Prevalence, toxin virulence genes and investigating the effect of mutations in the tetracycline gene (tetK) on the response of methicillin-resistant Staphylococcus aureus to antibiotics: a study in sickle cell disease patients in Riyadh, Saudi Arabia

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) is a major pathogen associated with antimicrobial resistance, particularly in bloodstream infections affecting individuals with underlying conditions such as sickle cell disease (SCD). Resistance to tetracycline and erythromycin in MRSA is often mediated by efflux pump genes, including tetK, tetM, ermA, and ermC. These genes play a crucial role in reducing the efficacy of commonly used antibiotics, posing significant challenges in clinical management. Understanding the genetic variations within these resistance genes and their association with phenotypic resistance patterns is essential for guiding effective treatment strategies and improving patient outcomes. However, earlier research has not thoroughly examined how changes in the genes tetK, tetM, ermA, and ermC relate to the antibiotic resistance seen in MRSA strains taken from SCD patients. This gap indicates that there must be a focused investigation to bridge the current knowledge deficit and support the development of more targeted therapeutic approaches. This study aimed to investigate the prevalence and genetic basis of antibiotic resistance in MRSA bloodstream isolates from sickle cell disease patients in Riyadh, Saudi Arabia. It looked at the resistance genes, like tetK, ermA, and ermC, and studied how changes in their sequences affected them using evolutionary and structural analysis over seven years. MRSA isolates (n = 34) were obtained from 3,979 SCD patients (2017–2024). Representative strains were analyzed for their antibiotic susceptibility using the VITEK 2 system and PCR-based identification of resistance genes (e.g., tetK, tetM, ermA, and ermC). Among SCD patients, 0.9% exhibited MRSA bloodstream infections, predominantly affecting individuals over 20 years of age. During our study, we made an intriguing discovery that the toxin genes (hlg, hla, Pvl, and sea) were predominant in the MRSA isolates. Sequencing of tetK, ermA, ermC, and 16S rRNA genes was performed, and variations were analyzed using bioinformatics tools (BLAST, MEGA X, CARD, BLASTX). Phylogenetic analysis was conducted, and the results were correlated with phenotypic resistance profiles. All isolates were resistant to β-lactam antibiotics but sensitive to vancomycin and tobramycin. The analysis of the genetic sequence revealed important changes in the tetK gene, with strain RHD-KSA30 exhibiting several different amino acids. Phylogenetic analysis grouped Riyadh strains into distinct clusters. Variations in tetK correlated with differential susceptibility to antibiotics like erythromycin, clindamycin, and ciprofloxacin. The genetic diversity of the tetK gene in MRSA strains and its function in mediating antibiotic resistance are highlighted in this study. Although vancomycin and tobramycin are still effective treatments, the resistance to other antibiotics shows the need for continuous monitoring and the development of tailored treatment plans, especially for high-risk groups like patients with sickle cell disease (SCD).

Introduction

Methicillin-Resistant Staphylococcus aureus (MRSA) is a Gram-positive bacterium that frequently causes infections in healthcare settings, posing a significant public health threat. It is a common source of infections acquired in hospitals (Garoy et al. 2019; Aslam et al. 2022). MRSA bacteria represent a major obstacle to treating infections because they are resistant to medications known as beta-lactamases (Alghamdi et al. 2023). One notable trait of MRSA bacteria is their capability to remain in the bloodstream for multiple days even when treated with suitable antibiotics (Parsons et al. 2023). MRSA infections spread throughout Saudi Arabia, exhibiting varying prevalence rates from one region to another, ranging from 27 to 42% (Aljeldah 2020). Hemoglobinopathies are among the most commonly inherited conditions in humans, with genetic carriers accounting for at least 5% of the global population, of whom 3.2% carry sickle cell disease (SCD) (Alsalman et al. 2023). SCA is a prevalent genetic disorder in Saudi Arabia (Alotaibi 2017). Bacterial infections play a crucial role in the morbidity and mortality rates of patients with SCD (Gbadoé et al. 2023). Individuals with SCA are at a higher risk of contracting MRSA bacterial infections, which often leads to frequent hospitalizations (Dayie et al. 2021).

Tetracycline resistance in S. aureus is a considerable challenge in clinical microbiology and public health. Resistance mechanisms in these bacteria comprise efflux pumps, ribosomal protective proteins, and, to a lesser extent, enzymatic inactivation. Most genes that make bacteria resistant to tetracycline (60%) code for energy-driven efflux pumps, and different types of bacteria often use similar ways to pump out the drug or protect their ribosomes (Speer et al. 1992). The tetracycline resistance genes tetK, tetM, tetO, and tetL are some of the main genes linked to tetracycline resistance in Gram-positive bacteria. In some studies, the tetK gene was found to be predominant in MRSA strains (Farhat Ullah et al. 2012). TetK is a well-researched resistance gene that encodes a tetracycline-specific efflux pump. The tetK gene encodes a membrane-bound protein that operates as an efflux pump. This pump efficiently expels tetracycline from the bacterial cell, diminishing the intracellular concentration and obstructing the antibiotic's binding to its target, the 30S ribosomal subunit (Zhu et al. 2021; Mlynarczyk-Bonikowska et al. 2022).

TetK is frequently located on plasmids, which are mobile genetic entities. This facilitates horizontal gene transfer among bacteria and disseminating resistance. The expression tetK is inducible, indicating that the presence of tetracycline or its analogs frequently enhances the gene's transcription. The tetK gene predominantly confers resistance to tetracyclines, such as tetracycline and doxycycline, but it generally does not provide resistance to minocycline because the efflux pump has limited substrate specificity. Plasmids that have tetK often also carry extra resistance genes (like blaZ, which makes β-lactamase), leading to resistance to multiple drugs. This co-resistance hampers therapy, especially in MRSA strains. TetK-mediated resistance is commonly reported in both community-acquired and hospital-acquired S. aureus isolates. Monitoring the prevalence of tetK is essential in monitoring initiatives to address antibiotic resistance (Souza-Silva et al. 2022).

The Comprehensive Antibiotic Resistance Database (CARD) and BLASTX are potent tools for detecting antibiotic resistance. CARD is useful in detecting antibiotic resistance genes (ARGs) within genomic data. It offers a curated compilation of ARGs and their corresponding resistance mechanisms. BLASTX is a bioinformatics program that aligns a nucleotide query sequence with a protein database by searching a nucleotide sequence against all protein sequences. It converts the nucleotide sequence into all six potential reading frames and juxtaposes the resultant amino acid sequences with the protein database. This renders it optimal for detecting potential protein-coding regions inside a nucleotide sequence and juxtaposing them with established ARGs (Mcarthur et al. 2013; Alcock et al. 2023).

Regular testing for tetK and additional resistance factors is crucial to inform empirical treatment and mitigate the dissemination of resistance. This study aims to evaluate the prevalence of MRSA and antimicrobial resistance among SCD patients at KKUH and molecularly characterize MRSA isolates for the presence or absence of genes including ermC, ermA, tetK, tetM, mecA, pvl, sea, seb, sec, hlg, and hla using PCR and to investigate whether genetic variation within the tetK gene of MRSA isolates, isolated from individuals with SCD, influences their resistance to antibiotics beyond tetracycline. The primary objective is to determine if mutations within the tetK gene contribute to different patterns of antibiotic susceptibility, potentially affecting treatment options for these patients. To achieve this goal, the study will employ genetic sequencing as the main methodological tool. The tetK gene will be amplified and sequenced from MRSA isolates obtained from sickle cell disease patients. The sequencing data will be analyzed to identify any mutations or variations in the tetK gene that could affect its function and subsequently alter the strain’s response to various antibiotics.

Even though there is a worldwide worry about MRSA infections in sickle cell disease (SCD) patients, there is very little information about how common antibiotic resistance, resistance genes, and related mutations are in MRSA samples from Saudi Arabia. To our knowledge, no previous longitudinal studies spanning more than five years have addressed these aspects in Saudi Arabia, thus highlighting a significant gap in the epidemiological and molecular characterization of MRSA among SCD patients. This study aimed to evaluate the prevalence of MRSA bloodstream infections among sickle cell disease (SCD) patients in Riyadh, Saudi Arabia, over a seven-year period. It looked at important genes that make bacteria resistant to antibiotics, especially tetK, ermA, and ermC, and studied how changes in these genes affect how well antibiotics work against them. Additionally, the study included a phylogenetic and structural mutation analysis of these genes to better understand their distribution and evolutionary relationships among MRSA isolates collected from blood samples at King Khalid University Hospital (KKUH).

Materials and methods

Study ethics

The study was performed at the Botany and Microbiology Department, College of Science, King Saud University, and Microbiology Department, King Khaled University Hospital (KKUH). On 10 October 2023, No. 23/0723/IRB, the KKUH institutional review board (IRB) in Riyadh, Saudi Arabia, approved all protocols and procedures, including sample collection, bacterial isolation, and data analysis.

Sample collection and selection of strains

Clinical samples were collected from patients diagnosed with SCD who exhibit signs of infection and capillary electrophoresis (CE) have been used to diagnose the SCD (Frömmel 2018; Ghosh et al. 2020). Samples were processed to isolate S. aureus strains, specifically focusing on MRSA. The research was carried out in the Microbiology Department, College of Science, King Saud University, and the Microbiology Department, King Khaled University Hospital. All bloodstream infections (BSIs) in SCD patients were discovered retrospectively at KKUH between January 2017 and January 2025 by checking the microbiology and hematology departments'computerized databases. The study included 34 strains that tested positive for MRSA in blood cultures from 3979 SCD patients, and we selected seven strains for sequence variation analysis. A subset of these isolates was purposefully selected for sequence variation analysis based on their anti-biotic resistance profiles. Specifically, these seven strains exhibited higher resistance and greater diversity in their resistance patterns compared to the remaining isolates. All samples were sent to the microbiology laboratory within two hours after collection for bacterial culture. The isolates were stored at −80 ± 5 °C until re-cultured for further testing. Seven MRSA strains were randomly selected from the isolates for sequence variation analysis. These strains were sub-cultured and propagated to obtain pure colonies for characterization.

Bacterial identification

The MRSA isolates were identified using Gram stain, morphological, biochemical tests. Initial test was conducted using Mannitol Salt Agar (MSA), a selective and differential medium in microbiology, primarily for the isolation and identification of staphylococci. Moreover, deoxyribonuclease (DNase) agar was used. It is a differential medium used in microbiology to detect bacteria's production of the enzyme deoxyribonuclease. The DNase test is especially helpful for telling apart harmful Staphylococcus species, like S. aureus, from harmless ones (coagulase-negative staphylococci). MALDI- TOF, VITEK 2 automated systems (Biomérieux, France), MicroScan automated systems (Beckman Coulte, USA) were applied. The final identification was confirmed by mecA PCR, and gene sequencing.

Antibiotic susceptibility testing

Antibiotic susceptibility profiles of the selected strains were determined using VITEK 2 and MicroScan system (Hernández-Durán et al. 2017). The AST-GP67 Test Kit, designed for gram-positive susceptibility, was employed to perform susceptibility tests on different antibiotic categories, including penicillin’s (such as amoxicillin (amox), ampicillin (amp), penicillin (pen), and oxacillin (oxa), quinolones (such as ciprofloxacin (cipro), levofloxacin (lvo), and moxifloxacin (mox)), cephalosporins (such as cefazolin (cefaz)), macrolides (such as erythromycin (erthro) and azithromycin (azith)), aminoglycosides (including gentamicin (genta) and tobramycin (tobra)), glycopeptides (such as vancomycin (vanco) and teicoplanin (teico)), as well as other antibiotics like clindamycin (clinda) and tetracycline (tetra). Antibiotic resistance is explained according to CLSI M100 (2024 edition).

Detection of virulence and antibiotic resistance genes

PCR assay was used to detect the following genes; virulence-gene-encoded enterotoxin (sea, seb, sec), hemolysins (hla and hlg), toxic shock syndrome (tst), panton-valentine leukocidin (pvl), tetracycline (tetK and tetM), macrolides-lincosamides-streptogramins (ermA and ermC genes), penicillin-like antibiotics (mecA) and 16S rDNA gene. Both positive (S. aureus strains with confirmed tetK, ermA, and ermC genes) and negative (no-template) controls were used to ensure reliability. Primer specificity was verified through in silico analysis using BLAST against other bacterial DNA such as Escherichia coli. The pure and fresh cultures of MRSA isolates were prepared to extract DNA using the DNeasy Blood & Tissue Kits (Qiagen, Germantown, MD, USA). The 25 μl reaction mixtures of PCR consisted of 12.5 μl 2 × DreamTaq Green PCR mastermix (Thermo Fisher Scientific, USA), 2 μl template DNA, 8.5 μl nuclease-free water, and 1 μl each of the forward and reverse primers. The DNA amplification was performed using a PCR thermocycler (Corbett Research PCR Thermal Cycler) under the specified reaction conditions: an initial denaturation at 95 °C for 15 min, followed by 35 cycles of denaturation at 94 °C for 1 min, annealing at temperatures indicated in Table 1 for 30 s, extension at 72 °C for 1 min, a final extension at 72 °C for 10 min, and then holding at 4 °C. The analysis of amplified genes was conducted on a 1.5–2% (w/v) agarose gel with 0.5 μg/mL of ethidium bromide stain at 120 V in 1X TAE buffer using a 100 bp DNA ladder. The sequenced amplicons were verified for their identity through BLAST analysis after sequencing at Macrogen, Inc. in Korea.

Table 1.

PCR primers for amplification of virulence and antibiotic resistance genes from MRSA strains associated with bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia

Gene Target*	5′—Oligo Seq—3′	Product Size (bp)	Annealing Temp. (°C)	Reference
Toxic virulence genes
pvl-R	TCTGCCATATGGTCCCCAACCA	894	60	(Paniagua-Contreras et al. 2012)
pvl-F	TGCCAGACAATGAATTACCCCCATT
sea-R	TGGTGTACCACCCGCACATTGA	252	60
sea-F	TTGCAGGGAACAGCTTTAGGCAATC
sec-R	CGCCTGGTGCAGGCATCATATC	602	62
sec-F	CCCTACGCCAGATGAGTTGCACA
tst-R	CCAATAACCACCCGTTTTATCGCTTG	306	64
tst-F	AGCCCTGCTTTTACAAAAGGGGAAAA
hlg-R	CGCCTGCCCAGTAGAAGCCATT	306	64
hlg-F	TTGGCTGGGGAGTTGAAGCACA
hla-R	CCAATCGATTTTATATCTTTC	744	53	(Tavares et al. 2014)
hla-F	CGAAAGGTACCATTGCTGGT
Antibiotic resistance genes
mecA-R	CTAGTCCATTCGGTCCA	314	55	(Duran et al. 2012)
mecA-F	CCTAGTAAAGCTCCGGAA
tetK-R	GTAGTGACAATAAAC CTCCTA	360	54
tetK-F	GTAGCGACAATAGGTAATAGT
ermC-R	TAATCG TGGAATACGGGTTTG	299	54
ermC-F	AAT CGTCAA TTCCTG CAT GT
ermA-R	TTC GCAAATCCCTTCTCAAC	190	58
ermA-F	AAGCGGTAAACCCCTCTG A
tetM-R	CATATGTCCTGG CGTGTCTA	158	54	(Duran et al. 2012)
tetM-F	AGTGGAGCGATTACAGAA
16S rDNA gene
16S rDNA-R	AAG GAG GTG ATC CAG CCG CA	1500	52	(Lane 1991)
16S rDNA-F	AGA GTT TGA TCC TGG CTC AG

* Gene Target = This column lists the specific virulence, toxin, or antibiotic resistance gene that the primers are designed to amplify. 5′—Oligo Seq—3′ = This is the sequence of the oligonucleotide primer, shown from its 5-prime to 3-prime end. Product Size (bp) = This indicates the expected length, in base pairs, of the DNA fragment that will be generated or amplified by PCR. Annealing Temp. (°C) = This is the specific temperature at which the PCR primers bind (or"anneal") to their complementary sequences on the single-stranded DNA template. Reference = This column is for the source or publication from which the primer information was obtained

Sequence variation analysis

The PCR products of the four antibiotic resistance genes (mecA, ermA, ermC,tetM, and tetK), and the 16S rDNA gene were sequenced at both strands using an automated sequencer (Macrogen, Korea) with the identical forward and reverse primers shown in Table 1. The 16 s rDNA, ermA, ermC and tetK genes sequences were aligned and analyzed using bioinformatics tools (Blast.ncbi, MegAlign program, BLASTX in CARD, and Swiss-Model). Variations and mutations within the tetK gene sequences were identified by comparing sequences across the seven MRSA strains. These strains were selected based on their response to antibiotic resistance, as these seven strains showed greater resistance and diversity of resistance than the rest of the strains. At this stage of re-search, it is important to emphasize that the primary objective of this stage is not to perform statistical comparisons between groups but rather to gain detailed insights into the genetic composition of these resistant isolates and to detect mutations in the TetK gene that may lead to changes in the strains'response to antibiotics. The raw sequence data underwent processing using the BioEdit program, version 7.0 (Ibis Biosciences, CA), and assembly was conducted with the Edit sequence tool in the MegAlign program, Lasergene software, version 3.18 (DNAStar, Madison, WI). Subsequently, the edited sequences were deposited to the GenBank database with the following accession numbers (ermA: PP315287- PP315291, tetK: PP315279- PP315286 and 16S rDNA: PP064175- PP064196). International sequences corresponding to each gene were retrieved from the gene bank database and used for multiple sequence alignment and phylogenetic tree construction. Both nucleotide and deduced amino acid sequences of Riyadh strains and their international counterparts were aligned using Clustal W, MegAlign program of Lasergene software, version 3.18 (DNAStar, Madison, WI). The phylogenetic tree for each gene was constructed by the neighbor-joining method using the MEGA X software (Pennsylvania State University, University Park, PA, USA). The bootstrapping (1000 replicates) was performed for the three trees and the values are shown on the trees’ branches. For the reference strain, we set a reference strain for each gene (for the ermA gene, the reference strain is BX571856, for the tetK gene, the reference strain is CP033114, for the ermC gene, the reference strain is NG_047815).

The nucleotide sequences were prepared in FASTA format. All sequences were cleaned to remove low-quality regions or contaminants. The Basic Local Alignment Search Too (BLASTX) was used to search the nucleotide sequences against the CARD protein database. The search parameters (E-value cutoff, word size) were adjusted as default. Modeling for all target sequences was done using Swiss-Model (https://swissmodel.expasy.org/interactive).

Experimental design and statistical analysis

The work was designed the experiment using a randomized experimental design to ensure the absence of any bias in its setup. Data and samples were collected throughout the study period via random selection, further minimizing bias. The values of antibiotic resistance and genes encoding antibiotic resistance were calculated as percentages, and the significant differences between proportions concerning males and females were estimated using the Chi-squared test in SPSS software. The bioinformatics analysis was done using the neighbor-joining method and a BLASTX search (which compares nucleotide sequences to all protein sequences), along with Swiss-Model to predict protein structures. A subset of these isolates was purposefully selected for sequence variation analysis based on their antibiotic resistance profiles. Specifically, these seven strains exhibited higher resistance and greater diversity in their resistance patterns compared to the remaining isolates. At this point in the research, the main goal is not to compare the groups statistically but to understand the genetic structure of these resistant isolates and to find specific changes in the tetK gene that could affect how the strains respond to antibiotics.

Results

Occurrence of MRSA strains in patients with SCD

Throughout the study period, 3,979 patients were identified with SCD, the present work discovered 34 isolates (0.9%) of bloodstream infections caused by MRSA bacteria. The age categories were divided into three groups. The age group over 20 was the most affected (61.7% of all samples).

Identification of MRSA strains

All the samples were placed on agar plates that included chocolate, blood, MacConkey, and mannitol salt. The results indicate that MRSA is characterized by a positive gram stain, specific cultural, a mannitol fermentation, golden-yellow colony formation Fig. 1, phenotypic, and biochemical features, including, catalase positivity, oxidase negative, coagulase positivity and DNase positivity. The results were confirmed using PCR, where MRSA was identified through the mecA gene and 16S rDNA gene sequences. The mecA gene was found in all isolates (34).

Fig. 1.

MRSA, cultivated on (A) Mannitol salt agar (MSA), (B) Deoxyribonuclease (DNase) agar. MRSA is typically DNase-positive, meaning that it produces the enzyme DNase. MRSA strains were isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia. MRSA colonies on MSA appear as small- to medium-sized, yellow colonies. The agar surrounding the yellow colonies also turned yellow, indicating mannitol fermentation. MRSA colonies on DNase agar produces the extracellular enzyme DNase, it breaks down (hydrolyze) the DNA in the medium surrounding its growth

Testing for antibiotic susceptibility

The susceptibility testing of the MRSA strains (N = 34) to different antibiotics revealed that 100%, 100%, 41%, 100%, 41%, 2.9%, 0%, 2.9%, 17.6% and 32.4 of the isolates were resistant to penicillin’s, carbapenems quinolones, cephalosporins, macrolides, aminoglycosides, glycopeptides, sulfonamide as well as clindamycin and tetracycline, respectively. The results, summarized in Tables 2 and 3, show significant variations in antibiotic susceptibility among MRSA (N = 34).

Table 2.

Percentages of antibiotic-resistant MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia (N = 34)

Antibiotic susceptibility	Resistant (%) *	Sensitive (%)	Total of resistance(N)
Penicillin’s	100	0	34
Quinolones	41	59	14
Macrolide	41	59	14
Aminoglycosides	2.9	97.1	1
Glycopeptide	0	100	0
Sulfonamide	2.9	97.1	1
Cephalosporins	100	0	0
Tetracycline	32.4	67.6	11
Clindamycin	17.6	82.4	6

Table 3.

Comparison of antibiotic resistance of MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia (N = 34) Between Male (N = 24) and Female (N = 10) patients

Antibiotic	Breakpoints*	Antibiotic resistance (N) and percent (%)	Male (N = 24)	Female (N = 10)	**p-Value
Amoxicillin	MRSA is intrinsically resistant	34 (100)	24	10	0.000
Ampicillin	MRSA is intrinsically resistant	34 (100)	24	10	0.000
Azithromycin	≥ 8 µg/mL	10 (29.4)	8	2	0.023
Cefazolin	MRSA intrinsically resistant	34 (100)	24	10	0.000
Ciprofloxacin	≥ 4 µg/mL	10 (29.4)	6	4	0.656
Clindamycin	≥ 4 µg/mL	6 (17.6)	4	2	0.567
Erythromycin	≥ 8 µg/mL	12 (35.3)	8	4	0.220
Imipenem	MRSA intrinsically resistant	34 (100)	24	10	0.000
Moxifloxacin	≥ 1 µg/mL	10 (29.4)	6	4	0.656
Oxacillin	≥ 4 µg/mL	34(100)	24	10	0.000
Penicillin	≥ 0.25 µg/mL	34 (100)	24	10	0.020
Tetracycline	≥ 16 µg/mL	11(32.4)	8	3	0.086
Tobramycin	≥ 16 µg/mL	1 (2.9)	1	0	1

*CLSI M100 (2024 edition). ** If the P-value is more than 0.05, this means that the observed difference in resistance between males and females to this antibiotic is not statistically significant. The statistical analysis was performed using Chi-squared test in SPSS (IBM SPSS Statistics 29, USA)

The overall trend shows a significant variation in rates of resistance to most antibiotics (Penicillin’s, Cephalosporins, Quinolones, Macrolide and Tetracycline).

Determination of virulence genes of MRSA isolates

We investigated the presence of toxin virulence genes (sea, tst, hlg, seb, pvl, sec, and hla genes) of MRSA isolates (N = 34), by using PCR with specific primers, as observed in Table 1. The current study confirmed the presence of the hlg and hla gene in 100% of isolates, and the sea, tst, seb, pvl, and sec genes were demonstrated in 38.2%, 5.9%, 41.1%, 53.2%, and 8.8%, respectively Table 4. The prevalent toxin genes were hlg, hla, Pvl, and sea Table 5.

Table 4.

Comparison of positive virulence genes of of MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia (N = 34) Between Male (N = 24) and Female (N = 10) patients

Gene*	Positive gene%	Carriage (N) Male	Carriage (N) Female	Total	**P-value
sea	38.2	8	5	13	0.434
Tst	5.9	2	0	2	1
pvl	53	15	4	19	0.000
hlg	100	24	10	34	0.000
hla	100	24	10	34	0.000
seb	41	10	4	14	0.012
sec	8.8	0	3	3	1

*sea = Staphylococcal enterotoxin A, Tst = Toxic shock syndrome toxin-1, pvl = Panton-Valentine leukocidin, hlg = Gamma-hemolysin gene, seb = Staphylococcal enterotoxin B, and sec = Staphylococcal enterotoxin C. ** If the P-value is more than 0.05, this means that the observed difference in resistance between males and females to this antibiotic is not statistically significant. The statistical analysis was performed using Chi-squared test in SPSS (IBM SPSS Statistics 29, USA)

Table 5.

Distribution of toxin genes among of MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia (N = 34)

Toxin genes*	percent (%)
Sea + seb	17.6%
Sea + sec	2.9%
Sea + pvl	26%
Seb + pvl	20.6%
Sec + pvl	0
Sec + tst	0
Sea + tst	2.9%
Seb + tst	0
Sec + hla + hlg	8.8%
Seb + hla + hlg	41.1%
Sea + hlg + hla	38.2%
Pvl + hlg + hla	55.9%
Tst + hlg + hla + pvl	5.9%

*sea = Staphylococcal enterotoxin A, Tst = Toxic shock syndrome toxin-1, pvl = Panton-Valentine leukocidin, hlg = Gamma-hemolysin gene, seb = Staphylococcal enterotoxin B, and sec = Staphylococcal enterotoxin C

The prevalence of antibiotic resistance genes among MRSA strains

All MRSA strains (n = 34) included in the study were resistant to penicillin and methicillin as they reacted positively for mecA genes (100%). The resistance of MRSA strains to tetracycline (tetK), (tetM) and erythromycin (ermA, ermC) genes recorded 53%, 0%, and (29%, 14.7%) respectively. The results, summarized in Table 6.

Table 6.

Percentage of antibiotic resistance genes identified in MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia (N = 34)

Gene*	Carriage (N)	Percentage (%)
mecA	34/34	100
tetK	18/34	53
ermC	10/34	29
ermA	5/34	14.7
tetM	0/34	0

* mecA = methicillin resistance gene A, tetK = tetracycline resistance gene K, ermC = erythromycin resistance methylase C, ermA = erythromycin resistance methylase A, and tetM = tetracycline resistance gene M

Nucleotide and deduced amino acid sequencing analysis

For sequence analysis, representative strains for each gene were selected; 5 strains for 5 strains for ermA, 7 strains for ermC, 8 strains for tetK, and 21 strains for 16S rRNA. The sequences of these genes were aligned with their international counterparts. In the tetK gene, the strain (RHD-KSA30) has 14 nucleotide mutations whereas a single nucleotide mutation was reported in strains RHD-KSA24, −28, and −29. These mutations changed the corresponding amino acids into: V317M (RHD-KSA28), V317R (RHD-KSA29), V317E (RHD-KSA30), D318G, K371Q, S378A, V382A, S387R, N390P, S393R, F394L (RHD-KSA30) (Figure 2A). A total of 60 nucleotide mutations were recorded in the 16S rRNA of 21 strains. Most of these mutations were reported in the strain RHD-KSA-01.

Fig. 2.

Phylogenetic analysis and deduced amino acids analysis of tetK, ermA and ermC identified in the selected MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia. The trees were generated by the Neighbor-Joining method using MEGA X. Deduced amino acids were generated by aligning Riyadh strains with international strains by using the Clustal W technique in the MegAlign programme (DNAstar). Sequence alignment for each gene was compared to consensus sequences. Identical amino acids are shown by dots. Amino acid changes are indicated in boxes

Five nucleotide mutations were reported in the ermA gene with 5 amino acids changes at residues: H93T, I94V, K97Q, G130A, and A132T (Figure 2B). Only one strain (RHD-KSA17) has three mutations in the ermC gene with three amino acids changes at F163L, M196K, and K197Q (Figure 2C).

Phylogenetic tree comparison of 16S rRNA gene with international strains

Phylogenetic trees for the four antibiotic resistance genes and the 16S rRNA gene were constructed with the available international strains. Based on the 16S rRNA gene, the strains were grouped into 5 clusters with Riyadh formed 3 clusters: A, B and D (Figure 3). Due to the sequence similarity of this gene, strains from different species such as S. saprophyticus and S. argenteus are clustered among S. aureus strains without forming distinct clades.

Fig. 3.

Phylogenetic tree based on the 16S rRNA gene for the selected MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia. The tree was constructed by the Neighbor-Joining method (Saitou and Nei 1987) using MEGA X (Kumar et al. 2018). The percentage of replicate trees showing taxa clustering together in the bootstrap test (1000 replicates) is displayed next to the branches (Felsenstein 1985). Evolutionary distances were determined using the p-distance method (Nei and Kumar 2000) and are measured in units of the number of base differences per site. This research involved 69 nucleotide sequences (21 Riyadh MRSA and 48 international strains)

Comprehensive tet(K) antibiotic resistance database (CARD), BLASTX, and structure assessment

The results (Table 7) indicate that all seven MRSA strains examined in this investigation possess the tet(K) gene responsible for tetracycline resistance. The Antibiotic Resistance Ontology (ARO) is assigned the accession number 3000178. The tetracycline efflux protein is found in Gram-negative bacteria (such as Haemophilus and Gallibacterium) and Gram-positive bacteria (including various species of mycobacteria). The gene sequences demonstrate significant similarity (88%–100%) with established sequences from S. aureus. The outcomes exhibit robust Bitscores (83–126) and significant expect value (E-values) (5.7896e-22 to 5.99428e-37), signifying dependable matching. In the context of bioinformatics, particularly in sequence alignment tools like BLAST, a lower E-value indicates a more statistically significant match.

Table 7.

Bioinformatic analysis of tetK gene sequences (generated in this study) obtained from Comprehensive Antibiotic Resistance Database (CARD) using BLASTX-Search a nucleotide sequence against all protein sequences

Bitscore*	ARO tag**	Name	E-value***	Identity	Species	GenBank accession(s)
85	ARO:3000178	tet(K)	5.7896e-22	100	MRSA	PP315279.1
126	ARO:3000178	tet(K)	5.99428e-37	97	MRSA	PP315280.1
85	ARO:3000178	tet(K)	5.7896e-22	100	MRSA	PP315282.1
85	ARO:3000178	tet(K)	5.7896e-22	100	MRSA	PP315283.1
84	ARO:3000178	tet(K)	1.65055e-21	98	MRSA	PP315284.1
83	ARO:3000178	tet(K)	3.56468e-21	98	MRSA	PP315285.1
84	ARO:3000178	tet(K)	1.01716e-21	88	MRSA	PP315286.1

*The Bitscore is a normalized measure of sequence similarity (a higher bitscore means better alignment). ** Antibiotic Resistance Ontology (ARO) is a comprehensive and structured vocabulary specifically designed to represent antibiotic resistance genes, mutations, and phenotypes. ***The expectation value (E-value) is a statistical measure that describes the number of hits one can"expect"to find by chance in a database of a particular size that has a score equal to or better than the observed bitscore

Table 8 indicates that the AMR gene family constitutes a major facilitator superfamily (MFS) antibiotic efflux pump. This family's antibiotic resistance mechanism entails the utilization of efflux pump complexes or subunits that provide antibiotic resistance.

Table 8.

Basic scientific information of tetK gene obtained from CARD (Comprehensive Antibiotic Resistance Database) using BLASTX-Search a nucleotide sequence against all protein sequences

Synonym(s)	tetK
CARD Short Name	tet(K)
Definition	TetK is a tetracycline efflux protein found in both Gram-negative (Haemophilus and Gallibacterium) and Gram-positive (many species, including mycobacteria) bacteria
AMR Gene Family	Major facilitator superfamily (MFS) antibiotic efflux pump
Drug Class	Tetracycline antibiotic
Resistance Mechanism	Antibiotic efflux
Efflux Component	Efflux pump complex or subunit conferring antibiotic resistance

Figure 4 details the structural composition and assessment of the tetracycline resistance protein TetK, including GenBank accession data and predictions based on computational models. The sequence identity percentages range from 91.95% to 100% for the various TetK protein models evaluated. All models are predicted to have transmembrane segments, indicating their functional role within the cellular membrane. The predicted oligomeric state for all models is monomeric. The AlphaFold DB and SWISS-MODEL repository were employed for structure prediction. The AlphaFold DB model, associated with the gene tetK from an uncultured bacterium, served as the primary template (UniProt: A0A0N7AS56).

Fig. 4.

Structural composition and structure assessment (Ramachandran plot) of tetracycline resistance protein TetK (generated in this study) according to https://swissmodel.expasy.org/interactive. Template: A0A0N7AS56.1.A Tetracycline resistance protein TetK. AlphaFold DB model of A0A0N7AS56_9BACT (gene: tetK, organism: uncultured bacterium). Predict: Transmembrane segment, and Oligo-State: Monomer for all sequences tested in this work. * GenBank accession (Accession ID) is the unique identifier of TetK gene deposited in GenBank. ** Seq Identity refers to the percentage of identical residues (amino acids) with the reference sequence

Impact of tetK gene sequence variation on antibiotic susceptibility in selected MRSA strains.

Table 9 assesses the impact of tetK gene sequence variation on the antibiotic susceptibility of selected MRSA strains. The strains were tested for susceptibility to 19 antibiotics, with results recorded as either resistant (R) or sensitive (S). All strains are resistant to amoxicillin (Amox), ampicillin (Amp), and penicillin (Pen), which is expected given their MRSA classification. In addition, all strains were resistant to cefazolin (Cefaz), and oxacillin (Ox). All strains were sensitive to Tobramycin (tobra) and vancomycin (Van), which are common treatments for MRSA infections. Variable sensitivity was noted for drugs like erythromycin (Erthro). Strain RHD-KSA20 showed resistance to a broader range of antibiotics compared to other strains, including azithromycin (Azith), clindamycin (clinda), and ciprofloxacin (cipro), indicating a more resistant phenotype. Strains RHD-KSA26, RHD-KSA26, and RHD-KSA23 exhibited similar sensitivity patterns, being resistant to a few antibiotics, including amoxicillin and oxacillin, but sensitive to clindamycin and others.

Table 9.

Effect of tetK sequence variation on antibiotic response in selected MRSA strains isolated from bloodstream infections in sickle cell disease (SCD) patients, Riyadh, Saudi Arabia

Strain(N)	Amox	Amp	Azith	Cefaz	Cipro	Clinda	Dapto	Erthro	Genta	Imi	Levo	Mox	Mup	Ox	Pen	Rif	Tetra	Tobra	Van
MRSA RxcHD-KSA20	R*	R	R	R	R	R	S	R	S	R	R	S	S	R	R	S	R	S	S
MRSA RHD-KSA29	R	R	R	R	S	S	S	R	S	R	S	R	S	R	R	S	R	S	S
MRSA RHD-KSA28	R	R	S	R	S	R	S	R	S	R	S	S	S	R	R	S	R	S	S
MRSA RHD-KSA27	R	R	S	R	S	S	S	S	S	R	S	R	S	R	R	S	R	S	S
MRSA RHD-KSA26	R	R	S	R	S	S	S	S	S	R	S	S	S	R	R	S	R	S	S
MRSA RHD-KSA25	R	R	S	R	S	S	S	S	S	R	S	S	S	R	R	S	R	S	S
MRSA RHD-KSA23	R	R	S	R	S	S	S	S	S	R	S	S	S	R	R	S	R	S	S

*R Resistant and S Sensitive

Discussion

Bacterial infections play a crucial role in the morbidity and mortality rates of patients with disease SCD (Gbadoé et al. 2023). Recently, MRSA has become the predominant source of bloodstream infections (BSIs) (Hofstetter et al. 2024). The present study was designed to provide a comprehensive understanding of MRSA bloodstream infections among sickle cell disease (SCD) patients in Riyadh, Saudi Arabia. The study specifically aimed to find out how common MRSA is, identify important antibiotic resistance genes like tetK, ermA, and ermC, and examine how changes in these genes affect how well antibiotics work against them. Through phylogenetic and structural mutation analyses conducted, the study sought to uncover the genetic diversity and evolutionary patterns of these resistance determinants in selected clinical isolates. The molecular analyses were used to identify the antibiotic resistance genes. During the study period, a prevalence of 0.9% of MRSA bloodstream infections was detected among individuals with sickle cell disease (SCD) at King Khalid University Hospital (KKUH) in Riyadh, Saudi Arabia. In contrast, there are no studies determining the percentage of MRSA in the blood of patients with sickle cell anemia. The susceptibility test revealed that all strains of MRSA were resistance to penicillin, ampicillin, amoxicillin, oxacillin and imipenem. This finding result was in agreement with (Al-Sarar et al. 2024). This result has been supported by retrospective study by (Almanaa et al. 2020). However, we exhibited sensitivity to non-beta-lactam antibiotics, including glycopeptides (100%), aminoglycosides (97%), sulfonamides (97%), and clindamycin (82.4%). This finding was in agreement with Almutairi and his colleagues (2024) (Almutairi et al. 2024).

Toxin virulence genes in MRSA bacteria play a crucial role in the pathogenicity and virulence of these organisms (Kot et al. 2022). All MRSA isolates have hlg gene. This finding was in agreement with (Elboshra et al. 2020). In our study, the presence of the seb and pvl genes in approximately 41% and 53% of the MRSA strains. These results were in agreement with (Monecke et al. 2012). The results of our study indicated that the most coexistent genes in the isolates were Pvl + hlg + hla genes, with a frequency of 55.9% (19 isolates). Interestingly, in separate gene frequency analyses, each of the hla or hlg genes alone was revealed to be the most frequent. The coexistence of the genes hla + hlg + seb and hla + hlg + sea, in combination, was found in 41.17% and 38.23% of the isolates, respectively. Our current results differ somewhat from those of the study conducted in Brazil for the coexistence of the genes (Rossato et al. 2018). The explanation for the considerable discrepancy is that Rossato and his colleagues'study employed a different approach compared to the one we applied.

The current study conducted a sequence and phylogenetic analysis of four important antibiotic resistance genes. The alignment of each gene's sequences with their international counterparts revealed several mutations that could potentially impact the functionality of each gene product. For the tetK gene, finding several changes in its building blocks and the resulting protein suggests that the misuse of antibiotics is putting pressure on it to change, showing that resistance genes can quickly adapt when antibiotics are overused (Linkevicius et al. 2016). The constructed trees showed the intimate genetic relationships between Riyadh MRSA strains and their international counterparts. Moreover, the analysis of the 16S rRNA gene further investigated the genetic diversity among Riyadh MRSA strains. Based on this gene, Riyadh strains formed distinctly separate clusters. MRSA strains may have adapted to local antibiotic use, causing genetic diversity (Boswihi et al. 2020).

The findings align with contemporary research on tetracycline efflux mechanisms. Regarding functional role, Tet(K) is a well-characterized MFS efflux pump. Studies, such as Marshall et al., (2020), reinforce its role in mediating resistance in S. aureus by actively exporting tetracycline antibiotics. The very close match in the genetic sequence (88%−100%) we found here aligns with results from global databases, where some sections of Tet(K) are linked to its ability to remove antibiotics and its specific targets. This conservation has been documented in works like (Li et al. 2023) on efflux-mediated resistance.

Bacterial pathogens often possess unique genes known as virulence factors, and these findings support the established understanding that TetK functions as a tetracycline efflux pump, which is a membrane-associated protein that expels tetracycline drugs from bacterial cells, thereby conferring resistance. Its anticipated transmembrane characteristics align with its function in creating pathways through the bacterial membrane. Prior research on analogous efflux proteins, such as TetA, has indicated significant sequence conservation and a transmembrane structure as essential for antibiotic resistance mechanisms. This aligns with the anticipated monomeric state typically observed in resistant efflux proteins. The differences in sequence identity (91.95%−100%) show that these proteins have similar functions with very few changes, which might suggest they can adapt to different types of bacteria. A study conducted by (Ramón-García et al. 2006; Stephen et al. 2023) on efflux proteins demonstrated comparable levels of identity among homologous resistance proteins. The utilization of AlphaFold DB signifies a recent advancement in protein structure prediction. This method provides more accurate predictions than previous computational methods like homology modeling alone.

The current discoveries require experimental validation of the anticipated structures by techniques such as X-ray crystallography or cryo-electron microscopy. Furthermore, it is necessary to perform mutation experiments to identify essential residues in the transmembrane regions vital for tetracycline transport and to compare functional assays of TetK with other efflux pumps such as TetA to investigate variations in substrate selectivity and resistance levels.

The findings reported that the amino acid sequences of the genes studied differ among strains (like PP315284.1, PP315285.1, etc.), with some showing changes that can be seen as mutations. Mutations are known to have potential consequences (Sundin and Weigand 2007; Horton and Taylor 2023), including substitutions in the first position that indicate substantial structural and functional differences, as the first amino acid often sets the tone for protein folding. Proline causes kinks in protein structure, perhaps decreasing flexibility. The transition from a nonpolar to a polar amino acid may affect hydrophobic interactions. A slight transition from polar to non-polar could have small structural consequences.

The tetK gene encodes an efflux pump that imparts resistance to tetracyclines. In this investigation, despite variations in the tetK gene, all strains exhibited sensitivity to tetracycline (Tetra). It is well-established in scientific literature that the presence of the tetK gene in bacteria does not necessarily equate to detectable phenotypic tetracycline resistance (Chopra and Roberts 2001; Vaz-Moreira et al. 2014). A previous study shows that tetracycline often works the same way, regardless of tetK, because these molecules have different structures (Trzcinski et al. 2000).

The common resistance to β-lactam antibiotics (like amoxicillin, ampicillin, and oxacillin) is related to how MRSA resists these drugs, which is made possible by the mecA gene that produces PBP2a. This discovery supports previous studies demonstrating inherent β-lactam resistance in MRSA. Certain strains'resistance to erythromycin is likely due to the presence of erm genes, which are frequently associated with MRSA. The variety noted among strains aligns with research on MRSA's heterogeneity in resistance characteristics (Bæk et al. 2014; Feßler et al. 2018). All strains demonstrated sensitivity to vancomycin (Van), demonstrating its continued efficacy as the preferred treatment for MRSA infections. Prior investigations corroborate this, with data indicating that resistance to vancomycin is comparatively uncommon but is increasing in certain MRSA isolates worldwide. Resistance to fluoroquinolones (e.g., ciprofloxacin, levofloxacin) in several strains is associated with research indicating changes in the gyrA and parC genes in MRSA, which influence quinolone binding (Schmitz et al. 1998; Hooper 2000).

Conclusions

To the best of our knowledge, this study is the first to report that 0.9% of patients with sickle cell disease (SCD) were diagnosed with MRSA bloodstream infections, with a higher prevalence observed in males compared to females. Older individuals appeared to be particularly susceptible to MRSA infections. The antimicrobial susceptibility analysis revealed that commonly used antibiotics such as penicillin, ampicillin, amoxicillin, cefazolin, imipenem, and oxacillin were largely ineffective against MRSA in SCD patients. In contrast, all MRSA isolates demonstrated susceptibility to glycopeptides and selected cephalosporins, indicating their potential suitability for treatment. Molecular characterization showed that the toxin genes hlg, hla, pvl, and sea were prevalent among the MRSA isolates. The analysis showed that MRSA strains from SCD patients in Riyadh are genetically similar to both harmful and harmless S. aureus strains found around the world, including those from people and the environment like air. These results suggest the possible involvement of international transmission routes. Additionally, the study showed that changes in the tetK gene affect how bacteria respond to antibiotics, showing a complicated pattern of resistance that matches earlier research. Even though there were many resistance patterns, the samples were still responsive to tetracyclines and vancomycin, which means these medications can still be used to treat MRSA infections. It is suggested to do more genetic analysis of resistance factors like mecA and erm genes to better understand how resistance works. Overall, these findings underscore the importance of genetic surveillance and effective antibiotic stewardship in limiting the spread of resistant MRSA strains, particularly among vulnerable populations such as individuals with SCD.

Author contributions

Conception, A.A.A and N.S.A.; methodology, A.A.A. and J.M.K.; writing—original draft preparation, A.A.A.; investigation, A.A.A., N.S.A., and J.M.K.; data curation, A.A.A., and A.SA.; formal analysis, A.A.A., SK; validation, A.A.A., ASA., O.T. K and N.S.A. Writing—review and editing, A.A.A., N.S.A., M.A.F., O.T.K., F.H.A and J.M.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Ongoing Research Funding program number (ORF-2025–70), King Saud University, Riyadh, Saudi Arabia.

Data availability

Not applicable: Data will be made available on reasonable request.

Declarations

Study ethics

The study was performed at the Botany and Microbiology Department, College of Science, King Saud University, and Microbiology Department, King Khaled University Hospital (KKUH). On 10 October 2023, No. 23/0723/IRB, the KKUH institutional review board (IRB) in Riyadh, Saudi Arabia, approved all protocols and procedures, including sample collection, bacterial isolation, and data anal-lysis.

Competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.