Microbiota in Chronic Suppurative Otitis Media: Association with Postoperative Tympanic Membrane Outcomes

Microbiota in Chronic Suppurative Otitis Media: Association with Postoperative Tympanic Membrane Outcomes | 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 Research Article Microbiota in Chronic Suppurative Otitis Media: Association with Postoperative Tympanic Membrane Outcomes Xiao Fu, Yuming Chen, Yanmei Wang, Binjun Chen, Mengke Chen, Jihan Lyu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7068085/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Mar, 2026 Read the published version in Applied Microbiology and Biotechnology → Version 1 posted You are reading this latest preprint version Abstract Chronic suppurative otitis media (CSOM) is a prevalent condition with global health implications due to its impact on hearing and quality of life. Conventional treatments often fail because of bacterial biofilms and antimicrobial resistance. Effective treatment of CSOM depends on the precise determination of the middle ear microbiota; however, current microbial detection methods do not meet this need. Postoperative re-perforation may compromise surgical outcomes. If the risk of perforation can be predicted immediately after surgery, sensitive antibiotics could be administered proactively for early intervention to optimize treatment efficacy. This study introduces 2b-RAD sequencing for the Microbiome (2b-RAD-M), a novel technology designed to provide a comprehensive profile of the CSOM microbiota and identify diagnostic biomarkers that predict postoperative outcomes. We analyzed ear swabs from patients with postoperative perforation (PO), non-perforation (NPO), and otosclerosis (CON) using microbial diversity, relative abundance, and composition analyses. Bacillus bombysepticus and Pseudomonas aeruginosa were identified as potential biomarkers, with B. bombysepticus demonstrating superior diagnostic accuracy (AUC = 0.92) compared to P. aeruginosa (AUC = 0.25). Functional predictions revealed that biological activities related to gene regulation, substance metabolism, and DNA repair were more prominent in the PO group. This study offers new insights into CSOM pathogenesis and progression, proposing B. bombysepticus as a novel biomarker for predicting postoperative outcomes that can indicate an increased risk of tympanic membrane re-perforation for the first time. 2b-RAD-M Chronic suppurative otitis media re-perforation Microbiota Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Key Points 2b-RAD-M technology enables comprehensive CSOM microbiota profiling and biomarker identification Bacillus bombysepticus (AUC=0.92) outperforms Pseudomonas aeruginosa in diagnostic accuracy B. bombysepticus predicts postoperative tympanic membrane re-perforation via functional activity analysis Introduction Chronic suppurative otitis media (CSOM) is one of the most common otolaryngological diseases, characterized by persistent ear discharge through a perforated tympanic membrane for over 6 weeks. It is a global health issue, with more than 30 million new cases annually and an estimated global prevalence that exceeds 200 million cases.(Chadha et al., 2021 ) The hearing impairment and tinnitus associated with CSOM have long-term negative effects on patients’ quality of life and mental health, creating a substantial financial burden(Sidam et al., 2024 ). Although surgery and antibiotics are effective for CSOM treatment, the formation of bacterial biofilms and development of antimicrobial resistance can lead to treatment failure, which ultimately results in recurrence of tympanic membrane perforation.(Bhutta et al., 2024) (Nguyen et al., 2012 , Santa Maria et al., 2021 )Furthermore, an inadequate understanding of the pathogenesis has hindered the development of new therapies.(Dhingra et al., 2023 , Bhutta et al., 2017) Thus, CSOM management remains a challenge for otologists. The pathogenesis of CSOM is believed to be intricately linked to changes in the middle ear microenvironment.(Frank et al., 2022, Neeff et al., 2016 ) Due to the limitations of early detection technologies, the middle ear was considered a sterile space.(Westerberg et al., 2009 , Hall-Stoodley et al., 2006 ) Consequently, CSOM was thought to be caused by pathogens that entered the middle ear from either the nasopharynx or external auditory canal.(Schilder et al., 2016 ) With the development of sequencing technology, however, it has been confirmed that the middle ear is not a sterile environment, suggesting that the occurrence and development of CSOM are related to disruption of the microbial balance.(Neeff et al., 2016 ) Although numerous bacteria have been confirmed to play significant roles in the pathology of CSOM, the involvement of fungi and other pathogens remains uncertain.(Daniel, 2012 , Shangali et al., 2023 ) The correlation between microbiome research findings and the treatment outcomes of CSOM patients also requires exploration.(Coleman et al., 2018 , Fujikawa et al., 2022 ) Therefore, a deeper understanding of the CSOM microbiota is needed for clinicians to develop optimal treatment strategies and prevent potential complications. Currently, hospitals routinely use culture techniques to identify the microbiota of CSOM. However, these methods are limited to the detection of specific microorganisms, overlooking other potentially significant pathogens. Moreover, many microorganisms are extremely difficult to culture under standard conditions, leading to possible omission of these crucial pathogens.(Suttle et al., 2024 , Chen et al., 2022 ) The collection of ear secretion samples also poses a risk of contamination by microorganisms from the external auditory canal, compromising the accuracy of detection results. To overcome these limitations, gene sequencing technology has been introduced to characterize the microbiota community composition in the middle ear. Although 16S rRNA sequencing can provide more comprehensive information about the middle ear microbiota, it generally offers only genus -level classification and cannot effectively identify other microorganisms, such as fungi.(Frank et al., 2022, Neeff et al., 2016 ) Moreover, 16S rRNA sequencing cannot directly provide information about microbial metabolic functions. Although whole metagenome shotgun sequencing can provide precise, reliable microbial information at the species level, this technique is time-consuming and costly. Additionally, ear swab samples often fail to meet the quality and quantity requirements necessary for whole metagenome shotgun sequencing.(Chen et al., 2023 , Ordinola-Zapata et al., 2024 , Schlegel et al., 2023 ) As a result, there is an urgent need for alternative techniques in CSOM microbiota research to overcome these challenges. Here, we introduce 2b-RAD sequencing for the Microbiome (2b-RAD-M), a novel sequencing method, to the CSOM microbial community study. This method uses type IIB restriction enzymes to digest the genomic DNA of the samples, producing DNA fragments of uniform length. These fragments are then amplified for sequencing and mapped to species -specific 2b-RAD markers for microbial characterization and quantification.(Xiao et al., 2024 , Huang et al., 2024 , Lam et al., 2022 ) By overcoming the limitations of conventional sequencing methods and microbial culture, 2b-RAD-M sequencing provides a comprehensive, species -resolved microbial profile of the CSOM microenvironment and enables prediction of therapeutic outcomes, allowing for prophylactic treatment in patients at risk of tympanic membrane perforation. We believe this innovative technological approach holds the potential to prognosticate surgical outcomes in CSOM and provide novel insights into therapeutic strategies. Methods Ethical Considerations The Ethics Committee of the Eye and ENT Hospital, Fudan University, approved the study protocol (approval number: 20200423) on April 23, 2020. The study was registered with the Chinese Clinical Trial Register (ChiCTR: 2000038981). Sample collection Surgery was performed under general anesthesia and sterile conditions. Swabs for microbial collection (Copan Italia) were rubbed against the middle ear mucosa during the operation. Effort was made to minimize contact with external skin to avoid contamination with skin flora. The swab stems were cut with sterile scissors; the collection tube was closed, sealed, and labeled. All samples were stored at − 40°C until shipment to OE BioTech, Qingdao on dry ice for 2b-RAD-M. Genomic DNA extraction, library preparation, and metagenomic sequencing Genomic DNA was extracted using the TIANamp Micro DNA Kit (Tiangen, Beijing, China) with the addition of carrier RNA to enhance yield. The extracted DNA was eluted in 20 µL of RNase-free water. Four units of Bcg I restriction enzyme (NEB, United States) were used to digest the genomic DNA at 37°C for 3 h. Subsequently, ligation with 0.2 µM of library-specific adaptors (Ada1 and Ada2) was performed at 4°C for 16 h, followed by heat inactivation at 65°C for 20 min. The ligation products were amplified by polymerase chain reaction (PCR) using 7 µL of ligated DNA, 0.1 µM of primers, 0.3 mM of dNTPs, 1× Phusion HF buffer, and 0.4 U of Phusion High Fidelity DNA Polymerase (NEB, USA). The PCR protocol consisted of 16–28 cycles of 98°C for 5 s, 60°C for 20 s, and 72°C for 10 s, with a final 10-min extension at 72°C. The library products were purified using the QIAquick PCR Purification Kit (QIAGEN) and sequenced on an Illumina HiSeq X™ Ten platform. Sequence processing and analysis Reads were scanned for the type IIB restriction enzyme recognition site, and sequences containing enzyme fragments were extracted. Clean reads were generated by the removal of reads that either contained more than 8% ambiguous bases or were classified as low-quality (more than 20% of bases with a quality value below Q30). Taxonomic classification was performed using a custom 2b-RAD-tag database, which included species from 173,165 microbial genomes (bacteria, bacteriophages, and archaea). Read coverage was determined for each identified genome to estimate the relative abundance of each taxon. Taxa were included in the downstream analysis if they had at least five taxon-specific 2b-RAD-tags and at least 15 sequenced reads. To assess potential cross-contamination during preparation, the ATCC® MSA-1002™ mock microbial community, consisting of 20 bacterial species with a genomic DNA abundance of ~ 5 ng, was processed along with the experimental samples. To control for false-positive species identification, a G score was calculated for each species as follows: G score species i = √(Si × ti), where Si is the number of reads assigned to all 2b-RAD-tags belonging to species i in the sample, and ti is the number of all possible 2b-RAD-tags of species i sequenced in the sample. The G score, which represents the harmonic mean of the read coverage of the 2b-RAD-tags of a species and the number of all possible 2b-RAD-tags for that species , was used to identify false positives with a threshold of 10. Finally, a secondary, sample-specific 2b-Tag-DB was constructed using only the identified candidate taxa; each taxon contained more specific 2b-RAD-tags compared with the default database. All reads were then re-mapped against this refined database to provide a more accurate assessment of the relative abundance of the candidate taxa. Sequences for these specimens are available in the NCBI Sequence Read Archive (SRA) under BioProject accession PRJNA1295442. Microbial diversity analysis Based on the classification abundance profile, the Chao1, Shannon, and Simpson alpha diversity indices were calculated using the "vegan" package and visualized as box plots. Beta diversity was estimated using Bray–Curtis, Binary Jaccard, and Euclidean distance metrics calculated by the "vegan" package, and visualized using Principal Coordinate Analysis (PCoA). Venn diagrams were used to visualize the unique and shared species between the PO and NPO groups. Linear discriminant analysis effect size (LEfSe) was used to identify differentially abundant taxa between the PO and NPO groups, with a log LDA score threshold of 2.0. Functions were predicted using Clusters of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Statistical analysis Statistical analyses were performed using SPSS (ver. 26) and R (ver. 4.1.1). The Wilcoxon test was used for pairwise comparisons of alpha diversity between groups, whereas permutational multivariate analysis of variance was used to compare beta diversity. The Kruskal–Wallis test was used to compare microbial communities among the PO, CON, and NPO groups. For functional predictions (COG and KEGG), the Wilcoxon test was used to analyze differences between groups. The threshold for statistical significance was set at p < 0.05. Results Patient characteristics and study design Middle ear swabs were obtained during surgery from 20 patients who underwent tympanoplasty between May 2020 and November 2021 at the Eye and ENT Hospital of Fudan University, Shanghai, China. The same treatment team evaluated the preoperative imaging and performed the surgical resection in all patients. Patients with CSOM were divided into perforation (PO) and non-perforation (NPO) groups based on whether perforation recurred postoperatively. Patients with otosclerosis and no inflammation were used as controls. Patient demographic information is presented in Table 1 . Table 1 Demographic and clinical characteristics of enrolled patients Group Patient Sex Age Side NPO NPO-1 F 21 Left NPO NPO-2 M 63 Right NPO NPO-3 M 66 Right NPO NPO-4 F 34 Left NPO NPO-5 F 45 Left NPO NPO-6 F 54 Left NPO NPO-7 M 38 Right NPO NPO-8 M 71 Left NPO NPO-9 F 70 Left NPO NPO-10 F 66 Left NPO NPO-11 F 62 Right NPO NPO-12 M 53 Right NPO NPO-13 M 30 Left PO PO-1 F 44 Right PO PO-2 F 70 Left PO PO-3 F 56 Right PO PO-4 F 19 Right CON CON-1 M 38 Left CON CON-2 F 36 Left CON CON-3 F 43 Right Microbial diversity of the middle ear specimens The obtained reads were aligned using 2b-Tag-DB and subsequently classified into 875 distinct microbial categories at the species level. Venn diagram analysis (Fig. 1 A) revealed 54 microbial species common to the three groups, whereas 320, 215, and 99 species were exclusive to the NPO, PO, and CON groups, respectively. For alpha diversity, the Shannon and Simpson indexes were calculated to evaluate community diversity; Chao1 was calculated to evaluate the community richness of the middle ear microbiome. These three indexes showed no significant difference among the NPO, PO, and CON groups. Both the PO and NPO groups with middle ear infection differed from the CON group without inflammation, but these differences were non-significant. The control group had greater richness and diversity. Although minimal differences were observed between the PO and NPO groups, the NPO group had greater richness and diversity, approaching that of the control group without inflammation. For beta diversity, PCoA revealed no differences in bacterial composition among the three groups based on Bray–Curtis, binary Jaccard, and Euclidean distances. Microbial community composition in the three groups Fungi (e.g., Agaricomycetes, Sordariomycetes, Blastocladiomycetes), Archaea (e.g., Halobacteria), and Eubacteria (e.g., Chlamydiia and Bacteroidia) were detected at the class level. Nineteen phyla were identified in the three groups, and Proteobacteria was the dominant phylum in all three groups (Fig. 2 A). At the class level, Gammaproteobacteria were the most prevalent in all three groups (Fig. 2 B). Moraxella was the dominant genus in the control group, whereas Pseudomonas was most prevalent in both the PO and NPO groups, comprising 74.7% of the perforated group (Fig. 2 C). In the three groups, 875 different species were detected. Pseudomonas aeruginosa , Sphingomonas sp. 000797515, Porphyromonas uenonis , and Fenollaria massiliensis were the most common species in the PO group. Staphylococcus aureus , P . aeruginosa , and Achromobacter xylosoxidans were the most common species in the NPO group. Finally, Moraxella catarrhalis , Cutibacterium acnes , and Ralstonia sp. 000620465 were the most common species in the control group. M . catarrhalis was present in 26.9% of the normal group but absent from both the NPO and PO groups (Fig. 2 D). Differential abundances of microbial taxa To characterize the differential representation of microorganisms, we performed Kruskal–Wallis analysis of taxonomic differences. This analysis revealed significant increases in the abundances of Acinetobacter johnsonii , Escherichia flexneri , Ralstonia pickettii , and other species at the species level in the CON group relative to both the PO and NPO groups (Figure S1 ). For the NPO and PO groups, at the phylum level, the abundances of Actinobacteriota, Ascomycota, and Basidiomycota significantly increased in the NPO group, whereas the NPO group had a significantly lower abundance of Chlamydiota compared with the PO group. Regarding genera, Acinetobacter , Bacillus , Corynebacterium , Cutibacterium , and Malassezia were significantly more abundant in the NPO group; Chlamydophila was more abundant in the PO group (Figure S2 ). At the species level, Bacillus bombysepticus , Burkholderia oklahomensis , Corynebacterium kefirresidentii , and C . acnes were more enriched in the NPO group, whereas P . aeruginosa , Pseudomonas alcaligenes , Pseudomonas protegens , Pseudomonas qingdaonensis , Pseudomonas sp. 003696305, Pseudomonas thermotolerans , Pseudomonas nitroreducens , and Pseudomonas panipatensis were more enriched in the PO group (Fig. 3 A). We also used LEfSe to identify differentially abundant taxa in the three groups. Nodes in each layer represent phylum/class/order/family/genus from inside out, respectively; the annotations of species markers in each layer represent phylum/class/order/family/genus (Fig. 3 B). LEfSe identified 15 discriminative features (LDA score ≥ 2.0) with significantly different relative abundances between the PO and NPO groups (Fig. 3 C). At the genus level, the microbiome of the NPO group was enriched with Bacillus , Corynebacterium , Cutibacterium , and Acinetobacter , whereas that of the PO group was enriched with Chlamydophila . At the species level, taxa that differentiated the two groups were B . bombysepticus , B . oklahomensis , C . kefirresidentii , and C . acnes in the NPO group and P . aeruginosa , P . thermotolerans , P . nitroreducens , and P . panipatensis in the PO group. These significantly different bacterial taxa can be used as indicators to distinguish the two groups (Fig. 3 B, C). Model prediction analysis in the three groups The indicator values of the species in each group were calculated, and statistical analysis was performed on the indicator values between the groups ( p < 0.05); this approach revealed the index species of each group, which were species with high group specificity. In the NPO group, the indicators were B . bombysepticus , Ralstonia sp. 000620465, C . acnes , and Sphingomonas sp. 000797515; conversely, P . protegens , P . alcaligenes , P . qingdaonensis , Pseudomonas sp. 003696305, P . aeruginosa , P . panipatensis , P . thermotolerans , and P . nitroreducens were indicators in the PO group (Fig. 4 A). Several species were correlated between the NPO and PO groups indicating close associations among them, including A . xylosoxidans , Porphyromonas sp. 900548415, F . massiliensis , Metamycoplasma salivarium , Porphyromonas somerae , Prevotella timonensis , Campylobacter rectus , and P . uenonis . Notably, Porphyromonas sp. 900548415 had the strongest association with the other species (Fig. 4 B). To assess the importance of the top 30 species based on relative abundance, we conducted random forest analysis (Fig. 4 C). Species importance point plots showed that P . aeruginosa was the most important species between the NPO and PO groups. The accuracy of using P . aeruginosa to identify postoperative perforations was assessed through receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) was 0.25, indicating relatively low accuracy using this species was used to detect perforation. In contrast, B . bombysepticus was more accurate (AUC = 0.92). The random forest model revealed that although B . bombysepticus had a large Gini index, suggesting strong predictive power, its mean decrease in accuracy was smaller than that of P . aeruginosa . This suggests that while B . bombysepticus may be a more accurate predictor of postoperative perforations, P . aeruginosa has a greater overall impact on model performance. The control group had numerous indicator species that distinguished it from the NPO and PO groups, including Methylobacterium fujisawaense , Ralstonia sp. 001078575, Brevundimonas aurantiaca , Malassezia globosa , A . johnsonii , Corynebacterium resistens , Nocardioides sp. 009699265, C . acnes , Blastomonas ursincola , Afipia broomeae , Tardiphaga sp. 002256345, and Xanthomonas campestris (Figure S3A). These indicator species likely play important roles in the maintenance of a normal microbial microenvironment in the middle ear. Moreover, positive correlations were observed in the correlation network diagram (Figure S3B). Pseudomonas , Aspergillus , and Achromobacter were identified as the most important genera in the NPO, PO, and CON groups, respectively, consistent with the three most important species in the NPO and PO groups. This finding indicates close relationships of these three species with postoperative outcomes and the presence of middle ear infections (Figure S3C). Differences in predictive functions among the three groups For the identified microbiota, we predicted their functions and used the Wilcoxon test to compare the NPO, PO, and CON groups. We identified COGs that differed among the three groups; the top five COGs were COG2207 (AraC-type DNA-binding domain and AraC-containing proteins), COG1269 (A/V-type ATP synthase), COG4974 (site-specific recombinase XerD), COG1289 (uncharacterized membrane protein YccC), and COG0564 (pseudouridine synthase RluA, 23S rRNA- or tRNA-specific) (Fig. 5 A). Analyses were performed based on the KEGG database of gene protein sequences (KEGG Genes), chemicals with endogenous and exogenous properties (KEGG Ligand), molecular interactions and metabolic pathways (KEGG Pathway), and hierarchical relationships among various organisms (KEGG Brite). The top three pathways with significant differences included putative ABC transport system permease protein (K02004), TatD DNase family protein (K03424), and nuclear receptors (K03310) (Fig. 5 B). Discussion Early research suggested that a healthy middle ear is typically sterile, highlighting the crucial role of pathogens from adjacent organs, such as the external auditory canal or eustachian tube, in the occurrence and development of CSOM. Given that these studies relied primarily on culture techniques and early molecular identification techniques, and that most microorganisms in nature are difficult or impossible to culture, hospital laboratory diagnoses may overlook unidentified bacteria, viruses, and fungi. Additionally, the limited quantity of DNA from ear secretions can also lead to false-negative PCR test results. The emerging DNA sequencing technology has unique advantages for the characterization of microbial communities in the middle ear. 16s rRNA sequencing-based research revealed that the healthy middle ear is not sterile but has a complex microbial ecology consisting of various microorganisms, which suggests a different pathogenesis theory for CSOM. Nevertheless, these studies may not accurately reflect the true middle ear microbial community, thereby affecting the accuracy and reliability of clinical diagnoses. Furthermore, the limited resolution of 16S rRNA sequencing, which identifies microorganisms only at the genus level, may have difficulty distinguishing closely related species , which is crucial for the development of effective treatment strategies. Here, 2b-RAD-M was used to provide a more detailed and comprehensive depiction of the middle ear microbiome in patients with otosclerosis (as an analogy to a healthy middle ear environment) and in CSOM patients with or without postoperative tympanic membrane perforation. In this study, the detection of numerous microorganisms in healthy middle ears supported the evidence that the healthy middle ear is not sterile. Additionally, no significant differences in the alpha or beta diversity of microorganisms were observed among the CON, PO, and NPO groups, indicating that the middle ear microbiota of CSOM patients is similar to that of healthy individuals. The conventional view is that the middle ear should normally be free of fungi, and the presence of a fungal infection in CSOM significantly increases the difficulty of treatment. Intriguingly, fungi were detected in the CON group in this study, suggesting their involvement in the maintenance of microbial balance in the healthy middle ear.(Chen et al., 2022 ) We also observed that Aspergillus , one of the most common pathogens in otomycosis, was significantly more abundant in the NPO group than in the PO group, suggesting that it can serve as an indicator to distinguish between these two groups.(Bojanović et al., 2022 , Bojanović et al., 2023 ) One possible explanation for this is that tympanic membrane perforation may lead to better ventilation and drainage, thereby inhibiting fungal growth. Another explanation is that patients with recurrent tympanic membrane perforations tend to use antibiotics more frequently, which suppresses the growth of fungi. Archaea, a unique class of single-celled microorganisms, also were detected in the middle ear of the CON group. To our knowledge, however, no studies have examined the presence and role of archaea in the middle ear microenvironment. Whether archaea play a role in the maintenance of microbial balance and immune regulation in the middle ear, similar to their role in the gut, merits further investigation.(Shi and Mu, 2017 , Wei et al., 2024 ) At the genus level, Pseudomonas was the dominant genus in both CSOM groups; its proportion was higher in PO (74.7%). Notably, other than P . aeruginosa , which is considered the most common pathogen associated with CSOM, the abundances of Pseudomonas species such as P . alcaligenes , P . protegens , P . qingdaonensis , Pseudomonas sp. 003696305, P . thermotolerans , P . nitroreducens , and P . panipatensis were significantly higher in the PO group than in the NPO group, suggesting that these species play important roles in the recurrence of tympanic membrane perforation. Because these Pseudomonas species are primarily found in the environment rather than in the human body, their presence in the middle ear suggests compromised immune function in CSOM patients with tympanic membrane perforation.(Miloloža et al., 2022 , Garrido-Sanz et al., 2023 , Lin et al., 2023 ) Our findings show that 2b-RAD-M can provide species -level microbial information, offering valuable guidance for the treatment of CSOM because these Pseudomonas species may have different sensitivities to antibiotics. Based on Kruskal–Wallis and LEfSe analyses, Acinetobacter guillouiae , B . bombysepticus , B . oklahomensis , C. kefirresidentii , and C . acnes were significantly more abundant in the NPO group than in the PO group. However, the involvement of these bacteria in CSOM remains unclear because few relevant reports have been published. We note that B . bombysepticus and C . kefirresidentii were not detected in either the CON or PO groups. We hypothesize that the relatively closed stable environment provided by the repaired tympanic membrane may allow these exogenous bacterial species to colonize and proliferate, ultimately contributing to the reconstruction of middle ear microbial homeostasis in CSOM patients after surgical intervention and systemic antibiotic therapy. The other three bacteria, A . guillouiae , B . oklahomensis , and C . acnes , were significantly more abundant in the NPO group than in the PO group; they were less abundant in the CON group. This finding suggests that major CSOM pathogens, such as P . aeruginosa , disrupt the microbial balance in the middle ear during an infection and significantly inhibit the growth of these three bacteria. During recovery, these bacteria may aid in the restoration of microbial homeostasis as resident flora, potentially preventing the recurrence of tympanic membrane perforation. M . catarrhalis , C . acnes , and Ralstonia sp. 000620465 were the dominant bacteria in the CON group. Of note, M . catarrhalis had a prevalence of 26.9% in the CON group, whereas it was entirely absent from both the NPO and PO groups. Although reports have suggested that M . catarrhalis , as a resident bacterium in the middle ear, constitutes a potential endogenous source of infection in CSOM, our results indicate that CSOM-induced dysbiosis of the middle ear microbiota may inhibit the survival of M . catarrhalis .(Mittal et al., 2014 ) Furthermore, M . catarrhalis may have a protective role in maintaining a healthy middle ear environment. Previous studies often have neglected to connect middle ear microbiota data with the clinical outcomes of CSOM. We performed random forest analysis on the 2b-RAD-M microbial data and found that B . bombysepticus had a high NPO indicator value, whereas P . aeruginosa had a high PO indicator value. ROC curve analysis was used to evaluate the reliabilities of these bacteria in distinguishing between NPO and PO. Intriguingly, although P . aeruginosa was significantly more abundant in the PO group, its ability to distinguish between the two groups was poor (AUC = 0.25). In contrast, B . bombysepticus may be a potential diagnostic biomarker for preventing tympanic membrane perforation after surgery for CSOM, considering its impressive AUC of 0.92. Functional annotation analyses were performed to compare differences in microbial function among the three groups. The COG and KEGG function predictions indicated enhancement of specific microbial functions in the PO group relative to the NPO and CON groups. Specifically, the increased abundances of COG4771, COG1269, COG0534, K02004, K03310, K03561, and K03327 suggest enhanced gene regulation and expression. The elevated levels of COG2207, COG4974, COG0564, COG1476, and COG0492 indicate improved efficiency in substance transport and metabolism. Additionally, the higher abundances of K03324 and K03630 imply enhanced DNA repair capabilities. The synergistic actions of these pathways ensure that microorganisms can efficiently perform metabolic activities, safeguard the stability of genetic material, maintain normal physiological activities and homeostasis, and ultimately better adapt and survive in harsh environments. Conclusion This is the first study to use 2b-RAD-M to analyze the middle ear microbiota in patients with CSOM and otosclerosis. The results provide more comprehensive data concerning the middle ear microbiota, suggesting potential mechanisms by which various microorganisms contribute to the pathogenesis and progression of CSOM. Importantly, we identify B . bombysepticus as a potential diagnostic biomarker that can indicate an increased risk of tympanic membrane re-perforation. We believe that our study offers a new target for predicting postoperative outcomes in CSOM patients. Abbreviations AUC, area under the curve COGs, clusters of orthologous groups CON, otosclerosis (control) CSOM, chronic suppurative otitis media KEGG, Kyoto Encyclopedia of Genes and Genomes LEfSe, linear discriminant analysis effect size NPO, non-perforation PCoA, principal coordinate analysis PCR, polymerase chain reaction PO, perforation ROC, receiver operating characteristic curve Declarations Ethics approval and consent to participate Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper. The Ethics Committee of the Eye and ENT Hospital, Fudan University, approved the study protocol (approval number: 20200423) on April 23, 2020. The study was registered with the Chinese Clinical Trial Register (ChiCTR: 2000038981). Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no conflict of interest. Funding This study is supported by the National Natural Science Foundation of China (grants 82271166, 81970880, and 81771017 to Dongdong Ren); Natural Science Foundation of Shanghai (grant 22ZR1410100 to Dongdong Ren); the “Zhuo-Xue Plan” of Fudan University (Dongdong Ren); Heng-Jie special technical support plan (Dongdong Ren); and the Shanghai Outstanding Young Medical Talent Program (Dongdong Ren). Authors' contributions Xiao Fu and Yuming Chen have contributed equally to this work and share first authorship. Conceptualization, Binjun Chen, Jianghong Xu and Dongdong Ren; Data curation, Xiao Fu and Yuming Chen; Formal analysis, Xiao Fu and Yanmei Wang; Funding acquisition, Dongdong Ren; Investigation, Jihan Lyu, Haojie Sun and Mengke Chen; Methodology, Xiao Fu and Yanmei Wang; Project administration, Jianghong Xu and Dongdong Ren; Resources, Dongdong Ren; Supervision, Zhujian Wang, Genglin Li and Dongdong Ren; Visualization, Dongdong Ren; Writing – original draft, Xiao Fu and Yuming Chen; Writing – review & editing, Jianghong Xu, Genglin Li and Dongdong Ren Acknowledgements We thank all the patients who participated in our study. References BHUTTA MF, LEACH, A. J., BRENNAN-JONES CG (2024) Chronic suppurative otitis media. Lancet 403:2339–2348 BHUTTA MF, THORNTON, R. B., KIRKHAM, L. S., KERSCHNER, J. E., CHEESEMAN MT (2017) Understanding the aetiology and resolution of chronic otitis media from animal and human studies. Dis Model Mech 10:1289–1300 BOJANOVIĆ M, STALEVIĆ IGNJATOVIĆA, ARSIĆ-ARSENIJEVIĆ M, RANĐELOVIĆ V, STOJANOVIĆ-RADIĆ MGERGINIĆV, ŽIVKOVIĆ-MARINKOV ZSTOJKOVIĆO, E., OTAŠEVIĆ S (2022) Clinical Presentations, Cluster Analysis and Laboratory-Based Investigation of Aspergillus Otomycosis-A Single Center Experience. J Fungi (Basel), 8 BOJANOVIĆ M, ARSIĆ-ARSENIJEVIĆ STALEVIĆM, IGNJATOVIĆ V, RANĐELOVIĆ A, GOLUBOVIĆ M, ŽIVKOVIĆ-MARINKOV M, KORAĆEVIĆ E, STAMENKOVIĆ G (2023) B. & OTAŠEVIĆ, S. Etiology, Predisposing Factors, Clinical Features and Diagnostic Procedure of Otomycosis: A Literature Review. J Fungi (Basel) , 9 CHADHA S, KAMENOV K, CIEZA A (2021) The world report on hearing, 2021. Bull World Health Organ 99:242–242a CHEN C, ZHANG Y, YAO X, LI YANQ, ZHONG S, LIU Q, TANG Z, LIU F, LI C, ZHU H, LING DLANW, LU Y, XU D, WANG HNINGQ, JIANG Y, WANG ZZHANGQGUGSUNL, N., WANG, G., ZHANG, A., ULLAH, H., SUN, W., MA W (2023) Characterizations of the multi-kingdom gut microbiota in Chinese patients with gouty arthritis. BMC Microbiol 23:363 CHEN CH, CHENG WANGCY, HSIH MY, W. H., TIEN, N., CHOU, C. H., LIN, P. C., CHI, C. Y., HO, M. W., LU MC (2022) Definite therapy of mixed infection alleviates refractory dilemma of adult chronic suppurative otitis media. J Microbiol Immunol Infect 55:1283–1292 COLEMAN A, WOOD A, BIALASIEWICZ S, WARE, R. S., MARSH, R. L., CERVIN A (2018) The unsolved problem of otitis media in indigenous populations: a systematic review of upper respiratory and middle ear microbiology in indigenous children with otitis media. Microbiome 6:199 DANIEL SJ (2012) Topical treatment of chronic suppurative otitis media. Curr Infect Dis Rep 14:121–127 DHINGRA S, VIR D, BAKSHI, J., RISHI P (2023) Mapping of audiometric analysis with microbiological findings in patients with chronic suppurative otitis media (CSOM): a neglected clinical manifestation. Crit Rev Clin Lab Sci 60:212–232 FRANK DN, BOOTPETCH MAGNOJPMVELASCOKJS, SALUD TC, MILLER JEDDAVIDKJV, PYLES ALYEEECDULNUANHP, GUCE RBLACUATAJACARBIZOJLKOFONOWJM, MENDOZA B K. M. D., ROBERTSON, C. E., ILUSTRE, G. M. S., CHIONG, A. N. E., LU, S. L., TONGOL, E. A., SACAYAN, N. D., YARZA, T. K. L., CHIONG, C. M. & SANTOS-CORTEZ, R. L. P. 2022. Microbiota Associated With Cholesteatoma Tissue in Chronic Suppurative Otitis Media. Front Cell Infect Microbiol , 12, 746428 FUJIKAWA T, TANIMOTO K, KAWASHIMA Y, ITO T, HONDA K, TAKEDA T, AOKI SONOBEA, BAI N, J., TSUTSUMI T (2022) Cholesteatoma has an altered microbiota with a higher abundance of Staphylococcus species . Laryngoscope Investig Otolaryngol 7:2011–2019 GARRIDO-SANZ D, HEIMAN ČAUŠEVIĆSVACHERONJ, SENTCHILO CM, VAN DER MEER V, J. R., KEEL C (2023) Changes in structure and assembly of a species -rich soil natural community with contrasting nutrient availability upon establishment of a plant-beneficial Pseudomonas in the wheat rhizosphere. Microbiome 11:214 HALL-STOODLEY L, GIESEKE HUFZ, NISTICO A, NGUYEN L, FORBES DHAYESJ, DICE MGREENBERGDP, STOODLEY BBURROWSAWACKYMPA, EHRLICH PPOSTJC, G. D., KERSCHNER JE (2006) Direct detection of bacterial biofilms on the middle-ear mucosa of children with chronic otitis media. JAMA 296:202–211 HUANG X, LI ZENGJ, CHEN S, WANG J, LI H, C., ZHANG S (2024) 16S rRNA, metagenomics and 2bRAD-M sequencing to decode human thanatomicrobiome. Sci Data 11:736 LAM T, CHEW D, ZHAO H, ZHU P, ZHANG L, DAI Y, LIU J, XU J (2022) Species -Resolved Metagenomics of Kindergarten Microbiomes Reveal Microbial Admixture Within Sites and Potential Microbial Hazards. Front Microbiol 13:871017 LIN C, LI LJ, ISABWE RENKZHOUSY, YANG A, YANG LYNEILSONR, X. R., CYTRYN, E., ZHU YG (2023) Phagotrophic protists preserve antibiotic-resistant opportunistic human pathogens in the vegetable phyllosphere. ISME Commun 3:94 MILOLOŽA M, CVETNIĆ UKIĆŠ, BOLANČA M, T., KUČIĆ GRGIĆ D (2022) Optimization of Polystyrene Biodegradation by Bacillus cereus and Pseudomonas alcaligenes Using Full Factorial Design. Polym (Basel), 14 MITTAL R, GRATI M, GERRING R, BLACKWELDER P, LI YAND, J. D., LIU XZ (2014) In vitro interaction of Pseudomonas aeruginosa with human middle ear epithelial cells. PLoS ONE 9:e91885 NEEFF M, HOGGARD BISWASK, M., TAYLOR, M. W., DOUGLAS R (2016) Molecular Microbiological Profile of Chronic Suppurative Otitis Media. J Clin Microbiol 54:2538–2546 NGUYEN CT, JUNG W, KIM J, CHANEY EJ, NOVAK M (2012) STEWART, C. N. & BOPPART, S. A. Noninvasive in vivo optical detection of biofilm in the human middle ear. Proc Natl Acad Sci U S A , 109, 9529-34 ORDINOLA-ZAPATA R, COSTALONGA M, DIETZ M, LIMA, B. P., STALEY C (2024) The root canal microbiome diversity and function. A whole-metagenome shotgun analysis. Int Endod J 57:872–884 SANTA MARIA PL, BACACAO KAUFMANAC, THAI B, CHEN A, CAO XXIAA, Z., FOUAD, A., BEKALE LA (2021) Topical Therapy Failure in Chronic Suppurative Otitis Media is Due to Persister Cells in Biofilms. Otol Neurotol 42:e1263–e1272 SCHILDER AG, CHONMAITREE T, ROSENFELD CRIPPSAW, HAGGARD RMCASSELBRANTML (2016) M. P. & VENEKAMP, R. P. Otitis media. Nat Rev Dis Primers , 2, 16063 SCHLEGEL I, DE GOÜYON MATIGNON DE PONTOURADE CMF, KELLER LINCKEJB, ZINKERNAGEL I, M. S., ZYSSET-BURRI DC (2023) The Human Ocular Surface Microbiome and Its Associations with the Tear Proteome in Dry Eye Disease. Int J Mol Sci, 24 SHANGALI A, KAMORI D, MASSAWE W, MASOUD S, KIBWANA U, MWANDIGHA MWINGWAAGMANISHAA, MIRAMBO AM, MANYAHI MMMSHANASE, J., MAJIGO M (2023) Aetiology of ear infection and antimicrobial susceptibility pattern among patients attending otorhinolaryngology clinic at a tertiary hospital in Dar es Salaam, Tanzania: a hospital-based cross-sectional study. BMJ Open 13:e068359 SHI Y, MU L (2017) An expanding stage for commensal microbes in host immune regulation. Cell Mol Immunol 14:339–348 SIDAM S, GUPTA SAHOOAKMISHRAUP, KUSHWAH V, A., SAHOO PK (2024) Impact of Chronic Suppurative Otitis Media on Quality of Life and Psychological Well-Being: A Cross-Sectional Study. Cureus 16:e54150 SUTTLE TK, ELS T, CURTIS TOMANJ, SIZEMORE DMCNABR, VAN A, CLEVE M, BROMBACHER RA (2024) Chronic Suppurative Otitis Media: A Prospective Descriptive Study of the Microbiology and Antimicrobial Susceptibility Patterns. Otolaryngol Head Neck Surg 171:90–97 WEI M, LIU H, SUN WANGY, M., SHANG P (2024) Mechanisms of Male Reproductive Sterility Triggered by Dysbiosis of Intestinal Microorganisms. Life (Basel), 14 WESTERBERG BD, BLONDEL-HILL KOZAKFKTHOMASEE, E., BRUNSTEIN, J. D., PATRICK DM (2009) Is the healthy middle ear a normally sterile site? Otol Neurotol 30:174–177 XIAO K, LI H, LI Y, ZHAN B, ZHAO FANGX, ZHANG B, WU X, WANG Y, F., JIA Y (2024) Protective effects and mechanism of Sangyu granule on acetaminophen-induced liver injury in mice. J Ethnopharmacol 331:118282 Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Published Journal Publication published 20 Mar, 2026 Read the published version in Applied Microbiology and Biotechnology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7068085","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498141841,"identity":"342325b5-1f7f-4691-8ca0-b46af6e1b9ef","order_by":0,"name":"Xiao Fu","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Fu","suffix":""},{"id":498141842,"identity":"8b480a67-179c-4267-ad1a-60d3369c4965","order_by":1,"name":"Yuming Chen","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Yuming","middleName":"","lastName":"Chen","suffix":""},{"id":498141845,"identity":"75a0369a-b750-4d5a-adf4-c236a294f024","order_by":2,"name":"Yanmei Wang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Yanmei","middleName":"","lastName":"Wang","suffix":""},{"id":498141847,"identity":"d89f3ec2-7752-43dc-8443-3c6866b9e63d","order_by":3,"name":"Binjun Chen","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Binjun","middleName":"","lastName":"Chen","suffix":""},{"id":498141849,"identity":"758248e0-67a6-4c74-9af0-4fa46f69e6b5","order_by":4,"name":"Mengke Chen","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Mengke","middleName":"","lastName":"Chen","suffix":""},{"id":498141850,"identity":"f9b3849a-4827-4317-9561-757d842a6043","order_by":5,"name":"Jihan Lyu","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Jihan","middleName":"","lastName":"Lyu","suffix":""},{"id":498141851,"identity":"41fb44b1-bae9-478f-9d84-5cbc913b7723","order_by":6,"name":"Haojie Sun","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Haojie","middleName":"","lastName":"Sun","suffix":""},{"id":498141852,"identity":"8fba6c1d-80f5-4589-bae2-9f7d13b0bc48","order_by":7,"name":"Zhujian Wang","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Zhujian","middleName":"","lastName":"Wang","suffix":""},{"id":498141854,"identity":"05d28c0a-577e-46ad-b3f8-557b1841e529","order_by":8,"name":"Jianghong Xu","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Jianghong","middleName":"","lastName":"Xu","suffix":""},{"id":498141855,"identity":"cf383042-b5bb-4438-877c-f6e28d478add","order_by":9,"name":"Genglin Li","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Genglin","middleName":"","lastName":"Li","suffix":""},{"id":498141856,"identity":"dc8c9083-378c-4901-98a4-3fc49d1fe242","order_by":10,"name":"Dongdong Ren","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYDCCA0DMA2EyPqhgYAazJIjVwmxwhlQtbBJEaeE73nv4xZuKO3bb23uPVRxss5Y3Z2A+eJuHwS4PlxbJM+fSLOeceZY8B8i4cbAt3XBnA1uyNQ9DcjEuLQY3csyMedsOJ0tI5Jjd/th2mHHDAR4zaR6GA4kNBLXIvzErONh22H7DAf5vhLQYPwZqsZOQ4DFjAGpJBNrChleL5JkzZoxzzhxOkODJMZY4cC49ecNhNmPLOQbJOLXwHe8x/vCm4rC9BPsZww8HyqxtNxxvfnjjTYUdTi0MoOgAEkgKwFFjgFs9SMkHIGGPV8koGAWjYBSMbAAAgOxdy860VjUAAAAASUVORK5CYII=","orcid":"","institution":"Fudan University","correspondingAuthor":true,"prefix":"","firstName":"Dongdong","middleName":"","lastName":"Ren","suffix":""}],"badges":[],"createdAt":"2025-07-07 18:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7068085/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7068085/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00253-026-13770-9","type":"published","date":"2026-03-20T15:59:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89066330,"identity":"1342ed0b-87ef-4fcf-b891-a7ef4221a5c5","added_by":"auto","created_at":"2025-08-14 10:42:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":211057,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in microbial diversity and composition within the middle ear among the CON, NPO, and PO groups. (A) The Venn diagram shows the \u003cem\u003especies \u003c/em\u003edistribution among the CON, NPO, and PO groups, as well as interrelationships among these groups. (B) Comparison of alpha diversity (Chao1, Simpson, and Shannon) of the three groups. (C) The three groups were compared using the Bray–Curtis, binary Jaccard, and Euclidean distance beta diversity metrics. The results of this analysis were visualized using 3D-PCoA plots, where each sample is represented by a point, and samples from the same group are shown in the same color. These plots provide insights into differences among the three groups based on the three distance matrices.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7068085/v1/62e9a1e9b3c49101b56d4b7a.png"},{"id":89066297,"identity":"2de1d5d5-61d3-4c63-9584-248faa553c50","added_by":"auto","created_at":"2025-08-14 10:42:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":560573,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of microbial composition and relative abundance in the three groups. (A) \u003cem\u003ePhylum\u003c/em\u003e- and (B) \u003cem\u003eclass\u003c/em\u003e-level relative abundances in the three groups. Bar charts show the top 30 most abundant (C) genera and (D) \u003cem\u003especies \u003c/em\u003ein the three groups.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7068085/v1/348fa491ad83db94ad33de2b.png"},{"id":89065979,"identity":"23b40dbd-705e-4f6a-afd9-cda7f92a4639","added_by":"auto","created_at":"2025-08-14 10:42:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":563911,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of differences in the abundance of microbial taxa between the NPO and PO groups. (A) Top 10 \u003cem\u003especies \u003c/em\u003ewith significant differences. (B) Differential \u003cem\u003especies \u003c/em\u003eannotated branching plots represent the taxonomic hierarchy of the discriminatory biomarkers identified with LEfSe. (C) Differential \u003cem\u003especies \u003c/em\u003escore plots present the \u003cem\u003especies \u003c/em\u003ewith relatively high abundances in each of the two groups.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7068085/v1/865c8d00d84206d2a0800eea.png"},{"id":89066116,"identity":"989cd67f-3337-41a8-aa69-48f4a6c55853","added_by":"auto","created_at":"2025-08-14 10:42:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":385891,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Indicator \u003cem\u003especies\u003c/em\u003e diagram of the PO and NPO groups. (B) \u003cem\u003eSpecies \u003c/em\u003ecorrelation network diagram depicting \u003cem\u003especies\u003c/em\u003e correlations between the PO and NPO groups. The figure shows \u003cem\u003especies \u003c/em\u003ewith a default threshold of |SpearmanCoef| \u0026gt; 0.8 and \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01. (C) \u003cem\u003eSpecies\u003c/em\u003e importance point diagram. Mean decreases in Gini and accuracy are important measures. (D) \u003cem\u003eP\u003c/em\u003e.\u003cem\u003e aeruginosa\u003c/em\u003e and \u003cem\u003eB\u003c/em\u003e.\u003cem\u003e bombysepticus\u003c/em\u003e had AUCs of 0.25 and 0.92, respectively, for identifying the PO and NPO groups.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7068085/v1/3c81937ead5ff774a66bd96f.png"},{"id":89066699,"identity":"5ea38cad-4681-47e7-8843-310befcd2a2e","added_by":"auto","created_at":"2025-08-14 10:42:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":463254,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in microbial function among groups according to functional annotation analysis. Results of the (A) COG and (B) KEGG function prediction for the top 10 most significant differences.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7068085/v1/d4a1eb7fe5b9ba114fc5c67d.png"},{"id":105223795,"identity":"51db0a7d-81f4-4375-86cb-03e38ce88027","added_by":"auto","created_at":"2026-03-23 16:11:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2842183,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7068085/v1/3dadc074-9596-46fa-a7c5-c08edc2c9f80.pdf"},{"id":89066653,"identity":"a5b38b04-d85b-434c-9967-8760c5755a06","added_by":"auto","created_at":"2025-08-14 10:42:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16083390,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7068085/v1/3c91aa260dc677c9b17656a9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Microbiota in Chronic Suppurative Otitis Media: Association with Postoperative Tympanic Membrane Outcomes","fulltext":[{"header":"Key Points","content":"\u003cul class=\"decimal_type\" start=\"50\"\u003e\n \u003cli\u003e2b-RAD-M technology enables comprehensive CSOM microbiota profiling and biomarker identification\u003c/li\u003e\n \u003cli\u003eBacillus bombysepticus (AUC=0.92) outperforms Pseudomonas aeruginosa in diagnostic accuracy\u003c/li\u003e\n \u003cli\u003eB. bombysepticus predicts postoperative tympanic membrane re-perforation via functional activity analysis\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eChronic suppurative otitis media (CSOM) is one of the most common otolaryngological diseases, characterized by persistent ear discharge through a perforated tympanic membrane for over 6 weeks. It is a global health issue, with more than 30\u0026nbsp;million new cases annually and an estimated global prevalence that exceeds 200\u0026nbsp;million cases.(Chadha et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) The hearing impairment and tinnitus associated with CSOM have long-term negative effects on patients\u0026rsquo; quality of life and mental health, creating a substantial financial burden(Sidam et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Although surgery and antibiotics are effective for CSOM treatment, the formation of bacterial biofilms and development of antimicrobial resistance can lead to treatment failure, which ultimately results in recurrence of tympanic membrane perforation.(Bhutta et al., 2024) (Nguyen et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Santa Maria et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)Furthermore, an inadequate understanding of the pathogenesis has hindered the development of new therapies.(Dhingra et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Bhutta et al., 2017) Thus, CSOM management remains a challenge for otologists.\u003c/p\u003e\u003cp\u003eThe pathogenesis of CSOM is believed to be intricately linked to changes in the middle ear microenvironment.(Frank et al., 2022, Neeff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) Due to the limitations of early detection technologies, the middle ear was considered a sterile space.(Westerberg et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Hall-Stoodley et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) Consequently, CSOM was thought to be caused by pathogens that entered the middle ear from either the nasopharynx or external auditory canal.(Schilder et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) With the development of sequencing technology, however, it has been confirmed that the middle ear is not a sterile environment, suggesting that the occurrence and development of CSOM are related to disruption of the microbial balance.(Neeff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) Although numerous bacteria have been confirmed to play significant roles in the pathology of CSOM, the involvement of fungi and other pathogens remains uncertain.(Daniel, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Shangali et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) The correlation between microbiome research findings and the treatment outcomes of CSOM patients also requires exploration.(Coleman et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Fujikawa et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) Therefore, a deeper understanding of the CSOM microbiota is needed for clinicians to develop optimal treatment strategies and prevent potential complications.\u003c/p\u003e\u003cp\u003eCurrently, hospitals routinely use culture techniques to identify the microbiota of CSOM. However, these methods are limited to the detection of specific microorganisms, overlooking other potentially significant pathogens. Moreover, many microorganisms are extremely difficult to culture under standard conditions, leading to possible omission of these crucial pathogens.(Suttle et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Chen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) The collection of ear secretion samples also poses a risk of contamination by microorganisms from the external auditory canal, compromising the accuracy of detection results. To overcome these limitations, gene sequencing technology has been introduced to characterize the microbiota community composition in the middle ear. Although 16S rRNA sequencing can provide more comprehensive information about the middle ear microbiota, it generally offers only \u003cem\u003egenus\u003c/em\u003e-level classification and cannot effectively identify other microorganisms, such as fungi.(Frank et al., 2022, Neeff et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) Moreover, 16S rRNA sequencing cannot directly provide information about microbial metabolic functions. Although whole metagenome shotgun sequencing can provide precise, reliable microbial information at the \u003cem\u003especies\u003c/em\u003e level, this technique is time-consuming and costly. Additionally, ear swab samples often fail to meet the quality and quantity requirements necessary for whole metagenome shotgun sequencing.(Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Ordinola-Zapata et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Schlegel et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) As a result, there is an urgent need for alternative techniques in CSOM microbiota research to overcome these challenges.\u003c/p\u003e\u003cp\u003eHere, we introduce 2b-RAD sequencing for the Microbiome (2b-RAD-M), a novel sequencing method, to the CSOM microbial community study. This method uses type IIB restriction enzymes to digest the genomic DNA of the samples, producing DNA fragments of uniform length. These fragments are then amplified for sequencing and mapped to \u003cem\u003especies\u003c/em\u003e-specific 2b-RAD markers for microbial characterization and quantification.(Xiao et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Huang et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Lam et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) By overcoming the limitations of conventional sequencing methods and microbial culture, 2b-RAD-M sequencing provides a comprehensive, \u003cem\u003especies\u003c/em\u003e-resolved microbial profile of the CSOM microenvironment and enables prediction of therapeutic outcomes, allowing for prophylactic treatment in patients at risk of tympanic membrane perforation. We believe this innovative technological approach holds the potential to prognosticate surgical outcomes in CSOM and provide novel insights into therapeutic strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eEthical Considerations\u003c/em\u003e\u003c/p\u003e\u003cp\u003e The Ethics Committee of the Eye and ENT Hospital, Fudan University, approved the study protocol (approval number: 20200423) on April 23, 2020. The study was registered with the Chinese Clinical Trial Register (ChiCTR: 2000038981).\u003c/p\u003e\u003cp\u003e\u003cem\u003eSample collection\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSurgery was performed under general anesthesia and sterile conditions. Swabs for microbial collection (Copan Italia) were rubbed against the middle ear mucosa during the operation. Effort was made to minimize contact with external skin to avoid contamination with skin flora. The swab stems were cut with sterile scissors; the collection tube was closed, sealed, and labeled. All samples were stored at \u0026minus;\u0026thinsp;40\u0026deg;C until shipment to OE BioTech, Qingdao on dry ice for 2b-RAD-M.\u003c/p\u003e\u003cp\u003e\u003cem\u003eGenomic DNA extraction, library preparation, and metagenomic sequencing\u003c/em\u003e\u003c/p\u003e\u003cp\u003eGenomic DNA was extracted using the TIANamp Micro DNA Kit (Tiangen, Beijing, China) with the addition of carrier RNA to enhance yield. The extracted DNA was eluted in 20 \u0026micro;L of RNase-free water. Four units of \u003cem\u003eBcg\u003c/em\u003eI restriction enzyme (NEB, United States) were used to digest the genomic DNA at 37\u0026deg;C for 3 h. Subsequently, ligation with 0.2 \u0026micro;M of library-specific adaptors (Ada1 and Ada2) was performed at 4\u0026deg;C for 16 h, followed by heat inactivation at 65\u0026deg;C for 20 min. The ligation products were amplified by polymerase chain reaction (PCR) using 7 \u0026micro;L of ligated DNA, 0.1 \u0026micro;M of primers, 0.3 mM of dNTPs, 1\u0026times; Phusion HF buffer, and 0.4 U of Phusion High Fidelity DNA Polymerase (NEB, USA). The PCR protocol consisted of 16\u0026ndash;28 cycles of 98\u0026deg;C for 5 s, 60\u0026deg;C for 20 s, and 72\u0026deg;C for 10 s, with a final 10-min extension at 72\u0026deg;C. The library products were purified using the QIAquick PCR Purification Kit (QIAGEN) and sequenced on an Illumina HiSeq X\u0026trade; Ten platform.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSequence processing and analysis\u003c/em\u003e\u003c/p\u003e\u003cp\u003eReads were scanned for the type IIB restriction enzyme recognition site, and sequences containing enzyme fragments were extracted. Clean reads were generated by the removal of reads that either contained more than 8% ambiguous bases or were classified as low-quality (more than 20% of bases with a quality value below Q30). Taxonomic classification was performed using a custom 2b-RAD-tag database, which included \u003cem\u003especies\u003c/em\u003e from 173,165 microbial genomes (bacteria, bacteriophages, and archaea). Read coverage was determined for each identified genome to estimate the relative abundance of each taxon. Taxa were included in the downstream analysis if they had at least five taxon-specific 2b-RAD-tags and at least 15 sequenced reads. To assess potential cross-contamination during preparation, the ATCC\u0026reg; MSA-1002\u0026trade; mock microbial community, consisting of 20 bacterial \u003cem\u003especies\u003c/em\u003e with a genomic DNA abundance of ~\u0026thinsp;5 ng, was processed along with the experimental samples. To control for false-positive \u003cem\u003especies\u003c/em\u003e identification, a G score was calculated for each \u003cem\u003especies\u003c/em\u003e as follows: G score \u003cem\u003especies\u003c/em\u003e i = \u0026radic;(Si \u0026times; ti), where Si is the number of reads assigned to all 2b-RAD-tags belonging to \u003cem\u003especies\u003c/em\u003e i in the sample, and ti is the number of all possible 2b-RAD-tags of \u003cem\u003especies\u003c/em\u003e i sequenced in the sample. The G score, which represents the harmonic mean of the read coverage of the 2b-RAD-tags of a \u003cem\u003especies\u003c/em\u003e and the number of all possible 2b-RAD-tags for that \u003cem\u003especies\u003c/em\u003e, was used to identify false positives with a threshold of 10. Finally, a secondary, sample-specific 2b-Tag-DB was constructed using only the identified candidate taxa; each taxon contained more specific 2b-RAD-tags compared with the default database. All reads were then re-mapped against this refined database to provide a more accurate assessment of the relative abundance of the candidate taxa. Sequences for these specimens are available in the NCBI Sequence Read Archive (SRA) under BioProject accession PRJNA1295442.\u003c/p\u003e\u003cp\u003e\u003cem\u003eMicrobial diversity analysis\u003c/em\u003e\u003c/p\u003e\u003cp\u003eBased on the classification abundance profile, the Chao1, Shannon, and Simpson alpha diversity indices were calculated using the \"vegan\" package and visualized as box plots. Beta diversity was estimated using Bray\u0026ndash;Curtis, Binary Jaccard, and Euclidean distance metrics calculated by the \"vegan\" package, and visualized using Principal Coordinate Analysis (PCoA). Venn diagrams were used to visualize the unique and shared \u003cem\u003especies\u003c/em\u003e between the PO and NPO groups. Linear discriminant analysis effect size (LEfSe) was used to identify differentially abundant taxa between the PO and NPO groups, with a log LDA score threshold of 2.0. Functions were predicted using Clusters of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using SPSS (ver. 26) and R (ver. 4.1.1). The Wilcoxon test was used for pairwise comparisons of alpha diversity between groups, whereas permutational multivariate analysis of variance was used to compare beta diversity. The Kruskal\u0026ndash;Wallis test was used to compare microbial communities among the PO, CON, and NPO groups. For functional predictions (COG and KEGG), the Wilcoxon test was used to analyze differences between groups. The threshold for statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003ePatient characteristics and study design\u003c/em\u003e\u003c/p\u003e\u003cp\u003eMiddle ear swabs were obtained during surgery from 20 patients who underwent tympanoplasty between May 2020 and November 2021 at the Eye and ENT Hospital of Fudan University, Shanghai, China. The same treatment team evaluated the preoperative imaging and performed the surgical resection in all patients. Patients with CSOM were divided into perforation (PO) and non-perforation (NPO) groups based on whether perforation recurred postoperatively. Patients with otosclerosis and no inflammation were used as controls. Patient demographic information is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eDemographic and clinical characteristics of enrolled patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePatient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSide\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNPO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPO-13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePO-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePO-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePO-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePO-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCON\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCON-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCON\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCON-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLeft\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCON\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCON-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eMicrobial diversity of the middle ear specimens\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe obtained reads were aligned using 2b-Tag-DB and subsequently classified into 875 distinct microbial categories at the \u003cem\u003especies\u003c/em\u003e level. Venn diagram analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) revealed 54 microbial \u003cem\u003especies\u003c/em\u003e common to the three groups, whereas 320, 215, and 99 \u003cem\u003especies\u003c/em\u003e were exclusive to the NPO, PO, and CON groups, respectively. For alpha diversity, the Shannon and Simpson indexes were calculated to evaluate community diversity; Chao1 was calculated to evaluate the community richness of the middle ear microbiome. These three indexes showed no significant difference among the NPO, PO, and CON groups. Both the PO and NPO groups with middle ear infection differed from the CON group without inflammation, but these differences were non-significant. The control group had greater richness and diversity. Although minimal differences were observed between the PO and NPO groups, the NPO group had greater richness and diversity, approaching that of the control group without inflammation. For beta diversity, PCoA revealed no differences in bacterial composition among the three groups based on Bray\u0026ndash;Curtis, binary Jaccard, and Euclidean distances.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eMicrobial community composition in the three groups\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFungi (e.g., Agaricomycetes, Sordariomycetes, Blastocladiomycetes), Archaea (e.g., Halobacteria), and Eubacteria (e.g., Chlamydiia and Bacteroidia) were detected at the \u003cem\u003eclass\u003c/em\u003e level. Nineteen phyla were identified in the three groups, and Proteobacteria was the dominant \u003cem\u003ephylum\u003c/em\u003e in all three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). At the \u003cem\u003eclass\u003c/em\u003e level, Gammaproteobacteria were the most prevalent in all three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). \u003cem\u003eMoraxella\u003c/em\u003e was the dominant \u003cem\u003egenus\u003c/em\u003e in the control group, whereas \u003cem\u003ePseudomonas\u003c/em\u003e was most prevalent in both the PO and NPO groups, comprising 74.7% of the perforated group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). In the three groups, 875 different \u003cem\u003especies\u003c/em\u003e were detected. \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eSphingomonas\u003c/em\u003e sp. 000797515, \u003cem\u003ePorphyromonas uenonis\u003c/em\u003e, and \u003cem\u003eFenollaria massiliensis\u003c/em\u003e were the most common \u003cem\u003especies\u003c/em\u003e in the PO group. \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e, and \u003cem\u003eAchromobacter xylosoxidans\u003c/em\u003e were the most common \u003cem\u003especies\u003c/em\u003e in the NPO group. Finally, \u003cem\u003eMoraxella catarrhalis\u003c/em\u003e, \u003cem\u003eCutibacterium acnes\u003c/em\u003e, and \u003cem\u003eRalstonia\u003c/em\u003e sp. 000620465 were the most common \u003cem\u003especies\u003c/em\u003e in the control group. \u003cem\u003eM\u003c/em\u003e. \u003cem\u003ecatarrhalis\u003c/em\u003e was present in 26.9% of the normal group but absent from both the NPO and PO groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eDifferential abundances of microbial taxa\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo characterize the differential representation of microorganisms, we performed Kruskal\u0026ndash;Wallis analysis of taxonomic differences. This analysis revealed significant increases in the abundances of \u003cem\u003eAcinetobacter johnsonii\u003c/em\u003e, \u003cem\u003eEscherichia flexneri\u003c/em\u003e, \u003cem\u003eRalstonia pickettii\u003c/em\u003e, and other \u003cem\u003especies\u003c/em\u003e at the \u003cem\u003especies\u003c/em\u003e level in the CON group relative to both the PO and NPO groups (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). For the NPO and PO groups, at the \u003cem\u003ephylum\u003c/em\u003e level, the abundances of Actinobacteriota, Ascomycota, and Basidiomycota significantly increased in the NPO group, whereas the NPO group had a significantly lower abundance of Chlamydiota compared with the PO group. Regarding genera, \u003cem\u003eAcinetobacter\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eCorynebacterium\u003c/em\u003e, \u003cem\u003eCutibacterium\u003c/em\u003e, and \u003cem\u003eMalassezia\u003c/em\u003e were significantly more abundant in the NPO group; \u003cem\u003eChlamydophila\u003c/em\u003e was more abundant in the PO group (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). At the \u003cem\u003especies\u003c/em\u003e level, \u003cem\u003eBacillus bombysepticus\u003c/em\u003e, \u003cem\u003eBurkholderia oklahomensis\u003c/em\u003e, \u003cem\u003eCorynebacterium kefirresidentii\u003c/em\u003e, and \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eacnes\u003c/em\u003e were more enriched in the NPO group, whereas \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e, \u003cem\u003ePseudomonas alcaligenes\u003c/em\u003e, \u003cem\u003ePseudomonas protegens\u003c/em\u003e, \u003cem\u003ePseudomonas qingdaonensis\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e sp. 003696305, \u003cem\u003ePseudomonas thermotolerans\u003c/em\u003e, \u003cem\u003ePseudomonas nitroreducens\u003c/em\u003e, and \u003cem\u003ePseudomonas panipatensis\u003c/em\u003e were more enriched in the PO group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003eWe also used LEfSe to identify differentially abundant taxa in the three groups. Nodes in each layer represent \u003cem\u003ephylum/class/order/family/genus\u003c/em\u003e from inside out, respectively; the annotations of \u003cem\u003especies\u003c/em\u003e markers in each layer represent \u003cem\u003ephylum/class/order/family/genus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). LEfSe identified 15 discriminative features (LDA score\u0026thinsp;\u0026ge;\u0026thinsp;2.0) with significantly different relative abundances between the PO and NPO groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). At the \u003cem\u003egenus\u003c/em\u003e level, the microbiome of the NPO group was enriched with \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eCorynebacterium\u003c/em\u003e, \u003cem\u003eCutibacterium\u003c/em\u003e, and \u003cem\u003eAcinetobacter\u003c/em\u003e, whereas that of the PO group was enriched with \u003cem\u003eChlamydophila\u003c/em\u003e. At the \u003cem\u003especies\u003c/em\u003e level, taxa that differentiated the two groups were \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e, \u003cem\u003eB\u003c/em\u003e. \u003cem\u003eoklahomensis\u003c/em\u003e, \u003cem\u003eC\u003c/em\u003e. \u003cem\u003ekefirresidentii\u003c/em\u003e, and \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eacnes\u003c/em\u003e in the NPO group and \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003ethermotolerans\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003enitroreducens\u003c/em\u003e, and \u003cem\u003eP\u003c/em\u003e. \u003cem\u003epanipatensis\u003c/em\u003e in the PO group. These significantly different bacterial taxa can be used as indicators to distinguish the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eModel prediction analysis in the three groups\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe indicator values of the \u003cem\u003especies\u003c/em\u003e in each group were calculated, and statistical analysis was performed on the indicator values between the groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05); this approach revealed the index \u003cem\u003especies\u003c/em\u003e of each group, which were \u003cem\u003especies\u003c/em\u003e with high group specificity. In the NPO group, the indicators were \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e, \u003cem\u003eRalstonia\u003c/em\u003e sp. 000620465, \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eacnes\u003c/em\u003e, and \u003cem\u003eSphingomonas\u003c/em\u003e sp. 000797515; conversely, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eprotegens\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003ealcaligenes\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eqingdaonensis\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e sp. 003696305, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003epanipatensis\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003ethermotolerans\u003c/em\u003e, and \u003cem\u003eP\u003c/em\u003e. \u003cem\u003enitroreducens\u003c/em\u003e were indicators in the PO group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Several \u003cem\u003especies\u003c/em\u003e were correlated between the NPO and PO groups indicating close associations among them, including \u003cem\u003eA\u003c/em\u003e. \u003cem\u003exylosoxidans\u003c/em\u003e, \u003cem\u003ePorphyromonas\u003c/em\u003e sp. 900548415, \u003cem\u003eF\u003c/em\u003e. \u003cem\u003emassiliensis\u003c/em\u003e, \u003cem\u003eMetamycoplasma salivarium\u003c/em\u003e, \u003cem\u003ePorphyromonas somerae\u003c/em\u003e, \u003cem\u003ePrevotella timonensis\u003c/em\u003e, \u003cem\u003eCampylobacter rectus\u003c/em\u003e, and \u003cem\u003eP\u003c/em\u003e. \u003cem\u003euenonis\u003c/em\u003e. Notably, \u003cem\u003ePorphyromonas\u003c/em\u003e sp. 900548415 had the strongest association with the other \u003cem\u003especies\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). To assess the importance of the top 30 \u003cem\u003especies\u003c/em\u003e based on relative abundance, we conducted random forest analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). \u003cem\u003eSpecies\u003c/em\u003e importance point plots showed that \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e was the most important \u003cem\u003especies\u003c/em\u003e between the NPO and PO groups. The accuracy of using \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e to identify postoperative perforations was assessed through receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) was 0.25, indicating relatively low accuracy using this \u003cem\u003especies\u003c/em\u003e was used to detect perforation. In contrast, \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e was more accurate (AUC\u0026thinsp;=\u0026thinsp;0.92). The random forest model revealed that although \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e had a large Gini index, suggesting strong predictive power, its mean decrease in accuracy was smaller than that of \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e. This suggests that while \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e may be a more accurate predictor of postoperative perforations, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e has a greater overall impact on model performance.\u003c/p\u003e\u003cp\u003eThe control group had numerous indicator \u003cem\u003especies\u003c/em\u003e that distinguished it from the NPO and PO groups, including \u003cem\u003eMethylobacterium fujisawaense\u003c/em\u003e, \u003cem\u003eRalstonia\u003c/em\u003e sp. 001078575, \u003cem\u003eBrevundimonas aurantiaca\u003c/em\u003e, \u003cem\u003eMalassezia globosa\u003c/em\u003e, \u003cem\u003eA\u003c/em\u003e. \u003cem\u003ejohnsonii\u003c/em\u003e, \u003cem\u003eCorynebacterium resistens\u003c/em\u003e, \u003cem\u003eNocardioides\u003c/em\u003e sp. 009699265, \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eacnes\u003c/em\u003e, \u003cem\u003eBlastomonas ursincola\u003c/em\u003e, \u003cem\u003eAfipia broomeae\u003c/em\u003e, \u003cem\u003eTardiphaga\u003c/em\u003e sp. 002256345, and \u003cem\u003eXanthomonas campestris\u003c/em\u003e (Figure S3A). These indicator \u003cem\u003especies\u003c/em\u003e likely play important roles in the maintenance of a normal microbial microenvironment in the middle ear. Moreover, positive correlations were observed in the correlation network diagram (Figure S3B). \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e, and \u003cem\u003eAchromobacter\u003c/em\u003e were identified as the most important genera in the NPO, PO, and CON groups, respectively, consistent with the three most important \u003cem\u003especies\u003c/em\u003e in the NPO and PO groups. This finding indicates close relationships of these three \u003cem\u003especies\u003c/em\u003e with postoperative outcomes and the presence of middle ear infections (Figure S3C).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eDifferences in predictive functions among the three groups\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFor the identified microbiota, we predicted their functions and used the Wilcoxon test to compare the NPO, PO, and CON groups. We identified COGs that differed among the three groups; the top five COGs were COG2207 (AraC-type DNA-binding domain and AraC-containing proteins), COG1269 (A/V-type ATP synthase), COG4974 (site-specific recombinase XerD), COG1289 (uncharacterized membrane protein YccC), and COG0564 (pseudouridine synthase RluA, 23S rRNA- or tRNA-specific) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Analyses were performed based on the KEGG database of gene protein sequences (KEGG Genes), chemicals with endogenous and exogenous properties (KEGG Ligand), molecular interactions and metabolic pathways (KEGG Pathway), and hierarchical relationships among various organisms (KEGG Brite). The top three pathways with significant differences included putative ABC transport system permease protein (K02004), TatD DNase family protein (K03424), and nuclear receptors (K03310) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEarly research suggested that a healthy middle ear is typically sterile, highlighting the crucial role of pathogens from adjacent organs, such as the external auditory canal or eustachian tube, in the occurrence and development of CSOM. Given that these studies relied primarily on culture techniques and early molecular identification techniques, and that most microorganisms in nature are difficult or impossible to culture, hospital laboratory diagnoses may overlook unidentified bacteria, viruses, and fungi. Additionally, the limited quantity of DNA from ear secretions can also lead to false-negative PCR test results. The emerging DNA sequencing technology has unique advantages for the characterization of microbial communities in the middle ear. 16s rRNA sequencing-based research revealed that the healthy middle ear is not sterile but has a complex microbial ecology consisting of various microorganisms, which suggests a different pathogenesis theory for CSOM. Nevertheless, these studies may not accurately reflect the true middle ear microbial community, thereby affecting the accuracy and reliability of clinical diagnoses. Furthermore, the limited resolution of 16S rRNA sequencing, which identifies microorganisms only at the \u003cem\u003egenus\u003c/em\u003e level, may have difficulty distinguishing closely related \u003cem\u003especies\u003c/em\u003e, which is crucial for the development of effective treatment strategies. Here, 2b-RAD-M was used to provide a more detailed and comprehensive depiction of the middle ear microbiome in patients with otosclerosis (as an analogy to a healthy middle ear environment) and in CSOM patients with or without postoperative tympanic membrane perforation.\u003c/p\u003e\u003cp\u003eIn this study, the detection of numerous microorganisms in healthy middle ears supported the evidence that the healthy middle ear is not sterile. Additionally, no significant differences in the alpha or beta diversity of microorganisms were observed among the CON, PO, and NPO groups, indicating that the middle ear microbiota of CSOM patients is similar to that of healthy individuals. The conventional view is that the middle ear should normally be free of fungi, and the presence of a fungal infection in CSOM significantly increases the difficulty of treatment. Intriguingly, fungi were detected in the CON group in this study, suggesting their involvement in the maintenance of microbial balance in the healthy middle ear.(Chen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) We also observed that \u003cem\u003eAspergillus\u003c/em\u003e, one of the most common pathogens in otomycosis, was significantly more abundant in the NPO group than in the PO group, suggesting that it can serve as an indicator to distinguish between these two groups.(Bojanović et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Bojanović et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) One possible explanation for this is that tympanic membrane perforation may lead to better ventilation and drainage, thereby inhibiting fungal growth. Another explanation is that patients with recurrent tympanic membrane perforations tend to use antibiotics more frequently, which suppresses the growth of fungi. Archaea, a unique \u003cem\u003eclass\u003c/em\u003e of single-celled microorganisms, also were detected in the middle ear of the CON group. To our knowledge, however, no studies have examined the presence and role of archaea in the middle ear microenvironment. Whether archaea play a role in the maintenance of microbial balance and immune regulation in the middle ear, similar to their role in the gut, merits further investigation.(Shi and Mu, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Wei et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eAt the \u003cem\u003egenus\u003c/em\u003e level, \u003cem\u003ePseudomonas\u003c/em\u003e was the dominant \u003cem\u003egenus\u003c/em\u003e in both CSOM groups; its proportion was higher in PO (74.7%). Notably, other than \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e, which is considered the most common pathogen associated with CSOM, the abundances of \u003cem\u003ePseudomonas species\u003c/em\u003e such as \u003cem\u003eP\u003c/em\u003e. \u003cem\u003ealcaligenes\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eprotegens\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eqingdaonensis\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e sp. 003696305, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003ethermotolerans\u003c/em\u003e, \u003cem\u003eP\u003c/em\u003e. \u003cem\u003enitroreducens\u003c/em\u003e, and \u003cem\u003eP\u003c/em\u003e. \u003cem\u003epanipatensis\u003c/em\u003e were significantly higher in the PO group than in the NPO group, suggesting that these \u003cem\u003especies\u003c/em\u003e play important roles in the recurrence of tympanic membrane perforation. Because these \u003cem\u003ePseudomonas species\u003c/em\u003e are primarily found in the environment rather than in the human body, their presence in the middle ear suggests compromised immune function in CSOM patients with tympanic membrane perforation.(Miloloža et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Garrido-Sanz et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Lin et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) Our findings show that 2b-RAD-M can provide \u003cem\u003especies\u003c/em\u003e-level microbial information, offering valuable guidance for the treatment of CSOM because these \u003cem\u003ePseudomonas species\u003c/em\u003e may have different sensitivities to antibiotics.\u003c/p\u003e\u003cp\u003eBased on Kruskal\u0026ndash;Wallis and LEfSe analyses, \u003cem\u003eAcinetobacter guillouiae\u003c/em\u003e, \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e, \u003cem\u003eB\u003c/em\u003e. \u003cem\u003eoklahomensis\u003c/em\u003e, \u003cem\u003eC. kefirresidentii\u003c/em\u003e, and \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eacnes\u003c/em\u003e were significantly more abundant in the NPO group than in the PO group. However, the involvement of these bacteria in CSOM remains unclear because few relevant reports have been published. We note that \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e and \u003cem\u003eC\u003c/em\u003e. \u003cem\u003ekefirresidentii\u003c/em\u003e were not detected in either the CON or PO groups. We hypothesize that the relatively closed stable environment provided by the repaired tympanic membrane may allow these exogenous bacterial \u003cem\u003especies\u003c/em\u003e to colonize and proliferate, ultimately contributing to the reconstruction of middle ear microbial homeostasis in CSOM patients after surgical intervention and systemic antibiotic therapy. The other three bacteria, \u003cem\u003eA\u003c/em\u003e. \u003cem\u003eguillouiae\u003c/em\u003e, \u003cem\u003eB\u003c/em\u003e. \u003cem\u003eoklahomensis\u003c/em\u003e, and \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eacnes\u003c/em\u003e, were significantly more abundant in the NPO group than in the PO group; they were less abundant in the CON group. This finding suggests that major CSOM pathogens, such as \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e, disrupt the microbial balance in the middle ear during an infection and significantly inhibit the growth of these three bacteria. During recovery, these bacteria may aid in the restoration of microbial homeostasis as resident flora, potentially preventing the recurrence of tympanic membrane perforation. \u003cem\u003eM\u003c/em\u003e. \u003cem\u003ecatarrhalis\u003c/em\u003e, \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eacnes\u003c/em\u003e, and \u003cem\u003eRalstonia\u003c/em\u003e sp. 000620465 were the dominant bacteria in the CON group. Of note, \u003cem\u003eM\u003c/em\u003e. \u003cem\u003ecatarrhalis\u003c/em\u003e had a prevalence of 26.9% in the CON group, whereas it was entirely absent from both the NPO and PO groups. Although reports have suggested that \u003cem\u003eM\u003c/em\u003e. \u003cem\u003ecatarrhalis\u003c/em\u003e, as a resident bacterium in the middle ear, constitutes a potential endogenous source of infection in CSOM, our results indicate that CSOM-induced dysbiosis of the middle ear microbiota may inhibit the survival of \u003cem\u003eM\u003c/em\u003e. \u003cem\u003ecatarrhalis\u003c/em\u003e.(Mittal et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) Furthermore, \u003cem\u003eM\u003c/em\u003e. \u003cem\u003ecatarrhalis\u003c/em\u003e may have a protective role in maintaining a healthy middle ear environment.\u003c/p\u003e\u003cp\u003ePrevious studies often have neglected to connect middle ear microbiota data with the clinical outcomes of CSOM. We performed random forest analysis on the 2b-RAD-M microbial data and found that \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e had a high NPO indicator value, whereas \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e had a high PO indicator value. ROC curve analysis was used to evaluate the reliabilities of these bacteria in distinguishing between NPO and PO. Intriguingly, although \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eaeruginosa\u003c/em\u003e was significantly more abundant in the PO group, its ability to distinguish between the two groups was poor (AUC\u0026thinsp;=\u0026thinsp;0.25). In contrast, \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e may be a potential diagnostic biomarker for preventing tympanic membrane perforation after surgery for CSOM, considering its impressive AUC of 0.92.\u003c/p\u003e\u003cp\u003eFunctional annotation analyses were performed to compare differences in microbial function among the three groups. The COG and KEGG function predictions indicated enhancement of specific microbial functions in the PO group relative to the NPO and CON groups. Specifically, the increased abundances of COG4771, COG1269, COG0534, K02004, K03310, K03561, and K03327 suggest enhanced gene regulation and expression. The elevated levels of COG2207, COG4974, COG0564, COG1476, and COG0492 indicate improved efficiency in substance transport and metabolism. Additionally, the higher abundances of K03324 and K03630 imply enhanced DNA repair capabilities. The synergistic actions of these pathways ensure that microorganisms can efficiently perform metabolic activities, safeguard the stability of genetic material, maintain normal physiological activities and homeostasis, and ultimately better adapt and survive in harsh environments.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis is the first study to use 2b-RAD-M to analyze the middle ear microbiota in patients with CSOM and otosclerosis. The results provide more comprehensive data concerning the middle ear microbiota, suggesting potential mechanisms by which various microorganisms contribute to the pathogenesis and progression of CSOM. Importantly, we identify \u003cem\u003eB\u003c/em\u003e. \u003cem\u003ebombysepticus\u003c/em\u003e as a potential diagnostic biomarker that can indicate an increased risk of tympanic membrane re-perforation. We believe that our study offers a new target for predicting postoperative outcomes in CSOM patients.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC, area under the curve\u003c/p\u003e\n\u003cp\u003eCOGs, clusters of orthologous groups\u003c/p\u003e\n\u003cp\u003eCON, otosclerosis (control)\u003c/p\u003e\n\u003cp\u003eCSOM, chronic suppurative otitis media\u003c/p\u003e\n\u003cp\u003eKEGG, Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n\u003cp\u003eLEfSe, linear discriminant analysis effect size\u003c/p\u003e\n\u003cp\u003eNPO, non-perforation\u003c/p\u003e\n\u003cp\u003ePCoA, principal coordinate analysis\u003c/p\u003e\n\u003cp\u003ePCR, polymerase chain reaction\u003c/p\u003e\n\u003cp\u003ePO, perforation\u003c/p\u003e\n\u003cp\u003eROC, receiver operating characteristic curve\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper. The Ethics Committee of the Eye and ENT Hospital, Fudan University, approved the study protocol (approval number: 20200423) on April 23, 2020. The study was registered with the Chinese Clinical Trial Register (ChiCTR: 2000038981).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study is supported by the National Natural Science Foundation of China (grants 82271166, 81970880, and 81771017 to Dongdong Ren); Natural Science Foundation of Shanghai (grant 22ZR1410100 to Dongdong Ren); the “Zhuo-Xue Plan” of Fudan University (Dongdong Ren); Heng-Jie special technical support plan (Dongdong Ren); and the Shanghai Outstanding Young Medical Talent Program (Dongdong Ren).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors' contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eXiao Fu and Yuming Chen have contributed equally to this work and share first authorship. Conceptualization, Binjun Chen, Jianghong Xu and Dongdong Ren; Data curation, Xiao Fu and Yuming Chen; Formal analysis, Xiao Fu and Yanmei Wang; Funding acquisition, Dongdong Ren; Investigation, Jihan Lyu, Haojie Sun and Mengke Chen; Methodology, Xiao Fu and Yanmei Wang; Project administration, Jianghong Xu and Dongdong Ren; Resources, Dongdong Ren; Supervision, Zhujian Wang, Genglin Li and Dongdong Ren; Visualization, Dongdong Ren; Writing – original draft, Xiao Fu and Yuming Chen; Writing – review \u0026amp; editing, Jianghong Xu, Genglin Li and Dongdong Ren\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the patients who participated in our study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBHUTTA MF, LEACH, A. J., BRENNAN-JONES CG (2024) Chronic suppurative otitis media. Lancet 403:2339\u0026ndash;2348\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBHUTTA MF, THORNTON, R. B., KIRKHAM, L. S., KERSCHNER, J. E., CHEESEMAN MT (2017) Understanding the aetiology and resolution of chronic otitis media from animal and human studies. Dis Model Mech 10:1289\u0026ndash;1300\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBOJANOVIĆ M, STALEVIĆ IGNJATOVIĆA, ARSIĆ-ARSENIJEVIĆ M, RANĐELOVIĆ V, STOJANOVIĆ-RADIĆ MGERGINIĆV, ŽIVKOVIĆ-MARINKOV ZSTOJKOVIĆO, E., OTAŠEVIĆ S (2022) Clinical Presentations, Cluster Analysis and Laboratory-Based Investigation of Aspergillus Otomycosis-A Single Center Experience. J Fungi (Basel), 8\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBOJANOVIĆ M, ARSIĆ-ARSENIJEVIĆ STALEVIĆM, IGNJATOVIĆ V, RANĐELOVIĆ A, GOLUBOVIĆ M, ŽIVKOVIĆ-MARINKOV M, KORAĆEVIĆ E, STAMENKOVIĆ G (2023) B. \u0026amp; OTAŠEVIĆ, S. Etiology, Predisposing Factors, Clinical Features and Diagnostic Procedure of Otomycosis: A Literature Review. \u003cem\u003eJ Fungi (Basel)\u003c/em\u003e, 9\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCHADHA S, KAMENOV K, CIEZA A (2021) The world report on hearing, 2021. Bull World Health Organ 99:242\u0026ndash;242a\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCHEN C, ZHANG Y, YAO X, LI YANQ, ZHONG S, LIU Q, TANG Z, LIU F, LI C, ZHU H, LING DLANW, LU Y, XU D, WANG HNINGQ, JIANG Y, WANG ZZHANGQGUGSUNL, N., WANG, G., ZHANG, A., ULLAH, H., SUN, W., MA W (2023) Characterizations of the multi-kingdom gut microbiota in Chinese patients with gouty arthritis. BMC Microbiol 23:363\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCHEN CH, CHENG WANGCY, HSIH MY, W. H., TIEN, N., CHOU, C. H., LIN, P. C., CHI, C. Y., HO, M. W., LU MC (2022) Definite therapy of mixed infection alleviates refractory dilemma of adult chronic suppurative otitis media. J Microbiol Immunol Infect 55:1283\u0026ndash;1292\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCOLEMAN A, WOOD A, BIALASIEWICZ S, WARE, R. S., MARSH, R. L., CERVIN A (2018) The unsolved problem of otitis media in indigenous populations: a systematic review of upper respiratory and middle ear microbiology in indigenous children with otitis media. Microbiome 6:199\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDANIEL SJ (2012) Topical treatment of chronic suppurative otitis media. Curr Infect Dis Rep 14:121\u0026ndash;127\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDHINGRA S, VIR D, BAKSHI, J., RISHI P (2023) Mapping of audiometric analysis with microbiological findings in patients with chronic suppurative otitis media (CSOM): a neglected clinical manifestation. Crit Rev Clin Lab Sci 60:212\u0026ndash;232\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFRANK DN, BOOTPETCH MAGNOJPMVELASCOKJS, SALUD TC, MILLER JEDDAVIDKJV, PYLES ALYEEECDULNUANHP, GUCE RBLACUATAJACARBIZOJLKOFONOWJM, MENDOZA B K. M. D., ROBERTSON, C. E., ILUSTRE, G. M. S., CHIONG, A. N. E., LU, S. L., TONGOL, E. A., SACAYAN, N. D., YARZA, T. K. L., CHIONG, C. M. \u0026amp; SANTOS-CORTEZ, R. L. P. 2022. Microbiota Associated With Cholesteatoma Tissue in Chronic Suppurative Otitis Media. \u003cem\u003eFront Cell Infect Microbiol\u003c/em\u003e, 12, 746428\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFUJIKAWA T, TANIMOTO K, KAWASHIMA Y, ITO T, HONDA K, TAKEDA T, AOKI SONOBEA, BAI N, J., TSUTSUMI T (2022) Cholesteatoma has an altered microbiota with a higher abundance of Staphylococcus \u003cem\u003especies\u003c/em\u003e. Laryngoscope Investig Otolaryngol 7:2011\u0026ndash;2019\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGARRIDO-SANZ D, HEIMAN ČAUŠEVIĆSVACHERONJ, SENTCHILO CM, VAN DER MEER V, J. R., KEEL C (2023) Changes in structure and assembly of a \u003cem\u003especies\u003c/em\u003e-rich soil natural community with contrasting nutrient availability upon establishment of a plant-beneficial Pseudomonas in the wheat rhizosphere. Microbiome 11:214\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHALL-STOODLEY L, GIESEKE HUFZ, NISTICO A, NGUYEN L, FORBES DHAYESJ, DICE MGREENBERGDP, STOODLEY BBURROWSAWACKYMPA, EHRLICH PPOSTJC, G. D., KERSCHNER JE (2006) Direct detection of bacterial biofilms on the middle-ear mucosa of children with chronic otitis media. JAMA 296:202\u0026ndash;211\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHUANG X, LI ZENGJ, CHEN S, WANG J, LI H, C., ZHANG S (2024) 16S rRNA, metagenomics and 2bRAD-M sequencing to decode human thanatomicrobiome. Sci Data 11:736\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLAM T, CHEW D, ZHAO H, ZHU P, ZHANG L, DAI Y, LIU J, XU J (2022) \u003cem\u003eSpecies\u003c/em\u003e-Resolved Metagenomics of Kindergarten Microbiomes Reveal Microbial Admixture Within Sites and Potential Microbial Hazards. Front Microbiol 13:871017\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLIN C, LI LJ, ISABWE RENKZHOUSY, YANG A, YANG LYNEILSONR, X. R., CYTRYN, E., ZHU YG (2023) Phagotrophic protists preserve antibiotic-resistant opportunistic human pathogens in the vegetable phyllosphere. ISME Commun 3:94\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMILOLOŽA M, CVETNIĆ UKIĆŠ, BOLANČA M, T., KUČIĆ GRGIĆ D (2022) Optimization of Polystyrene Biodegradation by Bacillus cereus and Pseudomonas alcaligenes Using Full Factorial Design. Polym (Basel), 14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMITTAL R, GRATI M, GERRING R, BLACKWELDER P, LI YAND, J. D., LIU XZ (2014) In vitro interaction of Pseudomonas aeruginosa with human middle ear epithelial cells. PLoS ONE 9:e91885\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNEEFF M, HOGGARD BISWASK, M., TAYLOR, M. W., DOUGLAS R (2016) Molecular Microbiological Profile of Chronic Suppurative Otitis Media. J Clin Microbiol 54:2538\u0026ndash;2546\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNGUYEN CT, JUNG W, KIM J, CHANEY EJ, NOVAK M (2012) STEWART, C. N. \u0026amp; BOPPART, S. A. Noninvasive in vivo optical detection of biofilm in the human middle ear. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e, 109, 9529-34\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eORDINOLA-ZAPATA R, COSTALONGA M, DIETZ M, LIMA, B. P., STALEY C (2024) The root canal microbiome diversity and function. A whole-metagenome shotgun analysis. Int Endod J 57:872\u0026ndash;884\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSANTA MARIA PL, BACACAO KAUFMANAC, THAI B, CHEN A, CAO XXIAA, Z., FOUAD, A., BEKALE LA (2021) Topical Therapy Failure in Chronic Suppurative Otitis Media is Due to Persister Cells in Biofilms. Otol Neurotol 42:e1263\u0026ndash;e1272\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSCHILDER AG, CHONMAITREE T, ROSENFELD CRIPPSAW, HAGGARD RMCASSELBRANTML (2016) M. P. \u0026amp; VENEKAMP, R. P. Otitis media. \u003cem\u003eNat Rev Dis Primers\u003c/em\u003e, 2, 16063\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSCHLEGEL I, DE GO\u0026Uuml;YON MATIGNON DE PONTOURADE CMF, KELLER LINCKEJB, ZINKERNAGEL I, M. S., ZYSSET-BURRI DC (2023) The Human Ocular Surface Microbiome and Its Associations with the Tear Proteome in Dry Eye Disease. Int J Mol Sci, 24\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSHANGALI A, KAMORI D, MASSAWE W, MASOUD S, KIBWANA U, MWANDIGHA MWINGWAAGMANISHAA, MIRAMBO AM, MANYAHI MMMSHANASE, J., MAJIGO M (2023) Aetiology of ear infection and antimicrobial susceptibility pattern among patients attending otorhinolaryngology clinic at a tertiary hospital in Dar es Salaam, Tanzania: a hospital-based cross-sectional study. BMJ Open 13:e068359\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSHI Y, MU L (2017) An expanding stage for commensal microbes in host immune regulation. Cell Mol Immunol 14:339\u0026ndash;348\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSIDAM S, GUPTA SAHOOAKMISHRAUP, KUSHWAH V, A., SAHOO PK (2024) Impact of Chronic Suppurative Otitis Media on Quality of Life and Psychological Well-Being: A Cross-Sectional Study. Cureus 16:e54150\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSUTTLE TK, ELS T, CURTIS TOMANJ, SIZEMORE DMCNABR, VAN A, CLEVE M, BROMBACHER RA (2024) Chronic Suppurative Otitis Media: A Prospective Descriptive Study of the Microbiology and Antimicrobial Susceptibility Patterns. Otolaryngol Head Neck Surg 171:90\u0026ndash;97\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWEI M, LIU H, SUN WANGY, M., SHANG P (2024) Mechanisms of Male Reproductive Sterility Triggered by Dysbiosis of Intestinal Microorganisms. Life (Basel), 14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWESTERBERG BD, BLONDEL-HILL KOZAKFKTHOMASEE, E., BRUNSTEIN, J. D., PATRICK DM (2009) Is the healthy middle ear a normally sterile site? Otol Neurotol 30:174\u0026ndash;177\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXIAO K, LI H, LI Y, ZHAN B, ZHAO FANGX, ZHANG B, WU X, WANG Y, F., JIA Y (2024) Protective effects and mechanism of Sangyu granule on acetaminophen-induced liver injury in mice. J Ethnopharmacol 331:118282\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"2b-RAD-M, Chronic suppurative otitis media, re-perforation, Microbiota","lastPublishedDoi":"10.21203/rs.3.rs-7068085/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7068085/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChronic suppurative otitis media (CSOM) is a prevalent condition with global health implications due to its impact on hearing and quality of life. Conventional treatments often fail because of bacterial biofilms and antimicrobial resistance. Effective treatment of CSOM depends on the precise determination of the middle ear microbiota; however, current microbial detection methods do not meet this need. Postoperative re-perforation may compromise surgical outcomes. If the risk of perforation can be predicted immediately after surgery, sensitive antibiotics could be administered proactively for early intervention to optimize treatment efficacy. This study introduces 2b-RAD sequencing for the Microbiome (2b-RAD-M), a novel technology designed to provide a comprehensive profile of the CSOM microbiota and identify diagnostic biomarkers that predict postoperative outcomes. We analyzed ear swabs from patients with postoperative perforation (PO), non-perforation (NPO), and otosclerosis (CON) using microbial diversity, relative abundance, and composition analyses. Bacillus bombysepticus and Pseudomonas aeruginosa were identified as potential biomarkers, with B. bombysepticus demonstrating superior diagnostic accuracy (AUC\u0026thinsp;=\u0026thinsp;0.92) compared to P. aeruginosa (AUC\u0026thinsp;=\u0026thinsp;0.25). Functional predictions revealed that biological activities related to gene regulation, substance metabolism, and DNA repair were more prominent in the PO group. This study offers new insights into CSOM pathogenesis and progression, proposing B. bombysepticus as a novel biomarker for predicting postoperative outcomes that can indicate an increased risk of tympanic membrane re-perforation for the first time.\u003c/p\u003e","manuscriptTitle":"Microbiota in Chronic Suppurative Otitis Media: Association with Postoperative Tympanic Membrane Outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-14 09:58:53","doi":"10.21203/rs.3.rs-7068085/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"db5d1c0f-291d-4a7d-947e-ed577fc2e18d","owner":[],"postedDate":"August 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T16:08:07+00:00","versionOfRecord":{"articleIdentity":"rs-7068085","link":"https://doi.org/10.1007/s00253-026-13770-9","journal":{"identity":"applied-microbiology-and-biotechnology","isVorOnly":false,"title":"Applied Microbiology and Biotechnology"},"publishedOn":"2026-03-20 15:59:47","publishedOnDateReadable":"March 20th, 2026"},"versionCreatedAt":"2025-08-14 09:58:53","video":"","vorDoi":"10.1007/s00253-026-13770-9","vorDoiUrl":"https://doi.org/10.1007/s00253-026-13770-9","workflowStages":[]},"version":"v1","identity":"rs-7068085","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7068085","identity":"rs-7068085","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}