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Article

CRISPR-Cas System, Antimicrobial Resistance, and Enterococcus Genus—A Complicated Relationship

by
Carmen Costache
1,2,
Ioana Colosi
1,
Dan-Alexandru Toc
1,2,*,
Karla Daian
3,
David Damacus
3,
Alexandru Botan
3,
Adelina Toc
3,
Adrian Gabriel Pana
3,
Paul Panaitescu
1,
Vlad Neculicioiu
1,
Pavel Schiopu
1,
Dumitrana Iordache
4,5 and
Anca Butiuc-Keul
4,5
1
Department of Microbiology, Iuliu Hatieganu University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
2
Cluj County Emergency Hospital, 400000 Cluj-Napoca, Romania
3
Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
4
Department of Molecular Biology and Biotechnology, Faculty of Biology and Geology, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
5
Centre for Systems Biology, Biodiversity and Bioresources, Babes-Bolyai University, 400006 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Biomedicines 2024, 12(7), 1625; https://doi.org/10.3390/biomedicines12071625
Submission received: 13 June 2024 / Revised: 7 July 2024 / Accepted: 18 July 2024 / Published: 22 July 2024
(This article belongs to the Special Issue Pathogenesis, Diagnosis, and Therapeutics of Infectious Diseases (2nd Edition))
Browse Figures
Versions Notes

Abstract

:
(1) Background: The rise in antibiotic resistant bacteria poses a significant threat to public health worldwide, necessitating innovative solutions. This study explores the role of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) in the context of antibiotic resistance among different species from the Enterococcus genus. (2) Methods: The genomes of Enterococcus included in the study were analyzed using CRISPRCasFinder to distinguish between CRISPR-positive (level 4 CRISPR) and CRISPR-negative genomes. Antibiotic resistance genes were identified, and a comparative analysis explored potential associations between CRISPR presence and antibiotic resistance profiles in Enterococcus species. (3) Results: Out of ten antibiotic resistance genes found in Enterococcus species, only one, the efmA gene, showed a strong association with CRISPR-negative isolates, while the others did not significantly differ between CRISPR-positive and CRISPR-negative Enterococcus genomes. (4) Conclusion: These findings indicate that the efmA gene may be more prevalent in CRISPR-negative Enterococcus genomes, and they may contribute to a better understanding of the molecular mechanisms underlying the acquisition of antibiotic resistance genes in Enterococcus species.

1. Introduction

The Enterococcus genus is a group of Gram-positive, facultatively anaerobic bacteria, commonly present in surface waters, soil, and even in the human and animal gastrointestinal tracts [1]. Isolated from water, they can be an indicator of fecal contamination, which is the result of the bacteria’s ubiquity in various environments [2]. Some of the Enterococcus species are harmless or even play essential roles relate to the host’s health, while others are opportunistic pathogens, hospitalized patients being the ones that contract infections more often [3].
Within the Enterococcus genus, E. faecalis and E. faecium are the most clinically relevant species, being commonly found in the gastrointestinal tract [4]. There are Enterococcus species that are not common and are known as “other enterococci (OE)”, this group being represented by E. avium, E. casseliflavus, E. durans, E. gallinarum, E. mundtii, and E. raffinosus [5]. The OE group is divided into two subgroups: the vanC subgroup, which is characterized by chromosomally encoded vancomycin-resistance genes and includes E. casseliflavus and E. gallinarum, and the non-vanC subgroup, which includes the other species of enterococci and consists of acquired resistance genes to vancomycin through mobile genetic elements [6].
CRISPR-Cas is a defense system that has been developed by bacteria to protect themselves against viruses and other foreign genetic elements. This system consists of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and associated genes for an endonuclease called CRISPR-associated protein (cas), which can integrate fragments of foreign nucleic acids from viruses and mobile genetic elements into the CRISPR array [7]. For the first time, in 1980, repetitive sequences were observed in the E. coli genome [8].
The CRISPR-Cas system is classified into 2 classes, 6 types, and 33 subtypes. Class 1 includes types I, II, and IV, while class 2 includes types III, V, and VI [9].
There are cases where bacteria may have cas genes but lack the CRISPR arrays. Even if a bacterium lacks CRISPR arrays, it can still be classified within a particular CRISPR-Cas type based on the organization of the Cas proteins [9].
There are several databases and tools available for CRISPR research and analysis, some of them being CRISPRCasdb (https://crisprcas.i2bc.paris-saclay.fr/, accessed on 17 July 2024), CRISPR-Cas9 Target Finder (https://flycrispr.org/target-finder/, accessed on 17 July 2024), CRISPRminer (http://www.microbiome-bigdata.com/CRISPRminer/, accessed on 17 July 2024), or CRISPRone (https://omics.informatics.indiana.edu/CRISPRone/, accessed on 17 July 2024). These databases provide valuable resources for studying and exploring the diversity and functions of CRISPR-Cas systems.
The CRISPR-Cas9 system has many applications as a gene editor as well as in the development of defense systems against resistant bacteria. Therefore, the system can be used in the treatment of various conditions, including cancer, genetic disorders (e.g., sickle cell, beta thalassemia, and others), infections (e.g., HIV) [10], Parkinson’s disease, diabetes mellitus, or Alzheimer’s disease [11].
By engineering bacteriophages with CRISPR-Cas, it is possible to create phages that can precisely target and disrupt specific genes in the bacterial genome. This approach can be particularly useful in targeting antibiotic resistance genes in pathogenic bacteria, thereby making them susceptible to treatment again [12]. Phage delivery of CRISPR-Cas antimicrobials is thought to be the most promising method currently available [13].
As a result of the extensive use of antibiotics, a large number of bacterial strains have developed defense mechanisms that lead to their resistance to antibiotics. Antibiotic resistance is primarily achieved through the transfer of specific resistance genes (ARGs) with the help of mobile genetic elements (MGEs), such as plasmids and integrons. The acquisition of ARGs by bacteria is accomplished through Horizontal Gene Transfer (HGT). The CRISPR-Cas system interferes with HGT and can prevent the transfer of ARGs [14]. As a result, bacteria with nonfunctional CRISPR-Cas systems are less likely to acquire foreign DNA, such as ARGs [15]. A nonfunctional CRISPR-Cas system refers to a system that is unable to perform its normal biological functions because it has lost his functions due to various reasons [16].
Previous studies showed that MDR Enterococcus strains usually lack an active CRISPR-Cas system [17]. Price et al. showed that the lack of a CRISPR-Cas system has a significant impact on the way conjugative plasmids behave in a biofilm setting [18]. Enterococci can harbor a variety of antibiotic resistance genes, allowing them to resist the action of many commonly used antibiotics [19]. Depending on the antibiotic resistance gene pattern, they can be resistant to vancomycin, aminoglycosides, tetracyclines, macrolides, chloramphenicol, clindamycin, or beta-lactams [20].
The acquired glycopeptide resistance in Enterococcus is linked to the presence of various genes, such as vanA, vanB, vanD, vanE, vanG, vanL, vanM, or vanN [21]. Among these, the vanA gene is the most prevalent and encodes enzymes involved in altering the bacterial cell wall structure, being responsible for resistance to not only vancomycin, but also to teicoplanin [22]. In contrast, the vanB gene is responsible for only vancomycin resistance, these enterococci remaining susceptible to teicoplanin. The vanM gene, along with vanR, vanS, vanH, vanY, and vanX genes, are referred to as the vanM cluster [23].
Another antibiotic-resistance-related gene is the efmA gene, which encodes an efflux pump directed to macrolides, expelling erythromycin and related antibiotics from the bacterial cell [24]. The same mechanism is available for the msrC gene, which encodes a macrolide-specific efflux pump [25].
The IsaE gene is responsible for resistance to lincosamides [26] and the InuG gene confers resistance to both lincosamide and streptogramin B [27].
Antibiotic resistance in Enterococcus species is a major global health challenge, making the treatment of enterococcal infections increasingly difficult. In this context, limiting the antibiotic resistance benefitting by the CRISPR-Cas system in Enterococcus species has been an area of growing interest [28].
This study aims to shed light on the role of CRISPR-Cas systems in Enterococcus antibiotic resistance and contribute to understanding the complex interplay between CRISPR-Cas systems and HGT of ARGs.

2. Materials and Methods

2.1. Identification of Enterococcus Isolates

The genomes of the Enterococcus isolates were obtained from the CRISPRCasdb, which is an online database that provides valuable information about CRISPR-Cas systems identified in various prokaryotic organisms. It consists of two programs: CRISPRCasFinder, used to detect CRISPRs and cas genes, and database tools [29]. The database was filtered to include only Enterococcus species with level 4 CRISPR arrays, which were considered CRISPR-positive. Isolates with lower CRISPR levels were considered CRISPR-negative, creating two groups: CRISPR-positive and CRISPR-negative.
The CRISPR arrays were classified in levels from 1 to 4, based on the structure of CRISPR array found in each isolate. The lowest levels represent the CRISPRs with fewer than four spacers and three or more perfect repeats. In a real CRISPR array, the conservation of repeats must be high and the similarity between spacers must be low. Level 4 CRISPR arrays are considered, in our study, CRISPR-positive, because they are the most reliable ones [29].

2.2. Genome Retrieval and Database Generation

For each Enterococcus isolate, the corresponding chromosome and, if applicable, plasmid sequences were retrieved from the database and were downloaded and compiled into a database using the BioEdit software, version 7.2.6. This database of genomes served as the basis for further analyses. The information obtained from the online database, including species identification, CRISPR status, and Cas type, was organized into a Microsoft Excel spreadsheet along with annotations for each Enterococcus isolate, resulting in a total of 280 Enterococcus strains. To validate the accuracy of the genome sequences and assess the genetic similarity among isolates, a Basic Local Alignment Search Tool (BLAST) analysis was performed. The downloaded genomes were subjected to BLAST searches within the National Center for Biotechnology Information (NCBI) nucleotide database. The BLAST results were used to confirm the species identity of the isolates and verify the presence of CRISPR arrays and cas genes.
Figure 1 provides a step-by-step visual guide for processing genomic data from Enterococcus isolates using CRISPRCasdb and subsequent software. The steps are:
  • CRISPRCasdb Interface: The genomes of Enterococcus isolates are shown with CRISPR-Cas elements identified. The “Download Data” button allows users to download the genomic data.
  • FASTA Format Sequence: Following data retrieval, the acquired information is depicted in the FASTA format, sourced from NCBI’s comprehensive nucleotide database. This format ensures accessibility and compatibility for subsequent analytical steps.
  • Sequence Compilation in BioEdit: In BioEdit, genomes can be introduced by importing sequence data files in various formats. Users typically navigate to the “File” menu and select options such as “Open” or “Import” to load sequence files. Common file formats supported by BioEdit include FASTA, GenBank, and other commonly used sequence file formats. Once imported, the sequences are displayed in the BioEdit workspace, where users can perform various sequence manipulation and analysis tasks. The procured sequence data undergo compilation and comprehensive analysis within the BioEdit software environment. Here, the software showcases the aligned sequences, furnishing researchers with a structured platform for in-depth exploration and investigation.
Biomedicines 12 01625 g001
Figure 1. Visual presentation of processing Enterococcus genomic data using CRISPRCasdb. The CRISPRCasdb interface shows Enterococcus genomes with identified CRISPR-Cas elements, allowing data download.
Figure 1. Visual presentation of processing Enterococcus genomic data using CRISPRCasdb. The CRISPRCasdb interface shows Enterococcus genomes with identified CRISPR-Cas elements, allowing data download.
Biomedicines 12 01625 g001

2.3. Identification of Antibiotic Resistance Genes and Statistical Analysis

Through the use of specialized bioinformatics tools and databases, such as CARD (Comprehensive Antibiotic Resistance Database) (https://card.mcmaster.ca/home, accessed on 17 July 2024), version 3.2.4, the antibiotic resistance genes found in the Enterococcus isolates were identified through chromosome and, if applicable, plasmid sequence analysis [30]. The number of isolates with antibiotic resistance genes was recorded in a Microsoft Excel for both the CRISPR-positive and CRISPR-negative groups. For each gene, statistical analysis, such as Fisher’s exact test, was performed to evaluate the significance of associations between the presence of the CRISPR-Cas system and antibiotic resistance genes. The level of significance for the Fisher’s exact test was determined to be p < 0.05, indicating a statistically significant result.

3. Results and Discussion

3.1. Comparative Analysis of CRISPR-Positive and CRISPR-Negative Enterococcus Genomes

Out of 280 Enterococcus isolates, 85 were CRISPR-positive and 195 were CRISPR-negative. Among the 85 CRISPR-positive strains, E. faecalis was the most prevalent species (74 strains), followed by E. faecium (6 strains), and 1 strain of each of the following: E. thailandicus, E. silesiacus, E. hirae, E. mundtii, and E. sp. DA9. On the other hand, among the 195 CRISPR-negative strains, E. faecalis (95 strains) and E. faecium (64 strains) were the most abundant species, along with 9 strains of E. durans, 13 strains of E. hirae, 2 strains of E. mundtii, 6 strains of E. cecorum, 2 strains of E. avium, 1 strain of E. casseliflavus, and 1 strain of E. gallinarum. The distribution of Enterecoccus strains is summarized in Figure 2.
The observed distribution of CRISPR-positive and CRISPR-negative strains among Enterococcus species highlights potential species-specific variations in CRISPR-Cas systems.
Among the 85 CRISPR-positive strains, three distinct CRISPR-Cas types were identified. The most prevalent type was IIA, present in 65 CRISPR-positive strains, followed by IIC found in 18 strains. Notably, one strain only was characterized by CRISPR-Cas type IC.
Based on the cas genes, the CRISPR-negative strains can also be classified into the above-mentioned types. Therefore, among the 195 CRISPR-negative strains, six CRISPR-Cas types were detected. Type IIA was the most common, observed in 97 CRISPR-negative strains, while type IIC was present in 92 strains. There is one isolate for each of the IA, IB, and IIIC types and three strains for the IC type (Figure 3).
Regarding the CRISPR-Cas types, our findings suggest a diverse distribution of CRISPR-Cas types in Enterococcus species, with high prevalence of types IIA and IIC. The presence of multiple CRISPR-Cas types enables them to adapt to diverse environmental challenges. These findings align with previous studies that have shown variations in CRISPR-Cas types across different bacterial species and strains [31]. Lyons et al. [31] showed that type II CRISPR1-Cas1 incidence varies significantly between species, CRISPR-Cas distribution being affected by the selective pressure of the environment.

3.2. Comparative Analysis of the Antibiotic Resistance Genes Found in the CRISPR-Positive and CRISPR-Negative Isolates

In this study, we assessed a total of 716 sequences of Enterococcus (having CRISPR array in chromosome and/or plasmids), of which 187 were classified as CRISPR-positive, while 529 were categorized as CRISPR-negative based on the presence or absence of level 4 CRISPR-Cas systems.
The large sample size allowed for a comprehensive analysis of the distribution of CRISPR-Cas systems in Enterococcus species. These sequences were derived from 280 Enterococcus strains, E. faecalis being the most prevalent, accounting for 169 strains, followed by E. faecium with 70 strains. These findings are consistent with previous reports highlighting the prominence of these two species in clinical settings and their association with various infections [32].
Among the CRISPR-positive isolates, there were identified 7 antibiotic resistance genes, and for the CRISPR-negative isolates there were 10 identified genes, as shown in Table 1.
Among the CRISPR-positive strains, the vanA gene was detected in 5 out of 187 genomes (2.7%), while in the CRISPR-negative strains, 9 out of 529 genomes (1.7%) carried the vanA gene. The difference in vanA gene prevalence between the two groups was not statistically significant (p = 0.3774). For the IsaE gene, 12 out of 187 CRISPR-positive genomes (6.4%) and 17 out of 529 CRISPR-negative genomes (3.2%) were positive. However, there was no significant association between the IsaE gene and CRISPR status (p = 0.0812). The vanM gene was found in 3 out of 529 CRISPR-negative genomes (0.6%), but none were detected in the CRISPR-positive group (p = 0.5713). Similarly, the InuG gene was detected in 1 out of 187 CRISPR-positive genomes (0.5%) and 3 out of 529 CRISPR-negative genomes (0.6%), with no significant association (p = 1.0000). Regarding the fexB gene, it was present in 1 out of 187 CRISPR-positive genomes (0.5%) and 2 out of 529 CRISPR-negative genomes (0.4%), showing no statistically significant association with CRISPR status (p = 1.0000). The fosB3 gene was not found in any of the CRISPR-positive genomes but was present in 2 out of 529 CRISPR-negative genomes (0.4%), and no significant association was observed (p = 1.0000). The AAC(6′)-Iih, dfrE, and msrC genes did not show statistically significant association with CRISPR status either. Remarkably, the efmA gene exhibited a statistically significant association with CRISPR status. It was detected in only 1 out of 187 CRISPR-positive genomes (0.5%), but was present in 52 out of 529 CRISPR-negative genomes (9.8%) (p = 0.00001). These results are highlighted in Table 1 and Table 2.
In this study, two heatmaps were generated to visualize the genomic characteristics of various Enterococcus isolates. The first heatmap (Figure 4) focuses on the presence of antibiotic resistance genes (ARGs) and plasmids. On the vertical axis, different Enterococcus isolates are listed, while the horizontal axis includes ARGs and plasmid presence. The presence of a specific ARG in an isolate is indicated by a green cell, while a red cell denotes its absence. Similarly, plasmid presence is color-coded: green indicates the presence of plasmids, and red indicates their absence. This heatmap allows for a quick and intuitive assessment of the distribution and prevalence of ARGs and plasmids among the Enterococcus isolates.
The second heatmap (Figure 5) provides information on the types of CRISPR-Cas systems found in the same Enterococcus isolates. Again, the vertical axis lists the Enterococcus isolates, while the horizontal axis shows the different types of CRISPR-Cas systems. The presence of a specific CRISPR-Cas type is marked by a green cell, and its absence is marked by a red cell. This heatmap enables the visualization of the diversity and distribution of CRISPR-Cas systems across the isolates.
These heatmaps together provide a comprehensive overview of the genomic landscape, highlighting the patterns and trends in antibiotic resistance genes, plasmid presence, and CRISPR-Cas systems.
The analysis revealed that the prevalence of the vanA, vanM, IsaE, fexB, InuG, fosB3, AAC(6′)-lih, dfrE, and msrC genes did not significantly differ between CRISPR-positive and CRISPR-negative Enterococcus strains. However, the efmA gene showed a strong association with CRISPR-negative strains, indicating that the efmA gene may be more prevalent in CRISPR-negative Enterococcus strains. Similar data were obtained from Tao S et al. in a study where they analyzed 110 strains of Enterococcus [33]. Their study showed an association between the CRISPR-negative strains and two antimicrobial resistance genes, AAC(6′)-Ii and efmA [33]. However, they mentioned that this observation might have been due to either small sample size or the selected strains not being representative. With an elevated sample size, our study was able to support their initial findings and conclude that there is indeed an association possible between the CRISPR-negative strains and the efmA gene.
Among the E. faecium isolates, the efmA gene presented a statistically significant association with CRISPR status, with 1 out of 24 CRISPR-positive genomes (4.1%) and 52 out of 217 CRISPR-negative genomes (23.9%) (p = 0.0341). Moreover, the vanA gene presented a statistically significant association with CRISPR status, with 5 out of 24 CRISPR-positive genomes (20.8%) and 9 out of 217 CRISPR-negative genomes (4.1%) (p = 0.007), as shown in Table 3. Interestingly, the CRISPR-positive strains presented a significant lower prevalence of antibiotic resistance genes compared to the CRISPR-negative strains, although the significance was observed only in one gene. Tao et al. [28] showed that the distribution of tetM, ermB, aadE, ant (6), and aac (6′)-aph (2″) between the CRISPR-negative and the CRISPR-positive isolates was statistically significant (p < 0.05) among E. faecalis and E. faecium strains. Palmer et al. [17] presented a significant distribution for the tetM and ermB genes (p = 0.0003) among E. faecalis and Gholizadeh et al. [34] presented a significantly lower distribution of the tetM, ermA, ermB, vanA, aac6′-aph(2″), aadE, and ant(6) genes in CRISPR-positive isolates (p < 0.05) among E. faecalis. However, in our study, the distribution of ARGs between CRISPR-positive and CRISPR-negative isolates was significant only for the efmA gene. These studies suggest that the CRISPR-Cas system might act as a natural barrier against the transmission of antibiotic resistance genes. The results of Pursey et al. [35] and Price VJ et al. [36] also align with these findings. Dos Santos et al. [37] reported an association between the presence of the vanA gene and CRISPR among E. faecalis strains. However, in our study, this association was only present among E. faecium strains.
In our investigation of CRISPR-positive Enterococcus isolates, we observed distinct patterns of plasmid presence and the distribution of specific antibiotic resistance genes. We categorized the strains based on their plasmid content, revealing intriguing associations with the prevalence of certain resistance genes.
Among the 85 CRISPR-positive strains, we identified 24 strains that lacked plasmids. Within this group, we found the presence of five IsaE genes and one InuG gene. Among the 61 strains that contained one or more plasmids, we noted the presence of one dfrE, five IsaE, one fexB, five vanA, one efmA and one msrC gene.
Regarding the 195 CRISPR-negative strains, we identified 55 strains that lacked plasmids. Within this group, there were four IsaE genes, five efmA genes, one vanA gene and one msrC gene. Among the 140 strains that contain one or more plasmids, there were 1 AAC(6′)-Iih gene, 1 dfrE gene, 2 fexb genes, 2 fosB3 genes, 3 vanM genes, 3 InuG genes, 8 vanA genes, 13 IsaE genes, and 47 efmA genes. A correlation between the presence of plasmids and the presence of antibiotic resistance genes was only shown for the efmA gene, which was found in 48 out of 201 isolates containing plasmids (23.8%) and in 5 out of 79 isolates without plasmids (6.3%) (p = 0.0006).
The majority of efmA genes were discovered in CRISPR-negative plasmids. These findings highlight the significance of HGT as a key mechanism for the dissemination of antibiotic resistance. The ability of plasmids to carry multiple resistance genes can have a substantial effect on the genetic diversity and adaptability of bacterial communities, making them important players in HGT. The rapid spread of antibiotic resistance may be facilitated by the absence of CRISPR-Cas systems in these plasmids, which could allow for the unrestricted transfer and acquisition of resistance genes, aligning with the results of other studies, such as Pinilla-Redondo et al. [38] suggesting the important contribution of plasmids to HGT and high prevalence of CRISPR-Cas systems on plasmids. Pinilla-Redondo et al. [39] also discovered that prokaryotic MGEs—the majority of which are thought to be plasmids—are primarily responsible for encoding type IV CRISPR-Cas system loci. Their findings suggest that, in order to dominate the host environment, plasmid-like elements use type IV systems to eradicate other plasmids with comparable characteristics. According to research by Murugesan et al. [40], many methicillin-resistant Staphylococcus coagulans isolates had type IIIA CRISPR-Cas systems and were present within the SCCmec (staphylococcal chromosomal cassette mec) mobile genetic element, demonstrating the involvement of CRISPR-Cas systems in blocking phage/plasmid invasion and horizontal gene transfer of antimicrobial resistance genes. Garneau et al. [41] suggest that Streptococcus thermophilus experiences plasmid loss as a result of the CRISPR/Cas system, which offers an easy way to create a strain of bacteria that is resistant to plasmids containing genes for antibiotic resistance.
As previously mentioned, the CRISPR-Cas system may act as an immune effector in fighting the acquisition of foreign DNA from different mobile genetic elements. Price VJ et al. analyzed the behavior of the CRISPR-Cas system in vitro and in vivo and their works showed that perhaps this system works better in vivo rather in vitro [36]. This work highlights an important challenge in using CRISPR-Cas-based approaches to tackle antimicrobial resistance phenomenon in different bacteria. Since these techniques are increasingly studied, we might be facing a lot of different new challenges and thus there is a need to approach them with cautiousness and in a systematic manner [42,43,44].
Future applications of CRISPR-Cas technology show great potential in medical and biological sciences. One significant area is the development of CRISPR-based screening tests for antibiotic-resistant strains, such as Enterococcus. These tests could quickly identify resistance genes, enabling timely and appropriate treatment decisions. Additionally, CRISPR-Cas could be utilized to design rapid diagnostic tests to detect a wide range of pathogens or genetic conditions. The use of CRISPR-Cas as a target for new medications is another promising application. By focusing on specific genes responsible for disease or antibiotic resistance, new therapeutic strategies can be devised to inhibit these genes, offering more effective treatments. By studying and manipulating the human microbiome using the CRISPR-Cas system, treatments for diseases associated with microbial imbalances, such as inflammatory bowel disease and obesity, could be developed. The potential applications of CRISPR-Cas are continuously expanding. Engaging in interdisciplinary research and collaboration is important for discovering new opportunities. For instance, combining CRISPR-Cas with artificial intelligence or bioinformatics could enhance precision in gene editing.

4. Conclusions

Our study provides evidence for a potential association between the CRISPR-Cas system and antibiotic resistance in Enterococcus species. CRISPR-positive isolates demonstrated a lower prevalence of antibiotic resistance genes, suggesting that the CRISPR-Cas system may act as a natural barrier against the spread of antibiotic resistance in these bacteria. Although this significant difference is only noticed for the vanA gene among E. faecium and the efmA gene. This phenomenon can be attributed to the likelihood that the CRISPR-Cas system is more active in antiviral protection, with bacteriophages serving as an active regulatory factor in bacterial communities.
These insights contribute to a better understanding of the molecular mechanisms underlying antibiotic resistance in Enterococcus and may contribute to the development of targeted strategies to combat multidrug-resistant infections, including in the development of specific bacteriophage therapy, which can be especially helpful in focusing on pathogenic bacteria’s antibiotic resistance genes, making them more susceptible to treatment.

Author Contributions

Conceptualization, A.B.-K., C.C. and D.-A.T.; methodology, A.B.-K., C.C., I.C., D.-A.T. and D.I.; software, D.I., K.D., D.D., A.B., V.N., A.G.P., P.S., A.T. and P.P.; validation, D.I. and D.-A.T.; formal analysis, D.I., K.D., D.D., A.B., V.N., A.G.P., P.S., A.T. and P.P.; investigation, D.I., K.D., D.D., A.B., A.G.P., P.S., A.T. and P.P.; resources, C.C., I.C., A.B.-K., D.-A.T. and D.I.; data curation, C.C., I.C., A.B.-K., D.-A.T. and D.I.; writing—original draft preparation, D.I., K.D., D.D., A.B., V.N., A.G.P., P.S., A.T. and P.P.; writing—review and editing, C.C., I.C., A.B.-K., D.-A.T. and D.I.; visualization, D.I., K.D., D.D., A.B., V.N., A.G.P., P.S., A.T. and P.P.; supervision C.C., I.C., A.B.-K., D.-A.T. and D.I.; project administration C.C., I.C., A.B.-K., D.-A.T. and D.I.; funding acquisition, C.C., I.C., A.B.-K., D.-A.T. and D.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Biomedicines 12 01625 g002
Figure 2. The distribution of the CRISPR-positive and CRISPR-negative isolates among the Enterococcus species strains. Each group, CRISPR-positive and CRISPR-negative, contains different Enterococcus species (horizontal axis), and for each species, a different number of strains (noted on the columns).
Figure 2. The distribution of the CRISPR-positive and CRISPR-negative isolates among the Enterococcus species strains. Each group, CRISPR-positive and CRISPR-negative, contains different Enterococcus species (horizontal axis), and for each species, a different number of strains (noted on the columns).
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Biomedicines 12 01625 g003
Figure 3. The distribution of the CRISPR-Cas types among the CRISPR-positive and CRISPR-negative isolates. Each group, CRISPR-positive and CRISPR-negative, contains a different number of Enterococcus isolates (noted on the columns) for each type (horizontal axis).
Figure 3. The distribution of the CRISPR-Cas types among the CRISPR-positive and CRISPR-negative isolates. Each group, CRISPR-positive and CRISPR-negative, contains a different number of Enterococcus isolates (noted on the columns) for each type (horizontal axis).
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Figure 4. Heatmap showing the relationship between the Enterococcus isolates and the presence of genes and plasmids. The vertical axis represents the Enterococcus isolates, while the horizontal axis denotes the genes and plasmids. Each cell within the heatmap is color-coded to indicate the presence or absence of the respective genes and plasmids in each isolate. A green color signifies the presence of a gene/plasmid, whereas a red color indicates its absence. The varying patterns of green and red across the heatmap highlight the differences in gene presence among the isolates.
Figure 4. Heatmap showing the relationship between the Enterococcus isolates and the presence of genes and plasmids. The vertical axis represents the Enterococcus isolates, while the horizontal axis denotes the genes and plasmids. Each cell within the heatmap is color-coded to indicate the presence or absence of the respective genes and plasmids in each isolate. A green color signifies the presence of a gene/plasmid, whereas a red color indicates its absence. The varying patterns of green and red across the heatmap highlight the differences in gene presence among the isolates.
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Biomedicines 12 01625 g005
Figure 5. Heatmap showing the relationship between the Enterococcus isolates and types of CRISPR-Cas. The vertical axis represents the Enterococcus isolates, while the horizontal axis denotes the CRISPR-Cas types. Each cell within the heatmap is color-coded to indicate the presence or absence of the respective types in each isolate (a different color for each type). A red color indicates the absence of the respective type.
Figure 5. Heatmap showing the relationship between the Enterococcus isolates and types of CRISPR-Cas. The vertical axis represents the Enterococcus isolates, while the horizontal axis denotes the CRISPR-Cas types. Each cell within the heatmap is color-coded to indicate the presence or absence of the respective types in each isolate (a different color for each type). A red color indicates the absence of the respective type.
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Table 1. The distribution of ARGs among CRISPR-negative and CRISPR-positive isolates. Each gene is found in a different number among the two groups, CRISPR-positive and CRISPR-negative.
Table 1. The distribution of ARGs among CRISPR-negative and CRISPR-positive isolates. Each gene is found in a different number among the two groups, CRISPR-positive and CRISPR-negative.
GeneCRISPR-Positive
(n = 187 Sequences)		CRISPR-Negative
(n = 529 Sequences)
AAC(6′)-Iih0 (0%)1 (0.19%)
dfrE1 (0.53%)1 (0.19%)
efmA1 (0.53%)52 (9.83%)
fexB1 (0.53%)2 (0.38%)
FosB30 (0%)2 (0.38%)
lnuG1 (0.53%)3 (0.57%)
lsaE12 (6.42%)17 (3.21%)
msrC1 (0.53%)1 (0.19%)
vanA5 (2.67%)9 (1.70%)
vanM0 (0%)3 (0.57%)
Table 2. The table presents the results of Fisher’s exact test for the ARGs. Only for the efmA gene is the test statistically significant (p < 0.05), which is represented in green.
Table 2. The table presents the results of Fisher’s exact test for the ARGs. Only for the efmA gene is the test statistically significant (p < 0.05), which is represented in green.
Genep (Fisher’s Exact Test)
efmAp < 0.05
fexB1
FosB31
lnuG1
lsaE0.0812
vanA0.3774
vanM0.5713
Table 3. Distribution (%) of the efmA and vanA genes among CRISPR-positive and CRISPR-negative isolates in E. faecium.
Table 3. Distribution (%) of the efmA and vanA genes among CRISPR-positive and CRISPR-negative isolates in E. faecium.
E. faeciumCRISPR-PositiveCRISPR-Negativep (Fisher’s Exact Test)
efmA4.1%23.9%0.0034
vanA20.8%4.1%0.007
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Costache, C.; Colosi, I.; Toc, D.-A.; Daian, K.; Damacus, D.; Botan, A.; Toc, A.; Pana, A.G.; Panaitescu, P.; Neculicioiu, V.; et al. CRISPR-Cas System, Antimicrobial Resistance, and Enterococcus Genus—A Complicated Relationship. Biomedicines 2024, 12, 1625. https://doi.org/10.3390/biomedicines12071625

AMA Style

Costache C, Colosi I, Toc D-A, Daian K, Damacus D, Botan A, Toc A, Pana AG, Panaitescu P, Neculicioiu V, et al. CRISPR-Cas System, Antimicrobial Resistance, and Enterococcus Genus—A Complicated Relationship. Biomedicines. 2024; 12(7):1625. https://doi.org/10.3390/biomedicines12071625

Chicago/Turabian Style

Costache, Carmen, Ioana Colosi, Dan-Alexandru Toc, Karla Daian, David Damacus, Alexandru Botan, Adelina Toc, Adrian Gabriel Pana, Paul Panaitescu, Vlad Neculicioiu, and et al. 2024. "CRISPR-Cas System, Antimicrobial Resistance, and Enterococcus Genus—A Complicated Relationship" Biomedicines 12, no. 7: 1625. https://doi.org/10.3390/biomedicines12071625

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