Genomic characterization of Corynebacterium diphtheriae isolates from human origin in Brazil, 1974-2024

Introduction: Diphtheria is a potentially fatal disease that still causes deaths mainly in unvaccinated children. Over the last decades, the incidence of this disease has reduced drastically in face to the increase in vaccination coverage. Diphtheria is mainly caused by toxigenic Corynebacterium diphtheriae, however, in more recent years, invasive infections due to nontoxigenic Corynebacterium diphtheriae have emerged. Given this epidemiological threat, the continued surveillance remains essential to guide prevention and control measures.

Methodology: Using whole genome sequencing, we characterized 299 Corynebacterium diphtheriae isolates, assessing their clinical origin, age distribution of patients, tox gene carriage, antimicrobial resistance markers, and phylogenetic relationships.

Results: The tox gene was identified in 255 isolates (85.3%). Antimicrobial resistance genes aph(3’’)-Ib, aph(3’)-Ia, aph(6)Id, cmx, tet(33), tet(O), tet(W), and tet(Z) were detected in low (<10%) frequencies, but sul1 was found in 72 (24.1%) isolates. Phylogenetic analyses identified 11 main clades comprising 286 isolates, represented by 46 different sequence types (ST); the remaining 13 isolates were distributed in the other 12 ST. Twenty-one novel ST were described, comprising 51 isolates.

Discussion: Our study represents the largest genomic survey of Corynebacterium diphtheriae in Latin America. These results enhance global understanding of diphtheria and reinforce the need for vigilance against reemergence in areas with suboptimal vaccination coverage.

Introduction

Diphtheria is a potentially fatal disease that still causes deaths mainly in unvaccinated children (Sharma et al., 2019). Over the last decades, the incidence of this disease has reduced drastically in face to the increase in vaccination coverage. Diphtheria is mainly caused by toxigenic Corynebacterium diphtheriae, however, in more recent years, invasive infections due to nontoxigenic C. diphtheriae have emerged (Dangel et al., 2018; Hoefer et al., 2021). In addition, diphtheria due to other toxigenic Corynebacterium species, such as C. ulcerans, has also been reported (Sharma et al., 2019; Acosta, 2022).

Clinical management of diphtheria consists of therapy with antitoxin and antimicrobial agents, which eliminate the bacteria in the patient and limit the transmission chain (Burkovski, 2014). Penicillin and erythromycin are the first-line agents to treat diphtheria (Husada et al., 2019). Usually, C. diphtheriae has been considered susceptible to the main drugs employed for the clinical management of infections. Conversely, increased use of antimicrobial therapy has occurred in recent years, as a result of the reduction in diphtheria antitoxin production (Hennart et al., 2020).Therefore, the selection of resistant isolates that can impair the clinical management of diphtheria cannot be ruled out as a problem soon.

Over the last years, with the development of highly discriminatory molecular typing methods, the phylogeny of C. diphtheriae has been unveiled. Recombination events are frequent in C. diphtheriae, contributing to its diversity. For example, diphtheria toxin is coded for by an incorporated bacteriophage gene, tox, which can infect different Corynebacterium isolates. Longitudinal molecular epidemiology studies with C. diphtheriae isolates are scarce. To date, only a few large studies have been conducted with this aim, such as one analyzing the Belarusian outbreak isolates (1994-2003) and another detailing the isolates from France and French territory isolates (Hennart et al., 2020; Grosse-Kock et al., 2017). More recently, a persistent outbreak of ST76 was identified among cutaneous C. diphtheriae isolates from a low-income population in Vancouver, Canada (Chorlton et al., 2020).

In Brazil, a continental country with huge social disparities and different levels of access to the healthcare system, diphtheria still occurs mainly among the most vulnerable population. Since the introduction of the diphtheria vaccine into our National Immunization Program (NIP) in 1973, we have observed a decrease in diphtheria incidence (Supplementary Figure 1) but in 2010 an outbreak was reported in the State of Maranhão, Northeast Region, involving 27 patients and three deaths (Santos et al., 2015). Since 2010, 95 cases have been reported in the country; therefore, diphtheria continues to occur in Brazil (Supplementary Figure 1).

To understand the evolutionary story and genomic aspects of diphtheria in Brazil, we conducted this laboratory-based study. It consists of the first comprehensive genomic report of C. diphtheriae from Latin America, and the largest one performed so far.

Material and methods

Bacterial isolates

We recovered 299 C. diphtheriae isolates, from non-repetitive individuals, from nasopharynx or oropharynx secretion, skin infection, or blood, sent to the Brazilian National Reference Laboratory for Diphtheria (Instituto Adolfo Lutz, São Paulo) and kept in the Collection Culture of Bacteriology Division, Instituto Adolfo Lutz, São Paulo, Brazil. We re-identified all the bacterial isolates with MALDI-TOF MS Microflex LT (Bruker Daltonics, Bremen, Germany).

DNA extraction and quality control

Following the isolation and purity confirmation of C. diphtheriae from the stock tube, we extracted the DNA using the commercial Promega Wizard kit (Madison, WI, USA) following the manufacturer’s recommendations. We performed the initial lysis with 10μl of lysozyme (40mg/mL) for 60 minutes/55°C. After extraction, we quantified the DNA in Qubit equipment (Thermo Fisher Sci., Waltham, MA, USA). We analyzed the integrity of the genetic material by agarose electrophoresis in an Egel platform (Invitrogen, Waltham, MA, USA).

Library preparation and whole genome sequencing

We sequenced the isolates using an Ion Torrent S5 equipment (Thermo Scientific, Waltham, MA, USA) following the manufacturer’s instructions for library preparation and run. When new alleles or ST were identified, we prepared new libraries for Illumina sequencing (San Francisco, CA, USA) in NextSeq equipment (since BIGSdb [https://bigsdb.pasteur.fr/] does not accept Ion Torrent results for assignment of novel alleles). We checked the run quality by including PhiX (Illumina, San Francisco, CA, USA) in each run.

Genome assembly and downstream analysis

We assembled the short reads with the Spades algorithm (Ion Torrent reads) or CLC Workbench (Qiagen, Hilden, Germany) (Illumina reads). Next, we determined quality control metrics (e.g., genome size, N50, N90, contig count, GC content) using QUAST (version 5.2.0) (Supplementary Table 1). Using the generated fasta file, we determined the sequence type based on seven housekeeping genes, by using the BIGSdb webserver (Jolley and Maiden, 2010). In addition, we employed ABRICATE to identify the virulence (Chen et al., 2005) and antimicrobial resistance genes (Bortolaia et al., 2020), in the Galaxy Europe environment (Afgan et al., 2022), using default parameters (minimum DNA identity 80% and minimum DNA coverage 80%) with ResFinder for AMR and VFDB for virulence markers (Chen et al., 2005). We also used the virulence factors database integrated into diphtOscan (available at the diphtOscan GitLab repository (https://gitlab.pasteur.fr/BEBP/diphtoscan) to identify the spuA gene (DIP0357). First, a BLAST database was created using the blastnmk command within the Galaxy environment. Then, blastn was run against our set of 299 genomes. A phylogenetic analysis was performed with the 299 genomes sequenced in this study using Prokka (version 1.14.6) and pan-genome analysis was performed with Roary (version 3.13.0). Core genome SNPs were extracted using SNP-sites (version 2.5.1), and phylogenetic inference was performed using IQ-Tree with 1,000 bootstrap replicates. Tree and respective metadata were visualized using Microreact (Argimón et al., 2016). SNP-distance matrices were computed using SNP-dists (version 0.8.2 – https://github.com/tseemann/snp-dists). A second approach of phylogeny was carried out, using the curated cgMLST scheme for C. diphtheriae implemented in BIGSdb (Institut Pasteur, Paris). Allelic profiles were calculated using the Genome Comparator tool, applying BLAST-based allele calling with default parameters. An allelic distance matrix was generated and a Neighbor-Joining tree was reconstructed using a custom Python script with Biopython (v1.84).

For both cases, the resulting Newick file was uploaded to Microreact for interactive visualization together with genome typing.

Results

We evaluated a total of 299 human C. diphtheriae isolates from 1974 to 2024, and received from all five administrative regions in Brazil. The C. diphtheriae isolates analyzed in this study were predominantly (n=287; 96.0%) recovered from respiratory secretions (nasopharynx or oropharynx); five isolates (1.7%) were recovered from cutaneous wounds (cutaneous diphtheria) and four (1.3%) were detected from blood; for three isolates the source information was not available. These isolates represented all regions of the country, including the North (4), Northeast (21), Central-West (5), Southeast (265), and South (4) (an interactive map can be accessed at https://microreact.org/project/fMTo7YUYNZsJ18Y8uuba5b-difteria299). Patients’ age (data available for 265/299 patients) ranged from <1 year old to 76 years, but the isolates were predominantly recovered from individuals aged <12 years old (median age was 7 years, interquartile intervals 4 and 12 years).

Of the 299 C. diphtheriae isolates, 255 were positive for the presence of the tox gene (85.3%). The tox gene was more frequently detected in isolates from the first years of the study. Half of the isolates (152) were recovered from 1974 to 1981, from which the tox gene positivity rate was 97.4%; the remaining 147 isolates were recovered between 1982 and 2024, and the tox gene positivity rate was 72.8% (p < 0.0001; Fisher Chi-Square test). When the same analysis was carried out during two similar periods, tox gene positivity was higher in the 1974–1999 period (90.2%) compared to the 2000–2024 period (56.8%) (p < 0.0001; Fisher Chi-Square test).

We analyzed the genomes of the C. diphtheriae isolates for the presence of the main genes responsible for pilus formation. The following pilus genes and their respective frequencies were found: spaA (26.1%), spaB (30.8%), spaC (21.7%), spaD (0.7%), spaE (19.7%), spaF (0.7%), spaG (6.4%), spaH (6.4%), spaI (6.4%). Regarding the genes encoding pilus-related sortases, the following rates were detected: srtA (30.4%), srtB (19.7%), srtC (19.7%), srtD (6.4%), srtE (6.4%). Fifty-two (17.4%) isolates exhibited the complete spaABC system, two (0.7%) the spaDEF, and 19 (6.4%), the spaGHI system. However, none of these genes were found in 203 isolates (67.9%). Based on the genomic data, only 15.7% (47/299) of the isolates carried the spu gene, indicating that these strains belong to the Gravis biotype. In contrast, the majority of isolates (84.3%; 252/299) lacked spu, suggesting that the remaining isolates represent strains of the Mitis biotype.

We detected the sulfonamide resistance gene sul1 in 72 isolates (24.1%), while other genes were found in low frequencies: aph(3’’)-Ib (1.3%), aph(3’)-Ia (1.3%), aph(6)Id (1.3%), cmx (9.7%), tet(33) (1.3%), tet(O) (3.0%), tet(W) (10.4%), and tet(Z) (0.3%). We did not observe a temporal pattern for antimicrobial resistance genes (Supplementary Figure 2).

MLST analysis revealed diversity within the isolates, with the presence of 58 different STs, 21 of them described for the first time in this study. An overall representation of clades (based on the SNP tree) along with the virulence and resistance genetic determinants is presented in Figure 1. Table 1 depicts the main characteristics of each clade, including the in silico determined biotype, the tox status, the ST and the number maximum of SNPs found in each one. A bubble plot showing the distribution of clades by year is also presented (Supplementary Figure 3). cgMLST approach retrieved the same topology and clades distribution as SNP analysis (Supplementary Figures 4, 5).

Figure 1

Figure 1. Phylogenetic relationship of 299 human C. diphtheriae recovered in Brazil, 1974-2024. The interactive tree, including the geographic localization, can be accessed in Microreact (https://microreact.org/project/fMTo7YUYNZsJ18Y8uuba5b-difteria299) and metadata is available fromSupplementary Table 1.

Table 1

Table 1. Distribution of ST, biotype and tox gene positivity according to clade determined by SNP analysis for human Corynebacterium diphtheriae recovered in Brazil, 1974-2024.

Some clades were characterized for the 100% positivity of the tox gene, such as clade 1, clade 2, clade 4, clade 5, and clade 8. The largest clade, clade 1, was composed of 64 isolates, all of them with tox gene, and belonging to 6 different ST, all of them representing the ST174 or some of its single locus variants (SLV) ST. Isolates from clade 1 were detected from 1980 until 2014, in Central-West, North, and Southeast Regions. SNP difference among the isolates of clade 1 was up to 5182. According to in silico analysis, clade 1, clade 2, clade 4 and clade 8 were identified as Mitis biotype, while clade 5 as Gravis.

The second most numerous clade, clade 6 (Mitis), encompassed 45 isolates, from diverse STs (resulting in a higher number of SNP, 17941), with 86.7% tox gene positivity. Isolates from this clade were recovered between 1977 and 2024, from Central-West, Northeast, and Southeast Regions. On the other hand, two clades were represented exclusively by non-toxigenic isolates. Clade 10 (Gravis) was formed by only six highly conserved isolates (maximum SNP count, 73) from the ST32, recovered from 2008–2024 in South and Southeast Regions. Clade 11 (Gravis) encompassed eight isolates, from three different ST (related to ST317), with a maximum SNP count of 2337. They were recovered from 1997 to 2015, from North and Southeast regions.

Discussion

This study presents the largest genomic investigation on C. diphtheriae isolates from Brazil. Through genomic analysis of 299 isolates of C. diphtheriae spanning more than 50 years, originating from all five geographical regions of the country, it was possible to obtain a representative scenario of the genetic characteristics of the C. diphtheriae population causing disease in Brazil in recent decades. A significant genomic diversity was observed in this population, consistent with the results obtained by other authors (Hoefer et al., 2021; Trost et al., 2012; Valadão, 2020; du Plessis et al., 2025). This study identified 58 different STs, 21 of them described in our isolates for the first time.

Although SNP distances within clades can exceed 10,000 SNPs due to long-term diversification and recombination, cgMLST showed identical phylogenetic topology, reinforcing that the clades represent population lineages rather than recent transmission clusters. The most prevalent clade 1, associated with ST174 and its SLV and DLV, was found to persist in three distinct geographic regions (CW, N, SE) for more than 30 years. Remarkably, all the isolates of this clade were found to carry the tox gene. ST174 is not recognized as a global clone. In the BIGSdb database, only one entry (id: 2166) showing this ST is retrieved (accessed January 31, 2025), corresponding to a Brazilian toxigenic isolate (without further information). The other STs from this clade 1 were ST798 (DLV of ST174) and ST847 (SLV of ST174), both with limited representativeness (one entry each) in BIGSdb. Outside Brazil, toxigenic ST174 (along with its SLV ST697) isolates were reported in Venezuela, in a large outbreak that took place from 2016-2019, affecting more than 300 patients (Strauss et al., 2021). Humanitarian crises and conflicts are resulting in an increase in the deprived population with difficulty accessing health services. Venezuela and Brazil are bordering countries in South America, and our country has experienced a substantial influx of Venezuelan migrants and refugees (McGill, 2024). As well documented, migrants, refugees, and asylum seekers are reported to have an increased risk condition for infectious disease transmission (Dinleyici and Borrow, 2020). Although the movement is significant, the increase in the number of Latin American migrants could not be associated with any of the recent diphtheria cases reported in our study. However, our study indicates that toxigenic ST174 is a relevant clone for South America.

Another frequent ST identified in our study was ST846, allocated in our clade 2 with its SLV ST841 and another ST846-DLV. This clade is composed exclusively of toxigenic isolates, only from Sao Paulo city, located in the Southeast region, from 1974-1985. Both ST846 and ST841 were not reported in public databases. Genomic profiles restricted, or at least predominant, in a particular country, are common in the epidemiology of C. diphtheriae, possibly due to the genetic heterogeneity of this pathogen (Chorlton et al., 2020; du Plessis et al., 2017).

The detection of ST32 (n=6) among our isolates was particularly noteworthy. This lineage was assigned to clade 10, and recovered among our isolates only in more recent decades (between 2008 and 2024). ST32 is a non-toxigenic lineage with a preference for respiratory infections and widespread circulation worldwide, particularly in Europe. Despite the absence of tox gene, virulence capacity of this clone is supported by experimental and genomic studies (Sangal et al., 2015). Considering that the emergence of ST32 as a recognized pathogen is relatively recent, during the 1980’s (Hoefer et al., 2021), the detection of this lineage among our isolates highlights the circulation of a toxin-negative clone with potential vaccine escape in the most recent isolates. Contrasting with the tox-negative results, this clade was markedly identified as spu positive, indicating that their isolates belong to Gravis biotype.

Sixty-eight percent (203/299) of our isolates lacked the traditional pili-encoding gene systems, indicating that other virulence factors may have influenced the onset of the disease. The lack of canonical pilus clusters in 67.9% of isolates did not significantly differ across clades, tox or spu gene status/biotype (Table 1), suggesting the maintenance of virulence through alternative adhesion pathways and host-adaptation mechanisms (Ott et al., 2022). To further explore the potential association between pilus systems and epidemiological or genomic features, we performed chi-square tests using the complete spaABC cluster (the most frequent) as a marker of canonical pilus presence. No significant association was found between spaABC and phylogenetic clustering (clustered vs non-clustered clades; χ² = 0.59, p = 0.44) or tox gene carriage (χ² = 0.63, p = 0.43). When comparing respiratory and non-respiratory isolates, spaABC was more frequent among the latter (50.0% vs 16.0%), and this difference reached statistical significance (χ² = 7.04, p = 0.008; Fisher’s exact test p = 0.008). However, this finding is based on only 12 non-respiratory isolates and should be interpreted with caution.

On the other hand, the majority (254/299, 85%) of the isolates in this study presented the tox gene. We observed that toxin gene detection frequency has declined in more recent years. In the last 10 years, we did not identify consistent circulation of toxigenic strains in our reference laboratory.

In 2024, a single sporadic case of respiratory diphtheria caused by toxigenic C. diphtheriae occurred in Sao Paulo state. Isolate was identified as ST67. ST67 C. diphtheriae was already reported in BIGSdb occurring in the Philippines, Vietnam, Russia, France, Belgium, and previously in Brazil. Epidemiological measures, such as active surveillance to identify contacts, selective vaccination blockade, and chemoprophylaxis for cases and/or carriers identified were taken on time, and no more cases were reported. This case is an illustration that diphtheria can still occur in recent days, reinforcing that the highest vaccination coverage must be re-established.

Historically, the vaccination coverage for diphtheria protection in Brazil began to increase significantly in the 1990s, accompanied by a decrease in the incidence rate of the disease (Supplementary Figure 1). Nevertheless, since 2016, vaccination coverage has been below the recommended coverage of >90% (Truelove et al., 2020). Among the isolates studied, a strict correspondence between the genomic clade and tox gene status was observed, which is in line with observations in the literature (Chorlton et al., 2020; du Plessis et al., 2017; Timms et al., 2018).

As the diphtheria vaccine is based on diphtheria toxoid, it only protects against toxigenic isolates, favoring an increase in infections caused by non-toxigenic isolates due to vaccine pressure, as observed in countries with high vaccination coverage (Dangel et al., 2018; Chorlton et al., 2020; Timms et al., 2018; Will et al., 2021). Despite the decline in vaccination coverage in our country in recent years, the vaccine continues to provide effective protection against toxigenic isolates.

For the non-toxigenic isolates, antimicrobial therapy plays a major role in diphtheria management. Currently, the main antimicrobial agents employed for diphtheria treatment are penicillin and erythromycin (Husada et al., 2019). We found that Brazilian isolates presented low detection rates of antimicrobial-resistant genes. More recently, some authors found a significant percentage of isolates resistant to penicillin and identified the pbp2m gene associated with beta-lactam resistance (Hennart et al., 2020), or ermX, associated with erythromycin resistance (Arcari et al., 2023). Both of these genetic determinants of resistance were not found in our study. The resistance genes detected were associated with resistance to aminoglycosides (aph(3’’)-Ib, aph(3’)-Ia, aph(6)Id), chloramphenicol (cmxA), sulfonamines (sul1), and tetracyclines (tet(33), tet(O), tet(W), and tet(Z)). Furthermore, although we identified antimicrobial resistance (AMR) markers, the presence of these genes does not necessarily translate into phenotypic resistance. Therefore, caution is required when interpreting these genomic findings.

Although this study has provided novel and highly relevant information, using state-of-the-art laboratory tools, we must address some limitations. The rarity of the disease required a retrospective study design, which inherently poses challenges in retrieving clinical and epidemiological data such as patient age or source of infection. The absence of clinical data (e.g., vaccinal status, and travel history) limits our conclusions. In addition, recovering vaccination records remains particularly challenging in Brazil, a continental country with heterogeneous surveillance practices and information systems that are not fully integrated across states and municipalities. As a result, access to reliable vaccination data is limited even for isolates collected in recent decades. Geographic metadata were also imprecise in older records, which sometimes reported only the State or the municipality; therefore, we standardized the analyses to State-level information. This constraint reflects the passive nature of national surveillance systems and restricts the granularity of spatial interpretations. The quality of epidemiological surveillance and laboratory diagnosis also varies across geographic regions, which contributes to an unequal representation of isolates in our collection. Ongoing efforts aim to reduce this gap and strengthen data retrieval, which will be essential for more robust epidemiological and genomic interpretations in future studies. Additionally, due to the retrospective nature, genetic isolation during storage cannot be ruled out. Since only Illumina sequencing data can be employed to assign new alleles and ST, some isolates were sequenced with this technology; cross-platform consistency analyses demonstrated that Ion Torrent and Illumina sequencing yielded comparable genomic metrics, indicating that the use of two platforms did not bias phylogeny, ST assignments, or AMR/virulence detection.

Our research unveiled a diverse population of C. diphtheriae in Brazil, with toxigenic lineages representing the largest population of isolates that caused diphtheria over the last 50 years. On the other hand, a low frequency of antimicrobial resistance genes was observed. Considering the vaccine-preventable nature of diphtheria, we emphasize the importance of vaccination policies, alongside continuous and prospective surveillance. These measures are crucial for mitigating the impact of the disease in Brazil, strengthening the public health response, and protecting the population from potential future outbreaks.

Data availability statement

The data presented in the study are deposited in the NCBI repository, accession number Bioproject PRJNA1209004, https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1209004.

Ethics statement

The C. diphtheriae isolates’ data studied here came from a retrospective collection of bacterial isolates gathered by the Institute Adolfo Lutz as part of national routine surveillance activities. Patient information was obtained through routine clinical care procedures, and, during this study’s analysis, patient identification was completely anonymous. No human or animal tissue or any other biological material was used in this study. This study was approved by the Institutional Review Board, Technical and Scientific Council (CTC12-I/2016) of the Institute Adolfo Lutz (São Paulo, Brazil) and by the local Ethics Committee (CAAE 43301320.00000.0059).

Author contributions

SB: Conceptualization, Formal Analysis, Methodology, Writing – original draft, Writing – review & editing. CS: Conceptualization, Methodology, Writing – review & editing. AL: Conceptualization, Writing – original draft, Writing – review & editing. ET: Software, Visualization, Writing – review & editing. MS: Formal Analysis, Methodology, Writing – review & editing. RA: Formal Analysis, Methodology, Writing – review & editing. KC: Formal Analysis, Methodology, Writing – review & editing. EC: Conceptualization, Formal Analysis, Software, Writing – review & editing. CC: Conceptualization, Formal Analysis, Software, Supervision, Visualization, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This study was carried out as part of our routine work. We are grateful to Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), which indirectly supported this study 2017/50333-7, 2018/21192-9.

Acknowledgments

We gratefully acknowledge the surveillance units, hospital staff, and Public Health Laboratory (LACENs) staff at the local, state, and federal levels for sending the C. diphtheriae isolates to the Institute Adolfo Lutz, and the Secretary of Health Surveillance (COVER, CGLAB, SVS), Brazilian Ministry of Health, for the coordination of the laboratory network, especially Gabriela Pereira for her invaluable support. We also thank the General Coordination of Scientific Incorporation and Immunization (CGICI/DPNI/SVSA/MS) in the name of Luciana Nascimento for guiding the obtaining of epidemiological data. The authors would also like to extend their particular thanks to the Fleury Group for providing the six C. diphtheriae isolates. We are grateful to Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), which indirectly supported this study 2017/50333-7, 2018/21192-9.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fbrio.2025.1718207/full#supplementary-material

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