https://orcid.org/0000-0002-1555-401X
Figures
Abstract
The increasing use of probiotics in livestock necessitates rigorous safety assessments to mitigate risks such as their inadvertent contribution to antimicrobial resistance (AMR) and horizontal gene transfer (HGT). This study employs whole-genome sequencing using both long-read (GridION, Oxford Nanopore Technologies) and short-read (Illumina, San Diego, CA, USA) platforms to assess the genomic and plasmidome profiles of five Thai strains of Pediococcus acidilactici, that previously have been evaluated for probiotic potential in livestock. Our comprehensive analysis identified genes encoding AMR, virulence factors, and probiotic-related genes. Notably, strains AF2519 and AF2019 harbored plasmid-borne tet(M) and erm(B) genes, with tet(M) embedded in a novel composite genetic arrangement flanked by mobile elements, suggesting historical recombination and altered mobility potential. Strains IAF6519, IAF5919, and P72N, free from plasmid-borne AMR genes, emerged as safer candidates, lacking virulence genes. Phenotypic tests revealed discrepancies with genomic data; for instance, AF2019 was resistant to clindamycin without detectable genes, and showed susceptibility to tetracycline despite the presence of tet(M). The absence of complete transfer machinery in AF2519 and AF2019 suggests a reduced HGT risk. These findings underscore the importance of integrating genomic and phenotypic approaches in probiotic safety evaluations. The presence of plasmid-borne AMR genes in certain strains advises caution in their use, impacting probiotic selection and regulatory compliance in agriculture. This research informs policies and best practices for safe probiotic deployment, ensuring both efficacy and safety.
Citation: Disastra Y, Wongsurawat T, Jenjaroenpun P, Hampson DJ, Kamwa R, Prapasarakul N (2025) Integrative genomic characterization of five Pediococcus acidilactici strains reveals differing probiotic safety profiles. PLoS One 20(9): e0332506. https://doi.org/10.1371/journal.pone.0332506
Editor: Míriam R. García, Spanish Council for Scientific Research (CSIC), SPAIN
Received: June 30, 2025; Accepted: September 1, 2025; Published: September 30, 2025
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: Sequence data supporting this study are available in the National Center for Biotechnology Information (NCBI) under BioProject accession number PRJNA1037750 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1037750)
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: ANI, Average Nucleotide Identity; BLAST, Basic Local Alignment Search Tool; CARD, Comprehensive Antibiotic Resistance Database; CDS, Coding Sequences; CLSI, Clinical and Laboratory Standards Institute; EFSA, European Food Safety Authority; EMBL, European Molecular Biology Laboratory; GECs, Genetic Exchange Communities; HCCA, α-cyano-4-hydroxycinnamic acid; HGT, Horizontal Gene Transfer; IBC, Institutional Biosafety Committee; iTOL, Interactive Tree of Life; KEGG, Kyoto Encyclopedia of Genes and Genomes; LAB, Lactic Acid Bacteria; MALDI-TOF MS, Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry; MGEs, Mobile Genetic Elements; MICs, Minimum Inhibitory Concentrations; MRS, deMan Rogosa and Sharpe; NCBI, National Center for Biotechnology Information; OriT, Origin of Transfer; RAST, Rapid Annotation using Subsystem Technology; rRNA, Ribosomal RNA; SNPs, Single Nucleotide Polymorphisms; VFDB, Virulence Factor Database; WGS, Whole Genome Sequencing; μl, Microliter
Introduction
Probiotics, defined by the Food and Agriculture Organization of the United Nations and the World Health Organization [1] as live microorganisms that confer health benefits when administered in adequate amounts, are increasingly sought for inclusion in livestock feed due to their benefits in gut health maintenance, immune modulation, and prevention of gastrointestinal disorders [2,3]. Among the diverse groups of lactic acid bacteria (LAB), Pediococcus acidilactici is notable for its robust probiotic properties, including antimicrobial activity and enhancement of gut health, which are crucial for improving livestock performance and health [4,5]. Despite these attributes, detailed genomic characterization of P. acidilactici strains is essential to fully assess their safety and efficacy.
Traditional phenotypic evaluations of probiotic strains often fail to capture genetic diversity and potential safety concerns such as their antimicrobial resistance profiles and presence of mobile genetic elements (MGEs) [6,7]. Whole genome sequencing provides a comprehensive approach to uncover these genetic traits, thereby supporting safer and more effective probiotic applications [8]. The European Food Safety Authority (EFSA) also underscores the importance of genetic investigations to identify antibiotic-resistant genes, especially those associated with MGEs, to mitigate health risks and prevent the spread of resistance [9,10].
This study focuses on five Thai strains of P. acidilactici—IAF6519, IAF5919, AF2519, AF2019 and P72N that were isolated from chicken and pig feces [11]. These strains have been shortlisted as potential probiotics due to their resilience under gastrointestinal conditions and demonstrated antagonistic effects against enteric pathogens including Escherichia coli and Salmonella [12]. By employing whole genomic sequencing (WGS), the study aimed to provide a comprehensive characterization of these strains, enhancing understanding of their functional properties and safety profiles, with broader implications for animal nutrition and functional food development.
Materials and methods
Bacterial strains and growth conditions
This study utilized five Thai strains of LAB, specifically P. acidilactici, obtained from the culture collection at the Faculty of Veterinary Science, Chulalongkorn University, Thailand. The strains included IAF6519, IAF5919, AF2519, AF2019 and P72N, all isolated from fecal samples of chickens or pigs. Strains IAF6519, IAF5919, AF2519, and AF2019 were sourced from various types of chickens, including broilers, layers, and native Thai chickens—across both commercial and household farms [11,13]. Strain P72N was isolated from a pig fecal sample collected from a farm that did not administer antibiotics. All strains were preserved in deMan Rogosa and Sharpe (MRS) broth supplemented with 20% glycerol and stored at −20°C. Prior to experimental use, the strains were cultured in MRS broth at 37°C for 24 hours. Following this, the cultures were plated on MRS agar and incubated for an additional 48 hours. All procedures adhered to institutional guidelines, with the use of LAB strains approved by the Chulalongkorn University Institutional Biosafety Committee (IBC) (Approval Number: 2,331,008)
Species confirmation of P. acidilactici strains
The species identity of the P. acidilactici strains was confirmed using two methods: Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) and the VITEK 2 Compact system. For MALDI-TOF MS analysis, colonies from MRS agar were placed on a target plate and overlaid with a solution of formic acid and α-cyano-4-hydroxycinnamic acid (HCCA). The analysis was conducted using MALDI Biotyper software (Bruker Daltonics), with species identification confidence assessed by score values: scores >2.3 indicated high confidence, 2.3–2.0 suggested high probability of correct species identification, and 2.0–1.7 indicated genus identification [14]. Following MALDI-TOF MS analysis, the VITEK 2 Compact system was employed for further confirmation. Colonies were suspended in 0.45% NaCl to achieve a McFarland standard of 0.50–0.63. The samples were then processed using VITEK GP ID and CBC cassettes at 35°C for six hours [15].
Antibiotic susceptibility testing of P. acidilactici strains
Antibiotic susceptibility of the strains was evaluated using the broth microdilution method following the guidelines of the Clinical and Laboratory Standards Institute (CLSI). The antibiotics tested included: ampicillin, vancomycin, gentamicin, kanamycin, streptomycin, erythromycin, clindamycin, tetracycline, and chloramphenicol. The test was performed using THAPH and THA1CLF Sensititre plates (Thermo Fisher Scientific), and the minimum inhibitory concentrations (MICs) were determined using the Sensititre Vizion Digital MIC Viewing System. Results were compared to microbiological cut-off values established by the EFSA to classify strains as either resistant (R) or susceptible (S). To ensure accuracy, two quality control strains, Enterococcus faecalis ATCC 29,212 and Escherichia coli ATCC 25,922 were included in each assay to validate MIC readings [16].
Hemolytic activity testing of P. acidilactici strains
The hemolytic activity of the LAB strains was assessed on tryptic soy agar (TSA) plates supplemented with 5% (v/v) sheep blood. After 48 hours of incubation at 37°C, the plates were examined for zones of hemolysis around bacterial colonies [17]. Three types of hemolysis were considered in this study. Beta-hemolysis (clear zone indicating complete red blood cell lysis), alpha-hemolysis (greenish zone indicating partial lysis), and gamma-hemolysis (no clear or greenish zone indicating no hemolytic activity) [18].
Whole-genome sequencing and analysis of P. acidilactici strains
DNA from the five Thai strains was extracted using the ZymoBIOMICS DNA Miniprep Kit [19]. Quality and quantity were assessed with a NanoDrop spectrophotometer and Qubit fluorometer (Life Technologies, Carlsbad, CA, USA) [20]. Following extraction, sequencing was performed using long-read (GridION, Oxford Nanopore Technologies) and short-read (Illumina , San Diego, CA, USA) technologies.
Raw nanopore reads were processed with Nanoplot v1.33.0 [21], and filtered FASTQ files were assembled using Flye v2.9.1-b1780 [22]. The assembled genomes were polished with NextPolish [23] and plasmid assembly was conducted using Unicycler [24]. Genome quality was assessed with QUAST v5.0.2 and CheckM v1.1.9 [25], and plasmid typing was performed using MOB-suite v3.0.3 [26,27]. The bacterial chromosome was identified by aligning against the GTDB-Tk database (R207_v2), and functional genes were annotated using Prokka v1.14.6 [28]. The genome was visualized with PyCircos and Proksee [29].
All analyses were conducted at the Siriraj Long-Read Lab (Si-LoL), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand. Sequence data supporting this study are available in the National Center for Biotechnology Information (NCBI) under BioProject accession number PRJNA1037750 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1037750) (S1 Table).
Phylogenetic analysis of P. acidilactici strains
Identification of the Thai LAB strains was performed using Average Nucleotide Identity (ANI) analysis with GTDB-Tk v2.1.0 [30,31,32]. For orthologous ANI analysis, the OrthoANI Tool (OAT) from CJ Bioscience on the EzBioCloud server was utilized [33]. Species-level predictions were made using SpeciesFinder v.2.0 based on genomic data [34]. To elucidate evolutionary relationships among the strains, a maximum-likelihood phylogenetic tree was constructed using core single nucleotide polymorphisms (SNPs) with RAxML [35], incorporating genomic sequences from the five Thai strains and 15 reference strains of P. acidilactici obtained from the NCBI database (S1 Table). The resulting phylogenetic tree was visualized and analyzed using the Interactive Tree of Life (iTOL) tool from the European Molecular Biology Laboratory (EMBL) [36]. Additionally, protein-encoding sequences were analyzed to identify the pan- and core-genomes of the five Thai P. acidilactici strains and P. acidilactici HN9 (from traditional Thai-style fermented beef Nhang). This was accomplished using the Orthovenn web platform (https://orthovenn3.bioinfotoolkits.net) with default parameters [37].
Analysis of antimicrobial resistance genes and virulence factors in P. acidilactici
An analysis of AMR genes and virulence factors was conducted on the genomes of the five Thai P. acidilactici strains using several publicly available databases. The Resistance Gene Identifier (RGI, v6.0.3) from the Comprehensive Antibiotic Resistance Database (CARD, v3.2.8), available at https://card.mcmaster.ca/analyze/rgi [38], ResFinder (v4.6) available at http://genepi.food.dtu.dk/resfinder [39], and the BlastKOALA tool from the KEGG database were employed for AMR gene identification, specifically inspected under “Brite ko01504: Antimicrobial resistance genes” [40]. For virulence factors, the Virulence Factor Database (VFDB) was utilized, accessible at http://www.mgc.ac.cn/cgi-bin/VFs/v5/main.cgi [41]. The analysis applied stringent criteria, requiring coverage and identity greater than 80% and an E-value of less than 1e-10 to ensure reliable results. This comprehensive approach enabled a robust evaluation of the genetic determinants associated with AMR and virulence, providing insights into potential resistance mechanisms present in the genomes.
Secondary metabolites analysis in P. acidilactici
The identification and analysis of secondary metabolites in the Thai P. acidilactici strains utilized AntiSMASH v6.0, allowing comprehensive detection of biosynthetic gene clusters [42], and BAGEL4 for its targeted prediction of bacteriocin genes [43]. This combination of tools provided a dual approach to explore not only the broad spectrum of potential secondary metabolites but also specific antimicrobial compounds critical for probiotic efficacy.
Genome stability assessment in P. acidilactici
The stability of the genomes of the five Thai P. acidilactici strains was evaluated using several bioinformatics tools. CRISPRCasFinder v1.1.2 was employed to predict CRISPR and cas genes associated with bacterial immunity [44], while PHASTER was utilized to identify prophage sequences [45], PlasmidFinder to detect plasmids ([46]), OriTFinder to search for origin of transfer (OriT) regions (https://bioinfo-mml.sjtu.edu.cn/oriTfinder/) [47], and IslandViewer 4 (incorporating SIGI-HMM, IslandPath-DIMOB, and IslandPick algorithms) to identify genomic islands [48]. This comprehensive approach provided insights into the genetic stability and potential for horizontal gene transfer (HGT) in the Thai LAB strains.
Analysis of probiotic functional genes and metabolic pathways in P. acidilactici
Probiotic functional genes and metabolic pathways in Thai P. acidilactici strains were meticulously analyzed by mining annotation files for relevant keywords and investigating functional subsystems via the RAST (Rapid Annotation using Subsystem Technology) server, which facilitates a nuanced understanding of bacterial functionalities. BLASTp comparisons with reference protein sequences further refined the specificity of gene identification. Metabolic pathways were then elucidated using the KEGG (Kyoto Encyclopedia of Genes and Genomes) Mapper Reconstruct Pathway tool, with BlastKOALA assigning KEGG identifiers (K numbers) to ensure accurate pathway mapping [49,50].
Results
Species confirmation of P. acidilactici strains
Species confirmation of P. acidilactici strains was achieved using MALDI-TOF analysis, with all five Thai LAB strains scoring between 2.10 and 2.36, indicating reliable species-level identification (S2 Table). In contrast, the VITEK 2 Compact system demonstrated lower discriminatory power, although it accurately identified strain AF2019 as P. acidilactici with a high confidence score of 94%.
Antimicrobial susceptibility testing of P. acidilactici strains
Antimicrobial susceptibility testing of the five Thai P. acidilactici strains was conducted according to EFSA guidelines. The MICs obtained indicated that strains IAF6519, IAF5919, and P72N were susceptible to all tested antibiotics, except for vancomycin, to which all strains exhibited intrinsic resistance. In contrast, strains AF2519 and AF2019 showed resistance to erythromycin and clindamycin, with AF2519 additionally being resistant to tetracycline. The detailed MIC results, categorized by EFSA’s predefined cut-off values, are presented in Table 1.
Hemolytic activity of P. acidilactici strains
The hemolytic activity of the five Thai P. acidilactici strains was assessed to gain more insight about their potential safety as probiotics. All strains exhibited alpha-hemolysis, which involves partial disruption of red blood cells without complete lysis, as depicted in S1 Fig.
Genome properties of P. acidilactici strains
WGS of the five Thai P. acidilactici strains revealed genome sizes ranging from 1.81 to 2.19 Mb, with a consistent G + C content between 41.9% and 42.2%, as shown in Table 2. The genomic assemblies achieved a completion rate of 99.4% with no detectable contamination, underscoring the reliability and accuracy of our sequencing results. The number of coding sequences (CDS) varied across the strains, reflecting diversity in their genomic content. Notably, strains IAF5919, AF2519 and AF2019 harbored plasmids, which are known to potentially enhance probiotic capabilities. However, the presence of plasmids in these strains also introduces the possibility of HGT. In contrast, strains IAF6519 and P72N were found to lack plasmids. Detailed circular genome maps, illustrating key genomic features, are provided in Fig 1.
The first circle presents CRISPR repeats in black. The second circle depicts the GC skew (G + C/G − C), with values >0 in green and values <0 in purple. The third circle denotes rRNA, tRNA, and the sites of CDS.
Strain identification and phylogenetic tree analysis of P. acidilactici strains
Species-level identification based on OrthoANI analysis confirmed that all five Thai isolates belong to P. acidilactici, showing >97% pairwise identity with the reference strain PMC65 (Fig 2). The high genomic similarity among strains, particularly between IAF6519 and IAF5919—was further supported by core SNP-based maximum likelihood phylogeny (Fig 3), reflecting close evolutionary relationships consistent with their shared origin from chicken fecal samples. A broader comparison including additional P. acidilactici and related species is provided in S2 Fig. A total of 2,715 orthologous clusters were identified across six P. acidilactici genomes, including five Thai isolates and the reference strain HN9 (Fig 4). Of these, 1,546 clusters were conserved across all strains. The number of strain-specific orthologous clusters varied among the genomes. HN9 contained 23 strain-specific clusters, followed by AF2019 with 11, AF2519 with 9, and P72N with 1. No strain-specific clusters were detected in IAF5919 or IAF6519. A complete list of strain-specific clusters and their corresponding gene annotations is provided in S3 Table.
The purple boxes display the values of shared or single orthologous clusters.
Identification of antimicrobial resistance genes of P. acidilactici strains
WGS revealed the presence and distribution of AMR genes across the five Thai P. acidilactici strains. The CARD analysis indicated that strains IAF6519, IAF5919 and P72N lacked notable AMR genes, suggesting a low risk profile for these strains, as shown in Table 3. In contrast, ResFinder results showed strain AF2519 harbored erm(B) and lnu(A) on unclassified DNA elements, with tet(M) located on plasmid pAF25191. Strain AF2019 exhibited a broader array of AMR genes, including erm(B), NarA, and NarB on plasmid pAF20193, along with tet(M) on plasmid pAF20191 (S4 Table). Additional KEGG analysis identified chromosome-associated AMR-related genes such as dltA, dltB, dltC, dltD, penP, and lsa in strains IAF6519 and IAF5919, which may impact their overall resistance profiles. Strains AF2519 and AF2019 displayed a more diverse range of resistance genes across multiple plasmids, suggesting enhanced adaptability and resistance capabilities. Detailed gene locations and summaries are provided in S3 Fig.
Identification of genes encoding virulence factors in the P. acidilactici strains
Genomic analysis of the five Thai P. acidilactici strains revealed the presence of several genes associated with core cellular functions and virulence, as detailed in Fig 5. Common genes across all strains included endopeptidase Clp ATP-binding chain C (clpC), enolase, elongation factor, glyceraldehyde-3-phosphate dehydrogenase, and chaperonin GroEL. Notably, the ATP-dependent Clp protease proteolytic subunit gene (clpP) was absent in strain AF2519, while the gene encoding dTDP-glucose-4,6-dehydratase (rmlB), involved in dTDP-rhamnose biosynthesis, was uniquely present in AF2019. Major virulence genes such as gelatinase (gelE), hyaluronidase (hyl), and enterococcal surface protein (esp) were absent in all strains. Additionally, the Enterolysin A biosynthetic gene cluster, linked to bacteriocin production and potential antimicrobial properties, was detected in all strains except P72N (S5 Table).
Blue indicates the presence of the virulence factor genes, while red indicates their absence.
Genome stability assessment of P. acidilactici strains
CRISPR-Cas systems in P. acidilactici strains.
All five Thai strains were found to contain a Type IIA CRISPR-Cas system, as identified using CRISPRCasFinder v1.1.2 (S6 Table). In strain IAF6519, the cas9_TypeII gene was located on the forward strand, and in strain P72N, the cas9_TypeII and csn2_TypeIIA genes were located on the reverse strand.
Prophage sequences of P. acidilactici strains.
Prophage regions were profiled using PHASTER. Strains IAF6519 and IAF5919 each contained one intact chromosomal prophage region (S7 Table). Strain AF2519 had two intact and three incomplete prophage regions, plus two plasmid regions. Strain AF2019 contained four intact chromosomal prophage regions and one plasmid region of questionable completeness. Strain P72N had one intact chromosomal prophage region.
Insertion sequences and composite transposons of P. acidilactici strains.
Insertion sequences and composite transposons were identified in all strains (S8 Table). IAF6519 contained two ISLpl1 insertion sequences and one cn_4153_ISLpl1 composite transposon on the chromosome. IAF5919 had two ISLpl1 sequences and one cn_4153_ISLpl1 composite transposon on the chromosome, plus one ISLhe30 and one ISS1N on a plasmid. AF2519 featured one ISLhe30 and one ISLpl1 on a plasmid, plus one ISS1N and two composite transposons (cn_18158_ISLpl1 and cn_10454_ISS1N). AF2019 exhibited two ISLpl1 sequences and one cn_7438_ISLpl1 composite transposon on the chromosome, plus one ISLhe30 and two ISLpl1 sequences on plasmids. P72N had two ISLpl1 insertion sequences and one cn_4466_ISLpl1 composite transposon on the chromosome.
Plasmid and genomic island analysis
Genomic analysis revealed multiple plasmids within the P. acidilactici strains, each carrying diverse CDS. Notably, strain AF2519 harbored three distinct plasmids: plasmid pAF25191, which included genes associated with nutrient transport and stress resistance, such as tet(M), oppB, and dppE; plasmid pAF25192, carrying genes potentially involved in secondary metabolite production and antibiotic resistance, including cypC and mccF; and an unclassified DNA element containing resistance genes such as erm(B). The plasmid in strain IAF5919, pIAF5919, contained genes linked to carbohydrate metabolism and stress adaptation, as detailed in Fig 6. OriTfinder analysis indicated that all strains possessed a single chromosomal relaxase gene but lacked crucial conjugation elements (T4CP and oriT) on the plasmids of strains AF2519, AF2019, and IAF5919, suggesting a limited potential for HGT (S9 Table). Additionally, IslandViewer4 analysis identified four genomic islands in strain AF2019, all located on the plasmid pAF20191. These islands feature genes such as tet(M) and insertion sequences, indicating genomic plasticity (S10 Table).
Blue indicates the presence of the virulence factor genes, while red indicates their absence.
Identification and analysis of probiotic functional genes and metabolic pathways
RAST (Rapid Annotation using Subsystem Technology) analysis of the five Thai P. acidilactici strains revealed diverse gene distributions across various subsystems. Notably, the ‘Carbohydrates’ subsystem was the most prominent, with strains AF2019 and AF2519 exhibiting the highest gene counts, suggesting robust capabilities in carbohydrate metabolism, as detailed in S11 Table. These strains also showed elevated gene counts in the ‘Phages, Prophages, Transposable Elements, Plasmids’ subsystem, indicative of significant genomic plasticity.
KEGG orthology analysis identified strain-specific variations in metabolic pathways. In the ‘Carbohydrate Metabolism’ category, strain AF2519 displayed the highest gene count. Additionally, the ‘Protein Families: Genetic Information Processing’ category revealed notable variations among the strains, with AF2519 again leading in gene counts, as shown in S12 Table. This comprehensive gene profiling highlighted the metabolic diversity and potential adaptability of these strains to various environmental conditions.
Probiotic-related genes of P. acidilactici strains
Genomic analysis identified probiotic-related genes grouped into seven functional categories: GIT survival and stress response, heat stress, acid stress, bile tolerance, adhesion, antioxidant defense, and immunomodulation (Table 4). All five Thai P. acidilactici strains were found to possess representative genes in all seven categories. These include ponA, pbpX (GIT survival); grpE, groS (heat stress); atpE, nhaC (acid stress); ppaC, cfa (bile tolerance); tuf, eno (adhesion); katA, trxA (antioxidant defense); and dllA, dllC (immunomodulation). A comprehensive list of probiotic-related genes identified across all strains is provided in S13 Table
Discussion
Probiotics are increasingly explored as safe alternatives to antibiotics for some applications in livestock, but comprehensive safety assessments remain critical, particularly regarding AMR. In this study, WGS and functional profiling were used to assess five P. acidilactici strains isolated from poultry and swine, focusing on both probiotic attributes and genomic safety indicators.
Phenotypic antimicrobial susceptibility testing (AST) revealed that most strains were susceptible to the antibiotics tested, except for consistent resistance to vancomycin across all isolates. This pattern is consistent with previous findings that vancomycin resistance in LAB, including P. acidilactici, is an intrinsic trait due to the presence of D-Ala-D-Lac termini in peptidoglycan precursors [51]. In contrast, two strains (AF2519 and AF2019) exhibited elevated MIC against erythromycin, clindamycin, and tetracycline, suggesting possible acquired resistance.
WGS of P. acidilactici AF2519 and AF2019 revealed that both strains harbor plasmids encoding classical AMR genes specifically tet(M), erm(B), and, in the case of AF2519, lnu(A). These findings are striking because most previously characterized P. acidilactici strains have shown either intrinsic or chromosomal ARGs, with plasmid-mediated resistance rarely reported [52,53]. In contrast, our isolates possess composite resistance loci located on plasmids, suggesting recent acquisition and higher mobility potential. This challenges the prevailing view of P. acidilactici as genetically stable and free of transferable ARGs.
Although the AMRG-carrying plasmids lacked canonical conjugation machinery (e.g., oriT, T4CP, T4SS), in trans mobilization cannot be ruled out. Interestingly, AF2019 harbored an additional plasmid (pAF20192) that contains a complete conjugation machinery, including relaxase, T4CP, and T4SS components, yet notably lacked any ARGs. This configuration suggests that pAF20192 could serve as a helper plasmid, facilitating mobilization of resistance-carrying elements via trans mechanisms under gut-like conditions [54]. Similar instances of tet(M) and erm(B) transfer from Lactobacillus to Enterococcus under gut conditions previously have been documented [55].
Furthermore, AF2019 was the only strain found to contain four genomic islands, all located on plasmid pAF20191, one of which co-localized tet(M) with multiple insertion sequences. Genomic islands are recognized hotspots for horizontal gene acquisition and dissemination, especially when harboring ARGs flanked by mobile elements. The fact that these islands reside on a plasmid, an inherently mobile genetic element, further increases the risk of horizontal transfer. This genomic configuration mirrors composite transposons described in E. coli and Streptococcus pyogenes [56,57], suggesting that these loci may represent evolutionary remnants of past mobilization events and retain the potential for future dissemination.
From a regulatory perspective, plasmid localization of tet(M) and erm(B) elevates concern. While chromosomal tet(M) has been reported in strain FAM 18,375 [58], the plasmid-borne configuration in our strains implies greater potential for dissemination. In line with EFSA guidance, strains harboring transferable ARGs, regardless of phenotypic resistance, should be excluded from probiotic use [59]. These findings reinforce the importance of incorporating mobility context into AMR screening protocols for probiotic candidates.
AF2019 exhibited notable genotype–phenotype discrepancies: these included susceptibility to tetracycline despite the presence of plasmid-borne tet(M), and resistance to clindamycin without detectable resistance genes. Such mismatches, reported in LAB and other Gram-positive bacteria, may result from several molecular mechanisms [60–62]. For tetracycline susceptibility, possible explanations include: (i) promoter inactivity or mutations in upstream regulatory regions reducing transcription efficiency [63,64], (ii) structural mutations in the tet(M) coding sequence (e.g., frameshift, missense, or nonsense mutations) impairing ribosomal protection [63], and (iii) inducible expression or gene silencing under laboratory conditions lacking environmental cues necessary for activation [64]. For clindamycin resistance without erm or lnu genes, potential mechanisms include: (i) chromosomal point mutations in 23S rRNA domain V or ribosomal proteins L4/L22 altering antibiotic binding [65], (ii) overexpression of multidrug efflux pumps such as MFS transporters capable of extruding lincosamides [66], and (iii) novel or uncharacterized resistance determinants not represented in current databases, such as the cfr gene, which methylates A2503 of 23S rRNA and confers cross-resistance to lincosamides and other antibiotic classes [65]. These possibilities underscore that phenotypic assays alone may underestimate hidden AMR risks, while purely genomic screens may overlook cryptic or novel resistance mechanisms, reinforcing the need for integrated phenotypic, genomic, and transcriptomic approaches in probiotic safety evaluation.
Beyond identifying individual AMR genes, the structural organization of resistance loci in AF2519 and AF2019 provides insight into their evolutionary and mobilization potential. In contrast to previous reports of tet(M) in chromosomal or isolated contexts [67], our strains harbor a plasmid-borne cluster of tet(M), erm(B), and lnu(A) co-localized with insertion sequences and recombinases, suggesting a mosaic scaffold shaped by historical recombination. Even without a complete conjugation system, such architecture may retain latent mobility under ecological pressure. Collectively, these findings challenge the assumption that resistance genes in probiotics are static or benign and highlight the value of high-resolution structural analysis in probiotic risk evaluation.
The genomes of the five Thai strains encoded a comprehensive set of stress-tolerance and host-interaction functions. These included high–molecular–weight penicillin-binding proteins (PBP1A/ponA, PBP2X/pbpX) that support peptidoglycan synthesis and cell-wall integrity under gut stress [68]. Classic heat-shock chaperones such as grpE and groS also were identified, consistent with LAB where GroESL systems enhance thermal survival during feed processing [69]. Acid tolerance genes, including atpF and nhaC, mediate pH homeostasis via proton extrusion [70]. For bile adaptation, ppaC and cfa were present; notably cfa (cyclopropane fatty acid synthase) modifies membrane lipids and has been linked to stress resilience in Lactococcus and Bacillus [71].
Surface-adhesion factors tuf (EF-Tu) and eno (enolase) were also detected, consistent with their roles as “moonlighting” adhesins in mucosal binding [72,73]. Oxidative stress defenses include trxA and katA; while trxA is ubiquitous in LAB [74], katA is rare in Pediococcus and suggests acquisition of catalase activity [75]. The presence of a complete dlt operon (dltA, dltC) indicates D-alanylation of teichoic acids, a modification known to enhance resistance to host antimicrobial peptides [76]. Notably, katA (heme-dependent catalase) and cfa (cyclopropane fatty acid synthase) have not been previously reported in P. acidilactici. The rarity of katA in lactic acid bacteria is linked to their fermentative metabolism and lack of a respiratory chain, suggesting its presence in our strains may have resulted from horizontal acquisition from catalase-positive bacteria in the gut or feed environment [77,78]. Catalase activity decomposes hydrogen peroxide, enhancing oxidative stress tolerance, improving survival during aerobic storage, and supporting viability in the gastrointestinal tract [79,80]. The cfa gene modifies membrane phospholipids to produce cyclopropane fatty acids, increasing membrane rigidity and hydrophobicity, which improves acid and bile tolerance, stability during feed processing, and persistence in intestinal environments [81,82]. The co-occurrence of katA and cfa in these strains may therefore represent a unique adaptive genomic signature, enhancing resilience during gut transit and feed storage, traits that directly contribute to their suitability as probiotic candidates for use in poultry and swine production [83].
The findings of this study present a refined view of P. acidilactici strains as probiotic candidates. While two strains carried plasmid-borne resistance genes, all lacked virulence markers and retained key probiotic traits. Although all five strains exhibited alpha-hemolysis on blood agar, this is a common and non-pathogenic characteristic among lactic acid bacteria, including P. acidilactici, and does not imply virulence [84]. Alpha-hemolysis, characterized by partial lysis of red blood cells, is frequently observed in probiotic LAB such as Lacticaseibacillus rhamnosus and Lactococcus lactis, and is generally considered safe in food and probiotic applications [85,86]. These findings underscore the need for strain-level evaluation grounded in genomic context rather than binary classification. The presence of rare genes such as katA and cfa further suggests host-adaptive potential. As probiotics gain prominence in livestock systems, whole-genome analysis should serve as a cornerstone for precision selection and responsible application.
Conclusions
This study demonstrates how whole-genome sequencing, when paired with targeted functional analysis, provides a high-resolution view of probiotic strain safety and performance [60,62,50,61]. Among the five P. acidilactici strains analyzed, three exhibited uncomplicated genomic backgrounds with strong probiotic features, while two harbored plasmid-borne ARGs with limited mobilization capacity. Whole-genome data also uncovered rare but functionally relevant genes, such as katA and cfa that may enhance oxidative and bile stress resilience, respectively. These findings reinforce the limitations of phenotypic-only approaches and affirm the importance of genomic context in evaluating both safety and functionality. As probiotics gain increasing relevance in livestock systems, this study positions WGS as a foundational tool for evidence-based strain selection, ecological fit, and regulatory assurance.
Supporting information
S1 Table. P. acidilactici strains used for phylogenetic analysis.
* The genomic sequences of the 15 control strains were obtained from the NCBI database. The accession numbers correspond to the genomes of the control strains.
https://doi.org/10.1371/journal.pone.0332506.s001
(XLSX)
S2 Table. MALDI-TOF and VITEK confirmation of P. acidilactici species identity.
https://doi.org/10.1371/journal.pone.0332506.s002
(XLSX)
S1 Fig. Hemolytic Activity Test of five Thai P. acidilactici strains.
1: IAF5919; 2: IAF6519; 3: AF2519; 4: AF2019; 5: P72N; 6: Bacillus sp.
https://doi.org/10.1371/journal.pone.0332506.s003
(TIF)
S3 Table. Unique clusters in strains AF2019, AF2519, and P72N from OrthoVenn3 analysis with HN9 as a reference.
https://doi.org/10.1371/journal.pone.0332506.s004
(XLSX)
S4 Table. Antimicrobial resistance genes identified in the genome sequences of the five Thai.
P. acidilactici strains by using ResFinder.
https://doi.org/10.1371/journal.pone.0332506.s005
(XLSX)
S2 Fig. OrthoANI heatmap showing pairwise average nucleotide identity (ANI) values among the five Thai P. acidilactici strains and additional reference strains from diverse Pediococcus species.
All five Thai strains shared >97% ANI with the reference P. acidilactici strain PMC65, confirming species identity. In contrast, ANI values between these and strains such as WCF51, L25F, and AF2319 were substantially lower (<70%), supporting their taxonomic distinction and reaffirming the correct species-level classification.
https://doi.org/10.1371/journal.pone.0332506.s006
(TIF)
S3 Fig. Antimicrobial resistance genes identified in the genome sequences of the five Thai P. acidilactici strains by using the KEGG database.
Blue indicates the presence of the virulence factor genes, while red indicates their absence.
https://doi.org/10.1371/journal.pone.0332506.s007
(TIF)
S5 Table. Identification and analysis of the Enterolysin A gene in the five Thai P. acidilactici. Strains.
https://doi.org/10.1371/journal.pone.0332506.s008
(XLSX)
S6 Table. CRISPR-Cas loci identified in the five Thai P. acidilactici strains.
https://doi.org/10.1371/journal.pone.0332506.s009
(XLSX)
S7 Table. Prophage regions predicted in the five Thai P. acidilactici strains.
https://doi.org/10.1371/journal.pone.0332506.s010
(XLSX)
S8 Table. Insertion sequences and composite transposons in the five Thai P. acidilactici strains.
https://doi.org/10.1371/journal.pone.0332506.s011
(XLSX)
S9 Table. Results of the OriTfinder analysis of plasmids in the five Thai P. acidilactici strains.
https://doi.org/10.1371/journal.pone.0332506.s012
(XLSX)
S10 Table. Predicted genomic islands, their sizes, and the methods used to identify them on plasmid pAF20191 of Pediococcus acidilactici strain AF2019.
https://doi.org/10.1371/journal.pone.0332506.s013
(XLSX)
S11 Table. RAST annotation of functional subsystems in the five Thai P. acidilactici strains.
https://doi.org/10.1371/journal.pone.0332506.s014
(XLSX)
S12 Table. KEGG pathway classification of annotated genes in the five Thai P. acidilactici. Strains.
https://doi.org/10.1371/journal.pone.0332506.s015
(XLSX)
S13 Table. Full probiotic-related gene list across 12 categories in the five Thai P. acidilactici. Strains.
https://doi.org/10.1371/journal.pone.0332506.s016
(XLSX)
Acknowledgments
We extend our gratitude to the staff of the Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University for their technical support. We also thank the Ratchadaphisek Somphot Scholarship, Chulalongkorn University, for supporting the presentation of our work at an international academic conference.
References
- 1.
FAO/WHO. Health and nutritional properties of probiotics in food including powder milk with live lactic acid bacteria. 2001. http://www.who.int/foodsafety/publications/fs_management/en/probiotics.pdf
- 2. Chakraverty R, Sasmal S. Probiotics and its Impact on Antibiotic-associated Diarrhea (AAD) and Clostridum difficile Infections (CDI) in Adult and Pediatric Patients: A Review. JPPCM. 2021;7(3):46–8.
- 3. Gul S, Durante-Mangoni E. Unraveling the Puzzle: Health Benefits of Probiotics-A Comprehensive Review. J Clin Med. 2024;13(5):1436. pmid:38592298
- 4. Bhagat D, Raina N, Kumar A, Katoch M, Khajuria Y, Slathia PS, et al. Probiotic properties of a phytase producing Pediococcus acidilactici strain SMVDUDB2 isolated from traditional fermented cheese product, Kalarei. Sci Rep. 2020;10(1):1926. pmid:32024895
- 5. Song Y-R, Lee C-M, Lee S-H, Baik S-H. Evaluation of Probiotic Properties of Pediococcus acidilactici M76 Producing Functional Exopolysaccharides and Its Lactic Acid Fermentation of Black Raspberry Extract. Microorganisms. 2021;9(7):1364. pmid:34201704
- 6. Bang WY, Ban O-H, Lee BS, Oh S, Park C, Park M-K, et al. Genomic-, phenotypic-, and toxicity-based safety assessment and probiotic potency of Bacillus coagulans IDCC 1201 isolated from green malt. J Ind Microbiol Biotechnol. 2021;48(5–6):kuab026. pmid:33904924
- 7. Shokryazdan P, Sieo CC, Kalavathy R, Liang JB, Alitheen NB, Faseleh Jahromi M, et al. Probiotic potential of Lactobacillus strains with antimicrobial activity against some human pathogenic strains. Biomed Res Int. 2014;2014:927268. pmid:25105147
- 8. Mileriene J, Aksomaitiene J, Kondrotiene K, Asledottir T, Vegarud GE, Serniene L, et al. Whole-Genome Sequence of Lactococcus lactis Subsp. lactis LL16 Confirms Safety, Probiotic Potential, and Reveals Functional Traits. Microorganisms. 2023;11(4):1034. pmid:37110457
- 9. Bifidobacterium breve PRL2020: Antibiotic-Resistant Profile and Genomic Detection of Antibiotic Resistance Determinants. Microorganisms. 2023;11(7):1649. pmid:37512822
- 10. Handa S, Sharma N. In vitro study of probiotic properties of Lactobacillus plantarum F22 isolated from chhang - A traditional fermented beverage of Himachal Pradesh, India. J Genet Eng Biotechnol. 2016;14(1):91–7. pmid:30647602
- 11. Khurajog B, Disastra Y, Lawwyne LD, Sirichokchatchawan W, Niyomtham W, Yindee J, et al. Selection and evaluation of lactic acid bacteria from chicken feces in Thailand as potential probiotics. PeerJ. 2023;11:e16637. pmid:38107571
- 12. Pupa P, Apiwatsiri P, Sirichokchatchawan W, Pirarat N, Nedumpun T, Hampson DJ, et al. Microencapsulated probiotic Lactiplantibacillus plantarum and/or Pediococcus acidilactici strains ameliorate diarrhoea in piglets challenged with enterotoxigenic Escherichia coli. Sci Rep. 2022;12(1):7210. pmid:35505092
- 13. Pupa P, Apiwatsiri P, Sirichokchatchawan W, Pirarat N, Maison T, Koontanatechanon A, et al. Use of Lactobacillus plantarum (strains 22F and 25F) and Pediococcus acidilactici (strain 72N) as replacements for antibiotic-growth promotants in pigs. Sci Rep. 2021;11(1):12028. pmid:34103574
- 14. Bungenstock L, Abdulmawjood A, Reich F. Evaluation of antibacterial properties of lactic acid bacteria from traditionally and industrially produced fermented sausages from Germany. PLoS One. 2020;15(3):e0230345. pmid:32160253
- 15. Lokapirnasari WP, Sahidu AM, Soepranianondo K, Supriyanto A, Yulianto AB, Al Arif A. Potency of lactic acid bacteria isolated from balinese bovine (Bos sondaicus) intestinal waste from slaughterhouse to improve nutrient content of wheat pollard as animal feedstuff by fermentation process. Vet World. 2018;11(8):1127–34. pmid:30250373
- 16. EFSA. Guidance on the characterisation of microorganisms used as feed additives or as production organisms. EFSA Journal. 2018;3.
- 17. Yasmin I, Saeed M, Khan WA, Khaliq A, Chughtai MFJ, Iqbal R, et al. In vitro Probiotic Potential and Safety Evaluation (Hemolytic, Cytotoxic Activity) of Bifidobacterium Strains Isolated from Raw Camel Milk. Microorganisms. 2020;8(3):354. pmid:32131456
- 18. Ahire JJ, Jakkamsetty C, Kashikar MS, Lakshmi SG, Madempudi RS. In Vitro Evaluation of Probiotic Properties of Lactobacillus plantarum UBLP40 Isolated from Traditional Indigenous Fermented Food. Probiotics Antimicrob Proteins. 2021;13(5):1413–24. pmid:33761096
- 19. Kruasuwan W, Jenjaroenpun P, Arigul T, Chokesajjawatee N, Leekitcharoenphon P, Foongladda S, et al. Nanopore Sequencing Discloses Compositional Quality of Commercial Probiotic Feed Supplements. Sci Rep. 2023;13(1):4540. pmid:36941307
- 20. Bunu S, Otele D, Alade T, Dodoru R. Determination of serum DNA purity among patients undergoing antiretroviral therapy using NanoDrop-1000 spectrophotometer and polymerase chain reaction. Biomed Biotechnol Res J. 2020;4(3):214.
- 21. De Coster W, D’Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics. 2018;34(15):2666–9. pmid:29547981
- 22. Kolmogorov M, Bickhart DM, Behsaz B, Gurevich A, Rayko M, Shin SB, et al. metaFlye: scalable long-read metagenome assembly using repeat graphs. Nat Methods. 2020;17(11):1103–10. pmid:33020656
- 23. Hu J, Fan J, Sun Z, Liu S. NextPolish: a fast and efficient genome polishing tool for long-read assembly. Bioinformatics. 2020;36(7):2253–5. pmid:31778144
- 24. Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol. 2017;13(6):e1005595. pmid:28594827
- 25. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25(7):1043–55. pmid:25977477
- 26. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29(8):1072–5. pmid:23422339
- 27. Robertson J, Nash JHE. MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies. Microb Genom. 2018;4(8):e000206. pmid:30052170
- 28. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30(14):2068–9. pmid:24642063
- 29. Stothard P, Grant JR, Van Domselaar G. Visualizing and comparing circular genomes using the CGView family of tools. Brief Bioinform. 2019;20(4):1576–82. pmid:28968859
- 30. Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk v2: memory friendly classification with the genome taxonomy database. Bioinformatics. 2022;38(23):5315–6. pmid:36218463
- 31. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci U S A. 2009;106(45):19126–31. pmid:19855009
- 32. Varghese NJ, Mukherjee S, Ivanova N, Konstantinidis KT, Mavrommatis K, Kyrpides NC, et al. Microbial species delineation using whole genome sequences. Nucleic Acids Res. 2015;43(14):6761–71. pmid:26150420
- 33. Lee I, Ouk Kim Y, Park S-C, Chun J. OrthoANI: An improved algorithm and software for calculating average nucleotide identity. Int J Syst Evol Microbiol. 2016;66(2):1100–3. pmid:26585518
- 34. Larsen MV, Cosentino S, Lukjancenko O, Saputra D, Rasmussen S, Hasman H, et al. Benchmarking of methods for genomic taxonomy. J Clin Microbiol. 2014;52(5):1529–39. pmid:24574292
- 35. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–3. pmid:24451623
- 36. Letunic I, Bork P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 2016;44(W1):W242–5. pmid:27095192
- 37. Wang Y, Coleman-Derr D, Chen G, Gu YQ. OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res. 2015;43(W1):W78-84. pmid:25964301
- 38. Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P, Tsang KK, et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res. 2017;45(D1):D566–73. pmid:27789705
- 39. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother. 2012;67(11):2640–4. pmid:22782487
- 40. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 2016;44(D1):D457-62. pmid:26476454
- 41. Gupta SK, Padmanabhan BR, Diene SM, Lopez-Rojas R, Kempf M, Landraud L, et al. ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob Agents Chemother. 2014;58(1):212–20. pmid:24145532
- 42. Blin K, Shaw S, Kloosterman AM, Charlop-Powers Z, van Wezel GP, Medema MH, et al. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Res. 2021;49(W1):W29–35. pmid:33978755
- 43. van Heel AJ, de Jong A, Song C, Viel JH, Kok J, Kuipers OP. BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins. Nucleic Acids Res. 2018;46(W1):W278–81. pmid:29788290
- 44. Couvin D, Bernheim A, Toffano-Nioche C, Touchon M, Michalik J, Néron B, et al. CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins. Nucleic Acids Res. 2018;46(W1):W246–51. pmid:29790974
- 45. Arndt D, Grant JR, Marcu A, Sajed T, Pon A, Liang Y, et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 2016;44(W1):W16–21. pmid:27141966
- 46. Carattoli A, Zankari E, García-Fernández A, Voldby Larsen M, Lund O, Villa L, et al. In silico detection and typing of plasmids using PlasmidFinder and plasmid multilocus sequence typing. Antimicrob Agents Chemother. 2014;58(7):3895–903. pmid:24777092
- 47. Li X, Xie Y, Liu M, Tai C, Sun J, Deng Z, et al. oriTfinder: a web-based tool for the identification of origin of transfers in DNA sequences of bacterial mobile genetic elements. Nucleic Acids Res. 2018;46(W1):W229–34. pmid:29733379
- 48. Bertelli C, Laird MR, Williams KP, Group SFURC, Lau BY, Hoad G, Winsor GL, et al. IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets. Nucleic acids research. 2017;45(W1):W30–W35.
- 49. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42(Database issue):D206–14. pmid:24293654
- 50. Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences. J Mol Biol. 2016;428(4):726–31. pmid:26585406
- 51. Song X, Li F, Zhang M, Xia Y, Ai L, Wang G. Effect of D-Ala-Ended Peptidoglycan Precursors on the Immune Regulation of Lactobacillus plantarum Strains. Front Immunol. 2022;12:825825. pmid:35126378
- 52. Barbosa J, Borges S, Teixeira P. Pediococcus acidilactici as a potential probiotic to be used in food industry. Int J of Food Sci Tech. 2015;50(5):1151–7.
- 53. Todorov SD, Holzapfel WH, Nero LA. Safety evaluation and bacteriocinogenic potential of Pediococcus acidilactici strains isolated from artisanal cheeses. LWT. 2021;139:110550.
- 54. Zhang J, Xu Y, Wang M, Li X, Liu Z, Kuang D, et al. Mobilizable plasmids drive the spread of antimicrobial resistance genes and virulence genes in Klebsiella pneumoniae. Genome Med. 2023;15(1):106. pmid:38041146
- 55. Alpert C-A, Mater DDG, Muller M-C, Ouriet M-F, Duval-Iflah Y, Corthier G. Worst-case scenarios for horizontal gene transfer from Lactococcus lactis carrying heterologous genes to Enterococcus faecalis in the digestive tract of gnotobiotic mice. Environ Biosafety Res. 2003;2(3):173–80. pmid:15612415
- 56. Sun Y-W, Liu Y-Y, Wu H, Wang L-F, Liu J-H, Yuan L, et al. IS26-Flanked Composite Transposon Tn6539 Carrying the tet(M) Gene in IncHI2-Type Conjugative Plasmids From Escherichia coli Isolated From Ducks in China. Front Microbiol. 2019;9:3168. pmid:30697195
- 57. Yu R, Zhang Y, Xu Y, Schwarz S, Li X-S, Shang Y-H, et al. Emergence of a tet(M) Variant Conferring Resistance to Tigecycline in Streptococcus suis. Front Vet Sci. 2021;8:709327. pmid:34490399
- 58. Lüdin P, Roetschi A, Wüthrich D, Bruggmann R, Berthoud H, Shani N. Update on Tetracycline Susceptibility of Pediococcus acidilactici Based on Strains Isolated from Swiss Cheese and Whey. J Food Prot. 2018;81(10):1582–9. pmid:30169118
- 59. Stefańska I, Kwiecień E, Jóźwiak-Piasecka K, Garbowska M, Binek M, Rzewuska M. Antimicrobial Susceptibility of Lactic Acid Bacteria Strains of Potential Use as Feed Additives - The Basic Safety and Usefulness Criterion. Front Vet Sci. 2021;8:687071. pmid:34277757
- 60. Card KJ, Thomas MD, Graves JL Jr, Barrick JE, Lenski RE. Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli. Proc Natl Acad Sci U S A. 2021;118(5):e2016886118. pmid:33441451
- 61. Kong M, Liu C, Xu Y, Wang J, Jin D. Concordance between Genotypic and Phenotypic Drug-Resistant Profiles of Shigella Isolates from Taiyuan City, Shanxi Province, China, 2005 to 2016. Microbiol Spectr. 2023;11(3):e0011923. pmid:37249442
- 62. Cunningham SA, Jeraldo PR, Schuetz AN, Heitman AA, Patel R. Staphylococcus aureus whole genome sequence-based susceptibility and resistance prediction using a clinically amenable workflow. Diagn Microbiol Infect Dis. 2020;97(3):115060. pmid:32417617
- 63. Grohs P, Trieu-Cuot P, Podglajen I, Grondin S, Firon A, Poyart C, et al. Molecular basis for different levels of tet(M) expression in Streptococcus pneumoniae clinical isolates. Antimicrob Agents Chemother. 2012;56(10):5040–5. pmid:22802249
- 64. Stasiak M, Maćkiw E, Kowalska J, Kucharek K, Postupolski J. Silent Genes: Antimicrobial Resistance and Antibiotic Production. Pol J Microbiol. 2021;70(4):421–9. pmid:35003274
- 65. Tait-Kamradt A, Davies T, Cronan M, Jacobs MR, Appelbaum PC, Sutcliffe J. Mutations in 23S rRNA and ribosomal protein L4 account for resistance in pneumococcal strains selected in vitro by macrolide passage. Antimicrob Agents Chemother. 2000;44(8):2118–25. pmid:10898684
- 66. Floyd JL, Smith KP, Kumar SH, Floyd JT, Varela MF. LmrS is a multidrug efflux pump of the major facilitator superfamily from Staphylococcus aureus. Antimicrob Agents Chemother. 2010;54(12):5406–12. pmid:20855745
- 67. Al-Emran HM, Moon JF, Miah ML, Meghla NS, Reuben RC, Uddin MJ, et al. Genomic analysis and in vivo efficacy of Pediococcus acidilactici as a potential probiotic to prevent hyperglycemia, hypercholesterolemia and gastrointestinal infections. Sci Rep. 2022;12(1):20429. pmid:36443433
- 68. Sornsenee P, Surachat K, Kang D-K, Mendoza R, Romyasamit C. Probiotic Insights from the Genomic Exploration of Lacticaseibacillus paracasei Strains Isolated from Fermented Palm Sap. Foods. 2024;13(11):1773. pmid:38891001
- 69. Desmond C, Fitzgerald GF, Stanton C, Ross RP. Improved stress tolerance of GroESL-overproducing Lactococcus lactis and probiotic Lactobacillus paracasei NFBC 338. Appl Environ Microbiol. 2004;70(10):5929–36. pmid:15466535
- 70. Corcoran BM, Stanton C, Fitzgerald GF, Ross RP. Survival of probiotic lactobacilli in acidic environments is enhanced in the presence of metabolizable sugars. Appl Environ Microbiol. 2005;71(6):3060–7. pmid:15933002
- 71. To TMH, Grandvalet C, Tourdot-Maréchal R. Cyclopropanation of membrane unsaturated fatty acids is not essential to the acid stress response of Lactococcus lactis subsp. cremoris. Appl Environ Microbiol. 2011;77(10):3327–34. pmid:21421775
- 72. Granato D, Bergonzelli GE, Pridmore RD, Marvin L, Rouvet M, Corthésy-Theulaz IE. Cell surface-associated elongation factor Tu mediates the attachment of Lactobacillus johnsonii NCC533 (La1) to human intestinal cells and mucins. Infect Immun. 2004;72(4):2160–9. pmid:15039339
- 73. Muscariello L, De Siena B, Marasco R. Lactobacillus Cell Surface Proteins Involved in Interaction with Mucus and Extracellular Matrix Components. Curr Microbiol. 2020;77(12):3831–41. pmid:33079206
- 74. Feng T, Wang J. Oxidative stress tolerance and antioxidant capacity of lactic acid bacteria as probiotic: a systematic review. Gut Microbes. 2020;12(1):1801944. pmid:32795116
- 75. An H, Zhou H, Huang Y, Wang G, Luan C, Mou J, et al. High-level expression of heme-dependent catalase gene katA from Lactobacillus Sakei protects Lactobacillus rhamnosus from oxidative stress. Mol Biotechnol. 2010;45(2):155–60. pmid:20195800
- 76. Kamar R, Réjasse A, Jéhanno I, Attieh Z, Courtin P, Chapot-Chartier M-P, et al. DltX of Bacillus thuringiensis Is Essential for D-Alanylation of Teichoic Acids and Resistance to Antimicrobial Response in Insects. Front Microbiol. 2017;8:1437. pmid:28824570
- 77. Li J, Wang B, Chen J, Du G, Fang F. Heme Dependent Catalase Conditionally Contributes to Oxygen Tolerance of Tetragenococcus halophilus Strains Isolated from Soy Sauce Moromi. Applied Sciences. 2022;12(16):8039.
- 78. Ricciardi A, Ianniello RG, Parente E, Zotta T. Factors affecting gene expression and activity of heme- and manganese-dependent catalases in Lactobacillus casei strains. Int J Food Microbiol. 2018;280:66–77. pmid:29783045
- 79. He J, Sakaguchi K, Suzuki T. Acquired tolerance to oxidative stress in Bifidobacterium longum 105-A via expression of a catalase gene. Appl Environ Microbiol. 2012;78(8):2988–90. pmid:22307289
- 80. Rochat T, Gratadoux J-J, Gruss A, Corthier G, Maguin E, Langella P, et al. Production of a heterologous nonheme catalase by Lactobacillus casei: an efficient tool for removal of H2O2 and protection of Lactobacillus bulgaricus from oxidative stress in milk. Appl Environ Microbiol. 2006;72(8):5143–9. pmid:16885258
- 81. Jiang X, Duan Y, Zhou B, Guo Q, Wang H, Hang X, et al. The Cyclopropane Fatty Acid Synthase Mediates Antibiotic Resistance and Gastric Colonization of Helicobacter pylori. J Bacteriol. 2019;201(20):e00374-19. pmid:31358615
- 82. Tabashiri R, Mahmoodian S, Pakdel MH, Shariati V, Meimandipour A, Zamani J. Comprehensive in vitro and whole-genome characterization of probiotic properties in Pediococcus acidilactici P10 isolated from Iranian broiler chicken. Sci Rep. 2025;15(1):28953. pmid:40774991
- 83. Velly H, Bouix M, Passot S, Penicaud C, Beinsteiner H, Ghorbal S, et al. Cyclopropanation of unsaturated fatty acids and membrane rigidification improve the freeze-drying resistance of Lactococcus lactis subsp. lactis TOMSC161. Appl Microbiol Biotechnol. 2015;99(2):907–18. pmid:25343977
- 84. Punyauppa-Path S, Kiatprasert P, Sawaengkaew J, Mahakhan P, Phumkhachorn P, Rattanachaikunsopon P, et al. Diversity of fermentative yeasts with probiotic potential isolated from Thai fermented food products. AIMS Microbiol. 2022;8(4):575–94. pmid:36694589
- 85. Amenu D, Bacha K. Probiotic potential and safety analysis of lactic acid bacteria isolated from Ethiopian traditional fermented foods and beverages. Ann Microbiol. 2023;73(1).
- 86. Srikham K, Daengprok W, Niamsup P, Thirabunyanon M. Characterization of Streptococcus salivarius as New Probiotics Derived From Human Breast Milk and Their Potential on Proliferative Inhibition of Liver and Breast Cancer Cells and Antioxidant Activity. Front Microbiol. 2021;12:797445. pmid:34975821