Resistance phenotype and genetic features of a heterogeneous vancomycin intermediate–resistant Staphylococcus aureus strain from an immunocompromised patient

Abstract

Strain C1 was successfully isolated from an immunosuppressed patient with persistent bacteremia, who had not previously been exposed to glycopeptide antibiotics. This strain was found to be a heterogeneous vancomycin intermediate–resistant Staphylococcus aureus (hVISA). It is noteworthy that, following a brief period of vancomycin treatment, strains C6, C8, and C9, which were obtained from blood and other body parts, exhibited a significant reduction in heterogeneity as determined by population analysis profile–area under the curve (PAP-AUC) detection. Genotyping analysis revealed that these bacterial strains belonged to the same SCCmecIVa-ST59-t437-agrI genotype and shared the same virulome and resistome. In this study, a comparative genomics analysis was conducted between strain C1 and strain N315 to identify potential hVISA-associated mutations. Ultimately, a total of 205 mutation sites in 19 candidate genes, likely associated with the hVISA phenotype, were identified.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42770-023-01192-y.

Introduction

Since the discovery of hVISA (heterogeneous vancomycin-intermediate Staphylococcus aureus) and VISA (vancomycin-intermediate Staphylococcus aureus) in 1996, these strains have garnered significant attention from researchers due to their distinctive resistance characteristics [1, 2]. The emergence of hVISA and VISA has been associated with prolonged bacteremia, increased complication rates, and treatment failure with vancomycin [3]. Notably, hVISA strains and VISA subpopulations exhibit varying degrees of vancomycin resistance, with a frequency of less than 10⁻⁵–10⁻⁶, making their identification challenging using routine antimicrobial susceptibility testing (AST) methods [1]. Until recently, the population analysis profile–area under the curve (PAP-AUC) approach was considered the most reliable method for detecting hVISA [4]. However, its cumbersome and time-consuming nature renders it impractical for clinical settings, leading to a decline in hVISA detection rates.

In addition to the difficulties in detection, hVISA also presents an unpredictable nature. It can serve as a transitional phase between vancomycin-sensitive Staphylococcus aureus (VSSA) and VISA [5, 6]. It can either progress to VISA through β-lactam or glycopeptide therapy or in vitro glycopeptide induction or regress to VSSA without any related medications or when grown on drug-free plates. This further adds to the challenges associated with hVISA detection.

In this study, four methicillin-resistant Staphylococcus aureus (MRSA) strains were isolated from a patient with persistent infection. Two strains were obtained from blood samples, one from secretion and one from pericardial effusion. Notably, one of the strains was identified as an hVISA strain, while the remaining three strains were classified as VSSA. We conducted drug sensitivity testing and genome sequencing to analyze their drug resistance phenotype and genetic information. Furthermore, comparative genomics analysis was employed to identify structural differences and single nucleotide polymorphisms (SNPs) between the hVISA strain and the N315 strain (a reference MRSA strain).

Materials and methods

Case introduction

The patient was a 63-year-old female with a history of type 2 diabetes and left breast cancer. On October 22, 2022, she was given a “fever” diagnosis and admitted to the emergency department of Beijing Friendship Hospital affiliated with Capital Medical University due to “fever.” Before admission, she received intravenous infusion of ceftriaxone, cefuroxime, ceftazidime, and cefepime-sulbactam (dose unknown) for anti-infective treatment. Upon admission, her blood test showed a white blood cell count of 0.68*10⁹/L, the neutrophil ratio of 39.6%, C-reactive protein of 288.73 mg/L, and positive blood culture with MRSA strain C1 (day 1). She was subsequently treated with intravenous infusion of vancomycin 500 mg q12 h. The cause of bacteremia was considered to be infusion port infection, with MRSA strain C6 isolated from the site on day 6. During this period, the blood concentration of vancomycin was controlled at 15–20 μg/mL. Subsequent blood culture showed positive results, with MRSA strain C8 isolated. The patient was also found to have a mitral valve aortic valve vegetation and infectious endocarditis with pericardial effusion on echocardiography, with MRSA strain C9 isolated from the pericardial effusion on day 9. Unfortunately, despite receiving curative therapy, the patient passed away as a result of several complications. All strains have been identified by MALDI-TOF/MS and stored at − 80 °C for later use. This study was approved by the Ethics Committee of Beijing Friendship Hospital, Capital Medical University(20210208). The patient’s family has provided informed consent. This study was conducted following the Declaration of Helsinki and adhered to laws and regulations.

Antimicrobial susceptibility testing

The susceptibility of all isolated Staphylococcus aureus strains to antimicrobial agents was determined using the automated Vitek 2 Compact system (Biomérieux, France), except for vancomycin (VAN) and teicoplanin (TEC), which were determined using the standard agar microdilution method, additionally. The other antibiotic agents used were penicillin (PEN), oxacillin (OXA), cefoxitin (FOX), linezolid (LZD), daptomycin (DAP), tigecycline (TGC), ceftaroline (CPT), clindamycin (CLI), erythromycin (ERY), levofloxacin (LVX), moxifloxacin (MFX), rifampin (RIF), gentamicin (GEN), and trimethoprim-sulfamethoxazole (SXT). The interpretation of susceptibility adhered to Clinical and Laboratory Standards Institute (CLSI) guidelines [7].

PAP-AUC

PAP-AUC was done as described by Wootton et al. [4] with minor modifications. Briefly, all strains were streaked onto blood agar and grown overnight at 35 °C for 18 to 24 h. Colonies were suspended in 0.85% saline to a density equivalent to a 0.5 McFarland turbidity standard. Dilutions of 10⁻³ (10⁵ cfu/mL) and 10⁻⁶ (10² cfu/mL) were prepared and 50 μL of bacterial suspensions was inoculated onto BHI agar plates containing increasing concentrations of vancomycin (0, 0.5, 1, 2, 2.5, 4, and 8 μg/mL). After incubation at 35 °C for 48 h, bacterial colony counts (log10 numbers of cfu/mL) were plotted against the vancomycin concentration (0 to 8 μg/mL). The GraphPad Prism software was used to draw the graph. The PAP-AUC ratio was calculated as AUC_strain/AUC_Mu3. ATCC29213 (MSSA strain) and Mu3 were included as negative and positive control strains, respectively. The criteria to define hVISA and VSSA were a PAP-AUC ratio ≥ 0.90 and a PAP/AUC ratio < 0.90, respectively [8].

Biofilm assay

The biofilm formation experiment mainly refers to the suggestions in the reviews [9, 10]. The blood plates inoculated with tested strains were incubated overnight at 35 ℃ for 24 h. The bacterial suspensions were suspended with 0.85% saline to obtain turbidity of 0.5 McFarland standard (⁓ 108 cfu/mL) and diluted 1:100 with BHI (containing 2% glucose and 2% sucrose). Two hundred microliters of the diluted bacterial solution was added to a 96-well plate culture plate (each tested strain has 6 parallel wells). Following incubation in a 35 ℃ incubator for 24 h, the content of each well was aspirated, and each well was washed five times with sterilized deionized water to remove bacterioplankton. The remaining attached bacteria were fixed with 200 μL of methanol for 15 min and the plate was left empty and air-dried. Afterward, each well was stained 15 min with 200 μL of 2% (w/v) crystal violet dye solution and excess dye was removed with flowing water. After the plate was air dried, the dye bound to the attached bacteria was resolubilized with 200 μL of 95% ethanol per well at room temperature for at least 30 min without shaking. Then, a microplate reader was used to measure OD570. The negative control strain is BHI containing 2% glucose and 2% sucrose.

Extraction of genome DNA

The QIAamp DNA Mini Kit was used to extract the genomic DNA from each strain following the manufacturer’s instructions. The agarose gel electrophoresis was used to identify the collected DNA, and a Qubit® 2.0 Fluorometer from Thermo Scientific was used to quantify it.

Identification of MRSA and molecular typing

All MRSA isolates were subjected to mecA, PVL, multilocus sequence typing (MLST), staphylococcal protein A typing (spa), staphylococcal chromosomal cassette(SCCmec), and agr types as previously described [11, 12]. PCR products were identified by 1.5% agarose gel electrophoresis containing ethidium bromide. The allelic profiles (allele numbers) and ST types were determined based on the MLST database (http://saureus.mlst.net/) and the spa types were established using the database (http://spaserver.ridom.de).

Genome sequencing and function annotations

The whole genome was sequenced using Illumina NovaSeq PE150 at the Beijing Novogene Bioinformatics Technology Co., Ltd. Sequencing libraries were generated using NEBNext® Ultra™ DNA Library Prep Kit for Illumina (NEB, USA) following the manufacturer’s recommendations and index codes were added to attribute sequences to each sample. The assembly results of the three software were integrated with CISA software and the assembly result with the least scaffolds was selected. Genome component prediction included the prediction of the coding gene, repetitive sequences, non-coding RNA, genomic islands, transposon, prophage, and clustered regularly interspaced short palindromic repeat sequences (CRISPR). To predict gene functions, KEGG [13, 14] (Kyoto Encyclopaedia of Genes and Genomes) and COG [15] (Clusters of Orthologous Groups) were utilized. The pathogenicity and drug resistance analyses were performed using VFDB [16] (Virulence Factors of Pathogenic Bacteria) and ARDB [17] (Antibiotic Resistance Genes Database).

Comparative genomic analysis

Comparative genomic analysis between hVISA strain C1 and N315(GCA_000009645.1) was performed using MUMmer [18].

Accession numbers

The nucleotide sequence data generated in this study are available in the GenBank database under the following accession nos. SRR24457822, SRR24457821, SRR24457820, and SRR24457819 (BioProject: PRJNA967998).

Statistical analysis

GraphPad Prism 8.0.1 was used for all statistical analysis and drawing. When appropriate, statistical significance was assessed using one-way analysis of variance (ANOVA) and unpaired t-tests, with a p-value cutoff of 0.05 deemed significant.

Results

Antimicrobial susceptibility and the result of PAP-AUC

The four Staphylococcus aureus strains were serially isolated and confirmed as MRSA by mecA. These strains exhibited resistance to β-lactams (PEN and OXA), lincosamides (CLI), and macrolide (ERY) among the tested drugs. Additionally, the blood isolates (C1 and C8) demonstrated higher minimum inhibitory concentrations (MIC) in glycopeptides (VAN and TEC) and fourth-generation cephalosporin (CPT) compared to the secreta isolate (C6) and the pericardial effusion isolate (C9) (Table 1). Notably, C1 was identified as hVISA based on PAP-AUC and MIC assessments (Fig. 1).

Table 1.

AST and PAP-AUC of four S. aureus isolates

Strain	PAP-AUC	PEN	OXA	FOX	VANa	TECa	LZD	DAP	CPT	TGC	CLI	ERY	D-test	LVX	MFX	RIF	GEN	SXT
C1	1.70	≥ 0.5b	≥ 4.0b	Positive	2	8	2	1	1	≤ 0.12	≥ 4.0b	≥ 8.0b	Negative	≤ 0.12	≤ 0.25	≤ 0.5	≤ 0.5	≤ 10.0
C6	0.46	≥ 0.5b	≥ 4.0b	Positive	1.5	2	2	0.25	0.5	≤  ≤ 0.12	≥ 4.0b	≥ 8.0b	Negative	≤ 0.12	≤ 0.25	≤ 0.5	≤ 0.5	≤ 10.0
C8	0.75	≥ 0.5b	≥ 4.0b	Positive	2	8	2	0.25	1	≤ 0.12	≥ 4.0b	≥ 8.0b	Negative	≤ 0.12	≤ 0.25	≤ 0.5	≤ 0.5	≤ 10.0
C9	0.80	≥ 0.5b	≥ 4.0b	Positive	1.5	2	2	0.25	0.5	≤ 0.12	≥ 4.0b	≥ 8.0b	Negative	≤ 0.12	≤ 0.25	≤ 0.5	≤ 0.5	≤ 10.0

^aStandard agar dilution; ^bresistance

Fig. 1.

Population analysis profile curves of four Staphylococcus aureus isolates and two control strains (Mu50 and Mu3)

Biofilm formation

Considering the potential colonization ability of the typing in the infusion port area, we opted to investigate the biofilm formation of hVISA strain C1 in comparison to Mu3 (hVISA), Mu50 (VISA), and ATCC29213 (MSSA). The mean absorbance values of isolate C1 (0.71 ± 0.21) were found to be higher than those of Mu3 (0.30 ± 0.05, p = 0.0011), Mu50 (0.29 ± 0.04, p = 0.0008), and ATCC29213 (0.42 ± 0.03, p = 0.0085) (Fig. 2).

Fig. 2.

Comparison of biofilm formation ability between C1 and other strains. NC negative control. Statistical significance was determined by one-way ANOVA with Bonferroni posttest (p < 0.01). **p < 0.005; ***p < 0.001

General genomic features

To characterize the genetic characteristics associated with the hVISA phenotype, draft genome sequences were obtained for all strains. The draft genome sequences of four S. aureus isolates revealed chromosome sizes ranging from 2.84 to 2.01 Mb. The genomes exhibited a low average G + C content of 32.83% and contained 2679 to 2683 genes per genome. All the sequenced genomes harbored 57 tRNA genes and 10 rRNA genes. Furthermore, all isolates were found to be isogenic (ST59, SCCmec IVa, spa t437, and agrI). The detailed genomic features can be found in Table 2.

Table 2.

General genomic features of four S. aureus isolates

Strain	Length(bp)	GC%	ORFs	tRNA	rRNA	SCCmec/MLST/spa/agr	Accession no
C1	2,813,372	32.83	2681	57	10	IVa-ST59-t437-I	SRR24457822
C6	2,815,616	32.82	2679	57	10	IVa-ST59-t437-I	SRR24457821
C8	2,812,376	32.83	2681	57	10	IVa-ST59-t437-I	SRR24457820
C9	2,814,340	32.82	2683	57	10	IVa-ST59-t437-I	SRR24457819

The genes that were relatively predicted were subjected to annotation using KEGG metabolic pathway classification and COG categories. The resulting distributions of these annotations were found to be largely similar. In this study, C1 (hVISA) was chosen as a representative example. In terms of KEGG pathways, the number of genes involved in metabolism was higher compared to other categories. Notably, the categories of global and overview maps (476 genes), carbohydrate metabolism (171 genes), and amino acid metabolism (143 genes) exhibited the highest enrichment (Fig. 3). Among the genes annotated with COG categories, the top three categories were amino acid transport and metabolism (220 genes), translation, ribosomal structure and biogenesis (213 genes), and general function prediction only (171 genes) (Fig. 3).

Fig. 3.

KEGG metabolic pathway classification (a) and COG categories (b) in C1

Virulome and resistome

The four strains exhibited identical virulomes and resistomes. Based on the virulome, virulence factors were primarily categorized into eight major groups, including adherence, toxins, exoenzyme genes, host immune evasion, invasion, secretion system, and iron uptake, all of which play a role in the pathogenic process. Adherence and colonization are the initial stages in the development of bacterial pathogenicity. Genes associated with adhesion process components, such as clumping factor (clfA, clfB), intercellular adhesion proteins (icaA, icaB, icaC, icaR), fibronectin-binding proteins (fnbA, sdrC, sdrD, sdrE, ebh, efp, emp, fbpA), cell surface elastin binding protein (ebp), and polar flagella (flmH, relA), were identified in the genome. The gamma-hemolysin component C, hlgC, encodes gamma hemolysin. Staphylococcal enterotoxin A and B (sea, seb) are responsible for the symptoms of food poisoning. Genes set8 to set39 encode exotoxins, while selk and selq encode enterotoxins. Regarding exoenzyme genes, coa, aur, hysA, geh, sspA, sspB, sspC, vWbp, nuc, lip, and sak encode staphylocoagulase precursor, zinc metalloproteinase aureolysin, hyaluronate lyase, glycerol ester hydrolase, V8 protease, cysteine protease precursor, staphostatin B, secreted von Willebrand factor-binding protein precursor, thermonuclease, triacylglycerol lipase precursor, and staphylokinase precursor, respectively, all of which are involved in the bacterial infection process. Cap5A to capP contribute to the synthesis of capsular polysaccharide, which prevents phagocytosis by host immune cells. The secretion system, encoded by esaA to esxA, plays a crucial role in promoting bacterial survival and long-term persistence. In terms of the resistome, 19 antimicrobial resistance genes were identified (Table 3). Only beta-lactam, lincosamide, and linezolid were consistent with their antibiotic resistance phenotypes, while the other resistome profiles were inconsistent. Despite possessing the same glycopeptide resistome, the four genotypes exhibited significant differences in glycopeptide susceptibility.

Table 3.

Resistomic and virulomic characterization

Virulome		Resistome
Adherence	clfA, clfB, eap/map, icaA, icaB, icaC, icaR, fnbA, sdrC, sdrD, sdrE, ebh, efb, emp, fbpA, ebp, flmH, relA	Aminoglycoside R	aph(3′)-IIIa, ant(6)-Ia, vanRE, kdpE
		Beta-lactam R	mecC, mecR1, pbp2x,
Toxins	hlgC, sea, seb, set8, set12, set19, set22, set24, set26, set30, set31, set34, set39, selk, selq	Lincosamide and linezolid R	cfrC
		Sulfonamide R	sul3
Exoenzyme genes	coa, aur, hysA, geh, sspA, sspB, sspC, vWbp, nuc, lip, sak	Tetracycline R	tetT, tetQ
Immune evasion	cap5A, cap5G, cap5M, cap8E, cap8H, cap8I, cap8J, cap8K, capA, capB, capC, capD, capF, capL, capM, capN, capO, capP	Glycopeptide R	vanRI, vanRF, arlR, vanHO, vanTG, vanHA, vanL
Secretion system	esaA, esaB, esaG8, essA, essB, essC, esxA	Lipopeptide R	Cls

R resistance

Comparative genomic analysis

To further investigate the genetic characteristics of the hVISA strain, we conducted comparative genomic analyses between C1 and N315. The structural variation types are depicted in Fig. 4, and a total of 9735 non-synonymous mutations were identified (see supplementary material). For the analysis, SNP synonymous mutations and SNPs in non-coding regions were omitted from the analysis. By referring to the mutations of hVISA/VISA listed in references [19–21], Table 4 provides a summary of potential mutations in the C1 genome associated with hVISA. Among these mutations, SA_RS11270, which encodes the LPXTG-anchored DUF1542 repeat protein FmtB, exhibited the highest number of mutation sites. This was followed by SA_RS06785 and SA_RS04530, which encode the bifunctional lysyl phosphatidylglycerol flippase/synthetase MprF and D-alanine-poly(phosphoribitol) ligase subunit DltA, respectively. The products encoded by the mutated genes were classified into six categories, with cell wall biogenesis and regulatory systems ranking first and second, respectively .

Fig. 4.

Pairwise plot of structural variation types in the whole genome of sample CN315_C1. The inner circle is genome C1, and the outer circle is reference genome N315. Collinear, Translocation, Inversion, Tran + Inver, Insertion, and Deletion indicate regions with the same linear arrangement, translocated regions, inverted regions, regions that are both translocated and inverted, regions with insertions of length greater than or equal to 50 bp, and regions with deletions of length greater than or equal to 50 bp, respectively. ComplexInDel represents regions that cannot be aligned, but whose positions correspond to each other. Forward_chain and Reverse_chain represent the forward and reverse chain of the genome sequence, respectively. Forward_CDS and Reverse_CDS represent the translated CDS on the forward chain and the reverse chain of the genome sequence, respectively. Subjoin_Forward_CDS and Subjoin_Reverse_CDS represent the translated CDS on the forward and reverse chain of the genome sequence with supplementary genome sequence, respectively

Table 4.

Non-synonymous SNPs related to the genome of C1 genome

N315 locus tag*	No. of the mutation site	Protein products	Functional category
SA_RS04530	5	D-Alanine-poly(phosphoribitol) ligase subunit DltA	Cell wall biogenesis
SA_RS04545	1	D-Alanyl-lipoteichoic acid biosynthesis protein DltD
SA_RS01560	4	Glycine-glycine endopeptidase LytM
SA_RS03435	4	Penicillin-binding protein PBP4
SA_RS10925	5	Lytic transglycosylase SceD
SA_RS03405	2	Teichoic acid biosynthesis protein TagA
SA_RS11270	140	LPXTG-anchored DUF1542 repeat protein FmtB
SA_RS06785	8	Bifunctional lysyl phosphatidylglycerol flippase/synthetase MprF	Membrane biosynthesis
SA_RS03525	4	Response regulator transcription factor GraR/ApsR	Regulatory systems
SA_RS03540	3	ABC transporter permease VraG
SA_RS09755	2	Two-component system response regulator VraR
SA_RS00250	1	Two-component system activity regulator YycH
SA_RS00255	3	Two-component system regulatory protein YycI
SA_RS06430	4	DNA mismatch repair endonuclease MutL	DNA/RNA synthesis
SA_RS07860	1	RNA polymerase sigma factor RpoD
SA_RS10750	1	RNA polymerase sigma factor SigB
SA_RS07000	11	sarA expression modulator MsaC	Virulence
SA_RS06835	3	Indole-3-glycerol phosphate synthase TrpC	Others
SA_RS08235	3	Adenine phosphoribosyltransferase Atp

Discussion

The patient under investigation in this study was a middle-aged elderly woman with a medical history of breast cancer and diabetes. Due to her prolonged illness and administration of immunosuppressive and other medications, her immune system was compromised. The patient experienced persistent bloodstream infections during her hospital stay, which were suspected to be caused by an infection at the infusion port and ultimately resulted in infectious endocarditis. All isolated strains were identified as MRSA, and their typing and genomic analysis revealed consistency. Therefore, it is postulated that Staphylococcus aureus colonization at the initial infusion port was not effectively suppressed by antibiotics, but rather progressed into bloodstream infections due to compromised immunity, ultimately leading to the development of infective endocarditis.

Despite the similarity in drug resistance phenotypes observed among strains from different sites or periods, except for VAN and TEC, the PAP-AUC analysis revealed heterogeneity in VAN resistance, specifically with C6 < C8 and C9 < C1. These findings suggest that the vancomycin-intermediate portion of the MRSA population colonized at the initial infusion port increased when exposed to cephalosporin selection, while the counterpart in the bloodstream decreased upon vancomycin treatment. Several explanations can be proposed for these results. Firstly, the induction of glycopeptide antibiotics does not appear to be a necessary factor for the emergence of hVISA [22–24]. Secondly, adherence to vancomycin treatment guidelines may play a role in preventing the development of hVISA [25, 26], emphasizing the importance of monitoring vancomycin blood levels [27]. Additionally, immunocompromised individuals, such as those with diabetes, are at an increased risk of hVISA infection [28]. Vancomycin, the last resort for treating MRSA, exhibits limited effectiveness against hVISA; however, it can impede its progression in the short term.

Numerous reported hVISA strains are predominantly associated with clonal complexes 5 or 8, specifically ST5 (CC5) and ST239 (CC8), as these strains are the most prevalent MRSA strains [29]. Furthermore, the majority of reported hVISA cases are attributed to hospital-associated MRSA strains, likely due to the higher selective pressures favoring the emergence of hVISA in the hospital environment. In contrast to the typical epidemic subtypes and origins, the strain genotype SCCmecIVa-ST59-t437-agrI in this particular case, previously documented in the Yellow River Delta region, represents an uncommon community-related genotype, highlighting the genetic diversity of hVISA isolates [30]. Additionally, this genotype exhibits a robust ability to form biofilms, which is consistent with previous studies [31, 32]. Biofilms are formed when bacteria adhere to an implant, produce proteins that tightly interact with the host matrix, and subsequently undergo autolysis to release extracellular DNA. The initial stage of biofilm formation involves bacterial adhesion to an implant and the expression of proteins that strongly interact with the host matrix, leading to the accumulation of extracellular DNA through bacterial autolysis. Other planktonic bacteria then interact with these attached bacteria, resulting in the formation of microcolonies [33]. Bacteria embedded within biofilms exhibit increased resistance to antibiotics and are inherently resistant to host immune responses [34]. Additional genomic data reveals the presence of numerous adherence-associated genes in the genome, along with genes encoding exoenzymes, toxins, immune evasion mechanisms, and secretion systems, collectively responsible for the entire process of combating the host. These findings partially elucidate why the patient experienced poor treatment outcomes despite the strains being susceptible to multiple antibiotics, except for beta-lactams, CLI, and ERY.

It is widely recognized that hVISA strains exhibit characteristics such as thickened cell walls, slow growth, and distinctive polymorphic traits, including tiny colony variation [35]. The thickening of cell walls and alterations in cell wall components have been identified as important factors contributing to VAN resistance [36]. The thickened cell walls result in the accumulation of free D-alanyl-D-alanine terminals, which act as false targets for glycopeptides and reduce their diffusion rate towards lipid II targets. Changes in cell wall components include an increase in non-amidated murein monomer in cell wall peptidoglycan, a decrease in PBP4 activity, and an increase in the glycan chain length. The thickened cell walls may be associated with excessive production of peptidoglycan, reduced peptidoglycan turnover, and reduced cell lysis [37]. It is believed that structural variations and gene mutations may be responsible for the hVISA phenotype. Therefore, we conducted a genomic comparison between hVISA strain C1 and N315. However, our research did not demonstrate any significant structural variations associated with the hVISA phenotype. Previous studies have observed an increase in IS256 in VISA strains [38, 39]. IS256 can disrupt certain genes, thereby altering vancomycin susceptibility in Staphylococcus aureus. However, most studies have focused on gene mutations. Based on a literature review, we identified a total of 205 mutations in 19 candidate genes encoding different proteins that are potentially associated with the hVISA strain [19]. Among these genes, fmtB, which had the highest number of mutations, is involved in the synthesis of glucosamine-1-phosphate and N-acetylglucosamine-1-phosphate, precursors of UDP-GlcNAc [40]. MprF, with the second highest number of mutations, is associated with cross-resistance to daptomycin and vancomycin in MRSA [21, 41]. Several mutations, such as dltA, dltD, lytM, pbp4, sceD, and tagA, have the potential to influence the biosynthesis and autolysis of cell walls [5, 42, 43]. In terms of regulatory systems, mutations in VraSR and GraSR have long been considered indicative of the hVISA phenotype [29]. Additionally, YycI-YycH regulates WalKR, while VraG functions as an ABC transporter [21, 42]. Mutations have also been identified in genes involved in DNA/RNA synthesis (mutL, rpoD, sigB), virulence (msaC), and other functions (trpC, atp) [19]. However, the identification of these mutations does not fully elucidate their significance. Further investigations, such as gene silencing and gene knockout experiments, are necessary to validate the impact of these single nucleotide polymorphisms (SNPs) as the underlying cause of hVISA.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contribution

Conceptualization: X.C., L.M., and J.S.; methodology: X.C. and Y.W.; software: X.C. and J.M.; validation: X.C. and W.S.; formal analysis: X.C. and Y.W.; investigation: X.C. and L.M.; resources: W.S.; data curation: X.C.; writing–original draft preparation: X.C.; writing, review, and editing: L.M. and J.S.; visualization: X.C.; supervision: J.S.; project administration: L.M. and J.S.; funding acquisition: J.S.

Funding

This study was financially supported by the National Key Research and Development Program of China (2021YFC2301004) and the National Key Inspection Specialty Construction Projects.

Data Availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Conflict of interest

The authors declare no competing interests.