https://orcid.org/0000-0003-2281-7858
Figures
Abstract
Background
In developing nations, Shigella species are the leading cause of epidemic dysentery, especially among children under five. Antibiotic resistance has spread quickly among Shigella species as a result of inappropriate antibiotic use, inadequacies of diagnostic facilities, unhygienic conditions, and insufficient healthcare practices. This review aimed to describe AMR genes of Shigella species analyzed globally via whole genome sequencing (WGS).
Methods
Relevant papers were found via a literature search using the databases of Google Scholar, Web of Science, PubMed, and Scopus. Full-text primary studies published in English, WGS, Shigella serogroup, and AMR gene statistics had to be included in the articles. The comprehensive meta-analysis software was used for data analysis. The Der Simonian–Laird random effect model was utilized and statistical heterogeneity between studies is measured by the I2 and Cochran’s Q test.
Results
Of the studies, resistant genes of S. flexneri was more studied and characterized. The overall prevalence of antibiotics resistance genes was in the range of 1.7% to 46.9% with gyrA S83L was the most frequent isolated revealed this gene as predominant in the quinolones resistant gene of S. sonnei. It was followed by mphA (resistant to macrolides) for S. flexneri, and sul2 (resistant to folate synthesis inhibitors) for S. dysenteriae and S. boydii. Pooled prevalence of AMR gene in Shigella species significantly varied among the studies (p = 0.001). There was no significant amount of heterogeneity in S. bodyii (Q (4)) =1.938. p = 0.747, I2 = 0%) however in S. flexneri (I2 = 63%) and S. sonnei (I2 = 84%) showed high heterogeneity within the studies.
Conclusion
Generally, there was considerable variation in the pooled prevalence of the AMR gene in Shigella species among the studies, with S. flexneri and S. sonnei showing the highest levels of heterogeneity. The effectiveness of treatment is seriously threatened by Shigella’s resistance to antibiotics. Therefore, it is imperative that Shigella species resistance be continuously monitored globally.
Citation: Ayele B, Beyene G, Mekonnen Z, Esmael A, Ayele A, Alemayehu DH, et al. (2025) Whole genome sequencing analysis of antibiotic resistant genes of Shigella species: A systematic review and meta-analysis. PLoS One 20(10): e0334701. https://doi.org/10.1371/journal.pone.0334701
Editor: Nabi Jomehzadeh, Ahvaz Jondishapour University of Medical Sciences Faculty of Medicine, IRAN, ISLAMIC REPUBLIC OF
Received: March 30, 2024; Accepted: October 1, 2025; Published: October 28, 2025
Copyright: © 2025 Ayele et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
The most frequent cause of epidemic dysentery worldwide, particularly in children under the age of five, is shigellosis, which is caused by different Shigella species primarily found in developing nations [1]. Based on serological and biochemical traits, Shigellacan be divided into four serogroups: S. dysenteriae, S. flexneri, S. boydii, and S. sonnei [2]. It is the main cause of infant diarrhea with high mortality rate in developing nations [3]. Inadequate hand washing following urination or diaper changes, as well as direct transmission from person to person through the fecal-oral pathway are the main route of acquiring the pathogens [4]. Compared to other causes of gastroenteritis, this microorganism is extremely contagious because only ten bacilli are required to cause an infection [5]. Typically, shigellosis is a severe invasive infection of the human colon and rectum that leads to severe inflammation and tissue necrosis.
The issue of shigellosis may have received less attention due to underreporting of cases and the existence of other illnesses deemed more serious [6]. The pattern of antimicrobial resistance (AMR) varies geographically and within a single region, and Shigella serogroups are evolving resistance to commonly used antimicrobial medications [2]. Multidrug resistance (MDR) to Shigella species is becoming more common, which poses a major risk, particularly in developing nations where there are issues with nutrition and health problems [7]. Antibiotic resistance has spread quickly among many bacterial classes as a result of inappropriate antibiotic use, inadequacies laboratory facilities, unhygienic conditions, and insufficient healthcare practices [8].
As resistance grows, antibiotics gradually lose their efficacy, allowing bacteria to adapt and thrive in their presence. Reduced efflux transport, target modification, restricted drug uptake, and enzyme-catalyzed inactivation are the main mechanisms that lead to the development of antibiotic resistance [9]. Antibiotics are transported from inside to the outside of bacteria by a broad class of protein pumps called efflux pumps. Additionally, through a series of DNA modifications or the synthesis of specialized enzymes that alter the antibiotic’s targets, bacteria can become resistant to a particular class of antibiotics [10]. Antibiotic absorption, however, can be restricted by certain proteins that have the ability to bind to either the antibiotics or their targets. Additionally, bacteria produce enzymes that recognize and break down the structural components of antibiotics, rendering them inactive [11]. Research has also shown that post-translational processes can contribute to the development of bacterial resistance [12]. These resistance mechanisms are classified as intrinsic or predicted resistance (present in all strains/bacteria) or acquired (first discovered) [13].
The phylogenetic analysis of strains and genes isolated domestically and their relationships to those found abroad is largely absent from conventional molecular methods [14]. Whole genome sequencing (WGS) is currently being used by researchers instead of more conventional methods, such as pulsed-field gel electrophoresis (PFGE), because of its higher resolution [15]. Due to insufficient facilities for precise detection and antibiotic resistance gene testing, Shigella species isolation is still difficult in the majority of public health laboratories [16]. Despite the high prevalence of shigellosis, there is a dearth of summary information on the genes of Shigella species that are responsible resistant to different antibiotics. Therefore, it is required to review WGS studies regarding the antibiotic-resistant genes in Shigella species.
2. Methods
2.1. Search strategy
Published papers were reviewed using information from a thorough literature search that included details on AMR genes and the Shigella species. The methodology for the literature search and review was guided by the predefined study protocol (S1 File). Using a full search approach and double-checking reference lists, relevant papers were found via a literature search using the databases of Google Scholar,Web of Science, PubMed, and Scopus. The following special index search phrases (medical subject headings, or MeSH) and Boolean operations were used to conduct a literature search: “Shigella” AND “WGS” OR “Epidemiology” AND “Drug Resistance Gene, Microbial” AND “Dysentery, Bacillary/ epidemiology” AND “title and abstract.” The published studies containing epidemiological and/or clinical data were the main focus of the article search. Endnote version 20 (Clarivate Analytics, Philadelphia, PA, USA) was used to manage all of the records. A search of the literature was done between July 10, 2023, and December 26, 2023. The study group was limited to humans, and the language was limited to English.
2.2. Eligibility criteria
Reviewed abstracts from the first search using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement’s (S2 File) serogroups and outcome approach as a guide for defining inclusion and exclusion criteria. All WGS studies in Shigella serogroups were examined; however, the remaining studies were not provided because of the requirements for article inclusion. The Shigella serogroups and the AMR genes studies using the WGS method were the focus of the study’s outcome search. For the review to be included, full-text primary studies published in English, WGS, Shigella serogroup, and AMR gene statistics had to be included in the articles (Fig 1).
Exclusion criteria: Unpublished thesis and dissertations as well as papers without the required information were excluded. Since we are unable to evaluate the quality of each article in the absence of their full texts, studies that were not fully accessed after reading the titles and abstracts were excluded. Following the completion of the searches, every record that was found was downloaded and kept in EndNote 20 (Thompson Reuters) in a single library.
2.3. Data extraction
The researcher (BA) extracted data using a pretested, standardized format created in Microsoft Excel (S3 File). First author, study design, region, publication year, sample size, population characteristics, prevalence of Shigella species, and resistance gene were all included in the data abstraction format. When not enough information was provided, the article as a whole was examined to decide whether or not it belonged there. The reviewer (BA) both manually and automatically removed duplicates from the EndNote library in order to select which studies to include in the narrative synthesis. The same reviewer then went through the remaining records, selecting them first by the abstract and then by the title. After that, the full texts of the shortlisted articles were obtained to assess their eligibility for final inclusion. Prior to being implemented, the extraction sheet format was tested in 5% of the randomly selected studies. On the basis of a full-text analysis, the article was included. When data was extracted, publications were thoroughly assessed due to variations in study design.
2.4. Quality assessment
The Joanna Briggs Institute (JBI) eight-point critical appraisal tools were used to evaluate quality. The established criteria include: a sample frame that is appropriate for the target population; study participants who are sampled appropriately; detailed descriptions of the study subjects and setting; data analysis that covers a sufficient portion of the identified sample; valid methods for identifying the condition; a standard and reliable method of measuring the condition for every participant; appropriate statistical analysis; and a sufficient response rate. According to the reviews’ goals, a score that was calculated using various parameters was given to each study. “No and not reported” received a score of 0 while “Yes” received a score of 1. The range of total scores was 0–8. Research with medium quality, which satisfied 50% of the quality assessment criterion, and high quality were incorporated into the analysis [17].
2.5. Statistical analysis
The comprehensive meta-analysis software was used for the data analysis. Figures, tables, funnel and forest plots were used to describe the original articles. The random effect model was utilized to calculate the Shigella species’ pooled prevalence and antimicrobial resistance gene due to the heterogeneity among the studies. A 95% confidence interval (CI) for the estimated pooled prevalence rate was provided. Based on the serogroups of Shigella (S. dysenteriae, S. flexneri, S. boydii, and S. sonnei), sub-group analysis was carried out. I statistic and the Cochran’s Q test were used to assess heterogeneity. The I2 gives an estimate of the proportion of effect estimate variability attributable to heterogeneity as opposed to chance differences or sampling error. Therefore, the Cochran’s Q test was used to confirm the presence of heterogeneity (p < 0.10 indicates statistically significant heterogeneity). The statistical heterogeneity between studies is measured by the I2 test. I2 values of ≤25%, 25 < I2 ≤ 50%, and >50%, respectively, are considered to indicate low, medium, and high heterogeneity [18].
3. Results
3.1. Antimicrobial resistance gene of Shigella species
Twenty three studies with 4658 samples were included in our review of 280 titles and abstracts, including 20 studies of S. flexneri research, 13 studies of S. sonnei, 3 studies of S. dysenteriae and 5 studies of S. boydii (Fig 1). The reviewed studies included 39 sample sizes with the smallest and 2468 samples with the largest for S. boydii and S. sonnei, respectively (Tables 3 and 6). The study was included clinical samples from diarrheic patients with six studies were done on men who have sex with men (MSM). A number of resistant genes of S. flexneri was more studied and characterized than others (Table 2 and Fig 2). The overall prevalence of antibiotics resistance genes was in the range of 1.7% to 46.9% with gyrA S83L was the most frequent isolated revealed this gene as predominant in the quinolones resistant gene of S. sonnei. I was followed by mphA (resistant to macrolides) for S. flexneri, and sul2 (resistant to folate synthesis inhibitors) for S. dysenteriae and S. boydii (Tables 1–6). The analysis of 23 studies, according to the Der Simonian–Laird random-effects model, revealed that the pooled prevalence of antibiotics resistant gene was 12% (95% CI −0.07–0.17) (Figs 3 and 4). Pooled prevalence of AMR gene in Shigella species significantly varied among the studies (p = 0.001), with 9% in S. flexneri, 11% in S. sonnei, and 48% in S. boydii. The proportion of S. dysenteriae resistant genes was 33% however pooled prevalence was not estimated due to few study observations than the number of parameter estimated. According to the Q test there was no significant amount of heterogeneity in S. bodyii (Q(4))=1.9379. p = 0.7472, I2 = 0%) however in S. flexneri (I2 = 63%) and S. sonnei (I2 = 84%) showed high heterogeneity within the studies (–).
3.1.1. Resistance to quinolones.
Three hundred thirty/5775 (5.7%), 928/6295(14.4%), 36/1134(3.2%), 20/222(9%) isolates had a gene mutation in gyrA leading to a S83L in S. flexneri, S. sonnei, S. dysenteriae and S. boydii, respectively. Additionally, 5.6% in S. flexneri and 13.4% S. sonnei in parC to S80I substitution but not detected from S. dysenteriae and S. boydii. Furthermore, 36(0.6%), 16(0.3%), zero and 13 (5.9%) isolates had the plasmid-mediated quinolone resistance determinant qnrS1 in S. flexneri, S. sonnei, S. dysenteriae and S. boydii, respectively (Tables 1–4).
3.1.2. Resistance to folate synthesis inhibitors.
Two hundred eight seven/5775 (5%) carried genes in S. flexneri conferring resistance to sulphonamides. Of these, 223(3.9%) had sul2 (Table 1). About 6.8%, 14.5% and 9.9% were sul2 for S. sonnei, S. dysenteriae and S. boydii, respectively. Four hundred fifty six/5775 (7.9%), 558/6295(8.9%), 185/1134(16.3%) and 33/222(14.9%) gene isolates carried conferring resistance to trimethoprim had 7%, 7.9%, 9.8% and 9.5% dfrA1 in S. flexneri, S. sonnei, S. dysenteriae and S. boydii, respectively.
3.1.3. Resistance to macrolides.
Of the isolated genes mphA and ermB genes potentially linked to conferring resistance to the macrolides. One thousand four hundred fifty five/5775 (25.2%) genes had 756(13.1%) mphA and 696(12.1%) ermB in S. flexneri, 1095(17.4%) genes had 514(8.2%) mphA and 531(8.4%) ermB in S. sonnei, 6(2.7%) genes had 2(0.9%) mphA and 2(0.9%) ermB in S. boydii but no gene detected in S. dysenteriae (Tables 1–4).
3.1.4. Resistance to tetracyclines.
One thousand eighty four/13426 (8.1%) genes were confirmed resistance to tetracyclines. High number of tetB(8.2%) genes were detected in S. flexneri whereas 1.9%, 12.4% and 5.9% tetA genes were isolated in S. sonnei, S. dysenteriae and S. boydii, respectively (Tables 1–4).
3.1.5. Resistance to phenicols.
Three hundred nighty four/13426 (2.9%) isolated genes conferring resistance to chloramphenicol. Of these, 315/5775(5.5%) were catA1 and one floR only was found in S. flexneri. Eleven (0.2%) and 67(5.9%) genes were catA1 in S. sonnei and S. dysenteriae, respectively (Tables 1–4).
3.1.6. Resistance to aminoglycosides.
The gene strA, strB and aadA1 isolates resistance to streptomycin more confirmed than other genes resistance to aminoglycosides (Tables 1–4). Three hundred seventy one/5775 (6.4%) isolates had aadA1 in S. flexneri. Four hundred thirteen/6295(6.6%) had strA and 6.4% had strB in S. sonnei, 12.9% had strA-strB in S. dysenteriae and 9% had strA-strB and aadA1 in S. boydii. Other low number of combinations of genes also confirmed resistance to a broad range of aminoglycosides, including streptomycin, gentamicin and tobramycin.
3.1.7. Resistance to β-lactams.
Nine hundred seventy one/13426 (7.2%) gene isolates carried conferring resistance to β-lactams (Table 1–4). The penicillinases blaOXA-1 (8.2%) in S. flexneri, blaOXA-1 (5.7%) and blaTEM-1(4.4%) in S. dysenteriae, blaTEM-1 (1%) in S. sonnei, blaTEM-1B (5.9%) in S. boydii and the extended-spectrum beta-lactamase (ESBLs) blaCTX-M-27 (1.1%) in S. sonnei were frequently detected (Tables 1–4).
4. Discussion
Many studies have been conducted worldwide, even though they have concentrated on the phenotypic characteristics of Shigella species. This review study described the AMR genes of Shigella species. In developing nations with poorer standards of hygiene, Shigellosis can be regarded as a significant pathogen [42]. This review used 23 studies to determine the pooled prevalence of AMR genes of Shigella species in various regions. The review’s findings indicate that 12% of the population had a pooled prevalence of an antibiotic resistance gene. The studies’ pooled prevalence of the AMR gene varied significantly, and it has also been linked to MSM sexual transmission. The geographical origin of the isolate and/or variations in the routes of transmission may be connected to the variation in AMR that has been observed [43]. In Asia and Africa, shigellosis is endemic, primarily affecting children under the age of five [44]. In developed regions such as Europe, the Americas, and Australia, Shigella infections are more common in HIV-positive people, the homeless, and travelers. Moreover, a noteworthy proportion of Shigella infections are contracted via intercourse. They have greater MDR rates than Shigella isolates with different modes of transmission [45]. In this review, there were variations in drug resistance between the Shigella serogroups. The range of antibiotic-resistant gene prevalence was 1.7% to 46.9%. The most common isolate, gyrA S83L, identified this gene as the predominant resistance gene to quinolones of S. sonnei. It was followed by mphA (resistant to macrolides) for S. flexneri, and sul2 (resistant to folate synthesis inhibitors) for S. dysenteriae and S. boydii. This could be the third-generation cephalosporin resistance that emerged in 2014 and spread among MSM in Europe and America, along with resistance to azithromycin and ciprofloxacin [46]. In this review, S. sonnei exhibited higher rates of gene resistance than other serogroups. Compared to S. flexneri, S. sonnei may have a higher rate of drug resistance gene element transmission, especially for antibiotics like quinolones/fluoroquinolones and folate synthesis inhibitors [47,48]. In S. flexneri and S. sonnei, the pooled prevalence of the AMR gene varied significantly across the studies with a notable degree of heterogeneity, but not in S. boydii.
When Shigella species develop resistance to first and second-line antibiotics used in clinical settings, it is extremely concerning. There have been reports of Shigella species becoming resistant to ciprofloxacin and ceftriaxone [49]. Two distinct mutations in the gyrA gene and one single mutation in the parC gene are the main causes of ciprofloxacin resistance in bacteria. Furthermore, it has been found that the emergence of plasmid-mediated quinolone resistance and efflux pumps facilitates the development of resistance levels to quinolones and fluoroquinolones [50]. The qnr genes have been classified into five families: qnrA1-7, qnrS1-4, qnrB1-31, qnrC, and qnrD. Each family has a different number of alleles. It is typical to recognize qnrA, qnrB, and qnrS among these [45]. In this review, the most frequently observed qnr genes were qnrS1 genes, followed by qnrB genes.
The gene that conferred resistance to sulphonamides in the current review was sul2, and the gene isolates that conferred resistance to trimethoprim had dfrA1. These genes are more acquired or co-occurring with blaTEM variants, tet(A) or tet(B), aph(3“)-Ib (strA) and/or aph(6)-Id (strB), or with sul2 and dfrA1 genes [51]. In this review, tetA genes were isolated from S. sonnei, S. dysenteriae, and S. boydii, while a high number of tetB genes were found in S. flexneri. According to a study by Mandomando et al., S. flexneri is associated with the presence of the tetB and dfrA1 genes, whereas S. sonnei is primarily associated with the presence of the tetA and dfrA1 genes [52]. Furthermore, compared to other genes resistant to aminoglycosides, this review demonstrated that isolates with the streptomycin resistance genes strA, strB, and aadA1 were more confirmed. The majority of the Shigella isolates carry strA/B, aadA1, tetA/B, catA1 and other genes that confer resistance to aminoglycosides, tetracycline and chloramphenicol [19].
The main mechanism of resistance for Shigella species to azithromycin is believed to be the presence of genes resistant to macrolides. Different bacteria have different mechanisms for resisting azithromycin. The mphA and ermB genes were reviewed in this study as possibly contributing to the macrolide resistance. The genetic structures IS26-mph(A)-mrx(A)-mph(R)(A)-IS6100 and mph(E)-msr(E)-IS482-IS6 that carry macrolide-resistant genes are found in Shigella [27]. Because of the increasing prevalence of resistance to ciprofloxacin and ceftriaxone, azithromycin is regarded as a last-resort, Food and Drug Administration (FDA)-approved antibiotic agent for the treatment of systemic infections, especially those caused by Shigella species [53].
In the current review, 7.2% of gene isolates had resistance to β-lactam antibiotics. The penicillinases blaOXA-1 in S. flexneri, blaOXA-1 and blaTEM-1 in S. dysenteriae, blaTEM-1 in S. sonnei, blaTEM-1B in S. boydii and the ESBLs blaCTX-M-27 in S. sonnei were frequently detected. Plasmids carrying multiple AMR genes are commonly identified in Shigella species, and these include IncFII, IncI1, IncI2, and IncB/O/K/Z plasmids. These plasmids are capable of containing various AMR gene types [54]. Shigella species’ resistance to ceftriaxone is partially attributed to genes encoding ESBL, such as blaTEM, blaSHV, blaCMY, blaCTX-M, and blaOXA [49].
Our study has some limitations. The information derived from our 23 WGS studies might not be universally representative of AMR genes. Our study’s findings were further constrained by insufficient data on AMR genes and the overall number of cases that were reported. A dearth of published data, particularly from Africa where Shigella was common, further restricted our study. As a result, the estimated AMR genes prevalence might not apply to other areas where studies assessing WGS Shigella species were lacking. On the other hand, Shigella AMR may be on the rise in most areas.
5. Conclusion
In summary, there was considerable variation in the pooled prevalence of the AMR gene in Shigella species among the studies, with S. flexneri and S. sonnei showing the highest levels of heterogeneity. The effectiveness of treatment is seriously threatened by Shigella’s resistance to antibiotics. Since this bacteria are multifactorial pathogen, drug resistance has varied noticeably in different serogroups, isolation sources, or geographic locations. Therefore, it is imperative that enteric Shigella resistance be continuously monitored globally.
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