Distinct bacteria profiles in primary and secondary/persistent endodontic infections: a 16S rRNA gene sequencing study

Abstract

Background

This study investigated the bacterial community composition, phenotypes, and differentially abundant taxa in primary and secondary/persistent endodontic infections.

Methods

Bacterial profiles of 12 primary and 12 secondary/persistent endodontic infections were analyzed using 16 S V3-V4 next-generation sequencing. Reads were processed into ASVs using DADA2 in Qiime2, and taxonomy was assigned with the SILVA dataset. Alpha and beta diversity were compared between groups using Kruskal-Wallis and PERMANOVA. LEfSe identified differentially abundant taxa (LDA > 2), and Bugbase predicted community phenotypes, which were compared with the Mann-Whitney-Wilcoxon test.

Results

The alpha-diversity and beta-diversity are higher in the secondary/persistent group than in the primary one. In the primary group, anaerobic, Gram-negative, and potentially pathogenic microbes are dominant, whereas facultatively anaerobic, Gram-positive microbes are more prevalent in the secondary/persistent group. The bacterial metabolic phenotype is associated with the tooth condition. Linear discriminant analysis effect size analysis reveals that the relative abundance of genera Clostridia_vadinBB60_group and Rothia are higher in the primary group, while Saccharimonadaceae, Veillonella, Actinomyces, Granulicatella, Haemophilus, Bergeyella, Leptotrichia, Capnocytophaga, TM7x, Neisseria, Centipeda, and Saccharimonadales are more dominant in the secondary/persistent group.

Conclusion

Significant differences in species and abundance were present between primary and secondary/persistent endodontic infections, with the bacterial community being more diverse in secondary/persistent group than in primary one. The taxonomic and phenotypic information derived from microbiome analysis helps elucidate the microbial basis for primary and secondary/persistent infections, identify potential causes of treatment failure, and guide downstream irrigation protocol, retreatment strategy, and risk assessment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-026-07821-w.

Introduction

Maintaining dental health is critically dependent on the health of the dental pulp. Endodontic infections involve inflammation or necrosis of the dental pulp and adjacent periradicular tissues, and are predominantly driven by bacterial species. Archaea, fungi, viruses, and protozoa have also been detected in such infections, but typically in far lower abundance and with uncertain clinical significance [1]. The limited blood supply in pulp tissue compromises its immune response, frequently resulting in uncontrolled bacterial growth, inflammation, and progressive damage. While endodontic treatment often successfully eliminates these infections through proper instrumentation, disinfection, and obturation, symptoms reappear in a significant proportion of cases due to residual microbes (persistent infection) and/or new microbial invasion (secondary infection), despite seemingly satisfactory earlier intervention [2–5]. The endodontic infection may not only increase the risk of systemic infection but also be associated with many systemic diseases, such as diabetes and cardiovascular diseases [6, 7]. A comprehensive investigation of the bacterial profile in the primary and secondary/persistent endodontic infections could help elucidate critical bacterial taxa responsible for the infection and treatment failure, thereby contributing to the development of more targeted therapeutics.

The microbial basis of root canal lesions has been extensively investigated using culture-dependent and culture-independent molecular methodologies. While culture-based approaches provide a foundational understanding of the bacterial community in endodontic infections [2–5], they are limited by time-consuming, labor-intensive, and prone to bias because they cannot cultivate many fastidious species [8]. The introduction of molecular methodologies, particularly next-generation sequencing (NGS), broadened the scope of microorganisms associated with endodontic infection beyond culturable bacteria to include a wide array of other microorganisms [9]. Despite the varying merits and weaknesses of each sequencing platform, the major bacterial phyla in primary and secondary/persistent endodontic infections—Actinobacteriota, Bacteroidota, Firmicutes, and Proteobacteria — are found consistently across studies [10–14]. Among these, Firmicutes [10, 12, 14–16] and Bacteroidota [11, 17] are often the most abundant phyla, while Proteobacteria has also been found to rank first in some studies from the Americas [18, 19]. However, findings on bacterial diversity and differentially abundant taxa across studies are inconsistent. Some studies report higher diversity in primary infections [14], others in secondary/persistent infections [10], and some show no significant difference [12]. This inconsistency is likely due to the inclusion of a range of tooth types with differing anatomical complexity, as well as the use of unequal sample sizes for each tooth type across investigations. To minimize potential confounding factors, the study focused on single-rooted teeth to analyze the taxonomic and phenotypic information for understanding the microbial etiology of primary versus secondary infections using 16 S sequencing.

The goal of this study is to analyze and compare the bacterial communities associated with primary and secondary/persistent endodontic infections using single-rooted teeth. The null hypothesis of this study is that there is no difference in the bacterial profile between primary and secondary/persistent endodontic infections, and that bacterial taxonomical and phenotypic information does not distinguish primary from secondary/persistent infections.

Materials and methods

Sample collection

This cross-sectional study received approval from the institutional ethics committee (IRB No. 10809-002), compliant with STROBE guideline. The required sample size was calculated using QIIME2 evident plugin to ensure 70% power (1 – β = 0.7) at a 10% significance level (α = 0.1) for detecting differences in Chao1 (total observations = 21.13) and Shannon (total observations = 22.04) indices between groups. Between October 2019 and May 2020, single-rooted teeth with endodontic infections were collected from patients with signed informed consent in Chi Mei Medical Center, Tainan, Taiwan. The study groups comprised 12 teeth with initial, untreated endodontic infections and 12 treatment failure teeth. The initial, untreated endodontic infection was categorized into the primary endodontic infection group and diagnosed based on: (1) Necrotic pulp (no response to pulp vitality testing), (2) Clinical signs (spontaneous pain, tenderness to percussion/palpation), and (3) Radiographic evidence of periapical radiolucency. Treatment failure teeth were designated into the secondary/persistent infection group, characterized by the presence of apical lesions with or without symptoms (e.g., pain, swelling, or sinus tract). These treatment failures were attributed to either persistent infection, which is caused by the survival of residual microbes following the initial treatment or secondary infection, which is caused by a new microbial invasion defined as microbial re-entry occurring either during the non-healing phase after initial treatment (e.g., via coronal leakage) or after a period of established successful healing, where success is defined as complete periapical resolution for a minimum of 12 months post-treatment. Exclusion criteria included antibiotic therapy within the past three months; systemic diseases (e.g., diabetes, cardiovascular disease, cancer); lifestyle habits such as smoking, alcohol consumption, or betel nut chewing; and under 20 years of age. Teeth with periodontal disease (probing depths > 4 mm) or root canal calcification were also excluded. All clinical procedures and sample collections were performed by a single experienced operator under strict aseptic conditions using rubber dam isolation. The operative field was disinfected sequentially with 30% hydrogen peroxide (FUJIFILM Wako Pure Chemical Co., Japan), 10% povidone iodine (Sinphar Pharmaceutical, Taiwan), and 3% sodium hypochlorite (Nihon Shiyaku Industries LTD., Japan), followed by inactivation with 5% sodium thiosulfate (Thermo Fisher Scientific, Lancashire, UK). The estimated working length was first measured as 2 mm short of the root apex on radiography. Final working length was determined as 1 mm short of the root apex using Root ZXII apex locator (J.Morita Co., Tokyo, Japan) and verified radiographically. Root canal samples were absorbed and collected by placing at least two sterile size-30/taper-0.04 paper points (Sure Dent Corporation, Gyeonggi-do, South Korea) into the canal for 60 s after dislodging microbes and infected tissue from the canal surface using a sterile #10K-type hand file (Maillefer, Ballaigues, Switzerland) and resuspension with normal saline. The collected samples were immediately transferred to a 2 ml microcentrifuge tube and stored at -80 °C for downstream analysis [20] .

DNA extraction and sequencing library preparation

DNA was extracted from tooth samples using the DNeasy PowerBiofilm Kit (QIAGEN, Hilden, Germany), following the manufacturer’s instructions. Metagenomic libraries were then prepared according to Illumina’s protocol. The V3-V4 region of the bacterial 16 S rRNA gene was amplified via PCR using the degenerate primers 341 F and 805R, and Kapa HiFi DNA polymerase (Roche, Basel, Switzerland), and unique sample barcodes were subsequently added to these primary PCR products through an indexing PCR. All PCR products were purified using Sera-Mag Select beads. The purified 16 S amplicons were quantified using Quant-iT™ dsDNA Assay Kits (Invitrogen, Carlsbad, CA, USA) and pooled into equimolar amounts for sequencing. To control for contamination, an extraction blank was included during library preparation. Furthermore, to minimize bias, the research staff performing DNA extraction and library preparation was blinded to the clinical information of the samples.

Sequencing

Paired-end sequencing was conducted on the Illumina MiSeq platform (Illumina, San Diego, CA, USA) using MiSeq Reagent Kits v3 (2 × 300 cycles) with a 20% PhiX spike-in.

Data processing and analysis

Sequence data were processed and analyzed using Qiime2 [21]. FASTQ files were imported, demultiplexed, and denoised, dereplicated [22], and filtered for chimeras using Non-16 S sequences were removed by BLASTing representative ASVs against the SILVA_138.1_SSURef database, and potential contaminants were identified and filtered by comparing against reads from extraction blank controls using QIIME2’s decontam-identify and decontam-remove functions with a decontam score threshold of 0.1 [23]. The filtered ASVs were used to calculate alpha-diversity (Chao1, Pielou’s evenness, Faith’s PD, Shannon index) within samples and beta-diversity (Jaccard, Bray-Curtis, weighted UniFrac, unweighted UniFrac) between groups. Group significance for alpha diversity was assessed with the Kruskal-Wallis test and beta diversity was assessed using PERMANOVA and PERMDISP tests. Taxonomy was assigned using the Qiime2 feature-classifier with a pre-trained SILVA SSU Ref NR 99 classifier [24]. Visualization of alpha diversity, beta diversity, and taxonomic composition was performed using the Dokdo (v1.16.0). Metagenomic biomarkers were identified using LEfSe [25], and bacterial phenotypes were predicted with Bugbase [26].

Results

Patient selection and sequencing results summary

To compare bacterial profiles in primary and secondary/persistent endodontic infections, defined as newly diagnosed and recurrent/persistent infections, respectively, we recruited 29 patients, including one negative control. After excluding four patients due to specific clinical criteria, 24 samples (12 primary infection and 12 secondary/persistent infection) were sequenced, yielding 3,952,823 reads (mean = 164,701). Processing with Qiime2 (version amplicon-2024.2) and quality filtering resulted in 347,533 high-quality reads (mean = 14,480.5). Removal of non-16 S sequences by BLAST against the SILVA_138.1 database and potential contaminants using Qiime2 decontam-identify and decontam-remove yielded 321,868 reads (mean = 13,411) for downstream analysis. Rarefaction curve analysis indicated that a sequencing depth of 4447 reads was sufficient to capture most bacterial diversity in our samples (Fig. 1), and this depth was used for subsequent comparisons between the infection groups. Detailed clinical characteristics of these patients are presented in Table 1. The differences in age, gender distribution, and lesion size between the two patient groups are not statistically significant, with p-values of 0.11876 (Mann-Whitney U test), 0.6464 (Fisher’s exact test), and 0.3843 (Mann-Whitney U test), respectively.

Fig. 1.

Rarefaction curves of microbial communities from each sample of the primary (P) and secondary/persistent (SP) infection groups. Each line was labeled with the group name and sample code

Table 1.

Clinical characteristics, tooth condition, and the number of identified bacterial phyla and species of patients for the study

Sample No.	Infection type	Age	Gender	Tooth No.	Pulp Dx	Apical Dx	Lesion size(mm)	Tooth condition	Phylum/Species
P1	P	63	M	43	PN	AS-AP	4x3	no specific	8/41
P2	P	69	M	23	PN	A-AA	7x8	C	9/80
P3	P	61	F	23	PN	C-AA	3x2	C	5/9
P4	P	23	F	22	PN	S-AP	PDL widening	C	6/16
P5	P	31	F	12	PN	C-AA	15x14	C	7/40
P6	P	32	F	12	PN	C-AA	9x10	C	8/44
P7	P	32	F	11	PN	AS-AP	4x3	C	6/20
P8	P	35	F	21	PN	AS-AP	2x1	C	11/49
P9	P	35	F	22	PN	A-AA	5x6	C	10/37
P10	P	35	F	12	PN	S-AP	10x7	C	9/37
P11	P	21	F	11	PN	A-AA	3x1	no specific	8/33
P12	P	25	F	12	PN	C-AA	11x7	C	8/19
SP1	SP	63	F	22	PT	AS-AP	3x3	IO	7/36
SP2	SP	63	F	23	PT	S-AP	3x3	IO	11/53
SP3	SP	30	M	11	PT	S-AP	12x8	GP overfilling	5/12
SP4	SP	63	F	12	PT	AS-AP	1x1	IO	7/25
SP5	SP	63	F	21	PT	AS-AP	3x1	IO	8/56
SP6	SP	45	M	31	PT	A-AA	9x8	C/IO/CL	10/56
SP7	SP	45	M	41	PT	AS-AP	2x1	C/IO/CL	12/57
SP8	SP	48	M	25	PT	S-AP	PDL widening	no specific	8/96
SP9	SP	39	F	21	PT	C-AA	4.5x1	C/IO/CL	12/81
SP10	SP	39	F	11	PT	AS-AP	5x5	C/IO/CL	10/50
SP11	SP	39	F	12	PT	AS-AP	4x3	C/IO/CL	9/36
SP12	SP	21	F	22	PT	A-AA	9x8	IO	8/45

Primary endodontic infection (P) is defined as newly diagnosed root canal infections with pulp necrosis (PN) in pulp diagnosis (Pulp Dx), and acute (A) or chronic (C) apical abscess (AA), or symptomatic (S) or asymptomatic (AS) apical periodontitis (AP) in apical diagnosis (Apical Dx). Secondary/persistent endodontic infection (SP) is defined as a recurrent and/or persistent root canal infection that occurs in a previously treated (PT) tooth at least 6 months after the completion of the initial treatment and is associated with various apical conditions. Abbreviations employed in describing lesion size and tooth condition include periodontal ligament widening (PDL widening), caries (C), gutta-percha overfilling (GP overfilling), inadequate obturation (IO), and coronal leakage (CL)

Alpha and beta diversity between the primary and secondary/persistent infection groups

Alpha-diversity, reflecting within-sample bacterial complexity, was assessed in primary and secondary/persistent infection groups using the Chao1, Pielou’s evenness, Shannon, and Faith’s PD indices and compared with the Kruskal-Wallis test (Fig. 2A). Secondary/persistent infection shows significantly higher estimated species richness (Chao1, p = 0.0262) and diversity considering abundance and evenness (Shannon, p = 0.0327) compared to primary infection. While not statistically significant, evenness (Pielou’s, p = 0.1659) and phylogenetic diversity (Faith’s PD, p = 0.1190) also trended higher in secondary/persistent infection. Beta-diversity, indicating between-group taxonomic differences, was evaluated using Jaccard, Bray-Curtis, weighted UniFrac, and unweighted UniFrac distances, and visualized with PCoA (Fig. 2B). Significant differences are found between the primary and secondary/persistent groups for Jaccard (p = 0.001), Bray-Curtis (p = 0.001), weighted UniFrac (p = 0.006) distances, and unweighted UniFrac (p = 0.033) based on the PERMANOVA test. To ensure that these findings are not driven by differences in within-group variation, we also perform the PERMDISP test, which shows no significant difference in dispersion between the groups in the four indices (Jaccard (p = 0.078), Bray-Curtis (p = 0.180), unweighted UniFrac (p = 0.447)), except weighted UniFrac (p = 0.008).

Fig. 2.

Comparison of alpha and beta diversity between primary (P) and secondary/persistent (SP) endodontic infection groups. (A) Alpha diversity indices (Chao1, Shannon entropy, Pielou’s evenness, Faith’s PD) were compared using the Kruskal-Wallis test; significant p-values (< 0.05) are indicated with asterisks. (B) Principal Coordinate Analysis (PCoA) plots visualize beta diversity differences between the groups based on Jaccard, Bray-Curtis, weighted UniFrac, and unweighted UniFrac distances, with statistical significance assessed by PERMANOVA and PERMDISP tests

Bacterial taxonomic composition in the primary and secondary/persistent endodontic infections

Taxonomic analysis using the SILVA SSU Ref NR 99 database [24] reveals 18 phyla in primary and 14 in secondary/persistent infections, with 13 shared. Archaea are exclusive to the primary group. The number of phyla per sample ranges from 5 to 11 (primary) and 5–12 (secondary/persistent), with averages of 7.92 and 8.92, respectively. Phylum relative abundance differs significantly between groups (Fig. 3A). In primary infection, median relative abundances of the top 5 phyla are Bacteroidota (33.83%), Firmicutes (10.30%), Actinobacteriota (2.79%), Proteobacteria (0.66%), and Campilobacterota (0.61%). In secondary/persistent infections, the top 5 are Firmicutes (18.70%), Proteobacteria (7.23%), Actinobacteriota (4.53%), Bacteroidota (4.29%), and Fusobacteriota (1.21%). At the species level, 246 and 253 species are identified in primary and secondary/persistent infections, respectively, with 126 shared. Species per sample ranged from 9 to 80 (primary) and 12–96 (secondary/persistent), averaging 35.42 and 50.25. A few common species are prevalent in both groups. Unique species show limited prevalence within their respective groups. The top 19 abundant species differ significantly between groups (Fig. 3B, Supplemental Table 1). Key species (> 5% abundance) in primary infection are Porphyromonas. gingivalis (19.53%), Phocaeicola abscessus (12.97%), Eubacterium nodatum (11.63%), F0058 spp. (8.09%), and Parvimonas spp. (5.63%); in secondary/persistent infections, they are Streptococcus spp. (13.37%), Pseudomonas spp. (13.01%), Fusobacterium spp. (12.12%), Streptococcus mutans (11.42%), and Corynebacterium matruchotii (5.88%). The only detected Archaea, Methanobrevibacter spp., is found in one primary infection sample.

Fig. 3.

Bacterial community taxonomy in root canals of primary (P) and secondary/persistent (SP) endodontic infections. (A) Distribution of top five bacterial phyla relative abundances is visualized as boxplots for each infection group. Outlier samples are marked with asterisks. Each box encompasses the 25th to 75th percentile, with the median indicated by a horizontal line. Whiskers extend to the minimum and maximum relative abundance values. (B) Species-level microbial composition of individual samples from primary and secondary/persistent infection groups is presented as a stacked bar chart. The relative abundance of the top 19 most abundant species is indicated by distinct colors (legend on the right), while less abundant species are grouped and colored light cyan

Differentially abundant taxa between the primary and secondary/persistent infection groups

To pinpoint taxa with significantly different abundances between primary and secondary/persistent endodontic infections, we performed LEfSe analysis (Fig. 4). This reveals that the genus Clostridia_vadinBB60_group (p = 0.0329) and Rothia (p = 0.031) are significantly more abundant in the primary infection group. In contrast, the secondary/persistent infection group shows a significant enrichment of the genera Saccharimonadaceae (p = 0.0063), Veillonella (p = 0.0014), Actinomyces (p = 0.0091), Granulicatella (p = 0.024), Haemophilus (p = 0.0329), Bergeyella (p = 0.0147), Leptotrichia (p = 0.002), Capnocytophaga (p = 0.0037), TM7x (p = 0.0025), Neisseria (p = 0.0028), Centipeda (p = 0.0329), and Saccharimonadales (p = 0.0063). The figure also provides information on the Gram staining characteristics, predicted metabolic phenotypes, and the prevalence (number of positive samples) of each of these differentially abundant genera.

Fig. 4.

Linear Discriminant Analysis Effect Size (LEfSe) analysis is performed to identify differentially distributed taxa between the primary (P) and secondary/persistent (SP) infection groups. The histogram of the LDA scores shows the differentially abundant taxa between the two groups. Genera labeled with group-specific colored underlines or squares indicate preferentially or exclusively presence in that specific group. The features and number of positive samples in primary and secondary/persistent infection groups of these differentially abundant genera are shown in the figure

Bacterial phenotype difference between the primary and secondary/persistent infection groups

The community-wide bacterial phenotypes of the primary and secondary/persistent infection groups were predicted using Bugbase [26] and compared across: aerobic, anaerobic, facultatively anaerobic, mobile element containing, biofilm forming, Gram-negative, Gram-positive, potentially pathogenic, and oxidative stress tolerant. The comparison was performed using the Mann-Whitney-Wilcoxon test (Fig. 5). The results show that bacteria in the primary infection group are more anaerobic, Gram-negative, and potentially pathogenic. In contrast, the secondary/persistent infection group contains more facultatively anaerobic and Gram-positive bacteria.

Fig. 5.

The community-wide bacterial phenotypes of the primary (P) and secondary/persistent (SP) endodontic infection groups predicted by Bugbase. The p-values between groups in different phenotype categories are labeled beneath each plot (Mann-Whitney-Wilcoxon test). The p-values of categories with a statistical difference are marked with asterisks

Discussion

Endodontic infections primarily stem from oral microbiota, and their microbial profiles share a high degree of similarity, with dominant phyla including Firmicutes, Actinobacteriota, Proteobacteria, Fusobacteriota, and Bacteroidota [27, 28]. The bacterial population within the infected root canal results from a dynamic balance between surviving residents and new invaders. The composition of the bacterial community at the infection site is mainly determined by the initial tooth condition and the thoroughness of the endodontic treatment. Consequently, the diversity can vary considerably from case to case, and the bacterial population can be either decreased, stabilized, or increased after treatment. The increased bacterial diversity observed in secondary/persistent endodontic infections in the study may correlate with deficiencies in the initial root canal disinfection and/or the entry of new bacteria through inadequate or leaking restorations. Supporting this speculation, retrospective reviews of clinical histories showed that teeth with secondary/persistent endodontic infection frequently presented with inadequate obturation (often displaying poor density and voids), coronal leakage from recurrent caries, or apical lesions. These tooth conditions are recognized as frequent causes of endodontic treatment failure [29, 30]. Nevertheless, since the microbiome data are not derived from paired sequential samples from the same patients, further investigation is still needed to determine whether the shifts in bacterial diversity are indicative of treatment failure due to persistence of the original infection or emergence of new bacterial invasion following previous endodontic treatment in secondary/persistent infection cases.

Different tooth conditions could create distinct growth niches that favor colonization of distinct bacteria and expression of particular traits. Consequently, the bacterial phenotype in endodontic infections could serve as a useful indicator of risk factors for treatment resistance or failure. Given that the pulp tissue, shielded by dentin and enamel, typically has lower oxygen tension, it’s generally believed that anaerobic bacteria are the most prevalent colonizers in initial root canal infections. Consistent with this, our study’s findings of a high prevalence of phyla known for their anaerobic members (e.g., Bacteroidota) and abundant presence of anaerobic species and genera (Phocaeicola abscessus, Porphyromonas gingivalis, Parvimonas spp., and Veillonella spp. Figure 3). This suggests a low-oxygen environment within the root canal in primary endodontic infections, likely established due to tiny cavities created by caries. While facultative anaerobes can survive anaerobically, their less effective growth compared to obligate anaerobes often explains their lower prevalence during initial anaerobic colonization, such as primary endodontic infections. On the contrary, secondary/persistent endodontic infection often arises because the initial procedure is inadequate or compromised, which could create more space for oxygen penetration and lead to elevated oxygen levels. The bacterial populations in these failed treatment root canal shift to more oxygen-tolerant bacterial groups (phyla), such as Firmicutes, Proteobacteria, and Actinobacteriota, dominated by aerobic or facultative anaerobic species like Pseudomonas spp. Streptococcus spp. and Corynebacterium matruchotii (Fig. 3). While bacteria from primary and secondary/persistent endodontic infections exhibit distinct oxygen utilization preferences, case-specific complexities (tooth condition, tissue health, treatment quality) can cause the bacterial community’s oxygen utilization preference to deviate from this pattern, as seen with the predominance of anaerobic Fusobacterium spp. and Saccharimonadaceae spp. in case SP3 and SP8 of the secondary/persistent infection group, respectively, and prevalence of aerobic, facultative anaerobic Rothia and Pseudomonas in P5 and P8 of the primary infection group, respectively. Such deviations underscore the inherent complexity and uniqueness of individual endodontic infections and highlight that taxonomic and phenotypic annotations from microbiome analysis provide valuable directions for dissecting factors influencing treatment prognosis, and guiding downstream treatment planning.

Determination of differentially abundant taxa for a specific infection condition is important for identification of critical bacteria of an infection, development of new disinfection methods, and tailored treatment. Using LEfSe analysis, Clostridia_vadinBB60_group and Rothia are identified as biomarkers for primary endodontic infection. Rothia species detected in this study, such as R. aeria and R. dentocariosa, have been associated with oral and dental infections and biofilm formation [31–33]. Clostridia_vadinBB60_group, belonging to the frequently found Clostridia class in endodontic infections [8], is capable of producing toxins and forming biofilms [34, 35]. While these groups are significant in the pathogenesis of primary infections, their presence in secondary infections warrants consideration of their roles in treatment failure. LEfSe analysis identifies another 12 marker genera for secondary/persistent endodontic infection. Six of them are preferentially present in the secondary/persistent group, including Actinomyces, Capnocytophaga, Veillonella, Leptotrichia, Granulicatella, and Neisseria, which have been reported to be involved in biofilm formation [27, 36–40], and may contribute to treatment resistance. The remaining 6 marker genera exclusively present in the secondary group are all microbes generally found in the oral cavity. Three of them, Bergeylla, Centipeda, and Haemophilus, are either aerobic, facultative anaerobic, or capable of biofilm formation [8, 13, 16, 41]. Their presence is observed to be correlated with non-healing cases. The other three, Saccharimonadales, Saccharimonadaceae, and TM7x, are currently unculturable. Their roles in secondary/persistent endodontic infections await further elucidation. Earlier studies frequently link many bacteria—including Streptococcus, Fusobacterium, Parvimonas, Prevotella, Porphyromonas, Dialister, and Tannerella—to primary endodontic infection; Streptococcus, Propionibacterium, Enterococcus, Prevotella, and Actinomyces are often cited as associated with secondary/persistent endodontic infection [8]. However, these taxa are not consistently found at high-ranked abundance, nor are they uniformly more prevalent in that specific infection condition across different studies [10–12, 14, 42]. This discrepancy could be due to factors, including differences in recruiting criteria, tooth type and condition, dietary habits of the study population, and different statistical methodologies across different studies. To identify critical taxa for specific endodontic infection conditions, more clearly defined clinical and demographic criteria and a consensus analytic pipeline will be needed. Further investigation into the roles of these marker bacteria in endodontic infection will help improve diagnosis, predict treatment outcomes, and guide the design of novel disinfection protocols, as well as patient-specific endodontic therapies.

Given the polymicrobial nature of most endodontic infections, which are influenced by complex interactions between tooth pathology, adjacent tissue health, and treatment quality, strategies targeting only specific bacterial groups must be insufficient for infection resolution. Consequently, broad-spectrum disinfection agents, such as calcium hydroxide, sodium hypochlorite (NaOCl), and chlorhexidine (CHX), remain essential for endodontic treatment. Further exploration of newer broad-spectrum disinfection strategies based on nanoparticles, novel botanical or chemical formulations, or advanced physical techniques like photodynamic therapy and photon-induced photoacoustic streaming (PIPS) is needed to enhance disinfection effectiveness and help eradicate recalcitrant species [5, 43]. However, achieving a cure in endodontic treatment should not rely only on repeated administration of broad-spectrum disinfection strategies. Instead, incorporation of microbiome-derived taxonomic and phenotypic information to support precision diagnosis and formulate tailored treatment could become extremely valuable for achieving effective endodontic resolution, especially for patients with compromised immunity.

Although the study employed high-throughput 16 S rRNA gene sequencing to provide detailed taxonomic and inferred phenotypic profiles of bacterial communities in endodontic infections, these findings are predominantly based on inference via comparison to reference databases (e.g., SILVA) and predictive platforms (e.g., BugBase) rather than on direct functional assessment. Many clinically important bacterial traits are strain-specific and only manifested under particular environmental or physiological conditions. Fully elucidating the roles and pathogenic mechanisms of microorganisms in endodontic conditions will require more advanced culture or cultivation-independent functional approaches. Additional limitations of the study include the relatively small sample size, the lack of balanced clinical and radiographic conditions between groups, the single-center design, the cross-sectional nature of the study, and the restriction to single-rooted teeth. The absence of significant microbiome data differences between acute versus chronic apical abscesses and between symptomatic versus asymptomatic periodontitis cases in the current study may be attributed to these limitations. Beyond the inherent challenge of simultaneously analyzing mixed secondary and persistent infections, a significant methodological limitation is the lack of precise information regarding the post-treatment follow-up process for the treatment failure teeth. This limitation precludes the reliable inclusion of pure secondary endodontic infection cases, which are characterized by microbial re-entry after stable periapical repair. Future studies should adopt more rigorous designs and address these limitations to reach clearer and more generalizable conclusions.

In summary, our 16 S rRNA sequencing analysis reveals that both α-diversity and β-diversity are greater in secondary/persistent endodontic infection than in primary one. Moreover, the two types of infection harbor distinct bacterial communities with differing phenotypic features closely correlated with the clinical condition of the tooth. These divergent bacterial signatures in primary versus secondary/persistent infections hold promise for enhancing diagnostic accuracy, forecasting treatment outcomes, and supporting the creation of tailored disinfection and endodontic treatment.

Abbreviations

DADA2

Divisive amplicon denoising algorithm 2

Qiime2

Quantitative insights into microbial ecology version 2

PERMANOVA

Permutational multivariate analysis of variance

PERMDISP

Permutational analysis of multivariate dispersions

LEfSe

Linear discriminant analysis effect size

LDA

Linear discriminant analysis

STROBE

Strengthening the reporting of observational studies in epidemiology

rRNA

Ribosomal ribonucleic acid

DNA

Deoxyribonucleic acid

PCR

Polymerase chain reaction

BLAST

Basic local alignment search tool

Authors’ contributions

K.-L.C. : Contributed to conception, design, drafted and critically revised the manuscript. I.-C.L., C.-A.C. and C.-Y.K.: Contributed participant enrollment and sample collection. Y.-Y.J.: Contributed to data acquisition and interpretation. Y.-C.L. and K.Y.: critically revised the manuscript J.L.: Contributed to data interpretation, drafted and critically revised the manuscript. All authors gave their final approval and agreed to be accountable for all aspects of the work.

Funding

The study was supported by grant CMFHR10889 from Chi Mei Medical Center, Tainan, Taiwan, grant CORPG6N0311 and CMRPG6N0151-2 from Chang Gung Memorial Hospital, Chiayi, Taiwan, grant 109-2314-B-182 A-146-MY2 from Ministry of Science and Technology, Taiwan, Republic of China, and 113-2314-B-182 A-057 from National Science and Technology Council, Taiwan, Republic of China.

Data availability

Raw sequencing data have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (accession number PRJNA1281861).

Declarations

Ethics approval and consent to participate

The study was performed according to the ethical standards set by the Declaration of Helsinki and was approved by the institutional ethics committee of Chi Mei Medical Center (IRB No. 10809-002). Written informed consent was obtained from all participants following a detailed explanation of the study protocols and prior to their enrollment.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.