003e\n\u003cli\u003eLeandro J, Houten SM. Saccharopine, a lysine degradation intermediate, is a mitochondrial toxin. \u003cem\u003eJ Cell Biol\u003c/em\u003e. 2019;218(2):391-392. doi:10.1083/jcb.201901033\u003c/li\u003e\n\u003cli\u003eLoesche WJ, Gibbons RJ. Amino acid fermentation by Fusobacterium nucleatum. \u003cem\u003eArch Oral Biol\u003c/em\u003e. 1968;13(2):191-202.\u003c/li\u003e\n\u003cli\u003eWang X, Yang S, Li S, et al. Aberrant gut microbiota alters host metabolome and impacts renal failure in humans and rodents. \u003cem\u003eGut\u003c/em\u003e. 2020;69(12):2131-2142. doi:10.1136/gutjnl-2019-319766\u003c/li\u003e\n\u003cli\u003eRUBIN AL, SPRITZ N, MEAD AW, HERRMANN RA, BRAVEMAN WS, LUCKEY EH. The use of L-lysine monomydrochloride in combination with mercurial diuretics in the treatment of refractory fluid retention. \u003cem\u003eCirculation\u003c/em\u003e. 1960;21:332-336.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"craniofacial microsomia, microflora, oral cavity, 16S rRNA, metagenomics","lastPublishedDoi":"10.21203/rs.3.rs-4673616/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4673616/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCraniofacial microsomia (CFM), the second most common congenital craniofacial deformity, has manifold clinical manifestations and treatments that may interact with oral bacteria dysbiosis (OBD). However, studies exploring the relationship between CFM and OBD are scanty.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e Saliva samples of 20 patients with CFM and 24 controls were collected, and oral microflora and gene function annotation were compared using 16S ribosomal RNA and metagenomics. The correlation between clinical phenotypes of CFM and microbiota community structure was also evaluated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e The oral microflora of CFM patients exhibited higher richness and evenness. The dominant genera in CFM were mainly pathogenic and included \u003cem\u003eActinomyces\u003c/em\u003e, \u003cem\u003eFusobacterium\u003c/em\u003e, and \u003cem\u003ePrevotella\u003c/em\u003e. The severity of CFM was significantly positively correlated with the abundance of \u003cem\u003eNeisseria\u003c/em\u003e and \u003cem\u003ePorphyromonas\u003c/em\u003e. The upregulated pathways were primarily enriched in biotin and amino acid metabolism, including Tryptophan metabolism, which positively correlated with the abundance of \u003cem\u003eNeisseria.\u003c/em\u003e\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003e This study suggests for the first time that patients with CFM exhibit distinct oral bacterial dysbiosis, characterized by an elevated prevalence of opportunistic pathogens and upregulated pathways associated with oral and systemic health. These findings provide evidence for corresponding preventions and therapeutic interventions of CFM.\u003c/p\u003e","manuscriptTitle":"Structural and functional changes in the oral microbiome of the patients with craniofacial microsomia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-09 16:04:02","doi":"10.21203/rs.3.rs-4673616/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-23T04:10:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-20T07:34:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201197724746464710165676066490971303600","date":"2024-09-05T06:21:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-02T05:12:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"159805627211665401207837527679982170651","date":"2024-08-22T01:07:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-21T05:47:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-14T15:25:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-11T15:04:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-08T02:45:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-07-02T10:45:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"851501f2-1b90-41e1-b88f-e2a7693af6a2","owner":[],"postedDate":"August 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-17T16:06:01+00:00","versionOfRecord":{"articleIdentity":"rs-4673616","link":"https://doi.org/10.1038/s41598-025-86537-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-02-13 15:57:32","publishedOnDateReadable":"February 13th, 2025"},"versionCreatedAt":"2024-08-09 16:04:02","video":"","vorDoi":"10.1038/s41598-025-86537-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-86537-3","workflowStages":[]},"version":"v1","identity":"rs-4673616","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4673616","identity":"rs-4673616","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}