Abstract
Purpose
The nasal cavity and lacrimal sac are anatomically continuous; however, whether their resident microbiota influence surgical outcomes after endoscopic dacryocystorhinostomy (DCR) remains unclear. This study aimed to determine whether preoperative lacrimal sac microbiome features are associated with postoperative recurrence after endoscopic dacryocystorhinostomy.
Methods
In this prospective study, paired lacrimal sac and ipsilateral nasal mucosa samples were collected intraoperatively from 17 patients (22 operated sides) with acquired nasolacrimal duct obstruction. Bacterial communities were analyzed using 16S rRNA sequencing. Microbial diversity, composition, and nasal–lacrimal similarity were compared between relapse and non-relapse groups.
Results
Overall microbial richness, evenness, and community structure of the lacrimal sac did not differ between relapse and non-relapse groups (all p > 0.05). Both groups were predominantly composed of Proteobacteria with similar phylum-level distributions. Despite overall compositional stability, relapse samples showed enrichment of Staphylococcus lugdunensis, Pseudomonas balearica, and Corynebacterium, whereas non-relapse samples exhibited higher relative abundance of Mesorhizobium, Reyranella, and Ralstonia (p < 0.05). Functional prediction revealed increased representation of bacterial invasion and signaling-related pathways in relapse cases, while metabolic and regulatory pathways were more prominent in non-relapse cases. Nasal–lacrimal microbial similarity within individuals did not differ by outcome (all p > 0.05).
Conclusion
The lacrimal sac microbiome remains compositionally stable in patients undergoing DCR; however, subtle differences in commensal composition and predicted microbial function are associated with postoperative outcomes. These findings suggest that the preoperative microbial environment may influence mucosal healing rather than reflect overt infection or disruption of the nasal–lacrimal continuum.
Keywords: Dacryocystorhinostomy, Lacrimal sac, Sinonasal microbiome, 16S rRNA sequencing, Nasal mucosa, Microbial diversity
Introduction
Nasolacrimal duct obstruction (NLDO) is a common cause of epiphora and dacryocystitis. Dacryocystorhinostomy is the standard surgical treatment and achieves success rates exceeding 90%, yet postoperative recurrence remains a clinically relevant challenge, particularly in idiopathic NLDO [1].
Surgical failure likely reflects a combination of inflammation, postoperative fibrosis, and microbial factors [2, 3]. Although infection and biofilms may contribute, aberrant wound healing and fibrosis are thought to be key drivers of recurrence [4]. Recent molecular studies suggest that the lacrimal sac harbors a commensal microbiota, commonly dominated by Staphylococcus, Corynebacterium, and Cutibacterium [5, 6]. Although these microorganisms can form biofilm-like structures, their pathogenetic relevance remains uncertain [7].
The nasal cavity and lacrimal drainage system are anatomically continuous and lined by pseudostratified ciliated respiratory epithelium, supporting a unified mucosal surface [8]. This continuity may permit bidirectional movement of microorganisms and inflammatory mediators and motivates the concept of a nasal–lacrimal microbial continuum. However, the microbial relationship between the nasal cavity and lacrimal sac remains poorly characterized because most studies focus only on the lacrimal sac.
We therefore performed paired sampling of ipsilateral nasal mucosa and lacrimal sac specimens collected during endoscopic DCR in patients with acquired NLDO. Using 16S rRNA sequencing and functional pathway prediction, we characterized microbial diversity, composition, nasal–lacrimal similarity, and associations between baseline microbial features and postoperative recurrence.
Materials and methods
Study design and patient enrollment
This prospective observational study enrolled 17 patients with acquired NLDO who underwent endoscopic DCR at a tertiary referral center between September 2023 and October 2024. Ethical approval was obtained from the institutional review board, and written informed consent was obtained. Patients with malignancy, congenital nasolacrimal obstruction, active sinus infection, or prior/revision dacryocystorhinostomy were excluded.
Preoperative evaluation included ophthalmologic assessment and nasal endoscopy, with imaging when clinically indicated to exclude coexisting sinonasal disease or relevant anatomic variation. Endoscopic DCR procedures were jointly performed by an ophthalmologist and an otorhinolaryngologist to standardize technique and specimen collection. Briefly, the procedure involved creation of a nasal mucosal flap, formation of the bony ostium, endonasal opening of the lacrimal sac, and placement of a silicone stent in all cases. Postoperatively, patients were followed weekly in both the rhinology and ophthalmology clinics during the first month. If healing was satisfactory, the silicone stent was removed 1 month after surgery, and patients then continued regular follow-up for an additional 3 to 6 months. All patients received 1 week of postoperative oral antibiotics, topical antibiotic eye drops, and topical steroid eye drops.
Clinical data included age, sex, laterality, etiology (idiopathic vs. trauma/iatrogenic), and outcome (relapse vs. non-relapse). Recurrence was defined as persistent or recurrent epiphora with endoscopic evidence of ostial obstruction during follow-up.
Sample collection and processing
Paired mucosal specimens were collected intraoperatively under sterile conditions from the lacrimal sac and ipsilateral lateral nasal wall at the planned rhinostomy site. Samples for microbiome analysis were stored at − 80 °C until DNA extraction.
DNA extraction and 16S rRNA sequencing
Bacterial genomic DNA was extracted using a commercial microbiome kit according to the manufacturer’s instructions. The V3–V4 region of the bacterial 16S rRNA gene was amplified and sequenced using paired-end reads. Reads were quality-filtered and processed using a standardized pipeline. Taxonomic classification was performed using the SILVA reference database (release 138). Non-bacterial and low-quality sequences were excluded from downstream analyses.
Bioinformatics and statistical analysis
Raw sequence data were analyzed using a standardized bioinformatics pipeline based on QIIME2 (v2020.8) and downstream R-based statistical tools.
(1) Taxonomic profiling
Low quality reads were removed, paired-end reads were merged and amplicon sequence variants (ASVs) were identified using the DADA2 algorithm. The resulting ASVs were used to generate taxonomic profiles, which were summarized at the phylum, genus, and species levels and visualized as stacked bar plots and Krona charts [9].
(2) Alpha and beta diversity
Alpha diversity indices, including Shannon, Chao1, and Faith’s phylogenetic diversity, were calculated in QIIME2. Between-group differences (relapse vs. non-relapse, idiopathic vs. trauma/iatrogenic) were evaluated using the Mann–Whitney U test.
Beta diversity was assessed using Bray–Curtis, weighted UniFrac, and unweighted UniFrac distances, followed by principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS). Differences in overall community composition were tested using PERMANOVA (adonis function, vegan package v2.4-1 in R).
(3) Differential abundance analysis
Taxa showing differential relative abundance between relapse and non-relapse groups were identified using LEfSe (Linear Discriminant Analysis Effect Size, v1.0),
with a Kruskal–Wallis p < 0.05 and LDA score > 2.0 as the significance threshold.
Confirmatory analyses were performed using STAMP (v2.1.3) and DESeq2 (v1.8.2) to ensure the robustness of the observed group-specific taxa [10].
(4) Functional pathway prediction
Predicted metagenomic functions were inferred from 16S rRNA gene data using PICRUSt2 (v2.2.0-b) [11]. Functional profiles were annotated based on KEGG Orthology (KO). Comparisons of predicted KEGG pathways between relapse and non-relapse lacrimal sac samples were performed using STAMP (Welch’s t-test, two-sided) with 95% confidence intervals. Pathways with p < 0.05 were considered significantly different [12].
(5) Nasal–lacrimal similarity and correlation analysis
To assess how similar the nasal and lacrimal sites were within the same patient, we used pairwise comparisons with Bray–Curtis and Sørensen–Dice indices.
Intergroup differences (relapse vs. non-relapse) were evaluated using the Mann–Whitney U test. Paired relationships were visualized as boxplots and ordination plots in R (v4.2). All statistical analyses were performed in Python (v3.9) and R (v4.2). A p-value < 0.05 was considered statistically significant.
Results
Clinical and sample characteristics
A total of 17 patients (9 males and 8 females; mean age, 61.0 ± 14.6 years; range, 26–75 years) who underwent endoscopic DCR were included in this study.
Twelve patients underwent unilateral endoscopic DCR and five underwent bilateral procedures, yielding a total of 22 operated sides (lacrimal sac specimens). For each operated side, paired specimens of nasal mucosa and lacrimal sac mucosa were obtained, resulting in 22 paired specimen sets (44 total samples).
Based on etiology, 18 specimens (82%) were idiopathic, and 4 specimens (18%) were trauma- or iatrogenic-related. Postoperative outcomes were classified as relapse (n = 6, 27%) or non-relapse (n = 16, 73%). Among the 4 trauma- or iatrogenic-related operated sides, 1 was classified as relapse and 3 as non-relapse. The 6 relapsing operated sides were derived from 4 individual patients, including 2 patients with bilateral primary acquired NLDO. The demographic and clinical characteristics of the lacrimal sac specimens are summarized in Table 1. There were no significant differences in age, sex, or laterality between relapse and non-relapse groups (all p > 0.05). The median follow-up duration after surgery was 11.76 months (range, 1.18–24.84 months). In relapse cases, recurrence was identified at a median of 3.02 months after surgery (range, 2.76–7.82 months).
Table 1.
Demographic and clinical characteristics of patients with acquired NLDO (17 patients, 22 operated sides)
| Variables | Total (n = 22) | Relapse (n = 6) | Non-relapse (n = 16) | p value |
|---|---|---|---|---|
| Age, years (mean ± SD) | 61.0 ± 14.6 | 58.3 ± 16.9 | 62.0 ± 14.1 | 0.60 |
| Sex (male / female) | 9 / 13 | 0 / 6 | 9 / 7 | 0.05 |
| Laterality (Unilateral / Bilateral) | 12 / 10 | 1 / 5 | 11 / 5 | 0.06 |
| Etiology (Idiopathic/Trauma or iatrogenic) | 18 / 4 | 5 / 1 | 13 / 3 | 1.00 |
Values are presented as mean ± SD or number of specimens. Statistical comparisons were performed between relapse and non-relapse groups using the Mann–Whitney U test for continuous variables and Fisher’s exact test for categorical variables. A total of 17 patients contributed 22 lacrimal sac specimens
Microbial diversity and composition
Analysis of alpha diversity revealed that the overall community richness and evenness were comparable between relapse and non-relapse groups in both nasal and lacrimal sites. No significant differences were observed in the ACE, Shannon and Chao1 diversity indices (p > 0.05) (Table 2). Beta diversity analysis based on Bray–Curtis, weighted, and weighted UniFrac distances showed no distinct clustering of samples in principal coordinate analysis (PCoA) (PERMANOVA: F = 0.85, R2 = 0.04, p = 0.69) (Fig. 1a). These findings indicate that microbial community structure remained largely stable, regardless of postoperative outcome.
Table 2.
Comparison of alpha diversity indices between relapse and non-relapse groups
| Alpha Diversity index | Non-relapse group (Mean ± SD) |
relapse group | Mann-whitney U test p value |
|---|---|---|---|
| ACE Richness | 156.567 ± 60.778 | 145.922 ± 53.528 | p > 0.05 |
| Chao1 Richness | 156.497 ± 60.775 | 145.538 ± 53 | p > 0.05 |
| Shannon Index | 3.691 ± 0.745 | 3.699 ± 0.656 | p > 0.05 |
(Data are presented as mean ± standard deviation; Mann–Whitney U test.)
Fig. 1.
Microbial diversity and taxonomic composition. (a) Weighted UniFrac principal coordinate analysis (PCoA) demonstrating the overall similarity of bacterial community structures between relapse (blue) and non-relapse (red) groups. Each point represents one lacrimal sac sample; ellipses indicate 95% confidence intervals. No distinct clustering was observed between groups (PERMANOVA: F = 0.85, R² = 0.045, p = 0.69 ). (b) Relative abundance of dominant bacterial phyla in lacrimal sac samples. Both relapse and non-relapse groups were mainly composed of Proteobacteria, followed by Firmicutes, Actinobacteriota, and Bacteroidota, with no statistically significant differences in proportional abundance (p > 0.05). (c) Genus-level composition showing similar microbial profiles across groups, dominated by Escherichia–Shigella, Acinetobacter, Enterobacter, Haemophilus, and Eikenella. Minor genera included Ralstonia, Pseudomonas, Aggregatibacter, Staphylococcus, and Corynebacterium, while other taxa collectively accounted for < 10% of total sequences. No significant difference in genus-level relative abundance was detected between relapse and non-relapse outcomes (Mann–Whitney U test, p > 0.05)
At the phylum level, the bacterial community of lacrimal sacs was dominated by Proteobacteria, followed by Firmicutes, Actinobacteriota, and Bacteroidota. (Fig. 1b). Proteobacteria accounted for more than 70% of total sequences in both relapse and non-relapse groups, with no statistically significant difference in relative abundance (p > 0.05). At the genus level, the microbial profiles were consistently dominated by Escherichia–Shigella, representing approximately one-third of the total reads in both groups (Fig. 1c). Other major genera included Acinetobacter, Enterobacter, Haemophilus, and Eikenella, whereas Ralstonia, Pseudomonas, Aggregatibacter, Staphylococcus, and Corynebacterium were present at lower proportions. The relative abundance of these dominant taxa showed no significant differences between relapse and non-relapse cases (p > 0.05), indicating that postoperative recurrence was not associated with a shift in the core bacterial composition of the lacrimal sac.
Nasal–lacrimal microbial similarity
Intra-patient analysis showed that the overall microbial similarity between nasal and lacrimal sac sites was largely preserved across patients, and this similarity did not differ between relapse and non-relapse groups (Fig. 2a). In the non-relapse group, unweighted UniFrac analysis revealed mild but statistically significant separation between nasal and lacrimal samples (PERMANOVA: F = 2.55, R2 = 0.07, p = 0.01) (Fig. 2b). In contrast, the relapse group exhibited a high degree of overlap between nasal and lacrimal samples, which showed no evidence of distinct site differentiation (PERMANOVA: F = 0.85, R2 = 0.05, p = 0.70) (Fig. 2c).
Fig. 2.
Intra-patient nasal–lacrimal microbial similarity and site-specific differentiation. (a) Pairwise comparison of nasal–lacrimal microbial dissimilarity between relapse and non-relapse groups. Each point represents the microbial distance between paired nasal and lacrimal sac samples from the same individual. No significant difference was observed between groups (Mann–Whitney U test, p > 0.05). (b) Unweighted UniFrac principal coordinate analysis (PCoA) comparing nasal (red) and lacrimal (blue) samples within the non-relapse group. Nasal and lacrimal samples exhibited mild but statistically significant separation, indicating limited site-specific differentiation (PERMANOVA: F = 2.55, R² = 0.07, p = 0.01). (c) Unweighted UniFrac PCoA of nasal (red) and lacrimal (blue) samples in the relapse group. The two sites largely overlapped, showing no evidence of distinct site differentiation (PERMANOVA: F = 0.85, R² = 0.05, p = 0.70)
Differential taxa between relapse and non-relapse groups
Although overall diversity metrics remained similar, compositional analyses identified distinct taxa differentiating the relapse and non-relapse lacrimal sac microbiota (Fig. 3).
Fig. 3.
(a) Linear discriminant analysis (LEfSe) identified taxa that were differentially enriched between relapse (green) and non-relapse (red) groups based on lacrimal sac samples. Taxa with LDA scores > 2.0 (p < 0.05) are displayed. Relapse samples were enriched with Staphylococcus lugdunensis, Pseudomonas balearica, Corynebacterium, and members of Bdellovibrionaceae and Devosiaceae, whereas Eikenella and Neisseriaceae predominated in non-relapse samples. (b) STAMP analysis of genus-level relative abundance shows significantly higher proportions of Mesorhizobium (4.31% vs. 0%; p = 0.0129), Reyranella (2.84% vs. 0.57%; p = 0.0203), and Ralstonia (4.27% vs. 1.49%; p = 0.0237) in the non-relapse group. Bars indicate mean proportions with 95% confidence intervals
LEfSe analysis revealed enrichment of several genera in the relapse group, including Staphylococcus lugdunensis, Pseudomonas baleárica, Corynebacterium, and members of Bdellovibrionaceae and Devosiaceae, whereas Eikenella and Neisseriaceae predominated in the non-relapse group (Fig. 3a). STAMP analysis further quantified these relative-abundance differences, showing that Mesorhizobium (4.31% vs. 0%; p = 0.0129), Reyranella (2.84% vs. 0.57%; p = 0.0203), and Ralstonia (4.27% vs. 1.49%; p = 0.0237) were significantly more abundant in the non-relapse group (Fig. 3b). These findings demonstrate specific taxonomic differences between relapse and non-relapse microbiota despite comparable overall diversity.
Predicted functional differences
Functional pathway analysis using PICRUSt2 followed by STAMP comparison identified several predicted KEGG pathways that significantly differed between relapse and non-relapse lacrimal sac samples (Fig. 4).
Fig. 4.
STAMP analysis of PICRUSt2-predicted KEGG pathways comparing relapse (blue) and non-relapse (red) groups. Bars represent mean proportions (%) with 95% confidence intervals; only pathways with p < 0.05 are displayed. Relapse samples exhibited higher representation of infection- and signaling-related pathways (e.g., bacterial invasion, calcium signaling, and TCA cycle), whereas non-relapse samples showed greater enrichment in metabolic and regulatory functions (e.g., adipocytokine signaling, steroid metabolism, and longevity-regulating pathways)
Pathways associated with bacterial virulence and host interaction, including bacterial invasion of epithelial cells (p = 0.029), calcium signaling (p = 0.018), citrate cycle (TCA cycle) (p = 0.018), Salmonella infection (p = 0.042), and Yersinia infection (p = 0.028), were enriched in the relapse group.
Conversely, the non-relapse group exhibited higher predicted activity in metabolic and regulatory pathways such as adipocytokine signaling (p = 0.029), aminobenzoate degradation (p = 0.032), longevity-regulating pathway – multiple species (p = 0.027), steroid degradation (p = 0.043), and steroid hormone biosynthesis (p = 0.025).
These findings indicate distinct functional trends between the two postoperative outcomes, with relapse samples showing enrichment in infection- and signaling-related pathways, whereas non-relapse samples displayed a predominance of metabolic and stress-regulation pathways.
Discussion
This study presents the first paired-site analysis of the nasal and lacrimal sac mucosa microbiome in acquired NLDO patients undergoing endoscopic DCR. Although overall microbial diversity and composition were stable between relapse and non-relapse groups, distinct compositional differences emerged. Specifically, relapse cases were associated with Staphylococcus lugdunensis, Pseudomonas balearica, and Corynebacterium, whereas non-relapse cases were characterized by Mesorhizobium, Reyranella, and Ralstonia. Functional pathway prediction further revealed contrasting profiles, with relapse samples showing enrichment in invasion- and signaling-related pathways and non-relapse samples in metabolic and regulatory pathways. Together, these results define both the compositional and functional characteristics of the nasal–lacrimal microbiota, establishing a foundation for subsequent interpretation of their biological and clinical relevance. Our comparisons capture baseline microbiome features at the time of the initial DCR surgery, which are then contrasted by later outcomes. Therefore, the differences we identify represent pre-existing microbial signatures linked to subsequent relapse, not changes that occur post-surgery or at the time of a revision procedure. From a clinical standpoint, evidence on nasolacrimal microbiology has largely been culture-based, with more recent sequencing studies expanding organism detection in primary NLDO and in revision/failed DCR. To place our findings in this clinical context, we summarize key prior studies and their clinical settings in Table 3.
Table 3.
Key prior studies on lacrimal sac/sinonasal microbiology and sequencing studies in NLDO/DCR
| Study | Clinical Setting | Study design | Sampling site and timing | Methods | Main organisms/Key findings |
|---|---|---|---|---|---|
| Mills et al. 2007 | Acute vs. chronic dacryocystitis | Prospective multicenter | Lacrimal sac material (clinical sampling / during procedures) | Culture dependent | Gram-positive predominant; Staphylococcus common; MRSA proportion higher in acute cases |
|
Chung et al. 2018 |
Dacryocystitis | Retrospective | Purulent material from lacrimal sac | Culture dependent | S. aureus, Pseudomonas spp., and Propionibacterium acnes frequently isolated |
| Blicker et al. 1993 | DCR patients | Clinical series | Lacrimal sac + ipsilateral nose + conjunctiva (peri-operative) | Culture dependent | Lacrimal sac commonly culture-positive; partial concordance with conjunctival/nasal flora; Staphylococcus common |
| Curragh et al. 2019 | Unilateral acquired NLDO (pre-DCR) | Prospective | Lacrimal sac + middle/inferior meatus (ipsilateral/contralateral), plus controls | 16S rRNA sequencing (V3-V4) | Lacrimal sac dominated by Staphylococcus and Corynebacterium; no major genus-level differences vs. adjacent sinonasal sites |
| Ali et al. 2023 | PANDO | Prospective | Lacrimal sac (intra-operative) | Shotgun metagenomics | Broad spectrum beyond culture; diverse community including Proteobacteria/Actinobacteria/Firmicutes and others |
| Ali et al. 2022 | PANDO | Prospective | Lacrimal sac (intra-operative) | Shotgun metagenomics | Functional profiling: metabolism most represented; followed by environmental/genetic information and cellular processes |
| Ali et al. 2024 | Failed DCR undergoing revision endoscopic DCR | Prospective | Lacrimal sac (revision intra-operative) | Shotgun metagenomics | Microbiota differed from primary NLDO; species such as S. maltophilia, Pseudomonas spp., and S. pneumoniae detected |
| Present study | PANDO undergoing endoscopic DCR | Prospective | Lacrimal sac + ipsilateral nasal mucosa (intra-operative) | 16S rRNA sequencing | Baseline signature differed between later recurrence vs. non-recurrence; overlap between lacrimal and nasal communities |
Abbreviations: NLDO nasolacrimal duct obstruction, DCR dacryocystorhinostomy, PANDO primary acquired NLDO.
Earlier studies suggested microbial overlap across the ocular–lacrimal–nasal axis. Blicker and Buffam et al. reported Staphylococcus species in lacrimal sac cultures from chronic dacryocystitis, with partial concordance in conjunctival and nasal samples on the same side [13]. Culture-dependent analyses in primary acquired NLDO frequently isolated Staphylococcus and reported mixed flora and polymicrobial growth [2, 3, 14, 15].
Metagenomic profiling further expanded the understanding of the lacrimal sac microbiome, revealing additional predominant taxa such as Acinetobacter johnsonii, Porphyromonas catoniae, Cutibacterium acnes, Pseudomonas alcaliphila, Escherichia coli, and Haemophilus influenzae, indicading that the microbial community is more complex than previously recognized [16]. In a later whole-genome shotgun analysis of primary acquired NLDO samples, Ali et al. [17] demonstrated a microbiome mainly composed of Proteobacteria, Bacteroidetes, Fusobacteria, Actinobacteria, and Firmicutes, with functional pathways enriched in metabolic and cellular processes, suggesting an active and ecologically structured community in the lacrimal sac.
Consistent with Curragh et al. [18], who demonstrated that the lacrimal sac and adjacent sinonasal mucosa share a highly similar bacterial community dominated by Staphylococcus and Corynebacterium, our study likewise found comparable alpha and beta diversity across the nasal–lacrimal interface. This overall similarity supports the concept of a continuous mucosal system which extends from the nasal cavity to the lacrimal drainage pathway. In our cohort, a mild but statistically significant difference between nasal and lacrimal microbiota was detected in the non-relapse group; however, this intra-group variation was not correlated with postoperative outcome and may reflect normal nasal- lacrimal variation rather than a factor associated with recurrence.
Prior work has highlighted the virulence adaptability of Staphylococcus species, including toxin production and biofilm formation, which may contribute to persistent inflammation and antimicrobial tolerance [19–21]. Similar mechanisms have been implicated in chronic rhinosinusitis and ocular infections [22–24].
Accordingly, the lack of outcome-associated differences in alpha or beta diversity suggests that postoperative recurrence is unlikely to be driven by large-scale dysbiosis, but may relate to subtle taxonomic or functional differences.
Outcome-stratified analyses identified taxa enriched in relapse samples (Staphylococcus lugdunensis, Pseudomonas balearica, Corynebacterium, Bdellovibrionaceae, and Devosiaceae) and taxa enriched in non-relapse samples (Eikenella, Neisseriaceae, Mesorhizobium, Reyranella, and Ralstonia).
Of note, the non-relapse group was characterized by the presence of taxa with diverse metabolic and redox-regulating abilities. Mesorhizobium strains are known to produce bioactive compounds, including exopolysaccharides with documented anti-inflammatory and immune-modulating properties, which may promote a local environment favorable for wound healing. These bacteria also release enzymes such as proteases and lipases that may contribute to tissue remodeling and reduce fibrotic scarring at the surgical site [25]. Similarly, comparative genomic studies have showed that Ralstonia species have unique metabolic pathways that support survival in low nutrient aquatic environments [26].
Although these genera are not typical mucosal commensals, their enrichment may reflect an ecological state associated with favorable postoperative remodeling.
Functional analysis provided additional insight into the potential mechanisms linking microbial composition to postoperative outcomes. In the relapse group, predicted pathways related to bacterial invasion of epithelial cells, calcium signaling, and the citrate (TCA) cycle were more active. These pathways suggest stronger bacterial interaction with host tissues and higher metabolic activity. These processes are often associated with epithelial barrier disruption, reactive oxygen species (ROS) generation, and activation of profibrotic signaling cascades such as calcium-dependent myofibroblast contraction and extracellular matrix remodeling [24]. Prior sinonasal work has linked epithelial innate immune activation to barrier compromise and inflammatory signaling [27]. Among the infection-related pathways, the Salmonella and Yersinia infection pathways represent conserved gene sets involved in bacterial adhesion, invasion, and TLR-mediated inflammation [28].
In contrast, the non-relapse group showed higher predicted activity in metabolic and regulatory pathways, including adipocytokine signaling, steroid metabolism, and longevity-regulating modules. These pathways are often linked to anti-inflammatory and tissue repair processes and may represent a stable metabolic environment that supports mucosal repair and epithelial regeneration [29–31].
Taken together, our findings suggest that recurrence after technically successful endoscopic DCR may relate more to subtle, outcome-associated microbial or functional signatures than to overt infection or disruption of the nasal–lacrimal continuum. If validated, these baseline features could support mechanistic studies of mucosal remodeling and future work on risk stratification or targeted perioperative modulation of the local microbial environment.
A major strength of this study is its paired-site design, which enables intra-individual comparison across the nasal–lacrimal interface and reduces inter-subject variation. Limitations include modest sample size and the limited taxonomic and functional resolution of 16S-based inference; unmeasured host, anatomical, or surgical factors may also influence recurrence.
Future work should validate these associations in larger cohorts and incorporate longitudinal sampling before and after DCR, ideally with higher-resolution metagenomic or multi-omics approaches to clarify temporal dynamics and causal relationships.
Acknowledgements
This work was conducted with the support of a research grant from Taipei Veterans General Hospital (Grant No. V113B-023).
Funding
Open access funding provided by Taipei Veterans General Hospital. This study was supported by a research grant from Taipei Veterans General Hospital (Grant No. V113B-023).
Data availability
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
Paired nasal mucosa and lacrimal sac microbiome features in recurrence after endoscopic dacryocystorhinostomy.
Declarations
Ethical approval
All procedures and data collection were approved by the Institutional Review Board of Taipei Veterans General Hospital (IRB No. 2023-06-006 C).
Conflict of interest
The authors declare that there are no conflicts of interest related to this work.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Yu-Wen Huang, Email: d40724008.y@nycu.edu.tw.
Wei-Kuang Yu, Email: wkyu3@vghtpe.gov.tw.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
Paired nasal mucosa and lacrimal sac microbiome features in recurrence after endoscopic dacryocystorhinostomy.