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Article

In Silico Detection of Genetic Determinants for the Acquired Antibiotic Resistance and Biologically Active Compounds of Lactic Acid Bacteria from the Human Oral Microbiome

by
Nikola Atanasov
1,2,*,
Yana Evstatieva
1,2 and
Dilyana Nikolova
1,2,*
1
Department of Biotechnology, Faculty of Biology, Sofia University “St. Kliment Ohridski”, 1164 Sofia, Bulgaria
2
Centre of Competence “Sustainable Utilization of Bio-Resources and Waste of Medicinal and Aromatic Plants for Innovative Bioactive Products” (BIORESOURCES BG), 1000 Sofia, Bulgaria
*
Authors to whom correspondence should be addressed.
Appl. Microbiol. 2025, 5(3), 60; https://doi.org/10.3390/applmicrobiol5030060
Submission received: 6 June 2025 / Revised: 27 June 2025 / Accepted: 27 June 2025 / Published: 29 June 2025
(This article belongs to the Special Issue Exclusive Papers Collection of Editorial Board Members and Invited Scholars in Applied Microbiology (2025))
Versions Notes

Abstract

The whole-genome sequencing of lactic acid bacteria provides a valuable resource for identifying the genetic determinants underlying molecular mechanisms related to their probiotic properties. Analysis of draft genome sequences relies on bioinformatics tools for genetic data processing and in silico analytical methods to pinpoint the genetic determinants encoding biologically active compounds. The aim of this study was to perform the phenotypic determination of the antibiotic sensitivity and bioinformatics analyses on whole-genome assemblies from LAB from the human oral microbiome, and determine the presence of acquired antibiotic resistance genes, peptidases, adhesion proteins, and bacteriocins. Bioinformatics processing was performed in order to establish the molecular mechanisms responsible for the previously observed probiotic properties. The tested LAB strains exhibited a broad spectrum of antibiotic multiresistance, but did not possess acquired antibiotic resistance genes. The detected genes for peptidase activity were from the Pep family of hydrolase enzymes. Genetic determinants for adhesion proteins contained LPxTG, YSIRK, KxYKxGKxW, and SEC 10/PgrA domains, as well as MucBP domains. Lectins were found for five of the strains with the presence of WxL domains from the CscC protein family and L-type lectin domains. The in silico analyses show that some of the tested strains possessed mechanisms for bacteriocin production.

1. Introduction

Lactic acid bacteria (LAB) are Gram-positive, microaerophilic bacteria which play essential roles in different biological processes [1]. Their innate safety makes many LAB strains ideal candidates for probiotics due to their significant health benefits to the host when consumed [2]. Oral LAB can exhibit their probiotic properties through multiple mechanisms, including the ability to adhere to dental and mucosal tissues, and compete for adhesion surfaces, form biofilms, as well as the possession of antibiofilm activity against other microorganisms, to produce different bioactive metabolites, etc., in order to exclude or reduce pathogenic presence [3,4].
Antibiotic resistance is one of the important standards when assessing the probiotic properties of LAB. The global health concern for increasing antibiotic resistance is more often associated with the presence of acquired antibiotic resistance genes, horizontally transferred through mobile genetic elements, including plasmids, transposons, and integrons, to other microorganisms, pathogens included [5,6]. As the oral cavity frequently comes into contact with other microorganisms, oral LAB can easily reach other sites of the body and spread to other hosts. Therefore, it is possible for oral LAB to acquire and transfer antibiotic resistance genes [7]. Moreover, the appearance of lactobacilli as reservoirs of such genes could increase the concern for health issues [6]. Thus, it is important to detect if transferable antibiotic resistance genetic determinants are present in LAB representatives which are candidates for oral probiotics.
In order to survive and thrive in different environments, LAB depend on their metabolic activity, which is also important for their future application in probiotic products [8]. The proteolytic system of LAB includes peptidases, proteinases, and specific transport proteins [9]. The peptidase system of LAB is one of their leading metabolic activities. Peptidases hydrolyse exogenous peptides into amino acids and smaller peptides which are essential for cell growth, housekeeping proteinases, and in the production of different beneficial metabolites [10,11].
The adhesion property of LAB is one of the first factors to determine their contribution in mediating health effects to the host. Their ability to adapt facilitates their probiotic properties by adhering to mucosal surfaces [12]. One of the important requirements for probiotic bacteria is high adherence capacity, as it is responsible for successful colonization in the oral cavity and gastro-intestinal tract (GIT) [13]. Surface proteins, called adhesins, are the major structural elements involved in the adhesion processes of lactobacilli [14]. After non-specific physical interactions between bacteria and the epithelium, a more specific interaction between bacterial adhesion proteins and mucosal surfaces takes place, including binding to specific receptors [12]. These adhesion factors include exopolysaccharides, surface layer proteins, and teichoic acids, as well as other membrane- or cell wall-associated proteins [15]. These adhesins are produced as cell wall-anchored proteins on the cell surface and are mainly multi-functional cytoplasmatic proteins that exhibit moonlighting functions [14].
Bacteriocins are antimicrobial peptides produced by many bacterial species that are involved in inter- and intraspecies interactions [16]. These proteins possess bacteriostatic or bactericidal activity against bacteria that are from similar or closely related species and usually possess a narrow spectrum of growth inhibition [17]. Based on their molecular weight, amino acid sequences, genetic characteristics, and posttranslational modifications, LAB bacteriocins are classified into three major classes. Class I bacteriocins are small post-translationally modified and thermostable peptides, which are subdivided into Class Ia (lantibiotics), Class Ib (labyrinthopeptins), and Class Ic (sanctibiotics). Class II bacteriocins are small, thermostable, non-modified peptides, subdivided into Class IIa (pediocin-like bacteriocins), Class IIb (two-peptide unmodified bacteriocins), Class IIc (circular bacteriocins), and Class IId (unmodified, linear, non-pediocin-like bacteriocins). Class III bacteriocins as larger, thermolabile peptides that are subdivided into two subclasses: IIIa (bacteriolysins) and IIIb (non-lytic) [18,19,20]. It is indicated that Class II bacteriocins are the most abundantly produced antimicrobial compounds by LAB species [21].
Bioinformatics is a major discipline that derives significant biological information from genomic data. From basic processing of raw sequencing reads to more complex analyses, including comparative genomics, metagenomics, structural, and metabolic modelling, etc., bioinformatics tools have been widely used and developed [22]. Numerous different sequencing technologies, as well as bioinformatics tools can be utilized, depending on the specific research [23]. High-throughput sequencing has eased the identification, as well as the characterization of LAB genomes. The detection of specific genetic determinants in the whole-genome sequences of LAB can reveal many promising metabolic potentials, which can increase their potential application [24]. In addition, the European Food Safety Authority (EFSA) has recently suggested examining the whole genomes of LAB due to safety concerns for acquired antibiotic resistance genes [25]. Additionally, bioinformatics tools can be applied to detect genetic determinants for encoding different biologically active compounds [26].
In this context, the aim of this work was to perform in vitro phenotypic antibiotic resistance screening, and in silico processing on the raw whole-genome sequences of previously isolated and selected oral LAB strains [27]. Bioinformatics tools were utilized to detect the presence of specific genetic determinants for acquired antibiotic resistance genes, as well as for three probiotic-related mechanisms: peptidase activity, adhesion proteins, and bacteriocin production.

2. Materials and Methods

2.1. Microorganism Strains

The studied LAB strains were previously isolated from the human oral cavity microbiome and were identified as follows: Limosilactobacillus fermentum N 2; Limosilactobacillus fermentum N 4-5; Weissella confusa AG 2-6; Latilactobacillus curvatus KG 12-1; Limosilactobacillus fermentum TC 3-11; Lactobacillus delbrueckii subsp. Allosunkii VG 1, according to the newly proposed nomenclature [28]; Lactobacillus delbrueckii subsp. Lactis VG 2; Lactobacillus delbrueckii subsp. Lactis MK 13-1; Weissella confusa NN 1; Lacticaseibacillus rhamnosus NA 1-8; Limosilactobacillus fermentum NA 2-2; and Lacticaseibacillus paracasei AV 2-1 [27].

2.2. Phenotypic Antibiotic Resistance

The agar disc diffusion assay was used for the phenotypic determination of the antibiotic resistance of the tested LAB strains with some modification [29,30]. Thirteen antibiotic substances were used in the form of paper discs with different concentrations: ampicillin (AMP)—10 mcg/disc; clindamycin (CD)—2 mcg/disc; vancomycin (VA)—5 mcg/disc; ciprofloxacin (CIP)—5 mcg/disc; trimethoprim (TR)—5 mcg/disc; chloramphenicol (C)—30 mcg/disc; erythromycin (E)—15 mcg/disc; gentamicin (GEN)—10 mcg/disc; kanamycin (K)—30 mcg/disc; neomycin (N)—30 mcg/disc; rifampicin (RD)—5 mcg/disc; streptomycin (S)—10 mcg/disc; and tetracycline (TE)—30 mcg/disc. Then, 24 h cultures of the tested strains were standardized to 0.5 McFarland and inoculated in petri dishes with molten MRS agar. After solidification, antibiotic discs (Oxoid, Basingstoke, UK) were placed on top of the agar media and the cultures were cultivated at 37 °C for 24 h. The results were measured by determining the diameter of the inhibitory zones, and interpreted according to the Clinical & Laboratory Standards Institute [31].
The index for multiple antibiotic resistance (MAR) for all strains was also determined [32] according to the following formula:
M A R   i n d e x = N u m b e r   o f   a n t i b i o t i c s   t h a t   i s o l a t e   i s   r e s i s t a n t T o t a l   n u m b e r   o f   a n t i b i o t i c s

2.3. DNA Isolation

Total DNA was isolated from 2 mL overnight cultures of the studied LAB in an MRS broth. DNA was extracted using the Quick-DNA™ Fungal/Bacterial Miniprep Kit (Zymo Research, Irvine, CA, USA), according to the manufacturer’s instructions. The final elution was performed in a 100 µL elution buffer from the kit. The isolated DNA was quantitatively and qualitatively analyzed with the NanoDrop™ OneC Microvolume UV-Vis Spectrophotometer (Thermo Fisher Scientific, Waltham, Massachusetts, USA). The DNA samples were further stored at −20 °C.

2.4. Whole-Genome Sequencing

First, 40 µL of each isolated DNA sample was sent at room temperature to Novogene Europe (Cambridge, UK) for whole-genome sequencing on the Illumina NovaSeq 6000 platform (Illumina, San Diego, California, USA) for PE150 sequencing with 1 Gb of raw data generation [24].

2.5. Bioinformatics Processing

All tasks were performed using the Galaxy Europe server (https://usegalaxy.eu, accessed on 5 May 2023), the Basic Local Alignment Search Tool (BLAST v. 2.14.0) on the NCBI website (https://blast.ncbi.nlm.nih.gov/Blast.cgi, accessed on 20 June 2023), and BAGEL4 (http://bagel.molgenrug.nl/, accessed on 2 April 2025). In situ processing was performed on data from cultures of the evaluated LAB strains without antibiotic exposure. The raw data from the Illumina platform was qualitatively monitored with the FastQC tool v. 0.11.9 [33]. Then, the data was processed for read trimming and filtering with the Trimmomatic tool v. 0.39 [34], followed by another FastQC monitoring. The Shovill assembly tool v. 1.1.0 [35] was then used to assemble the contigs and the scaffolds. The quality of the assembled contigs was assessed with the Quast tool v. 5.2.0 [36]. The assembled contigs of the draft genomes of the studied LAB strains were later deposited to the NCBI genetic database for whole genomes. The ABRicate tool v. 1.0.1 [37] was used for the detection of acquired antibiotic resistance genetic determinants, compared with the NCBI database. In order to detect genetic determinants for functional proteins, a BLAST database was created with the makeblastdb tool v. 2.14.1 and the tblastn tool v. 2.14.1 [38] was used to compare specific protein queries to the translated nucleotide database of each LAB strain. Following the last step, the resulting nucleotide sequences were compared to the NCBI database using the BLASTx algorithm. In addition, the BAGEL4 platform was used specifically for the detection of genetic determinants for encoding bacteriocins [39].

3. Results

3.1. Antibiotic Resistance and Detection of Acquired Genes

All evaluation of the antibiotic resistance is one of the main important standards related to the technological application and probiotic potential of LAB. Evaluating the antibiotic resistance of LAB by applying phenotypic and genotypic analyses is based on determining the possible horizontal transfer of antibiotic resistance genes to commensal and pathogenic microorganisms, the relationship of some species in some disease cases, and the possibility of a combined antibiotic treatment with probiotics in order to restore the normal microflora in the GIT [5].
Thirteen antibiotics were assessed in the antibiotic resistance analysis of the tested strains (Table 1). The used antibiotics were selected depending on their mechanism of action: inhibition of the protein synthesis, inhibition of the cell wall synthesis, and inhibition of the DNA synthesis.
The susceptibility of all LAB strains to five of the tested antibiotics (ampicillin, clindamycin, chloramphenicol, erythromycin, and tetracyclin) was reported. Resistance to rifampicin was reported for the two W. confusa AG 2-6 and NN 1 strains. The tested strains exhibited expressed resistance to three of the tested antibiotics, i.e., kanamycin, neomycin, and streptomycin, which are inhibitors of the protein synthesis. Only the L. fermentum TC 3-11 strain showed intermediate susceptibility to gentamicin, while all other strains were resistant. Only the L. rhamnosus NA 1-8 strain showed intermediate susceptibility to ciprofloxacin, which inhibits DNA synthesis, while all other strains were resistant. The three L. delbrueckii strains showed intermediate susceptibility to vancomycin, which inhibits the cell wall synthesis, while all other strains were resistant. Resistance to trimethoprim was reported for most of the strains, except the L. fermentum N2, TC 3-11 and NA 2-2 strains which were susceptible to this antibiotic. In addition, the tested strains showed different MAR patterns with values between 0.385 and 0.615 for the different strains.
In addition to the phenotypic antibiotic resistance analysis, an in silico bioinformatics analyses for the detection of acquired antibiotic resistance genes were held. The whole-genome sequences were processed and the results show that the tested LAB strains did not possess acquired cat, erm(B), and tet(M) antibiotic resistance genes, which are one of the mainly tracked. This result allowed for the strains to be evaluated as safe under the Qualified Presumption of Safety (QPS) requirements of the EFSA [40].

3.2. Detection of Genetic Determinants for Peptidase Activity

LAB provide their cells with essential amino acids for their growth process by exhibiting hydrolase activity and can produce different substances that are beneficial to human health [11].
In silico bioinformatics analyses of the whole-genome sequences were carried through for the presence of genetic determinants and different genes for peptidase activity were detected for the studied strains. The detected genes are from the Pep family of hydrolase enzymes which hydrolyze different proteins, including dipeptides, tripeptides, and oligopeptides, to amino acids (Table 2).

3.3. Detection of Genetic Determinants for Adhesion Proteins

Many bioinformatics tool for genetic processing are present, as well as analytical techniques for the determination of molecular mechanisms responsible for the recognition and adhesion of bacterial cells on mucosal surfaces. Such mechanisms also include carbohydrate–protein interactions through adhesion proteins synthesized on the surface of bacterial cells [41,42,43].
The in silico bioinformatics analyses of the whole-genome sequences were carried through for the presence of genetic determinants for adhesins responsible for the determined adhesion characteristics of the tested strains from the in vitro analyses, of which results are described in a previous work [27]. Two types of adhesion proteins were discovered in bioinformatics processing: adhesins, which facilitate the adhesion of LAB to tissues and other cells, and lectins, which facilitate the binding of LAB to carbohydrates and other proteins [14].
It was established that genetic determinants for encoding adhesion proteins are present in the tested LAB strains. They contain LPxTG, YSIRK, KxYKxGKxW, and SEC 10/PgrA domains, as well as MucBP domains that are a part of the mucin-binding protein family (Table 3). On the other hand, lectins were found for L. curvatus KG 12-1, L. rhamnosus NA 1-8, L. paracasei AV 2-1, W. confusa AG 2-6, and NN 1 with the presence of WxL domain from the CscC protein family and L-type lectin domain (Table 4).

3.4. Detection of Genetic Determinants for Bacteriocin Production

LAB can synthesize substances with antimicrobial activity, including bacteriocins. The synthesis of such substances can be induced by different factors for strains that possess the corresponding genetic determinants.
An in silico analysis of the whole-genome sequences was held and the results show that some of the tested strains possessed mechanisms for bacteriocin production. L. curvatus KG 12-1, L. rhamnosus NA 1-8, and L. paracasei AV 2-1 were found to possess genetic determinants for encoding Class II bacteriocins and the three studied L. delbrueckii strains were found to encode a Class III bacteriocin (Table 5).

4. Discussion

The determined antibiotic resistance of the twelve tested strains is defined by different intracellular mechanisms [44]. Most of the LAB representatives possessed high resistance to glycopeptide antibiotic substances, including vancomycin, as this characteristic is determined by differences in the chromosome coding for the peptidoglycan assembly pathway [45]. Also, LAB were mostly resistant to aminoglycoside antibiotics, including kanamycin, neomycin, streptomycin, and gentamicin, as this phenotypic characteristic is considered to be due to two main factors: low bacterial cell wall permeability to aminoglycosides and the absence of elements of cytochrome-mediated electron transfer [46,47]. It is also reported that LAB which possessed intrinsic resistance to diaminopyrimidines, including trimethoprim, did not possess the biosynthetic pathway for the production of folic acid, as the antibiotic blocks dihydropteroat synthetase activity in the cells [48,49]. The resistance to fluoroquinolone antibiotics, including ciprofloxacin, is probably due to cell wall impermeability, as well as mutations in the quinolone resistance regions which determine the genetic basis for antibiotic resistance for LAB [50,51].
From numerous studies, it is considered that the resistance to specific antibiotic groups, as well as the susceptibility to other depends on the source of origin of the isolates. It is hypothesized that human-derived LAB isolates exhibit more widespread resistance due to the higher likelihood of exposure to antibiotic substances in their natural environment [49,52,53]. In addition, an MAR index above 0.2 indicates that the isolates originate from sources with higher antibiotic application [49]. The established resistances for the studied strains are also confirmed by other authors [54,55,56,57], as well as in other previously cited references.
The endopeptidase system of LAB consists of aminopeptidases (PepN, PepC, PepM, and PepA), endopeptidases (PepE, PepF, and PepO), dipeptidases (PepV and PepD), tripeptidase PepT, and proline peptidases (PepX, PepP, PepQ, PepR, and PepI). Many peptides with essential physiological functions were found in casein hydrolysates, such as opioid peptide, blood pressure-lowering peptide, antithrombotic peptide, immunostimulant peptide, mineral ion-absorption-promoting peptide, etc. These peptides are around 1000 Da and can be easily absorbed in the GIT [58,59]. The presence of peptidase activities is an essential characteristic which has potential for the production of biologically active peptides and complements the probiotic properties of the different LAB strains. Regarding the tested strains in our study, genetic determinants for PepF, PepT, and PepV were the most abundant. PepC and PepQ were found only in the L. delbrueckii subsp. allosunkii VG 1 and L. delbrueckii subsp. lactis MK 13-1 genomes and PepA genetic determinant was found only in the genomes of the two W. confusa strains.
In a study by Falasconi et al., the authors carried out genomic analyses for L. fermentum and W. confusa strains, and reported an almost complete Pep system, including the PepA, PepF, PepT, and PepV genes, for all tested strains [60]. Grizon et al. identified a total of 13 peptidase genetic determinants, including the PepC, PepF, PepQ, PepT, and PepV genes, for 15 newly isolated L. delbrueckii strains [61]. The presence of the PepF gene for L. paracasei SP5 strain was also reported by Kiousi et al. by analyzing the whole-genome sequence of the strain [62].
Adhesins produced by LAB are classified according to the target place for adhesion on the mucous tissue, as well as their localization and/or their binding to the cell surface [63]. The cell surface contains protein molecules in its structure, which are connected to the cell wall by a binding domain at the C-terminus, coded by an LPxTG sequence. Different domains with YSIRK и KxYKxGKxW sequences are bound at the N-terminus of the protein molecule which determine the adhesive properties of LAB, as well as their competitiveness to various pathogenic representatives. The SEC 10/PgrA domain determines the ability to perform adhesion and the MucBP domain is responsible mainly for the binding of bacterial cells to the mucin proteins on the mucosal surface [64,65].
For LAB producing lectins, the WxL domain is responsible for the localization of cell surfaces and the L-type lectin domain is responsible for the interaction with mucosal epithelial cells [66,67]. The detection of genetic determinants for adhesion proteins supports the previously established results for autoaggregation, where all of the strains showed strain-specific autoaggregative properties; binding to mucin, where the tested strains exhibited an expressed mucin binding ability at 5 logs CFU/mL; and biofilm formation, where all of the strains showed the ability to form self-biofilms, for most of them measured above 46% [27,68]. These cell surface structures could also play a role in co-aggregation with pathogens and in antibiofilm activity. From the results described in our previous work, the tested strains showed expressed co-aggregative ability with Streptococcus mutans and Candida albicans, and expressed antibiofilm activity, where most of the strains exhibited inhibition properties above 79% against S. mutans and above 45% against C. albicans [68].
Lactobacilli species are well known to possess surface expressed adhesion factors. The detected genetic determinants for adhesion proteins for the studied strains in our work are considered to play an important role in establishing many of their probiotic properties. The presence of these genetic determinants in LAB are also reported by other authors [69,70,71,72,73]. The reported detection of adhesion proteins shows possible cell-to-cell and cell-to-host interactions. Further analyses for evaluating the functional roles of the detected genetic determinants will be a part of our future study, including in vitro epithelial cell adhesion.
The Blp family class II bacteriocin is commonly found genetic determinant in orally and GIT-associated Streptococcus species, but is found in the genomes of oral and GIT lactobacilli species as well, including Ligilactobacillus salivaruis, Ligilactobacillus murinus, L. paracasei, Lactobacillus paragasseri, Lactobacillus zeae, etc. (https://www.ncbi.nlm.nih.gov/gene, accessed on 19 May 2025). Authors report that the blp locus encodes bacteriocins which possess antimicrobial activity against a wide spectrum of Gram-positive bacteria, including Cutibacterium acnes, Enterococcus faecalis, Listeria monocytogenes, and Streptococcus pyogenes, as well as oral pathogens, including S. mutans [74]. Class IIa bacteriocins, including leucocins and sakacins, are known to cause pore formation and disrupt the integrity of target cell membranes, leading to the expelling of crucial intracellular metabolites [75]. Genetic determinants for encoding leucocins and sakacins are reported to be present in the genomes of L. murinus, Ligilactobacillus ruminis, and L. zeae (https://www.ncbi.nlm.nih.gov/gene, accessed on 19 May 2025), and display potent activity against Gram-positive bacteria, including E. faecalis, Enterococcus faecium, L. monocytogenes, and Staphylococcus aureus [76,77]. Sakacins are a bacteriocin group mainly produced by Latilactobacillus sakei strains [78], and sakacin Q is reported to be produced by L. curvatus strains [79]. The genetic determinant for the production of bacteriocins in the Class IIb bacteriocin, lactobin A/cerein 7B family is reported to be present in the Lacticaseibacillus genus [80]. Carnocin CP52 is an immunity bacteriocin associated with the induction of pore formations to the cell membrane of Gram-positive pathogens [81]. It is reported that the species of the Lacticaseibacillus genera, including L. rhamnosus and L. casei, possess genetic determinants for its production [82,83]. The Class IIIb bacteriocin helveticin J genetic determinant encodes proteins that are capable of disrupting the cell wall and inner cytoplasmic membrane of Gram-positive bacteria, and disorganizing the outer membrane of Gram-negative bacteria, which ultimately leads to cell death [84]. This genetic determinant is mainly found within the Lactobacillaceae family, including Lactobacillus amylovorus, Lactobacillus helveticus, Lactobacillus intestinalis, L. crispatus, Lentilactobacillus parabuchneri, etc. (https://www.ncbi.nlm.nih.gov/gene, accessed on 19 May 2025), and is reported to possess antimicrobial activity against Gram-positive and Gram-negative Enterobacter, Escherichia, Listeria, Salmonella, Vibrio, and Yersinia [85]. LSEI 2386 is a putative bacteriocin which is encoded in the genomes of Lacticaseibacillus casei and L. paracasei strains, and possesses antimicrobial activity against S. mutans and Listeria spp. [86,87]. The Enterolysin A bacteriocin cluster was also be detected in the genomes of L. paracasei and is reported to have a role in cell-wall degradation [88,89]. The detected genetic determinants for bacteriocins for six of the studied LAB strains is possibly play a role in the established phenotypic antimicrobial and antagonistic activities in our previous studies [27,68]. Wide antimicrobial activity was shown from the studied L. delbrueckii strains against pathogens, including Escherichia coli, Bacillus subtilis, Bacillus cereus, S. aureus, and Pseudomonas aeruginosa [27]. The evaluated antagonistic activity against S. mutans and C. albicans shows expressed co-aggregation and antibiofilm activity, as previously mentioned. From the direct co-culturing with the two oral pathogens, well-expressed antagonism was indicated from most of the strains against S. mutans, by 2–5 logs of viability decrease, and a decrease by 1–2 logs against C. albicans from all of the studied strains until 48 h [68].
The previously established activities from the co-culturing can be connected to the possible production of bacteriocins from the studied LAB strains that inhibit bacterial pathogens in the oral cavity. The combination of antimicrobial peptides and adhesion factors, including adhesins and lectins, possibly possesses direct antagonistic activity against yeast pathogens. It is important to study these antimicrobial mechanisms in order to establish the exact inhibition pathways against pathogenic species, and our future studies will include research on this topic.

5. Conclusions

In conclusion, the objective of this study was to assess the in vitro phenotypic antibiotic resistance profiles and conduct in silico detection of specific genetic determinants within the whole-genome sequences of the selected oral LAB strains. The results indicate that while exerting a wide range of antibiotic resistance, the studied LAB strains did not possess acquired antibiotic resistance genes. These findings could be due to the human oral cavity being the natural environment of these strains, which leads to higher probability of exposure to different antibiotic substances. The further in silico characterisation provided information on the presence of genetic determinants mainly for encoding endopeptidase, dipeptidase, and tripeptidase activity which acknowledges their proteolytic activity. The detected genetic determinants for adhesins and lectins are in support of the previously established adhesion characteristics and probiotic properties of the studied LAB strains. Furthermore, possessing synthesis mechanisms for these adhesion factors could contribute to the initialization of their antagonistic interactions with different oral pathogens, including C. albicans. Six of the strains also possessed genetic determinants encoding bacteriocins which might be involved in the previously established antagonistic activity against S. mutans. Overall, the identified genetic elements contributed to the probiotic profile of the studied LAB strains, and are prerequisite for further analyses and their successful administration in oral probiotic products.

Author Contributions

Conceptualization, N.A. and D.N.; formal analysis, N.A., Y.E. and D.N.; investigation, N.A. and D.N.; methodology, N.A., Y.E. and D.N.; software, N.A.; supervision, D.N.; writing—original draft, N.A.; writing—review and editing, Y.E. and D.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The genomic sequences of the tested LAB strains are available in the NCBI BioProject database under accession number PRJNA991968.

Acknowledgments

This work was supported by Project “Sofia University Marking Momentum for Innovation and Technological Transfer (SUMMIT)”, grant number BG-RRP-2.004-0008-C01. The support of the Centre of Competence “Sustainable Utilization of Bio-resources and Waste of Medicinal and Aromatic Plants for Innovative Bioactive Products” (BIORESOURCES BG), project BG16RFPR002-1.014-0001, funded by the Program “Research, Innovation and Digitization for Smart Transformation” 2021-2027, co-funded by the EU, is greatly acknowledged.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Antibiotic resistance of the tested LAB strains.
Table 1. Antibiotic resistance of the tested LAB strains.
StrainAntibioticsMAR Index
AMPCDVACIPTRCEGENKNRDSTE
N 2SSRRSSSRRRSRS0.462
N 4-5SSRRRSSRRRSRI0.538
AG 2-6SSRRRSSRRRRRS0.615
KG 12-1SSRRRSSRRRSRS0.538
TC 3-11SSRRSSSIRRSRS0.385
VG 1SSIRRSSRRRSRS0.462
VG 2SSIRRSSRRRSRS0.462
MK 13-1SSIRRSSRRRSRS0.462
NN 1SSRRRSSRRRRRS0.615
NA 1-8SSRIRSSRRRSRS0.462
NA 2-2SSRRISSRRRSRS0.462
AV 2-1SSRRRSSRRRSRS0.538
R—resistant, I—intermediate, S—susceptible (CLSI, 2020); antibiotics: ampicillin (AMP)—10 mcg/disk; clindamycin (CD)—2 mcg/disk; vancomycin (VA)—5 mcg/disk; ciprofloxacin (CIP)—5 mcg/disk; trimethoprim (TR)—5 mcg/disk; chloramphenicol (C)—30 mcg/disk; erythromycin (E)—15 mcg/disk; gentamicin (GEN)—10 mcg/disk; kanamycin (K)—30 mcg/disk; neomycin (N)—30 mcg/disk; rifampicin (RD)—5 mcg/disk; streptomycin (S)—10 mcg/disk; tetracycline (TE)—30 mcg/disk. Strains: L. fermentum N 2, L. fermentum N 4-5, W. confusa AG 2-6, L. curvatus KG 12-1, L. fermentum TC 3-11, L. delbrueckii subsp. allosunkii VG 1, L. delbrueckii subsp. lactis VG 2, L. delbrueckii subsp. lactis MK 13-1, W. confusa NN 1, L. rhamnosus NA 1-8, L. fermentum NA 2-2, and L. paracasei AV 2-1.
Table 2. Determined peptidase activity genes for the tested LAB strains.
Table 2. Determined peptidase activity genes for the tested LAB strains.
StrainpepApepCpepFpepQpepTpepV
L. fermentum N 2 + ++
L. fermentum N 4-5 + ++
W. confusa AG 2-6+ + ++
L. curvatus KG 12-1 + ++
L. fermentum TC 3-11 ++
L. delbrueckii subsp. allosunkii VG 1 +++++
L. delbrueckii subsp. lactis VG 2 + +
L. delbrueckii subsp. lactis MK 13-1 +++++
W. confusa NN 1+ + ++
L. rhamnosus NA 1-8 +
L. fermentum NA 2-2 + ++
L. paracasei AV 2-1 + ++
Table 3. Detection of adhesin genetic determinants.
Table 3. Detection of adhesin genetic determinants.
AdhesinStrain
KxYKxGKxW signal peptide domain-containing proteinL. fermentum N 2;
L. fermentum N 4-5;
W. confusa AG 2-6;
L. fermentum TC 3-11;
W. confusa NN 1;
L. rhamnosus NA 1-8;
L. fermentum NA 2-2
LPxTG cell wall anchor domain-containing proteinAll studied strains
MucBP domain-containing proteinL. fermentum N 2;
W. confusa AG 2-6;
L. curvatus KG 12-1;
L. fermentum TC 3-11;
W. confusa NN 1;
L. rhamnosus NA 1-8;
L. fermentum NA 2-2;
L. paracasei AV 2-1
SEC 10/PgrA surface exclusion domain-containing proteinL. fermentum N 2;
L. fermentum N 4-5;
L. fermentum TC 3-11;
L. delbrueckii subsp. allosunkii VG 1;
L. delbrueckii subsp. lactis VG 2;
L. delbrueckii subsp. lactis MK 13-1;
L. fermentum NA 2-2;
L. paracasei AV 2-1
YSIRK-type signal peptide-containing proteinL. fermentum N 2;
L. fermentum N 4-5;
L. fermentum TC 3-11;
L. delbrueckii subsp. allosunkii VG 1;
L. delbrueckii subsp. lactis VG 2;
L. delbrueckii subsp. lactis MK 13-1;
L. fermentum NA 2-2
Table 4. Detection of lectin genetic determinants.
Table 4. Detection of lectin genetic determinants.
LectinStrain
WxL domain-containing proteinW. confusa AG 2-6;
L. curvatus KG 12-1;
W. confusa NN 1;
L. rhamnosus NA 1-8;
L. paracasei AV 2-1
L-type lectin-domain-containing proteinW. confusa AG 2-6;
W. confusa NN 1;
L. paracasei AV 2-1
Table 5. Detected bacteriocin-producing mechanisms for the tested strains.
Table 5. Detected bacteriocin-producing mechanisms for the tested strains.
StrainDetected Bacteriocin-Encoding Genetic Determinants
NCBI BLASTxBAGEL4
L. fermentum N 2NDND
L. fermentum N 4-5NDND
W. confusa AG 2-6NDND
L. curvatus KG 12-1Blp family class II bacteriocin;Sakacin Q;
leucocin A/sakacin P family class II bacteriocinSakacin P
L. fermentum TC 3-11NDND
L. delbrueckii subsp. allosunkii VG 1helveticin J family class III bacteriocinHelveticin J
L. delbrueckii subsp. lactis VG 2helveticin J family class III bacteriocinHelveticin J
L. delbrueckii subsp. lactis MK 13-1helveticin J family class III bacteriocinND
W. confusa NN 1NDND
L. rhamnosus NA 1-8class IIb bacteriocin, lactobin A/cerein 7B familyCarnocin CP52;
LSEI 2386;
Enterocin Xβ
L. fermentum NA 2-2NDND
L. paracasei AV 2-1Blp family class II bacteriocinCarnocin CP52;
Enterolysin A;
LSEI 2386;
Enterocin Xβ
ND—genetic determinant not detected in the genomes.
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Atanasov, N.; Evstatieva, Y.; Nikolova, D. In Silico Detection of Genetic Determinants for the Acquired Antibiotic Resistance and Biologically Active Compounds of Lactic Acid Bacteria from the Human Oral Microbiome. Appl. Microbiol. 2025, 5, 60. https://doi.org/10.3390/applmicrobiol5030060

AMA Style

Atanasov N, Evstatieva Y, Nikolova D. In Silico Detection of Genetic Determinants for the Acquired Antibiotic Resistance and Biologically Active Compounds of Lactic Acid Bacteria from the Human Oral Microbiome. Applied Microbiology. 2025; 5(3):60. https://doi.org/10.3390/applmicrobiol5030060

Chicago/Turabian Style

Atanasov, Nikola, Yana Evstatieva, and Dilyana Nikolova. 2025. "In Silico Detection of Genetic Determinants for the Acquired Antibiotic Resistance and Biologically Active Compounds of Lactic Acid Bacteria from the Human Oral Microbiome" Applied Microbiology 5, no. 3: 60. https://doi.org/10.3390/applmicrobiol5030060

APA Style

Atanasov, N., Evstatieva, Y., & Nikolova, D. (2025). In Silico Detection of Genetic Determinants for the Acquired Antibiotic Resistance and Biologically Active Compounds of Lactic Acid Bacteria from the Human Oral Microbiome. Applied Microbiology, 5(3), 60. https://doi.org/10.3390/applmicrobiol5030060

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