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Article

Genetic Diversity of Streptococcus pneumoniae Isolated from Thirteen Arab Countries and over 22 Years: A Retrospective Bioinformatics Analysis

by
Muhammad Halwani
1,
Manal Al Daajani
2 and
Safa Boujemaa
3,*
1
Department of Medical Microbiology, Faculty of Medcine, Al Baha University, Al Baha 65431, Saudi Arabia
2
Deputyship of Population Health, Ministry of Health, Riyadh 11176, Saudi Arabia
3
Biologica Training and Consulting Company, La Marsa 2070, Tunisia
*
Author to whom correspondence should be addressed.
Microbiol. Res. 2026, 17(1), 12; https://doi.org/10.3390/microbiolres17010012
Submission received: 25 October 2025 / Revised: 30 December 2025 / Accepted: 6 January 2026 / Published: 7 January 2026
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Abstract

Streptococcus pneumoniae (S. pneumoniae) is responsible for a wide range of infections. The aim of this study was to investigate the clonal diversity of S. pneumoniae in thirteen Arab countries. Multi-Locus Sequence Typing (MLST) data were extracted from PubMLST database. Genetic analysis was performed using DnaSP software version 6.0. A Minimum Spanning Tree (MST) analysis was conducted to evaluate the population structure of S. pneumoniae strains. Genetic data from 1008 Arab S. pneumoniae strains, collected over 22 years (1996–2018), were analyzed. MLST analysis identified a highly diverse population comprising 600 sequence types grouped into 87 clonal complexes and 295 singletons. Both internationally disseminated clones (e.g., ST156) and country-specific lineages (e.g., ST2307, Saudi Arabia) were observed, indicating substantial geographic structuring. Significant associations were detected between sequence types and geographical origin, decade of isolation, patient age, disease type, and serotype (p < 0.05). Although recombination events were presented, the population retained a predominantly clonal structure over time (ISA = 0.0715, p < 0.001). Overall, these findings demonstrated extensive genetic heterogeneity and spatiotemporal structuring of S. pneumoniae in the Arab region, providing valuable insights for regional surveillance and vaccine-related strategies.

1. Introduction

Streptococcus pneumoniae (S. pneumoniae) is a Gram-positive, extracellular, opportunistic pathogen that colonizes the mucosal surfaces of the human upper respiratory tract [1]. Carriage of S. pneumoniae represents a commensal interaction between the bacterium and the host, and up to 27–65% of children and less than 10% of adults are carriers [2]. S. pneumoniae is a major bacterial cause of bacteremia, meningitis, otitis media, and community-acquired pneumonia (CAP), primarily asymptomatically in both adults and children, and one of the principal bacterial pathogens colonizing the nasopharynx [3]. In the pre-antibiotic era, 95% of pneumonia cases were thought to be caused by S. pneumoniae. Currently, it is responsible for up to 15% of pneumonia infections in the United States and 27% of pneumonia cases globally [4]. In 2017, the World Health Organization (WHO) listed S. pneumoniae as one of the 12 priority pathogens. Data about the clinical burden of pneumococcal disease in the majority of countries of the Middle East and Northern Africa (MENA) region are limited. Recent data estimate that pneumococcal disease incidence in Saudi Arabia is 2.5–9.6 per 100,000 children aged <5 years, with the exception of Al-Baha City where the incidence is 21.6 per 100,000 [5].
The pathophysiology of pneumococcal infection is strongly influenced by the capsular polysaccharides of S. pneumoniae, and at least 100 serotypes have been identified based on variations in the capsule synthesis locus (cps) gene [6]. The fifteen serotypes that cause pneumococcal invasive diseases are 14, 6, 1, 19, 3, 4, 5, 9, 18, 23, 12, 7, 2, 25, and 8. In many Arab and Middle Eastern/North African countries, pneumococcal vaccines—including conjugate vaccines such as PCV7, PCV10, and PCV13 as well as the polysaccharide vaccine PPV23—have been introduced into national immunization schedules to increase coverage of invasive serotypes; for example, PCV13 and PCV10 are in routine use in several countries across the region, although uptake and introduction timing vary among national programs [7].
Molecular studies have demonstrated that S. pneumoniae can undergo intra- and interspecies DNA recombination, leading to alterations in virulence factors, antibiotic resistance, molecular type, and capsule composition [8]. These phenomena pose significant obstacles to pneumococcal disease prevention and treatment. Consequently, the use of genotyping techniques is crucial to comprehending the population biology of S. pneumoniae.
A number of molecular typing techniques were created to track the S. pneumoniae epidemiology [9]. Among these, Multi-Locus Sequence Typing (MLST) can offer strong discriminatory and resolving capacity for application in both local and worldwide epidemiology. An MLST scheme based on the sequencing of internal regions of seven housekeeping genes (aroE, ddl, gdh, gki, recP, spi, and xpt) has been proposed and is currently in widespread use to better assess the evolution and proliferation of S. pneumoniae [10].
Comprehensive epidemiological studies of invasive S. pneumoniae strains in Arab countries remain limited, with most existing research focusing on serotype distribution and antimicrobial resistance [11,12]. Therefore, the aim of this retrospective study was to genetically characterize geographically and temporally diverse strains of S. pneumoniae isolated in thirteen Arab countries using the MLST scheme.

2. Materials and Methods

2.1. Bacterial Strains and Data Sources

This study analyzed 1008 S. pneumoniae strains collected between 1996 and 2018 from thirteen Arab countries: Saudi Arabia, Qatar, Egypt, Iraq, Morocco, Tunisia, Kuwait, Lebanon, Syria, Jordan, Oman, United Arab Emirates, and Yemen (Supplementary Table S1). Available epidemiological data included geographic origin, decade of isolation (1990s, 2000s, 2010s), patient age group (infant 0–1 year, toddler 2–5 years, child 6–12 years, adolescent 13–18 years, young adult 20–45 years, middle adult 46–65 years, and old adult >65 years), disease type, and serotype, although not all variables were reported for every strain. MLST allelic profiles and nucleotide sequences of the seven housekeeping genes (aroE, ddl, gdh, gki, recP, spi, and xpt) were retrieved from the PubMLST database. The MLST scheme described by Enright and Spratt [10] was used as a reference framework for sequence typing, while all genetic and epidemiological tests were performed on the Arab-country strains extracted from PubMLST database (https://pubmlst.org/organisms/streptococcus-pneumoniae, accessed on 1 December 2024) hosted at the University of Oxford, Oxford, UK). MLST data consisted of allelic profiles and nucleotide sequences of the seven housekeeping genes. Allelic profiles were used for population structure analysis (goeBURST and MST), while concatenated nucleotide sequences were used for genetic polymorphism and recombination analysis.

2.2. Genetic Polymorphism Analysis

Genetic polymorphism analysis was performed using DnaSP software version 6.0 (University of Barcelona, Spain) [13]. Genetic polymorphism analysis included the calculation of the total number of alleles for each locus, the number of polymorphic sites and mutations, and the haplotype diversity (H). Polymorphic sites refer to nucleotide positions showing variation among sequences, whereas the number of mutations represents the total count of mutational events inferred at these sites. We calculated the ratio of non-synonymous to synonymous substitution (dN/dS) to evaluate the mode of natural selection affecting the seven loci. dN/dS < 1 indicated a purifying selection, dN/dS = 1 indicated a neutral selection, while dN/dS > 1 revealed a positive selection throughout population evolution. To evaluate the neutrality of the observed DNA polymorphisms, Tajima’s D values were calculated. No evidence of selection was estimated by Tajima’s D values not significantly different from 0. A recent selective sweep or population expansion after a recent bottleneck was detected if Tajima’s D values were significantly < 0, while proved balancing selection or sudden population contraction was proved if Tajima’s D values were significantly > 0 [14].

2.3. Discriminatory Power of MLST

The Simpson’s Index of Diversity (SID) was calculated to assess the discriminatory power of the MLST scheme, using PHYLOViZ version 2.0 software (University of Lisbon, Lisbon, Portugal) [15]. The SID is a diversity metric that considers both the total number of strains and their relative abundance. The SID value ranges from 0 to 1, where 0 represents absence of diversity and 1 represents absolute diversity [16]. Hence, a highly biodiverse population will have a high SID value.

2.4. Population Structure

The allelic profiles of the 1008 S. pneumoniae strains were examined to find closely linked genotypes within extremely similar clusters. Using PHYLOViZ version 2.0 software [15], clonal complexes (CC) were identified using goeBURST analysis, indicating a consensus ancestral type. We used the single locus variable (SLV) criterion to assess the genetic relatedness of S. pneumoniae strains. This indicates that a difference of no more than one locus was permitted within a CC. We performed a Minimum Spanning Tree (MST) analysis using PHYLOViZ version 2.0 software to evaluate the eventual association between sequence type (ST) and the geographic origin, decade of isolation, patient age, disease type, and serotype associated with each strain.

2.5. Recombination Tests

SplitsTree version 4.0 software (University of Tübingen, Tübingen, Germany) was adopted to create the split network of STs using the neighbor-net approach [17]. Recombination was estimated using the pairwise homoplasy index (phi) test; a p-value < 0.05 indicates the presence of recombination [18]. Based on the concatenated sequences of the seven loci (3199 bp), the per site recombination/mutation ratio (ρ/θ) was computed by RDP version 5.0 software (University of Cape Town, Cape Town, South Africa) and using 100,000 Markov chain Monte Carlo (MCMC) iterations [19]. Recombination events were detected using six methods reported in RDP version 5.0 software: RDP, GeneConv, MaxChi, Chimaera, SiScan, and 3Seq. The standardized index of association (ISA) was computed in order to assess the linkage disequilibrium from allelic profiles. An ISA value of zero signifies a recombining population structure (linkage equilibrium), whereas an ISA value significantly deviating from zero indicates a clonal population (linkage disequilibrium). ISA was examined over 1000 iterations on the allelic profile based on Monte Carlo approach and via LIAN version 3.7 website (http://guanine.evolbio.mpg.de/cgi-bin/lian/lian.cgi.pl/query, accessed on 15 December 2024) [20].

2.6. Statistical Analysis

The Chi-square exact test was performed using IBM SPSS Statistics 25 (Chicago, IL, USA) [21] to assess the association between ST and geographical origin, decade of isolation, age of patients, disease and serotype. A p-value of < 0.05 was considered statistically significant [22].

3. Results

3.1. Allelic Polymorphism of the Seven Loci

The total number of mutations varied from 12 (recP) to 91 (ddl), while the number of polymorphic sites ranged from 12 (recP) to 80 (ddl), resulting in an allelic variation of 48 (aroE) to 88 (ddl) (Table 1). The haplotype diversity (H) varied from 0.793 (recP) to 0.909 (ddl) (Table 1). The ratio dN/dS ranged from 0.041 (gki) to 0.307 (aroE), showing a purifying selection (Table 1). The Tajima’s values ranged from −1.700 (ddl) to 0.247 (gki) and showed no statistical significance, suggesting that the genes are evolving neutrally (Table 1).

3.2. goeBURST Analysis

The 1008 S. pneumoniae strains evaluated by MLST were assigned to 600 STs (Supplementary Table S1), yielding a SID value of 0.9968 (95%CI: 0.9961–0.9974), which is a high discriminatory value for a molecular typing method. Among 600 STs, 440 (73.33%) were represented by a single strain, which resulted in the widespread topology of the MST (Supplementary Figure S1).
Among STs shared by several strains, the most frequently encountered were ST156 (23/1008, 2.28%), ST700 (19/1008, 1.88%) and ST11237 (18/1008, 1.79%) (Supplementary Table S2).
The eBURST analysis resolved the 600 STs into 87 clonal complexes and 295 singletons. The major CCs were CC1, which grouped 17 STs (37/1008, 3.67%), CC2 including 13 STs (37/1008, 3.67%), CC3 including 13 STs (29/1008, 2.88%), and CC4 grouping 12 STs (20/1008, 1.98%) (Figure 1). The eBURST analysis identified ST230, ST156, ST2218 and ST63 as the ancestral clone of CC1, CC2, CC3, and CC4, respectively (Figure 1).

3.3. Population Structure According to Geographical Origin, Decade of Isolation, Age Group, Disease Type, and Serotype

3.3.1. Geographical Origin

The majority of strains were from Saudi Arabia (325/1008, 32.24%) followed by Qatar (240/1008, 23.81%) and Egypt (154/1008, 15.28%) (Supplementary Table S3). The MST of the four major CCs revealed the presence of many international ST clones. Indeed, ST2013 grouped strains from Morocco, Egypt, Iraq and Qatar (Figure 2 CC1) and ST156, the most frequent clone, included strains from Iraq, Lebanon, Morocco, Qatar, Saudi Arabia, and Syria (Figure 2 CC2). We noticed that ST172 and ST1078 included Egyptian and Qatari strains (Figure 2 CC3). However, several STs were associated with a specific country. Indeed, ST2307, ST1447, ST2218, ST6000, ST6009, ST5999, and ST9847, were specifically detected in Saudi Arabia (Figure 2 CC1, CC3 and CC4) while ST15104, ST557, and ST13331 (Figure 1 CC1, CC2 and CC4) were linked to Iraq. This country-specific association was statistically significant, as confirmed by the Pearson Chi-square test (p < 0.001).

3.3.2. Decade of Isolation

Only 942 out of 1008 strains reported the decade of isolation of strains. The majority of strains were isolated in the 2010s (684/942, 72.61%), followed by the 2000s (225/942, 23.89%) and the 1990s (33/942, 3.5%) (Supplementary Table S1). The MST analysis revealed that some clones were isolated from different decades (ST2013, ST230, ST2037) (Figure 3 CC1), while some clones were associated with a specific decade. Indeed, ST11429, ST15104, ST13536, ST557, ST176, ST1373, ST13331, ST7340, ST2662, ST11503 included strains isolated in the 2000s, while ST4838 was associated with the 1990s (Figure 3 CC4). This specific association was statistically significant, as confirmed by the Pearson Chi-square test (p < 0.001).

3.3.3. Age of Patients

Only 552 out of 1008 strains reported the age of patients. The majority of strains were isolated from middle adults (205/552, 37.13%) followed by infant (99/552, 17.93%) and young adult (90/552, 16.30%) (Supplementary Table S4). The MST analysis revealed that some clones were isolated from different age groups. Indeed, the ancestral clone ST156 grouped strains isolated from young adults, middle adults, infants, and older adults, while ST320 included strains isolated from infants, toddlers, and middle adults (Figure 4 CC1 and CC2). However, some clones were associated with a specific age group. Indeed, ST11905, ST11430, ST1373, ST2568 were associated with middle adults (Figure 4 CC1 and CC3), while ST557, ST271, ST11904, and ST176 included strains isolated from infants (Figure 4). This specific age-group association was statistically significant, as confirmed by the Pearson Chi-square test (p < 0.001).

3.3.4. Disease

Only 307 out of 1008 strains reported the disease associated with each strain. The majority of strains were associated with carriage (98/307, 31.92%), followed by meningitis (75/307, 24.43%) and bacteremia (73/307, 23.78%) (Supplementary Table S5). The MST analysis revealed that only some clones were associated with different diseases. The ancestral clone ST156 grouped strains associated with bacteremia and pneumonia (Figure 5 CC1), while ST303 included strains linked to bacteremia, pneumonia and other infections (Figure 5 CC3). However, the majority of clones were associated with a specific type of infection. ST2128, ST933, ST2037, ST6227, ST2019, and ST2034 were associated with meningitis (Figure 5 CC1–CC3), while ST11501, ST494, and ST143 were specifically linked to conjunctivitis, otitis media, and meningitis/bacteremia, respectively (Figure 5). This specific association between clones and diseases was statistically significant, as confirmed by the Pearson Chi-square test (p < 0.001).

3.3.5. Serotype

Only 873/1008 strains reported the serotype associated with each strain. The most frequent serotype was 3 (68/873, 7.79%) followed by 14 (49/873, 5.61%), 19F (48/873, 5.50%), 1 (45/873, 5.15%), 19A (43/873, 4.93%), and 23F (41/873, 4.70%) (Supplementary Table S6). Hence, there were 208/873 (23.83%) strains included in PCV7, as well as 432/873 (49.48%) strains grouped into PCV13 serotypes.
The MST analysis revealed that the majority of STs were associated with a specific serotype and only some clones were associated with different serotypes. The ancestral clone ST156 grouped serotypes 14, 11A, 9A and 9V (Figure 6 CC2), while ST1078 included strains linked to serotypes 13, 15A, and 23F (Figure 6 CC3). However, the majority of clones were associated with a specific serotype. ST230 and ST8857 were associated with serotype 24F (Figure 6 CC1), while ST1864 and ST11921 were specifically linked to serotype 9V (Figure 6 CC2). This specific association was also confirmed by the Pearson Chi-square test (p < 0.001).

3.3.6. Recombination Analysis

The split network analysis of the 600 STs was conducted to evaluate the impact of recombination events on the evolution of S. pneumoniae. The results showed a network-like structure with rays of varying length and parallelogram-shaped groupings (Figure 7). This result was statistically validated by the phi-test (p < 0.001). Similarly, the per site recombination/mutation ratio (ρ/θ) value was computed using the concatenated sequences of the 600 STs to evaluate the proportional contributions of both recombination and mutation to the genetic variability of S. pneumoniae. This ratio was 9.025, suggesting that recombination is a major driving evolutionary force in S. pneumoniae population, since it was found to occur almost nine times more frequently than mutation.
To investigate further evidence for intergenic recombination, we performed six different tests (RDP, GenConv, MaxiChi, Chimera, SiScan, 3Seq) for recombination on concatenated sequences. A total of 115 potential recombination events were detected, of which twelve recombination events were supported by all tests (Table 2). Among these recombination events, the majority of STs predicted to be recombinants originated from Saudi Arabia (n = 8). Notably, ST172 from Egypt and Qatar was predicted to be a major parent of ST1447 from Saudi Arabia. Furthermore, half of the majority of parents (3/6) identified by the detection methods were isolated from Saudi Arabia. However, the minor parents identified by the detection methods were isolated from geographically diverse countries (Table 2).
A linkage disequilibrium analysis was also conducted to further assess the likelihood of recombination. Although S. pneumoniae population was found to undergo recombination, the standardized index of association revealed a tendency of linkage disequilibrium between the alleles (ISA = 0.0715, p < 0.001). This finding suggests the presence of clonally evolving STs within the population over time.

4. Discussion

S. pneumoniae is a leading cause of morbidity and mortality worldwide, particularly among the elderly and young children. This pathogen, which is the primary bacterial cause of pneumonia, sepsis, and meningitis, colonizes the nasopharynx as part of the normal flora [23]. Due to the substantial impact of S. pneumoniae on global public health systems, a thorough understanding of its clinical and genetic features is crucial for predicting vaccine effectiveness and for guiding vaccine design. However, epidemiological data on the genetic diversity of S. pneumoniae in Arab countries are limited.
Therefore, we used the MLST scheme, which is the gold standard for long-term epidemiological surveillance of several bacterial species [24], to investigate the genetic relationships among geographically and temporally diverse S. pneumoniae strains. This approach may aid in evaluating the effectiveness of pneumococcal conjugate vaccines used in the Arab region.
To the best of our knowledge, this study is the first to report a comprehensive genotypic analysis of S. pneumoniae strains isolated from Arab countries. A total of 1008 strains collected from thirteen Arab countries over an extended period (1996–2018) were analyzed. The findings indicated that the dN/dS ratios of all seven genes were low, suggesting an absence of positive selection pressure at these loci and confirming the suitability of these genes for population genetic studies [25]. The MLST scheme demonstrated strong discriminatory power, with a SID value of 0.996 based on comparative sequencing analysis of conserved regions in the seven housekeeping genes. This implies a greater than 99% probability that two randomly selected strains would belong to different alleles. Additionally, the identification of 600 STs out of 1008 strains highlights the high genetic heterogeneity of this species, suggesting ongoing genetic evolution [26]. Genetic heterogeneity in S. pneumoniae includes single-nucleotide polymorphisms as well as the presence or absence of large genomic islands encoding virulence factors such as pili and capsule. Genetic recombination can result in the exchange of more than 90 distinct capsule types [27]. Consequently, genetic variability among S. pneumoniae strains collected at different time points has been documented in Italy [28], India [29], and China [30], and appears to be common worldwide. MLST analysis revealed high diversity among Arab strains, with ST156, ST700, and ST11237 being the most frequent, all of which are globally distributed clones [31,32,33]. This finding is consistent with a study from Singapore, in which ST156 was among the most prevalent STs in children [34]. In contrast, a study in Spain involving 614 S. pneumoniae cases reported ST304 and ST306 as the most common clones [35], indicating geographical variation in clone distribution. ST156, also known as the Spain(9V)-ST156 clone, is a globally disseminated multi-resistant lineage that has been significantly overrepresented in invasive infections. It originated from a penicillin-susceptible ancestor (ST162) and likely first emerged in Spain [36,37]. Despite relatively limited antibiotic use, this clone has contributed substantially to the recent decline in penicillin susceptibility among pneumococci [32]. In Arab countries, the Spain9V-ST156 clone disseminated across six countries (Saudi Arabia, Iraq, Lebanon, Morocco, Qatar, Syria) over an 11-year period (2005–2016). Interestingly, ST700, the second-most frequent clone in Arab countries, shows wide dissemination in African countries (Kenya, South Africa, Ghana, Togo, Malawi, The Gambia, Nigeria). Previous carriage studies demonstrated that ST700 expanded following the introduction of PCV13 in Malawi and is now the most prevalent clone [38]. Accordingly, our results suggest that pneumococcal clonal types circulating in Arab countries are similar to those reported in Poland [32], Spain [39], Japan [40], Malawi [33], and Kenya [41]. However, ST11237, the third-most frequent clone in Arab countries, was detected exclusively in Iraq, although it has also been reported in the United Kingdom according to the PubMLST database(https://pubmlst.org/organisms/streptococcus-pneumoniae, accessed on 1 December 2024).
Understanding the geographic distribution of infections is crucial for implementing effective control strategies, including vaccination, and for strengthening the health system. Our study revealed a clear geographic clustering of S. pneumoniae clones, suggesting predominantly clonal spread. For example, ST700 was only detected in Iraq. In addition, MST analysis revealed the presence of international ST clones (e.g., ST156). Transmission of S. pneumoniae by carrier secretions may occur through direct contact between individuals or through bacterial spread on contaminated surfaces [1]. Several factors, including frequent and long-distance travel, could explain the spread of pneumococcus in Arab countries. Furthermore, the spread of S. pneumoniae among Arab countries may be attributed to frequent visits, and participation in the Hajj pilgrimage [42]. Pathogens can spread through increasingly complex and quick networks due to ongoing internal migration and daily commuting. The variety of dispersion brought about by human movements can be described by mechanical models using transportation networks and human travel data [43].
Using the conventional MLST technique, we were also able to obtain a reliable representation of the evolution of S. pneumoniae over time. Over the past twenty-two years, some STs have vanished while other clones have emerged. Indeed, the clones ST4838, ST2663, and ST12361 were found in the 1990s and were not found in strains from 1999 or later. However, ST320 appeared in 2012 and was not seen after 2017. Additional investigation is required to confirm the potential association between these chronological changes and the pathogenicity of S. pneumoniae. Given that more recent strains have a greater diversity of STs, it is probable that new strains are emerging more quickly now than in the past. Our findings were in line with those reported in China, where 32/85 STs were identified for the first time from a collection of 169 S. pneumoniae strains [44]. Similarly, a high prevalence of novel STs in S. pneumoniae that caused invasive diseases was detected in Kuwait in 2018 [45]. However, our findings should be interpreted with caution. The uneven temporal distribution of strains, with a higher sampling density in the 2010s, may partially account for the observed increase in diversity. Therefore, while the data suggest ongoing genetic diversification of S. pneumoniae, this trend may reflect, at least in part, differences in sampling intensity rather than an accelerated emergence of novel strains.
Our study also demonstrated a strong association between patient age and STs. It is not surprising since similar results were detected in a previous study indicating the influence of patient age on S. pneumoniae serotypes. Indeed, Inostroza et al. examined 247 S. pneumoniae strains and revealed that eight serotypes were identified in all age groups, while forty-two serotypes were found exclusively in one age group [46]. Similarly, we suggested that S. pneumoniae strains could be associated with specific clinical manifestations. Indeed, ST2128, ST933, ST2037, ST6227, ST2019, and ST2034 were associated with meningitis. In accordance with the findings of the current investigation, potential correlations between S. pneumoniae genotypes and infectious disease have been examined previously [10,47].
Serotypes 3 (68/873, 7.79%), 14 (49/873, 5.61%), 19F (48/873, 5.50%), 1 (45/873, 5.15%), 19A (43/873, 4.93%), and 23F (41/873, 4.70%) were the most common serotypes in all identified strains, which was similar to previous studies [48]. Considering the high prevalence of PCV7 serotypes (4, 6B, 9V, 14, 18C, 19F and 23F) and serotypes 1, 3 and 19A, the introduction of PCV13 (1, 3, 4, 5, 6A, 6B, 7F, 9V, 14, 18C, 19A, 19F, and 23F) may represent a promising preventive strategy to control the increasing trend of clonal spread in Arab countries. For example, the PCV7 vaccine was first introduced in Saudi Arabia as a part of the National Immunization Program in 2008, before the switch to PCV13 in 2010 [49]. Similarly, PCV7 was licensed in Tunisia in 2008 and was replaced by PCV10 and PCV13 in 2012 [50]. We observed that the serotype coverage of PCV7 and PCV13 among the analyzed strains was 23.83% and 49.48%, respectively, which is considerably lower than coverage reported in other regions. For comparison, PCV13 coverage in China was 83.2% [51], suggesting that PCVs in Arab countries resulted in decreased frequency of some vaccine serotypes and an emergence of some non-vaccine serotypes (e.g., 34, 12F, 11A, 35B, 10A).
Although population structure was analyzed separately according to geographic origin, age group, disease type, and serotype, formal interaction analysis between these variables was not performed. This was primarily due to incomplete epidemiological metadata for several strains and the retrospective design of the study. Future investigations using harmonized datasets and multivariable approaches could further elucidate potential interdependencies between host, geographic, and clinical factors influencing S. pneumoniae population structure.
Beyond serotype distribution and vaccine coverage, the evolutionary mechanisms driving the observed genetic diversity warrant further consideration. In particular, genetic recombination plays a crucial role in shaping pneumococcal population structure and may influence both clonal expansion and vaccine escape. Indeed, the high genetic variability among clinical strains of S. pneumoniae may be due to ongoing recombination within the population [52]. In this context, this study revealed that S. pneumoniae is an inherently capable organism that promotes genetic recombination through transformation over its whole genome, not just at the region encoding the capsular serotype, which was observed in another study [53]. Pneumococci have a high level of genome-wide diversity across populations due to this process, which has allowed them to accept and delete genetic changes throughout time [54]. Although it has been suggested that certain strains of pneumococcal bacteria are more likely than others to engage in recombination, it is not well understood whether genotypes exhibiting a history of recombination vary geographically [54]. Furthermore, recent research has demonstrated that the primary cause of genomic heterogeneity in S. pneumoniae is homologous recombination, and that recombination events can result in the interchange of MLST alleles across unrelated strains [55]. According to our recombination analysis, the idea that there is a homogeneous population of an ancestral genotype may be supported by the fact that there is a geographic separation between recombinants and major/minor parents. Despite the presence of recombination events indicated by the phi test, this study demonstrates extraordinary clonal evolution. This is supported by the observation that the same clones are isolated in different countries and over a long period of time [56].
For example, ST156 was isolated in six Arab countries and roughly 11 years apart. Our results are consistent with previous epidemiological studies that identified dominant lineages and clonal spread of S. pneumoniae at the national level [33,57].
It implies that recombination events are not significant enough to change the current clonal population structure, even though they are not completely eliminated by a clonal structure. Further bioinformatic analysis will therefore be essential to highlight the role that recombination has played in the evolution of S. pneumoniae.
The lack of complete clinical metadata, including patient sex, clinical outcomes, and detailed age information for all invasive cases, represents a limitation of this retrospective database-based study. Future studies combining molecular typing with comprehensive clinical data, particularly for severe infections such as meningitis and bacteremia/sepsis, would provide deeper insights into disease severity, regional risk patterns, and prevention priorities.

5. Conclusions

This study provides the most comprehensive molecular epidemiological analysis of S. pneumoniae isolates reported to date from Arab countries, offering an integrated overview of their spatial and temporal population structure over a 22-year period. The study revealed high levels of genetic variation across S. pneumonia strains using the MLST scheme, which appears to be strongly discriminatory for use in global epidemiological studies. Considering the high prevalence of PCV7 serotypes and serotypes 1, 3 and 19A, the introduction of PCV13 may be a promising preventive strategy to control the increasing trend of clonal spread in Arab countries. Implementation of vaccination programs targeting prevalent serotypes, combined with continuous molecular surveillance, is essential to reduce the morbidity and mortality associated with S. pneumoniae.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microbiolres17010012/s1, Figure S1: Minimum spanning tree analysis of 600 STs identified among 1008 Arab S. pneumoniae strains using goeBURST analysis. Each circle corresponds to a distinct allelic profile, and the circle size corresponds to the number of isolates sharing the same profile. Table S1: Characteristics of the strains. Table S2: Frequency of STs among 1008 Arab S. pneumoniae strains. Table S3: Geographical origin of 1008 Arab S. pneumoniae strains. Table S4. Age groups of patients. Table S5: Frequency of diseases among the 1008 Arab S. pneumoniae strains. Table S6: Frequency of serotypes among the 1008 Arab S. pneumoniae strains.

Author Contributions

S.B.: Conceptualization, Methodology, Data curation Writing—original draft, Writing—review and editing. M.H.: Conceptualization, Data curation, Writing—original draft, Writing—review and editing. M.A.D.: Conceptualization, Data curation, Writing—original draft, Writing—review & editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

Author Safa Boujemaa was employed by Biologica Training and Consulting company. The authors declare no conflicts of interest.

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Microbiolres 17 00012 g001
Figure 1. Minimum spanning tree showing the population structure of S. pneumoniae strains belonging to the four major clonal complexes (CC1–CC4) identified among Arab countries. Each node represents a distinct sequence type (ST), and node size is proportional to the number of strains. Yellow color corresponds to the ancestral ST.
Figure 1. Minimum spanning tree showing the population structure of S. pneumoniae strains belonging to the four major clonal complexes (CC1–CC4) identified among Arab countries. Each node represents a distinct sequence type (ST), and node size is proportional to the number of strains. Yellow color corresponds to the ancestral ST.
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Figure 2. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to the four major clonal complexes (CC1–CC4). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to the geographical origin of the strains.
Figure 2. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to the four major clonal complexes (CC1–CC4). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to the geographical origin of the strains.
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Figure 3. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to the four major clonal complexes (CC1–CC4). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to the decade of isolation.
Figure 3. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to the four major clonal complexes (CC1–CC4). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to the decade of isolation.
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Figure 4. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to three clonal complexes (CC1–CC3). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to patient age group.
Figure 4. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to three clonal complexes (CC1–CC3). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to patient age group.
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Figure 5. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to three clonal complexes (CC1–CC3) and three singletons. Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to disease type.
Figure 5. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to three clonal complexes (CC1–CC3) and three singletons. Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to disease type.
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Figure 6. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to three clonal complexes (CC1–CC3). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to serotype.
Figure 6. Minimum spanning tree illustrating the population structure of S. pneumoniae strains belonging to three clonal complexes (CC1–CC3). Each node represents a distinct sequence type (ST), with node size proportional to the number of strains sharing the same ST. Nodes are color-coded according to serotype.
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Figure 7. Split network analysis based on the concatenated sequences of 600 STs identified among 1008 S. pneumoniae strains by neighbor-net method.
Figure 7. Split network analysis based on the concatenated sequences of 600 STs identified among 1008 S. pneumoniae strains by neighbor-net method.
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Table 1. Nucleotide polymorphism of MLST loci.
Table 1. Nucleotide polymorphism of MLST loci.
GeneAmplicon Size (bp)No. of AllelesNo. of Polymorphic Sites (%)Total Number of Mutations (%)Haplotype
Diversity (H)		dN/dSTajima’s Test (D)
aroE4054814 (3.46)14 (3.46)0.8430.307−0.325, p > 0.10
ddl4418880 (18.14)91 (20.63)0.9090.072−1.700, p > 0.10
gdh4606832 (6.96)33 (7.17)0.8670.193−1.557 p > 0.10
gki4836334 (7.04)35 (7.24)0.8460.0410.247, p > 0.10
recP4505212 (2.67)12 (2.67)0.7930.296−0.665, p > 0.10
spi4745834 (7.17)34 (7.17)0.8830.184−0.237, p > 0.10
xpt4868417 (3.50)17 (3.50)0.8360.146−0.233, p > 0.10
Table 2. The detection of putative recombination events using six different tests.
Table 2. The detection of putative recombination events using six different tests.
EventRecombinantMajor ParentMinor ParentDetection Method
RDPGenConvMaxiChiChimeraSiScan3Seq
1ST11446 (Qatar)UnknownST11448 (Qatar)++++++
2ST1447 (Saudi Arabia)ST172 (Egypt/Qatar)Unknown++++++
3ST8935 (Saudi Arabia)UnknownST172 (Egypt/Qatar)++++++
4ST8488 (Egypt)ST306 (Morocco/Qatar)Unknown++++++
5ST9215 (Saudi Arabia)UnknownST13528 (Tunisia)++++++
6ST9598 (Saudi Arabia)UnknownST9220 (Saudi Arabia)++++++
7ST9186 (Saudi Arabia)ST9188 (Saudi Arabia)Unknown++++++
8ST9185 (Saudi Arabia)ST9184 (Saudi Arabia)Unknown++++++
9ST13528 (Tunisia)ST11501 (Qatar)Unknown++++++
10ST11452 (Qatar)UnknownST3804 (Saudi Arabia)++++++
11ST9218 (Saudi Arabia)ST8933 (Saudi Arabia)Unknown++++++
12ST9221 (Saudi Arabia)UnknownST2685 (Iraq/Kuwait/Qatar)++++++
+: presence of recombination event.
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Halwani, M.; Al Daajani, M.; Boujemaa, S. Genetic Diversity of Streptococcus pneumoniae Isolated from Thirteen Arab Countries and over 22 Years: A Retrospective Bioinformatics Analysis. Microbiol. Res. 2026, 17, 12. https://doi.org/10.3390/microbiolres17010012

AMA Style

Halwani M, Al Daajani M, Boujemaa S. Genetic Diversity of Streptococcus pneumoniae Isolated from Thirteen Arab Countries and over 22 Years: A Retrospective Bioinformatics Analysis. Microbiology Research. 2026; 17(1):12. https://doi.org/10.3390/microbiolres17010012

Chicago/Turabian Style

Halwani, Muhammad, Manal Al Daajani, and Safa Boujemaa. 2026. "Genetic Diversity of Streptococcus pneumoniae Isolated from Thirteen Arab Countries and over 22 Years: A Retrospective Bioinformatics Analysis" Microbiology Research 17, no. 1: 12. https://doi.org/10.3390/microbiolres17010012

APA Style

Halwani, M., Al Daajani, M., & Boujemaa, S. (2026). Genetic Diversity of Streptococcus pneumoniae Isolated from Thirteen Arab Countries and over 22 Years: A Retrospective Bioinformatics Analysis. Microbiology Research, 17(1), 12. https://doi.org/10.3390/microbiolres17010012

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