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Review

Prevalence of icaADBC Genes, and Correlation with Biofilms and Antibiotic Resistance in S. aureus: A Systematic Review and Meta-Analysis

by
Khadijeh Bamneshin
1,
Mohsen Poudineh
2,
Roya Haji Alibabaei
2,
Mohammad Reza Jabbari Amiri
3,
Zahra Sadat Fateminasab
2,
Zahra Ghorbani
2,
Reyhaneh Maleki
2 and
Azad Khaledi
2,*
1
Department of Medical Physics, School of Medicine, Iranshahr University of Medical Sciences, 46 Imam Khomeini Street, Khomeini Corner, Iranshahr 9916643535, Iran
2
Infectious Diseases Research Center, Kashan University of Medical Sciences, 5th of Qotb–e Ravandi Blvd., Kashan 87154, Iran
3
Invasive Fungi Research Center, Department of Medical Mycology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari 19395-4763, Iran
*
Author to whom correspondence should be addressed.
GERMS 2024, 14(4), 387-401; https://doi.org/10.18683/germs.2024.1448 (registering DOI)
Submission received: 19 June 2024 / Revised: 29 December 2024 / Accepted: 30 December 2024 / Published: 31 December 2024

Abstract

We evaluated the gene prevalence of the icaADBC operon, its correlation with biofilm formation and antibiotic resistance through a global meta-analysis. We searched for articles that reported the prevalence of icaADBC operon, biofilm, and antibiotic resistance in S. aureus from 2000 up to 1st March 2024. The search was done in scientific databases such as PubMed, Scopus, Google Scholar, EMBASE, and Web of Science. The MESH keywords were: icaADBC operon, biofilm, methicillin-resistant Staphylococcus aureus, antibiotic resistance. Comprehensive Meta-Analysis Software was used for data analysis. The estimation of the combined prevalence of each desired variable was performed by depicting a forest plot through the random-effects model with a 95% confidence interval. Data heterogeneity was estimated by Q and I2 indices, and p-value <0.05 was reflected as statistically significant heterogeneity. Fifteen articles were eligible for inclusion. The prevalence of ica operon genes varied between 28–51.5%. The prevalence of total ica operon genes in S. aureus was reported at 42.4% (95%CI: 29.4–56.5). Biofilm formation prevalence of S. aureus isolates in different studies was reported between 10-100%. The rate of total biofilm in S. aureus was 95.8%. The rate of total strong, moderate, and weak biofilm in S. aureus was reported at 35.4%, 35.3%, and 23.9%, respectively. Most reviewed studies reported a correlation between ica genes and biofilm. We found that many studies reported a correlation between the high prevalence of ica operon genes, phenotypic biofilm production, and antibiotic resistance. Also, regardless of whether the strains were MRSA or not, the high biofilm formation ability was reported at 95.8% by most studies.

Introduction

Staphylococcus aureus is known as an important pathogen in hospitals. The spread of infections caused by methicillin-resistant Staphylococcus aureus (MRSA) strains in all health-treatment centers of the world, especially vital units such as the intensive care unit (ICU) and the respiratory unit, has been reported [1]. Today, widespread and increasing resistance to the antibiotics available to treat infections caused by this microorganism has reached its peak, which depicts a difficult future for infections caused by MRSA strains [2].
From the pathogenic aspects of this microorganism, we can mention the extraordinary ability to form biofilm outside and inside the human body in different infections [3]. This high ability to produce biofilm has led to the spread of resistance against current antibiotics and disinfectants [4,5].
Attachment to host cells is the primary stage necessary for the initiation and establishment of infection. The organization of Staphylococcus aureus is facilitated by the expression of multiple proteins and adhesins, notably the microbial surface components that identify adhesive matrix molecules (MSCRAMMs), enabling binding to laminin, fibrinogen, fibronectin, and collagen [6]. Once the initial attachment is established, the biofilm forms and expands through proliferation and extracellular matrix production. Extracellular matrix components such as polysaccharide extracellular adhesions, extracellular DNA, proteins, and teichoic acids contribute to biofilm formation [7]. Also, S. aureus provides biofilm thickening through the synthesis of polysuccinyl glucosamine. All these steps are regulated and controlled by icaADBC operon specifically icaD gene [8]. The icaA gene encodes the enzyme N-acetyl-glucosaminyl transferase, which plays a crucial role in the synthesis of N-acetyl-glucosamine oligomers derived from UDP-N-acetyl-glucosamine. The complete phenotypic manifestation of the capsular polysaccharide is associated with the icaD gene [9]. The produced polysaccharide wraps around the bacterial cells, functioning as a shield against the immune system of the host and the action of antimicrobial agents [10].
The involvement of the icaADBC operon in biofilm development and its link to antibiotic resistance has been convincingly demonstrated in various research efforts. However, there is currently no extensive review that integrates all these foundational studies. This global systematic review and meta-analysis intends to fill this gap by thoroughly examining the relationship between the icaADBC operon, biofilm production, and antibiotic resistance.

Methods

Search plan

The search plan was based on articles that reported the prevalence of the icaADBC operon, biofilm, and antibiotic resistance in S. aureus from 2000 up to 1st March 2024. The search was done in scientific databases such as PubMed, Scopus, Google Scholar, EMBASE, and Web of Science. The MESH keywords were: icaADBC operon, biofilm, biofilm formation, S. aureus, and methicillin-resistant Staphylococcus aureus, S. aureus, MRSA, antibiotic resistance, antimicrobial resistance, ica genes.

Eligibility criteria

The studies that reported the prevalence of biofilm-related genes, biofilm, and the relationship with microbial resistance, from clinical samples between 2000 up to 1st March 2024, were included in our analysis. Studies on non-clinical strains (environmental and animal) were excluded from our study. Systematic review studies, case controls, and clinical trials were excluded from the current review.

Quality assessment

To determine the quality of the studies, a checklist of Appraisal tools for Cross-Sectional Studies (AXIS) was used [11], in which 20 different questions were asked about varied parts of the study, from the title to the conclusion, and finally, studies characterized by weaknesses were omitted (Supplementary S1).

Data extraction

In this review, our authors independently used a series of designed forms that contained information such as first author, publication time, first name, year of study, year of publication, type of study, location, sample size, S. aureus isolates, ica gene prevalence, molecular methods for detecting genes, biofilm formation, methods for measuring biofilm. The extracted data were entered into these forms.

Data analysis

For the purpose of data analysis, Comprehensive Meta-Analysis software (version 3.3.070) was employed. The combined prevalence of the targeted variables was estimated by constructing a forest plot utilizing a random-effects model, which provided a 95% confidence interval (CI). Heterogeneity among the data was measured using the Q and I2 indices, with a p value of less than 0.05 denoting statistically significant heterogeneity. To assess potential publication bias, both Egger’s linear regression test and a funnel plot were utilized.

Results

Among the 417 articles retrieved from the different databases, there were 201 duplicates that were deleted. Records were screened. A series of articles were removed and the rest of the articles were evaluated for retrieval. At this stage again, with the exclusion of several articles, the eligibility of other studies was checked, and finally, due to the reasons mentioned in Figure 1, only 15 articles were eligible to be included in this review. Included studies used standard techniques for biofilm evaluation such as microtiter plate (MTP), Tissue culture plate (TCP), and Congo Red Agar (CRA). All the studies included here, used PCR for the detection of ica operon genes (Table 1).

Prevalence of total ica operon genes in S. aureus

The prevalence of ica operon genes varied between 28.0% and 51.5%. The prevalence of total ica operon genes in S. aureus was reported at 42.4% (95%CI: 29.4-56.5), Z=1.06, p=0.280. The frequencies of icaA, icaB, icaD and icaA/D were reported 38.4% (95%CI: 21.0-59.3), 65.5% (95%CI: 57.6-72.6), 67.8% (95%CI: 52.6-79.9), and 47.7% (95%CI: 22.8-73.9), respectively (Supplementary S2a, b, c, d, e and Table 2). The prevalence of icaA gene varied (between 3.1% and 80%), icaB (between 52.0% and 68.8%), icaD (between 38.5% and 91.5%), and icaA/D (between 3.8% and 74.2%).

Total biofilm formation rate in S. aureus strains

The prevalence of biofilm formation by S. aureus isolates in different studies was reported between 10-100% (Table 3). The rate of total biofilm in S. aureus was 95.8% (95%CI: 88.2-98.6), Z=5.4, p<0.001. The rates of total strong, moderate, and weak biofilm in S. aureus were reported at 35.4% (95%CI: 20.4-53.9), 35.3% (95%CI: 24.6-47.7), and 23.9% (95%CI: 11.7-42.6), respectively (Supplementary S3a, b, c, d and Table 2). The rate of total biofilm in MRSA strains was reported at 95.4% (95%CI: 83.6-98.8), Z=4.23, I2=90.9, p<0.001 (Table 2 and Table 4). The rate of total strong, moderate and weak biofilm in MRSA strains was 26.9% (95%CI: 15.3-42.9), 33.5% (95%CI: 23.2-45.8), and 30.6% (95%CI: 19.0-45.3), respectively (Table 2 and Table 4). The rates of total biofilm in MSSA isolates were reported at 25.1% (95%CI: 14.4-40.1), 50.0% (95%CI: 36.9-63.2), and 37.5% (95%CI: 14.4-68.1), respectively (Table 2 and Table 4).

Correlation between the prevalence of these genes with biofilm formation and antibiotic resistance

Most studies encompassed in this review have indicated a connection between ica genes and biofilm, regardless of the extent of biofilm development. Certain studies have established a link between robust biofilm production and increased antibiotic resistance, whereas other investigations have found no such association. They concluded that the ability to form biofilm, regardless of its degree, can increase antibiotic resistance.

Heterogeneity analysis and publication bias among the studies included

The heterogeneity indices reported for total biofilm were as follows: Q2=180.3, I2=91.2, and t=5.2, with a significance level of p<0.001. A visual assessment of the funnel plot concerning ica operon genes indicated the presence of publication bias, which was further corroborated by the Egger regression test yielding p<0.001. Conversely, the funnel plot analysis for ica operon genes also suggested publication bias among the reports (Figure 2a), while the Egger regression test indicated no such bias (p=0.790). Additionally, both the funnel plot and the Egger regression test confirmed the presence of publication bias related to biofilms (Fig. 2b), with a significance level of p<0.001.

Sensitivity analyses

To perform this test, the studies with both the highest and lowest sample sizes were omitted from the analysis, and a new meta-analysis was conducted. The results indicated that the original findings remained consistent.

Discussion

Data obtained from this review showed that the prevalence of ica operon genes varied between 28.0-51.5%, while the prevalence of total ica operon genes in S. aureus was reported at 42.4%. The combined prevalence of around 42.0% of ica genes indicates that the biofilm formed by S. aureus is not only dependent on the presence of these genes but other mechanisms independent of these genes are involved. In line with this fact, Piechota et al. [21] reported that although the prevalence of icaABCD genes was in a small percentage of MSSA isolates, there was no significant correlation between the existence of strong, moderate, poor biofilm types, and the strains that harbored these genes.
Biofilm prevalence of S. aureus isolates in different studies was reported between 10%-100%, while the rate of combined biofilm rate in S. aureus strains was 95.8%. This high rate of combined biofilm production in either MSSA or MRSA strains shows the importance of biofilm in the pathogenesis of S. aureus, even though methicillin-resistant strains use this biological-biofilm layer to prevent antibiotic penetration inside bacteria.
An interesting finding obtained from these studies was that apart from whether the strains were resistant to methicillin (MRSA) or not, the high biofilm formation ability has been reported by most reports except the study conducted by Jasińska et al. [6] It should be mentioned that the reports of some studies indicated a high rate of biofilm production in methicillin-sensitive strains (MSSA) compared to MRSA strains [12,24]. Furthermore, some research findings have shown that there is not a notable difference in biofilm when comparing MSSA and MRSA [8,14,24], but this was the opposite regarding the prevalence of strains containing ica genes, so MRSA strains showed a higher rate [24]. S. Oufrid et al. [23] reported that 100% of the strains with ica genes were also biofilm producers. Similar data has been presented by dos Santos-Goes et al. [18], where using PCR technique, more than 91% of the isolates had icaD gene and the simultaneous presence of icaD and icaA genes was reported in about 59%, which showed the role of these genes for creating biofilm because 100% of them were biofilm producers. Furthermore, findings from a study carried out by Azmi et al. [19] indicated that all strains harboring the icaD/icaA genes were associated with biofilm formation, which indicates a correlation between the existence of these genes and phenotypic biofilm. Manandhar et al. [24] showed that MRSA strains were resistant to most antibiotics, and the biofilm was also higher in these isolates. Meanwhile, strong biofilm producers displayed more drug resistance. Besides, the biofilm-producing strains that harbor icaAD genes recorded higher drug resistance compared to the planktonic counterparts [24]. El-Mahallawy et al. [17] reported that 92% of the ica-gene-positive strains were biofilm positive and 88% of the ica-gene-negatives were biofilm-producing negative.
In contrary, Jasińska et al. [6] have shown that a small number of biofilm producers harbored ica gene, and no noteworthy correlation was observed between ica gene, biofilm, and methicillin resistance, but Bimanand et at [20]. reported a substantial relationship between ica gene and biofilm, but this was not significant between the biofilm and drug resistance. Shivaee et al. [15] pointed out the high expression of icaA/D genes in both MSSA and MRSA. Reports from Shafi et al. [13] and Babra et al. [16] highlight that, apart from the type of biofilm (strong, moderate, and weak), biofilm producers have a higher level of resistance.
Of course, it is worth mentioning that this difference in the prevalence of the ica operon genes and the amount of biofilm formed by the isolates depends on the type of clinical samples (source), geographical region, molecular techniques used for gene detection, phenotypic method of biofilm detection and many other factors.
The analysis of the studies incorporated in this meta-analysis revealed a notable correlation between biofilm-associated genes and both biofilm development and antibiotic resistance. This finding underscores the critical role of biofilms in fostering resistance, as they create a protective biological layer that hinders the effective penetration of antibiotics and disinfectants into the microorganisms. Microorganisms residing within biofilms exhibit distinct characteristics compared to their planktonic forms [25]; they typically demonstrate enhanced resistance against adverse conditions, including exposure to chemical biocides, bacteriophages, antibiotics, and antibodies [26]. Consequently, it is imperative to implement various strategies aimed at inhibiting biofilm formation, such as modifying the properties of abiotic surfaces to deter biofilm establishment, manipulating signaling pathways to suppress biofilm development and promote dispersal, and employing external forces to eliminate existing biofilms [27].
Regardless of the MRSA status of the strains surveyed or their capacity for biofilm production (whether strong, moderate, or weak), biofilm-producing strains consistently exhibited greater antibiotic resistance. Thus, prioritizing the eradication and prevention of biofilm formation is essential in managing clinical microbial infections. Future research should delve into the interplay between biofilm formation, the ica operon, and its related genes across various bacterial species. Additionally, investigations should be conducted to explore the connections between strains harboring these genes and biofilm-forming strains that exhibit resistance to critical antibiotics, such as vancomycin and teicoplanin, which are commonly employed against multidrug-resistant (MDR) and MRSA infections.
Heterogeneity occurs when a collection of studies that are closely related or conceptually aligned on a specific topic produce results that significantly diverge from what would typically be expected due to sampling error. This situation suggests that the observed differences are not simply random variations; rather, they point to fundamental discrepancies in the data, methodologies, participant characteristics, interventions, and outcomes utilized across the studies. In light of this heterogeneity in our study, a random-effects meta-analysis was employed to synthesize the findings. In the context of heterogeneous studies, a random-effects meta-analysis assigns greater weight to smaller studies compared to a fixed-effect meta-analysis. This approach is justified because smaller studies provide more valuable insights into the variability of effects across the research landscape, rather than merely contributing to an assumption of a uniform intervention effect. Consequently, this method allows for a more nuanced understanding of the data.
To further explore the sources of heterogeneity, publication bias was assessed using funnel plots and the Egger regression test, which corroborated the presence of heterogeneity among the studies included in the analysis. To mitigate the impact of this heterogeneity on the results of the meta-analysis, subgroup analyses were conducted, categorizing studies based on the strength of biofilm formation-strong, moderate, and weak. This stratification aimed to clarify the effects observed and enhance the robustness of the findings.
Findings from this review indicated a notable presence of publication bias among the studies included. To assess this further, a visual examination of the funnel plot was conducted alongside the Egger regression test. The existence of publication bias can skew the results of meta-analyses by exaggerating effect sizes, thus highlighting the importance of its identification and correction. Funnel plots and Egger's Test are effective in detecting such biases, while the trim-and-fill method is used for their correction; nonetheless, these methods have inherent limitations, making sensitivity analyses imperative. In order to validate the results, a sensitivity analysis was performed, revealing no significant changes in the findings of this meta-analysis.

Conclusions

Our findings showed that many studies reported a correlation between the high prevalence of ica operon genes, phenotypic biofilm production, and antibiotic resistance. Also, regardless of whether the strains were MRSA or not, the high biofilm formation ability was reported at about 95.8% by most studies. Although some reported that certain MRSA strains exhibit a notably high capacity for biofilm formation, others did not consider such a difference between MRSA and MSSA.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.18683/germs.2024.1448/s1, S1: The Joanna Briggs Institute Prevalence Critical Appraisal Tool. S2: a. Forest plot of the meta-analysis of the combined ica gene prevalence in S. aureus retrieved from clinical samples; b. Forest plot of the meta-analysis of the icaA gene prevalence in S. aureus retrieved from clinical samples; c. Forest plot of the meta-analysis of the icaB gene prevalence in S. aureus retrieved from clinical samples; d. Forest plot of the meta-analysis of the icaD gene prevalence in S. aureus retrieved from clinical samples. S3: a. Forest plot of the meta-analysis of the total biofilms in S. aureus isolated from clinical samples; b. Forest plot of the meta-analysis of the total strong biofilm in S. aureus isolated from clinical samples; c. Forest plot of the meta-analysis of the Total moderate biofilm in S. aureus isolated from clinical samples; d. Forest plot of the meta-analysis of the total weak biofilm in S. aureus isolated from clinical samples.

Author Contributions

KB, MP and RHA undertook the collection and analysis of the data and completed the background literature review for the manuscript. The laboratory experiments, statistical analyses, and manuscript drafting were executed by MRJA, ZSF, ZG, RM and AK. All authors have read and approved the final manuscript version.

Funding

None to declare.

Data Availability Statement

The data supporting the findings of this study are available within the article [Figures/Tables and supplementary materials].

Acknowledgments

The authors would like to thank the Clinical Research Development Unit of Kashan Shahid Beheshti Hospital in Kashan University Medical Sciences.

Conflicts of Interest

All authors – none to declare.

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Figure 1. Flow diagram for selection of studies included in this review. 
Figure 1. Flow diagram for selection of studies included in this review. 
Germs 14 00387 g001
Figure 2. Funnel plot of meta-analysis on the ica gene prevalence (top image), and biofilm formation (below image) in S. aureus isolated from clinical samples. 
Figure 2. Funnel plot of meta-analysis on the ica gene prevalence (top image), and biofilm formation (below image) in S. aureus isolated from clinical samples. 
Germs 14 00387 g002
Table 1. Characteristics of included studies in the present review. 
Table 1. Characteristics of included studies in the present review. 
Study Year of study Publication Location Samples S. aureus isolates Biofilm total
(n)
MSSA
biofilm
(n)
MRSA biofilm
(n)
Methods for biofilm Molecular methods ica
genes n/%
icaA gene
icaB gene
icaA/DicaD
Šmitran et
al. [12]
2019-
2020
2022 Bosnia and Herzegovina 363 60 53 29 24 MTP PCR 30 - - - -
Shafi et al. [13] 2019-
2020
2022 Egypt 66 46 46 - - MTP PCR - 9 10 - -
Manandhar et
al. [14]
2017-
2018
2021 Nepal 375 161 84 14 70 TCP PCR 45 - - - -
Shivaee et al. [15] - 2019 Iran - 100 100 50 50 MTP Real-time
PCR
- - - - -
Babra et al. [16] - 2013 Australia - 31 31 - - CRA/TCP PCR - - -- 23 -
El-Mahallawy
et al. [17]
- 2009 Egypt - 10 6 - - CRA - - 5 - - -
Jasińska et al. [6] 2021 Poland - 26 7 5 2 MTP PCR 11 - - 1 10
dos Santos-
Goes et al. [18]
2017 2021 Brazil 63 59 59 - - CRA PCR - 38 - 35 54
Azmi et al. [19] 2015-
2018
2019 Palestinian- 248 248 - 248 MTP PCR - 41 - 248 207
Bimanand et
al. [20]
2012-
2013
2018 Iran - 96 92 - 92 MTP PCR -
15
66 - 66
Piechota et
al. [21]
2015-
2017
2018 Poland 130 129 57 72 MTP PCR 67 4 - 20 -
Mollaahmadi
et al. [22]
- 2021 Iran 80 39 39 - 39 CRA PCR - 25 25 - 25
Yousefi
Nojookambari
et al. [8]
2015-
2016
2018 Iran - 85 85 - 45 CRA/TCP PCR - 45 - - 45
Oufrid et al. [23] - 2015 Morocco - 20 18 - - MTP PCR- 16 - - 11
Manandhar et
al. [24]
- 2018 Nepal - 161 161 30 131 CRA, TM, and TCP PCR - - - 45 -
CRACongo Red Agar; MRSA – methicillin-resistant Staphylococcus aureus; MSSA – methicillin-susceptible Staphylococcus aureus; MTP – microtiter plate; TCP – tissue culture plate; TM – tube method.
Table 2. Subgroups analysis for different variables in the present review. 
Table 2. Subgroups analysis for different variables in the present review. 
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Table 3. Total biofilm producing isolates of S. aureus. 
Table 3. Total biofilm producing isolates of S. aureus. 
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Table 4. Biofilm production in both MSSA and MRSA isolates. 
Table 4. Biofilm production in both MSSA and MRSA isolates. 
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Bamneshin, K.; Poudineh, M.; Alibabaei, R.H.; Amiri, M.R.J.; Fateminasab, Z.S.; Ghorbani, Z.; Maleki, R.; Khaledi, A. Prevalence of icaADBC Genes, and Correlation with Biofilms and Antibiotic Resistance in S. aureus: A Systematic Review and Meta-Analysis. GERMS 2024, 14, 387-401. https://doi.org/10.18683/germs.2024.1448

AMA Style

Bamneshin K, Poudineh M, Alibabaei RH, Amiri MRJ, Fateminasab ZS, Ghorbani Z, Maleki R, Khaledi A. Prevalence of icaADBC Genes, and Correlation with Biofilms and Antibiotic Resistance in S. aureus: A Systematic Review and Meta-Analysis. GERMS. 2024; 14(4):387-401. https://doi.org/10.18683/germs.2024.1448

Chicago/Turabian Style

Bamneshin, Khadijeh, Mohsen Poudineh, Roya Haji Alibabaei, Mohammad Reza Jabbari Amiri, Zahra Sadat Fateminasab, Zahra Ghorbani, Reyhaneh Maleki, and Azad Khaledi. 2024. "Prevalence of icaADBC Genes, and Correlation with Biofilms and Antibiotic Resistance in S. aureus: A Systematic Review and Meta-Analysis" GERMS 14, no. 4: 387-401. https://doi.org/10.18683/germs.2024.1448

APA Style

Bamneshin, K., Poudineh, M., Alibabaei, R. H., Amiri, M. R. J., Fateminasab, Z. S., Ghorbani, Z., Maleki, R., & Khaledi, A. (2024). Prevalence of icaADBC Genes, and Correlation with Biofilms and Antibiotic Resistance in S. aureus: A Systematic Review and Meta-Analysis. GERMS, 14(4), 387-401. https://doi.org/10.18683/germs.2024.1448

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