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Full Length Article
04 2024
:36;
103111
doi:
10.1016/j.jksus.2024.103111

Isolation and characterization of the lytic bacteriophages and their application in combination with amoxicillin against Aeromonas dhakensis

Department of Microbiology, Faculty of Science, Srinakharinwirot University, Bangkok 10110, Thailand
National Biobank of Thailand (NBT), National Science and Technology Development Agency, Pathum Thani 12120, Thailand
Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand
Translational Medicine Research Center, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok 10110, Thailand
Frontier Research Center (FRC) Vidyasirimedhi Institute of Science and Technology (VISTEC), Wangchan Valley, Rayong 21210, Thailand
Laboratory of Microbial Genetic Technology, Department of Bioscience and Biotechnology, Graduate School of Agriculture, Kyushu University, Fukuoka 812-8581, Japan
Department of Microbiology, Faculty of Medicine, Srinakharinwirot University, Bangkok 10110, Thailand
Division of Biological Science, Faculty of Science, Prince of Songkla University, Songkhla, Hat Yai, 90110, Thailand

⁎Corresponding author. onanong@g.swu.ac.th (Onanong Pringsulaka) opringsulaka@gmail.com (Onanong Pringsulaka)

Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Aeromonas dhakensis stands out as the most potent Aeromonas species causing a range of human diseases. This research marks the pioneering effort in isolating and characterizing virulent phages targeting A. dhakensis. Only the AM isolate among the Aeromonas isolates showed compatibility for phage isolation and was identified as A. dhakensis. Computational analysis identified the presence of virulence factors and antimicrobial resistance genes in A. dhakensis AM. Phage isolation was conducted using this particular strain as the host, resulting in the isolation of four virulent phages: vB_AdhM_DL, vB_AdhS_TS3, vB_AdhM_TS9, and vB_AdhS_M4. Bacterial numbers significantly decrease after both pre-treatment and post-treatment with individual phages and phage cocktails, ranging from 2.82 to 6.67 log CFU/mL and 4.01 to 6.49 log CFU/mL, respectively. Combining a phage cocktail with sub-MIC amoxicillin led to complete inactivation in both pre-treatment and post-treatment scenarios within a 200 µL volume. The complete genomes of phages vB_AdhM_DL, vB_AdhS_TS3, and vB_AdhM_TS9 were determined to be 42,388 bp, 115,560 bp, and 115,503 bp, respectively. This study establishes the effectiveness of using phages as an complement with sublethal antibiotic concentrations, presenting a potential and effective therapeutic approach.

Keywords

Aeromonas dhakensis
Phage−antibiotic synergy
Phage therapy
Genome analysis
1

1 Introduction

Aeromonas dhakensis, a member of the Aeromonas genus, represents a significant pathogenic species with distinct characteristics and implications for human health. Prior to the identification of A. dhakensis, the most prevalent Aeromonas species included A. hydrophila, A. caviae, and A. veronii. However, A. dhakensis, formerly synonymous with A. hydrophila subsp. dhakensis (Huys et al., 2002) and A. aquariorum (Martinez-Murcia et al., 2008), presents a unique challenge in identification. Phenotypic methods often misidentify it as A. hydrophila (Beaz-Hidalgo et al., 2013), and 16S rRNA sequencing has been deemed unreliable for distinguishing Aeromonas species at the species level (Janda and Abbott, 2010). Despite these challenges, A. dhakensis has garnered increasing attention due to its capacity to cause a spectrum of infections in humans, including gastroenteritis, wound infections, bacteremia, skin and soft-tissue infections, and respiratory infections (Janda and Abbott, 2010; Beaz-Hidalgo et al., 2013).

A. dhakensis exhibits distinct geographic prevalence, primarily in hot climate countries like Bangladesh, Taiwan, Australia, Malaysia, and Thailand (Huys et al., 2002; Chen et al., 2014; Aravena-Roman et al., 2011; Puthucheary et al., 2012; Yano et al., 2015). A. dhakensis's enhanced virulence is attributed to its various virulence factors, including hemolysins and extracellular enzymes, contributing significantly to its invasiveness (Cascon et al., 2000). Clinical strains are found in various anatomical sites, from stool to blood and wounds (Chen et al., 2014). Antibiotics play a vital role in treating A. dhakensis infections, yet increasing resistance to agents like amoxicillin, cephalothin, and cefoxitin is concerning (Figueras et al., 2009). Additionally, the biofilm-forming ability of some strains complicates treatment by allowing adherence to surfaces, evading conventional medications. Given these challenges, exploring alternative treatments is crucial.

Bacteriophages are viruses that kill specific bacteria without disturbing other flora. Many studies have isolated phages against A. hydrophila and have determined their efficacy for protective and therapeutic effects against disease (Jun et al., 2015; Easwaran et al., 2017; El-Araby et al., 2016). However, there have been few reports on the isolation and characterization of lytic phages specific to A. dhakensis. The objective of this study was to isolate and characterize a new lytic phage from water that infects A. dhakensis. This study also investigated the lytic activity of the isolated phage and its combination with antibiotics against A. dhakensis in vitro.

2

2 Materials and methods

2.1

2.1 Isolation of Aeromonas

To isolate Aeromonas species, 30 samples were collected from different sources, including fishponds, canal water, and rivers in Bangkok, Thailand. The samples were streaked onto an Aeromonas isolation medium (HiMedia, India) supplemented with ampicillin. The plates were incubated for 24 h at 30 °C. The dark green colonies resembling Aeromonas sp. were selected. Gram-negative bacteria capable of degrading nitrates to nitrites, glucose fermenters, oxidase, and catalase-positive isolates resembling the genus Aeromonas were selected for 16S rRNA gene sequencing analysis. Other biochemical tests were used to differentiate between Aeromonas genera. L-arabinose fermentation was also differentiated between A. hydrophila and A. dhakensis. Likewise, salicin fermentation allowed differentiation between A. hydrophila and A. dhakensis from A. hydrophila subsp. ranae (Beaz-Hidalgo et al., 2013).

2.2

2.2 Identification of Aeromonas spp

The genomic DNA obtained from the Aeromonas isolate underwent extraction utilizing the AccuPrep® Genomic DNA Extraction Kit (Bioneer, Korea) and was employed as templates for PCR amplification. The 16S rRNA gene was amplified using a pair of universal primers, 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-GGCTACCTTGTTACGACTT-3′) as described by Lane (1991). Subsequently, the sequenced fragments were compared to the GenBank database through the Basic Local Alignment Search Tool (BLAST), and phylogenetic trees were constructed using the neighbor-joining method in the MEGA 5.1 software package.

2.3

2.3 Antimicrobial susceptibilities of Aeromonas isolates

Aeromonas isolates were underwent MIC testing using MIC test strips, which included amoxicillin, chloramphenicol, doxycycline, gentamicin, and tetracycline (Liofilchem® MTS™, Italy). The interpretative criteria were in accordance with the Clinical and Laboratory Standards Institute (CLSI) VET04 guidelines (CLSI, 2020).

2.4

2.4 Phage isolation and detection

The isolated Aeromonas strains served as hosts for bacteriophage isolation, following the method described by Sunthornthummas et al. (2017). The presence of phages was determined using the double-layer agar plate method on NA medium. Phage plaques were counted following an overnight incubation at 30 °C and expressed as plaque-forming units (PFU/mL).

2.5

2.5 Electron microscopy

Phage morphology was visualized by transmission electron microscopy (TEM) using carbon-formvar-coated grids, 1% (w/v) uranyl acetate staining (pH 4.5), and a TECNAI 20 TWIN transmission electron microscope operating at 120 kV with a magnification of 120,000×.

2.6

2.6 Host-range determination and determination of optimal multiplicity of infection (MOI)

The host range of the isolated phages was determined using the spot test method. Other reference strains of Aeromonas were tested for susceptibility to phages. Bacterial sensitivity to the phage was indicated by the presence of a plaque at the spot. Additionally, a host strain suspension (108 CFU/mL) in NB was mixed with the phage stock at four different ratios (0.01, 0.1, 1, and 10 PFU/CFU) to determine the optimal MOI. The ratio with the highest phage titer was considered the optimal MOI (Pringsulaka et al., 2011).

2.7

2.7 One-step growth curve experiments

A one-step growth curve for each phage isolate was performed as Sunthornthummas et al. (2017). The latent period, rise period, and burst size were calculated using the one-step growth curve (Adams, 1959).

2.8

2.8 pH and thermal stability

For the pH stability tests, NB was pre-adjusted to a range of pH values (pH 2.0–11.0). A phage suspension (1010 PFU/mL) was inoculated and incubated for 90 min at 30 °C. For thermal inactivation experiments, phage lysates (1010 PFU/mL) were subjected to heat treatment at 4, 30, 37, 45, 63, 72, and 100 °C in NB. The phage titer was determined using the double-layer agar plate method for both the pH stability tests and thermal inactivation experiments.

2.9

2.9 Whole genome sequencing and computational analyses

2.9.1

2.9.1 DNA extraction and sequencing

Genomic DNA of Aeromonas sp. AM was extracted using an AccuPrep Genomic DNA Extraction Kit (Bioneer, Daejeon, Korea). Phage DNA was isolated as previously described (Sunthornthummas et al., 2017). The purified genomic DNA was sent to the Beijing Genomics Institute (BGI) in China for short-read sequencing.

2.9.2

2.9.2 Genome assembly and annotation

De novo assembly of Aeromonas sp. AM and three phage genome sequences were constructed using SPAdes 3.12 (Bankevich et al., 2012). The examination of read quality was conducted using FASTQC (Brown et al., 2017), and trimming was performed using Trimmomatic 0.39 (Bolger et al., 2014). Functional annotation was performed using Prokka v1.14 (Seemann, 2014).

2.9.3

2.9.3 Bioinformatics analyses

Nucleotide and amino acid sequences were compared using Blastn software. Translated open reading frames (ORFs) were compared to the non-redundant GenBank protein database using the Blastp software. To further improve the annotation of predicted proteins, we utilized tools such as the hhpred server (https://toolkit.tuebingen.mpg.de/tools/hhpred). Additionally, the genomic DNA of A. dhakensis AM and three phages was screened for the presence of virulence genes using the Virulence Factors of Pathogenic Bacteria (VFDB) (Liu et al., 2022a), PlasmidFinder 2.1 (Carattoli et al., 2014), Comprehensive Antibiotic Resistance Database (CARD) databases (Alcock et al., 2020), and PHASTER was used to identify prophages in bacterial genomes (Zhou et al., 2011). The genome of Aeromonas sp. AM and the three phages were visualized using the CGView webserver (https://beta.proksee.ca/) (Grant and Stothard, 2008).

2.9.4

2.9.4 Accession numbers

The genome sequences of A. dhakensis AM were deposited in the NCBI database under accession number JAPHNH000000000, and the genome sequences of phage vB_AdhS_TS3, vB_AdhM_TS9, and vB_AdhM_DL were deposited in the NCBI database under accession number OP820700, OP820701, and OP820702, respectively.

2.10

2.10 A. dhakensis growth inhibition by single phage and phage cocktail in vitro

Phage therapy was divided into two treatments: pre- and post-treatment. In the pre-treatment experiment, phages or phage cocktail were added before inoculation with A. dhakensis AM (1 × 108 CFU/mL), resulting in MOIs of 0.1, 1, and 10. In the post-treatment experiment, A. dhakensis AM suspensions (1 × 108 CFU/mL) were inoculated into NB and incubated for 3 h. Equal volumes of phages or phage cocktail were added at MOIs of 0.1, 1, and 10. Both treatments were performed in a 250 mL Erlenmeyer flask containing 50 mL of NB at 200 rpm and incubated at 30 °C for 48 h. For each assay, two control samples were set: the bacterial control and the phage control. The bacterial control was inoculated with A. dhakensis but not phages, and the phage controls were inoculated with phages but not bacteria. The control and test samples were incubated under the same conditions. Aliquots of the test samples and their controls were sampled at 0, 6, 12, and 24 h of incubation. In all assays, phage titer was determined in triplicate using the double-layer agar plate method. The bacterial concentration was determined in triplicate in the NA medium. Three independent experiments were performed for each condition.

2.11

2.11 A. dhakensis growth inhibition by phage cocktail and antibiotics combination

The inhibitory effects of the selected two-phage cocktail with effective MOIs in combination with antibiotics at sub-MIC (1/2 MIC) were determined as previously described. In the pre-treatment experiment, a combination of the selected two-phage cocktail with effective MOIs and amoxicillin at sub-MIC was added before inoculation with A. dhakensis AM (1 × 105 CFU/mL). In the post-treatment experiment, A. dhakensis AM suspensions (1 × 105 CFU/mL) were inoculated into NB and incubated for 3 h. Equal volumes of the selected three-phage cocktail with effective MOIs and amoxicillin at sub-MICs were added. Only the phage cocktail and antibiotics at MIC were also administered in both pre-and post-treatment. Phage and bacterial counts were determined in NB in two different volumes: 200 μL in 96-well microtiter plates and 20 mL in 250 mL Erlenmeyer flasks. The latter was incubated on an orbital shaker with a shaking speed of 200 rpm. After incubation at 30 °C, the aliquots of each sample and their controls were collected every 6 h for 48 h and were serially diluted to determine viable bacteria (CFU/mL) in NA plates incubated for 24 h at 30 °C.

2.12

2.12 Statistical analysis

Statistically significant differences in all experiments were determined by one-way analysis of variance (ANOVA), and post-hoc Tukey’s test was applied to illustrate significant differences between bacterial concentrations between treatment groups over time. A p-value < 0.05 was considered to indicate statistical significance. SPSS statistical software package (version 13.0) was used for all analyses.

3

3 Results and discussion

3.1

3.1 Aeromonas isolation and identification

Three of the 40 isolates from 30 collection sites were preliminarily identified as Aeromonas by biochemical tests. These Aeromonas strains were then used as hosts for phage isolation. However, only the Aeromonas isolate AM was able to isolate phages using the enrichment technique. The isolated AM was further characterized using 16S rRNA gene sequencing, revealing a 99% identity with A. dhakensis. The neighbor-joining tree indicated that strain AM was most closely related to A. dhakensis (Fig. 1). The biochemical tests of A. dhakensis AM are shown in Table 1. To distinguish A. dhakensis from A. hydrophila subsp. hydrophila and A. hydrophila subsp. ranae, the results confirmed that strain AM was negative for L-arabinose and positive for salicin fermentation, confirming its classification as A. dhakensis. Furthermore, for more comprehensive characterization, a whole genome sequence analysis of strain AM was included in this study.

Phylogenetic tree of Aeromonas spp. based on the 16S rRNA gene using neighbor-joining method. Bootstrap values (%) of 1000 replicates are represented on the branches.
Fig. 1
Phylogenetic tree of Aeromonas spp. based on the 16S rRNA gene using neighbor-joining method. Bootstrap values (%) of 1000 replicates are represented on the branches.
Table 1 Biochemical tests of A. dhakensis AM.
Biochemical tests Results
Indole +
Methyl red +
Voges-Proskauer +
Citrate +
Hemolysis β
Deoxyribonuclease +
Gelatinase +
Catalase +
Oxidase +
Oxidative/fermentation glucose test F
Motility +
Urease +
Nitrate +
TSI (Acid/Alkali) A/A
Arginine dihydrolase +
Lysine decarboxylase +
Ornithine decarboxylase
Acid from
Lactose
Sucrose +
L-arabinose
Mannitol +
Salicin +

+ represents positive, − represents negative, and F represents fermentation.

3.2

3.2 Antimicrobial susceptibility of A. dhakensis AM

The MICs of six antimicrobial agents against A. dhakensis AM were evaluated. Notably, amoxicillin had the highest MIC of 64 µg/mL among the antibiotics, a value significantly higher than the Clinical and Laboratory Standards Institute (CLSI) MIC breakpoints (>8 µg/mL) (data not shown). Considering the limited availability of information regarding the susceptibility profiles of A. dhakensis, our findings provide valuable insights into the antibiotic susceptibility of A. dhakensis AM. Specifically, our results demonstrate that A. dhakensis AM displays susceptibility to chloramphenicol, doxycycline, and gentamicin. Traditionally, Aeromonas have shown susceptibility to a range of antimicrobial agents, including 4th-generation cephalosporins, aminoglycosides, fluoroquinolones, tetracycline, and trimethoprim-sulfamethoxazole (Aravena-Roman et al., 2012). It is important to highlight that only a limited selection of antimicrobial agents, including oxytetracycline, amoxicillin, sulfadimethoxine/ormetoprim, and enrofloxacin, have been approved for use in aquaculture in Thailand (Baoprasertkul et al., 2012). Our results underscore the resistance rate to amoxicillin, in line with the report by Aravena-Roman et al. (2011), which noted that only 1.6% of 193 Aeromonas isolates were susceptible to amoxicillin. Recognizing the unique resistance pattern of amoxicillin against the target bacteria, we chose to incorporate amoxicillin at sub-MIC levels for our evaluation of synergism between the antibiotics and the phage cocktail. This choice was driven by the need to explore alternative treatment strategies given the observed resistance and to assess the potential of phages in complementing amoxicillin's limited efficacy in addressing A. dhakensis AM infections.

3.3

3.3 Genomic features of A. dhakensis AM

The in silico genome of A. dhakensis AM comprises one circular chromosome of 4,884,279 bp with a G + C content of 61.9% (Fig. 2). The genome contained 4256 coding DNA sequences (CDSs). We emphasized the antimicrobial resistance genes and virulence factors corresponding to the main bacterial virulence determinants. Antimicrobial resistance genes were identified in the genome of A. dhakensis AM (Table S1). Virulence factor genes were identified in the genome of A. dhakensis AM (Table S2). Several typical toxin-encoding genes have been identified, such as aerolysin, hemolysin, and exotoxin. Five prophages were identified in the genome (Table S3), and no plasmids were found during genome analysis.

Genome features of A. dhakensis AM. Circular representation of the following characteristics are shown from the outside to the center of the diagram. Circle 1: coding sequence (CDS) on the reverse strand, circle 2: coding sequence (CDS) on the forward strand, circle 3: GC contents, circle 5: GC skew values (GC skew + shown in green, GC skew- shown in pink).
Fig. 2
Genome features of A. dhakensis AM. Circular representation of the following characteristics are shown from the outside to the center of the diagram. Circle 1: coding sequence (CDS) on the reverse strand, circle 2: coding sequence (CDS) on the forward strand, circle 3: GC contents, circle 5: GC skew values (GC skew + shown in green, GC skew- shown in pink).

3.4

3.4 Phage isolation, purification and phage morphology

Four phages, designated as vB_AdhS_TS3, vB_AdhM_TS9, vB_AdhM_DL, and vB_AdhS_M4 were isolated using A. dhakensis AM as the host. These phages exhibited clear plaques with diameters ranging from 1.7 to 2.0 mm (Fig. 3). The electron micrographs revealed distinct morphologies for the isolated phages. Phage vB_AdhS_TS3 exhibited an icosahedral head of approximately 75.2 nm and a contractile tail with a length of 225.3 nm, while phage vB_AdhS_M4 had an icosahedral head of approximately 64.8 nm and a tail length of 185.4 nm. In contrast, phages vB_AdhM_DL and vB_AdhM_TS9 displayed different morphologies, with phage vB_AdhM_DL possessing an icosahedral head with dimensions of 50.4 nm and a tail length of 210.4 nm, and phage vB_AdhM_TS9 featuring an icosahedral head of approximately 85.1 nm and a shorter tail measuring 101.4 nm (Fig. 3). In a study by Bai et al. (2019), it was reported that among 51 complete genome sequences of Aeromonas phages in GenBank, the majority of Aeromonas phages were classified into different families. However, it's important to note that the ICTV's updated classification emphasizes that these morphological categories do not hold formal taxonomic significance in the classification of phages.

Plaques and TEM images of phage vB_AdhS_TS3 (A), vB_AdhS_M4 (B), vB_AdhM_DL (C), and vB_AdhM_TS9 (D). Scale bar = 100 nm.
Fig. 3
Plaques and TEM images of phage vB_AdhS_TS3 (A), vB_AdhS_M4 (B), vB_AdhM_DL (C), and vB_AdhM_TS9 (D). Scale bar = 100 nm.

3.5

3.5 Host range determination

All phages were infected only with A. dhakensis and did not infect other Aeromonas spp., such as A. hydrophila, A. caviae, A. sobria, A. trota, or A. veronii (data not shown). Bacteriophage vB_AdhM_TS3 and vB_AdhM_TS9 are the broadest host range phage, able to infect A. dhakensis in five out of the six strains tested.

3.6

3.6 Optimal multiplicity of infection determination (MOI) and one-step growth curve

Phage vB_AdhS_TS3, vB_AdhM_DL, vB_AdhS_M4 and vB_AdhM_TS9 generated a maximum titre of 9.68 ± 0.05, 9.94 ± 0.05, 10.41 ± 0.06 and 8.85 ± 0.25 PFU/mL when infected at an optimal MOI of 10 (data not shown). The one-step growth curve of the phages revealed latent periods of approximately 40, 30, 50, and 30 min for vB_AdhS_TS3, vB_AdhM_DL, vB_AdhS_M4, and vB_AdhM_TS9, respectively. The burst sizes for these phages were estimated as 1380, 1280, 253, and 630 PFUs/infected cells, respectively (data not shown). Among the four phages, phage vB_AdhS_M4 had the longest latent period, smallest burst size, and narrowest host range. Therefore, we selected the other three phages, vB_AdhS_TS3, vB_AdhM_DL, and vB_AdhM_TS9, for further studies.

3.7

3.7 pH and thermal stability

All phages were resistant to a wide range of pH values after 2 h of incubation, and the optimum range was pH–6–8 (data not shown). No plaques were seen at pH 2. Regarding thermal stability, the phages maintained their stability relatively well after a 60-minute incubation at 4 °C, 25 °C, 30 °C, and 37 °C but were sensitive to higher temperatures (data not shown).

3.8

3.8 Whole genome sequencing and computational analyses

The genome size of vB_AdhS_TS3 was 115,560 bp with a G + C content of 41.10% (Fig. 4). The open reading frames (ORFs) of vB_AdhS_TS3 were identified with a total of 272 predicted ORFs. Among these genes, 58 were predicted to have known functions (Table 2, Fig. 4), and 184 ORFs were predicted to encode hypothetical proteins. Similarly, the genome size of vB_AdhM_TS9 was 115,503 bp, with a G + C content of 35.34%, and encoded 199 proteins. Out of 199 ORFs, 136 ORFs were hypothetical, whereas only 63 ORFs predicted functions (Table 2, Fig. 4). The genome size of vB_AdhM_DL was 42,388 bp, with a G + C content of 34.43% and 79 proteins, respectively. Of the 79 encoded proteins, Only 29 out of 79 encoded predicted functions, whereas 50 ORFs were hypothetical (Table 2, Fig. 4). We did not find an ORF encoding a protein with known toxins, antibiotic-resistant genes (ARGs), virulent factors (VFs) of bacterial origin, or lysogenic markers such as integrase, recombinase, repressor/anti-repressor protein, and excisionase in all three phage genomes.

Genomic characterization of three bacteriophages targeting A. dhakensis AM, A) vB_AdhS_TS3 B) vB_AdhM_TS9 C) vB_AdhM_DL. Circles from outermost to innermost correspond to predicted genes (BLASTp, nr database, E value of 〈10−5) on the forward strand, reverse strand, and GC content.
Fig. 4
Genomic characterization of three bacteriophages targeting A. dhakensis AM, A) vB_AdhS_TS3 B) vB_AdhM_TS9 C) vB_AdhM_DL. Circles from outermost to innermost correspond to predicted genes (BLASTp, nr database, E value of 〈10−5) on the forward strand, reverse strand, and GC content.
Table 2 Features of the ORFs of three bacteriophages, predicted functions of proteins, and conserved domains detected.
ORF start stop strand Predicted function Probability E value Conserved domain no.
phage vB_AdhS_TS3
1 691 29 Hydrolase 99.74 1.60 × 10−16 2GO7_C
3 2625 1045 UDP-2,3-diacylglucosamine hydrolase 98.95 2.30 × 10−8 5K8K_A
15 7483 7596 + Fimbrial protein 98.4 9.10 × 10−7 4IXJ_B
29 13,672 12,083 Nicotinamide phosphoribosyltransferase 100 6.40 × 10−75 8DSC_B
31 14,698 13,916 Ribose-phosphate pyrophosphokinase 100 2.00 × 10−38 5MP7_A
32 14,979 14,695 Pyrophosphatase 98.22 2.80 × 10−5 2GTA_C
52 22,228 21,368 Membrane protein 100 2.80 × 10−29 7VHP_G
57 24,326 23,766 lemA protein 99.82 1.30 × 10−18 2ETD_A
59 26,185 25,436 Serine/Threonine phosphatases 99.95 1.20 × 10−25 1G5B_B
63 28,284 27,661 DNA polymerase III subunit epsilon 99.42 1.50 × 10−11 5M1S_D
81 34,516 34,310 Thioredoxin glutathione reductase 98.23 7.60 × 10−5 7B02_A
82 36,153 35,326 Putative ATP-dependent Clp protease proteolytic subunit 99.72 6.80 × 10−16 1TG6_E
83 36,371 36,150 Deoxynucleoside monophosphate kinase 99.06 2.20 × 10−9 1DEK_B
88 38,453 37,983 Ribonuclease H 99.73 5.90 × 10−15 3H08_B
89 39,040 38,522 Dihydrofolate reductase 99.91 3.50 × 10−23 3CSE_A
90 40,222 39,101 Ribonucleotide reductase R2 100 9.80 × 10−53 1MXR_A
91 42,660 40,411 Ribonucleoside-diphosphate reductase 1 subunit alpha 100 1.80 × 10−113 2XAP_C
93 43,815 43,324 Phosphate starvation-inducible protein 99.51 6.70 × 10−12 3B85_A
94 44,031 43,831 RNA complex 98.27 2.20 × 10−6 2XZO_A
100 48,501 46,093 DNA polymerase 100 4.80 × 10−73 4XVK_A
102 48,947 48,792 DNA primase 98.24 3.40 × 10−6 5VAZ_A
104 50,009 49,644 DnaB-like replicative helicase 99.39 4.70 × 10−11 8DUE_B
109 51,631 51,071 snRNA-activating protein complex subunit 4 99.35 3.20 × 10−10 7XUR_A
110 52,415 51,624 DNA ligase 99.97 8.80 × 10−29 1DGS_B
111 53,608 52,598 DNA ligase 100 8.00 × 10−73 4GLX_A
112 53,819 53,640 DNA binding protein 99.52 4.20 × 10−13 5A4O_A
115 54,925 54,623 Homing endonuclease-DNA 99.42 4.30 × 10−13 1A73_A
117 55,801 55,109 DNA binding protein 99.04 1.60 × 10−8 2LVS_A
122 59,955 57,031 Eukaryotic initiation factor 99.77 2.00 × 10−16 5ZC9_A
127 61,708 63,414 + Anaerobic ribonucleotide-triphosphate reductase 100 1.70 × 10−54 1HK8_A
129 63,875 64,339 + Outer membrane protein A 99.43 4.60 × 10−11 3NB3_B
136 66,830 67,258 + Endonuclease V 100 5.40 × 10−43 2END_A
152 69,872 70,051 + Antitermination protein 97.97 1.60 × 10−5 7UBN_Q
175 74,745 74,855 + 30S ribosomal protein 98.9 1.10 × 10−8 2K4X_A
186 78,078 78,416 + Circadian Clock Protein 98.81 3.30 × 10−8 1R8J_B
187 78,413 79,444 + Transcriptional regulator NadR 100 4.20 × 10−35 1LW7_A
188 79,441 80,118 + Nicotinamide riboside transporter 100 1.40 × 10−42 4QTN_A
197 83,112 83,480 + DNA binding protein 99.37 2.80 × 10−12 2A1K_B
198 83,707 84,393 + Nuclease SbcCD subunit D 99.66 8.20 × 10−15 7DOG_B
204 86,807 87,541 + Exodeoxyribonuclease 100 1.80 × 10−31 5HML_B
205 87,726 88,226 + Deoxyuridine 5′-triphosphate nucleotidohydrolase 99.95 3.00 × 10−25 3MDX_A
209 89,272 89,156 Muramidase Lysozyme-like Peptidoglycan-binding 98.76 5.90 × 10−8 6V3Z_B
210 89,551 89,420 Muramidase Lysozyme-like Peptidoglycan-binding 99.21 2.20 × 10−11 6V3Z_B
218 93,068 92,955 Large tail fiber protein P34 98.11 8.60 × 10−6 4UXF_C
224 95,866 95,729 Probable central straight fiber 98.97 6.50 × 10−10 7ZQB_i
225 96,037 95,885 Probable central straight fiber 98.83 9.60 × 10−10 7ZQB_i
228 97,213 97,067 Probable central straight fiber 99.72 3.00 × 10−18 7ZQB_i
230 98,169 97,900 Baseplate 99.31 2.80 × 10−11 8GTC_O
233 98,787 98,620 Tip attachment protein 99.04 5.10 × 10−10 8IYK_J
234 99,393 98,908 Probable baseplate hub protein 99.66 1.90 × 10−15 7ZHJ_c
238 100,667 100,473 Distal tail protein 99.06 1.30 × 10−9 6F2M_C
253 106,959 106,681 Tail tube protein 99.51 7.40 × 10−14 5NGJ_A
254 107,559 107,401 Tail tube protein 98.92 2.70 × 10−9 5NGJ_A
258 109,315 109,010 Neck protein 99.46 1.10 × 10−12 6TE9_C
259 110,749 109,370 Major capsid protein 100 1.10 × 10−30 6TSU_J4
264 112,437 112,033 Portal protein 99.65 1.90 × 10−14 8FQL_E
265 112,737 112,504 Portal protein 99.45 1.10 × 10−12 8FQL_E
267 113,538 113,413 Terminase large subunit 98.47 4.60 × 10−7 2WBN_A
phage vB_AdhM_TS9
2 1373 516 HNH restriction endonuclease 98.93 6.00 × 10−9 3M7K_A
3 2597 1494 RNA ligase 100 5.30 × 10−47 6VTB_A
6 3846 3484 Deoxycytidylate deaminase 99.77 4.50 × 10−17 2W4L_D
11 5550 5029 Ribonuclease HI 98.6 3.10 × 10−5 2E4L_A
20 7598 8854 + AAA ATPase 100 8.80 × 10−46 8BNS_B
21 8871 10,661 + DNA primase/helicase 100 1.70 × 10−53 6N7I_D
22 10,673 12,955 + DNA polymerase 100 1.30 × 10−50 1X9M_A
23 13,082 13,474 + HNH homing endonuclease 99.74 9.20 × 10−17 1U3E_M
24 13,686 13,892 + DNA polymerase 97.95 2.40 × 10−5 1X9M_A
25 13,931 14,488 + Helix-destabilizing protein 99.85 5.00 × 10−20 1JE5_A
28 17,556 15,607 Tailspike protein 99.92 2.20 × 10−21 6NW9_A
29 18,558 17,695 Ribosome 99.55 3.90 × 10−14 7ANE_at
30 19,162 18,899 Ribosome 99.56 2.40 × 10−14 7ANE_at
33 20,422 20,012 Tail fiber assembly protein 99.41 2.10 × 10−11 5YVQ_B
35 21,764 21,150 Baseplate wedge protein 99.89 2.40 × 10−21 7KH1_B2
36 23,276 21,777 Baseplate wedge protein 100 7.60 × 10−38 7KH1_I5
38 26,234 25,623 Baseplate 99.82 5.30 × 10−19 7YFZ_p
39 26,879 26,244 Baseplate 99.95 4.10 × 10−26 4RU3_A
40 27,875 26,961 Baseplate 100 3.50 × 10−29 8EON_E
41 28,289 27,963 Baseplate 99.92 5.90 × 10−24 7YFZ_h
42 29,017 28,289 Baseplate complex 99.92 1.00 × 10−23 7KH1_D3
45 32,552 31,395 DUF4379 domain-containing protein 99.85 1.40 × 10−20 6YXX_E2
48 34,011 33,538 Sheath-tube 99.97 6.40 × 10−29 8HDW_n
49 35,430 34,036 Tail sheath protein 100 4.90 × 10−57 7KJK_C6
50 36,034 35,492 E217 gateway protein 99.94 6.60 × 10−25 8FVH_b
51 36,463 36,044 Head completion protein 99.74 6.10 × 10−17 7KJK_A4
55 39,046 38,006 Major capsid protein 100 2.90 × 10−35 6XGP_B
56 39,443 39,066 Head decoration protein 99.71 5.70 × 10−16 1TD4_A
59 42,170 41,184 DUF4379 domain-containing protein 99.67 3.30 × 10−16 6YXX_E2
60 43,797 42,250 Portal protein 100 8.30 × 10−37 5NGD_D
61 44,884 43,829 Large subunit terminase 99.75 1.20 × 10−16 5OE8_B
62 45,891 45,199 HNH homing endonuclease 99.91 9.40 × 10−24 1U3E_M
63 46,728 46,330 Large subunit terminase 99.42 2.60 × 10−12 5OE8_B
65 48,423 47,194 DUF4379 domain-containing protein 99.9 1.80 × 10−23 6YXX_E2
70 50,487 49,771 Serine/Threonine protein phosphatases 99.95 2.60 × 10−25 1G5B_B
72 51,548 50,973 Phage terminase large subunit 99.78 4.30 × 10−17 7KS4_B
76 54,958 53,627 Apicoplast DNA polymerase 99.47 1.30 × 10−12 7SXQ_A
79 56,048 56,602 + ATP-dependent protease subunit 99.6 3.80 × 10−14 6KR1_J
89 60,225 61,226 + DUF4379 domain-containing protein 99.66 8.90 × 10−16 6YXX_E2
91 61,794 62,804 + DUF4379 domain-containing protein 99.65 8.70 × 10−16 6YXX_E2
95 63,585 64,844 + DUF4379 domain-containing protein 99.9 4.70 × 10−23 6YXX_E2
98 65,569 65,874 + Putative pyrophosphohydrolase 99.67 4.80 × 10−15 4YF1_C
101 66,802 68,175 + DNA ligase 100 4.10 × 10−62 6DT1_E
102 68,190 68,552 + Hydrolase 99.4 3.70 × 10−11 2Q73_B
107 69,697 70,458 + HNH homing endonuclease 99.07 2.40 × 10−10 1U3E_M
108 70,448 71,497 + Ribonuclease H 99.94 1.00 × 10−25 3H7I_A
116 73,445 74,005 + Crossover junction endodeoxyribonuclease 99.93 1.00 × 10−23 7XHJ_B
118 74,196 74,768 + Recombination endonuclease VII 100 6.30 × 10−33 1E7L_B
122 75,504 76,004 + Spore cortex-lytic enzyme 99.93 5.70 × 10−24 4F55_A
125 76,580 77,542 + DNA polymerase III subunit epsilon 99.35 7.90 × 10−12 5M1S_D
127 78,015 78,590 + 5′-Nucleotidase 99.88 4.80 × 10−21 4L57_A
130 79,134 79,979 + Thymidylate synthase 100 1.90 × 10−57 3V8H_B
131 80,000 80,548 + Dihydrofolate reductase 99.93 4.50 × 10−23 8SSX_A
133 81,217 82,260 + DUF4379 domain-containing protein 99.64 2.40 × 10−15 6YXX_E2
138 83,439 85,700 + Ribonucleoside-diphosphate reductase 1 subunit alpha 100 4.10 × 10−112 2XAP_C
139 85,754 86,842 + Ribonucleotide reductase 100 9.30 × 10−53 1MXR_A
140 86,916 87,191 + Circadian clock protein 99.01 3.50 × 10−8 5JWO_B
141 87,288 89,378 + Anaerobic ribonucleoside-triphosphate reductase 100 5.30 × 10−70 8P28_A
142 89,375 89,848 + Molybdenum cofactor biosynthesis protein A 99.45 9.10 × 10−13 1TV8_A
148 92,147 92,887 + Phosphate starvation-inducible protein 99.89 8.00 × 10−20 3B85_A
155 95,869 96,417 + lemA protein 99.85 1.00 × 10−19 2ETD_A
158 97,221 98,105 + Proteasome 99.61 4.40 × 10−14 2JAY_A
196 114,449 113,181 Apicoplast DNA polymerase 99.55 1.30 × 10−13 7SXQ_A
phage vB_AdhM_DL
1 346 2 Major capsid protein 99.21 9.00 × 10−11 7SJ5_A
2 743 366 Head decoration protein 99.72 2.80 × 10−16 1TD4_A
4 2312 1827 Prohead core protein protease 92.43 3.9 5JBL_B
5 3470 2484 DUF4379 domain-containing protein 99.67 3.30 × 10−16 6YXX_E2
6 5097 3550 Portal protein 100 8.30 × 10−37 5NGD_D
7 6184 5129 Large subunit terminase 99.75 1.20 × 10−16 5OE8_B
8 7191 6499 HNH homing endonuclease 99.91 9.90 × 10−24 1U3E_M
9 8028 7630 Large subunit terminase 99.42 2.60 × 10−12 5OE8_B
11 9729 8494 DUF4379 domain-containing protein 99.9 5.40 × 10−23 6YXX_E2
16 11,787 11,071 Serine/Threonine protein phosphatases 99.95 2.60 × 10−25 1G5B_B
18 12,848 12,273 Phage terminase large subunit 99.78 4.30 × 10−17 7KS4_B
23 16,258 14,927 Apicoplast DNA polymerase 99.47 1.30 × 10−12 7SXQ_A
26 17,348 17,902 + ATP-dependent protease subunit 99.56 1.70 × 10−13 6KR1_J
36 21,525 22,526 + DUF4379 domain-containing protein 99.66 8.90 × 10−16 6YXX_E2
38 23,094 24,104 + DUF4379 domain-containing protein 99.65 7.10 × 10−16 6YXX_E2
42 24,885 26,144 + DUF4379 domain-containing protein 99.91 1.20 × 10−23 6YXX_E2
44 26,496 26,726 + DUF4379 domain-containing protein 99.91 1.20 × 10−23 6YXX_E2
45 26,869 27,174 + Putative pyrophosphohydrolase 99.66 5.40 × 10−15 4YF1_C
48 28,102 29,475 + DNA ligase 100 4.10 × 10−62 6DT1_E
54 30,997 31,758 + HNH homing endonuclease 99.07 2.40 × 10−10 1U3E_M
55 31,748 32,797 + Ribonuclease H 99.94 1.00 × 10−25 3H7I_A
63 34,745 35,305 + Crossover junction endodeoxyribonuclease 99.93 1.00 × 10−23 7XHJ_B
65 35,496 36,068 + Recombination endonuclease VII 100 5.60 × 10−33 1E7L_B
69 36,804 37,304 + Spore cortex-lytic enzyme 99.93 5.20 × 10−24 4F55_A
72 37,880 38,842 + DNA polymerase III subunit epsilon 99.35 1.10 × 10−11 5M1S_D
74 39,315 39,890 + 5′-Nucleotidase 99.88 4.80 × 10−21 4L57_A
77 40,434 41,279 + Thymidylate synthase 100 1.80 × 10−57 3V8H_B
78 41,300 41,848 + Dihydrofolate reductase 99.93 4.50 × 10−23 8SSX_A

3.9

3.9 Effect of single in pre- and post-treatment to control A. dhakensis AM growth

The lytic effect of individual phages on the growth of A. dhakensis AM was evaluated at different MOIs. Both pre-and post-treatment, the maximum cell decrease for all phages was observed during 6–12 h of incubation at all MOIs compared with the uninfected bacterial control. The pre-treatment with phages vB_AdhS_TS3, vB_AdhM_DL, and vB_AdhM_TS9 reduced the maximum bacterial count by 5.40, 6.67 and 3.91 log CFU/mL, respectively, after 6 h of incubation. In post-treatment, the maximum inactivation was achieved at 12 h with the log reduction number of 4.68, 5.25 and 4.43 log CFU/mL, respectively. The growth of bacteria cultured with phages decreased remarkably depending on the regrowth of bacteria at 48 h in all treatments (Fig. 5). When the phages were incubated in the presence of the host, the phages gradually increased and then became stable over 48 h of incubation. Based on the maximum inhibition, the combination of two phages as a phage cocktail in pre- and post-treatment with optimal MOIs was chosen, as shown in Fig. 6.

The log reduction in A. dhakensis number in pre- and post-treatment using single phage vB_AdhS_TS3, vB_AdhM_DL and vB_AdhM_TS9. The data were expressed as mean ± SD. All assays were carried out in triplicates.
Fig. 5
The log reduction in A. dhakensis number in pre- and post-treatment using single phage vB_AdhS_TS3, vB_AdhM_DL and vB_AdhM_TS9. The data were expressed as mean ± SD. All assays were carried out in triplicates.
The log reduction in A. dhakensis number in pre- and post-treatment groups using phage cocktail vB_AdhS_TS3, vB_AdhM_DL and vB_AdhM_TS9. The data are expressed as mean ± SD. All assays were carried out in triplicates.
Fig. 6
The log reduction in A. dhakensis number in pre- and post-treatment groups using phage cocktail vB_AdhS_TS3, vB_AdhM_DL and vB_AdhM_TS9. The data are expressed as mean ± SD. All assays were carried out in triplicates.

3.10

3.10 Effect of phage cocktail in pre- and post-treatment to control A. dhakensis AM growth

The effectiveness of the phage cocktail in the reduction of A. dhakensis AM is shown in Fig. 6. Cocktail 3, composed of phages vB_AdhM_TS9 and vB_AdhM_DL, was more effective against A. dhakensis AM than the other cocktails. Upon pre-treatment, the maximum inactivation with cocktail 3 (vB_AdhM_TS9 (MOI 1) + vB_AdhM_DL (MOI 0.1)) was 5.08 ± 0.51 log CFU/mL after 6 h of incubation compared with uninfected control. In post-treatment, the maximum reduction with cocktail 3 (vB_AdhM_TS9 (MOI 1) + vB_AdhM_DL (MOI 1)) was 4.71 ± 0.49 log CFU/mL after 12 h of incubation when compared with those of the bacterial control. Bacterial regrowth was observed at 24 h in all treatments. The phage alone was constant throughout the experiment. While phage cocktails hold promise in preventing the emergence of phage-resistant mutants, it's essential to acknowledge that prolonged incubation of phages and bacteria may lead to the development of phage-resistant strains (Malik et al., 2021). Another challenge in phage therapy is the high specificity of phages for their target bacteria. Each bacterial strain often requires a specific phage, and identifying the right phage for a particular infection can be a time-consuming process. In urgent or novel situations, this may not always be feasible. Thus, we have investigated the combination of phages with antibiotics as a strategy to mitigate potential limitations and expand the scope of treatment.

3.11

3.11 A. dhakensis growth inhibition by phage cocktail and antibiotics combination

To establish the phage-antibiotic synergy (PAS) effect, we determined the bacterial inactivation by three combinations of phage cocktails with amoxicillin at sub-MIC (32 μg/mL) in different volumes (200 µL and 20 mL). In the presence of amoxicillin and phage alone, the antibiotic- and phage-resistant variants rapidly grew after 6 h of incubation. In the pre-treatment, the combination of phage cocktail 1 or 2 with amoxicillin at sub-MIC resulted in complete inhibition during 48 h and 12 h in a volume of 200 µL and 20 mL, respectively (Fig. 7). At a volume of 20 mL, a significant reduction in bacterial numbers was observed when treated with a combination of phage cocktail 1 or 2 and sub-MIC amoxicillin at 48 h of incubation (p < 0.05). After post-treatment, the combination of phage cocktail 1 or 2 with amoxicillin at sub-MIC resulted in complete inhibition for 48 h in 200 µL (Fig. 7). However, only partial inhibition was observed after 12 h at a volume of 20 mL. Bacterial regrowth gradually increased after 12 h, and no significant reduction in viable bacteria was observed after 48 h of incubation compared to the phage cocktail of antibiotics alone. In this study, the bacterial concentration in this treatment (1 × 105 CFU/mL) was much higher than in natural bacterial contamination. Moreover, this study was performed in a higher volume of medium (20 mL), which may reduce the interaction between phages and/or antibiotics before reaching the bacteria. However, phage cocktails 1 and 2 decreased the CFU 1.2–1.7 log CFU/mL compared to the control and other groups treated individually after incubation for 48 h. Our study strongly suggests that the synergistic antibacterial effects of antibiotics and phages should be performed in the early stages when the bacterial number is low. The first use of the phage–antibiotic synergy (PAS) strategy was described by Comeau et al. (2007). Sublethal concentrations of antibiotics may help lytic bacteriophages reproduce rapidly and promote their antibacterial effects. Additionally, in combination with antibiotics, phages have multiple mechanisms to augment antibiotic effectiveness. They can break down bacterial biofilms using phage enzymes such as depolymerases and lysins, rendering bacteria more susceptible to antibiotics (Liu et al., 2022b). Additionally, this combination therapy can reduce the likelihood of bacterial resistance development to both phages and antibiotics (Segall et al., 2019). Our study underscores the potential of phage-based approaches in combating A. dhakensis and demonstrates the efficacy of combination therapy utilizing phage cocktails and sublethal antibiotic concentrations. Furthermore, the ability of phages to target antibiotic-resistant strains, which are often challenging to treat with antibiotics alone, adds to the value of this approach. By focusing on A. dhakensis, we provide insights that extend to the broader challenge of antimicrobial resistance, emphasizing the importance of exploring innovative strategies to combat this critical global health issue.

Effect of phage cocktail and amoxicillin combination at 1/2 MIC against A. dhakensis AM. The bar graph represents the bacterial concentration (log CFU/mL), and the line graph represents the phage concentration (log PFU/mL). The data are expressed as mean ± SD. All assays were carried out in triplicates. Each lowercase label corresponds to a significantly different (p < 0.05) bacterial concentration within each time point. Capital letters denote significantly distinct (p < 0.05) bacterial concentrations and time points compared to each other time point within the same conditions.
Fig. 7
Effect of phage cocktail and amoxicillin combination at 1/2 MIC against A. dhakensis AM. The bar graph represents the bacterial concentration (log CFU/mL), and the line graph represents the phage concentration (log PFU/mL). The data are expressed as mean ± SD. All assays were carried out in triplicates. Each lowercase label corresponds to a significantly different (p < 0.05) bacterial concentration within each time point. Capital letters denote significantly distinct (p < 0.05) bacterial concentrations and time points compared to each other time point within the same conditions.
Effect of phage cocktail and amoxicillin combination at 1/2 MIC against A. dhakensis AM. The bar graph represents the bacterial concentration (log CFU/mL), and the line graph represents the phage concentration (log PFU/mL). The data are expressed as mean ± SD. All assays were carried out in triplicates. Each lowercase label corresponds to a significantly different (p < 0.05) bacterial concentration within each time point. Capital letters denote significantly distinct (p < 0.05) bacterial concentrations and time points compared to each other time point within the same conditions.
Fig. 7
Effect of phage cocktail and amoxicillin combination at 1/2 MIC against A. dhakensis AM. The bar graph represents the bacterial concentration (log CFU/mL), and the line graph represents the phage concentration (log PFU/mL). The data are expressed as mean ± SD. All assays were carried out in triplicates. Each lowercase label corresponds to a significantly different (p < 0.05) bacterial concentration within each time point. Capital letters denote significantly distinct (p < 0.05) bacterial concentrations and time points compared to each other time point within the same conditions.

Our study demonstrates that phage-based approaches are an attractive way to inactivate A. dhakensis in vitro. The cocktail of three different bacteriophages (phage vB_AdhS_TS3, vB_AdhM_DL and vB_AdhM_TS9) revealed promising in vitro lytic activity on A. dhakensis. Furthermore, the combination therapy using phage cocktails and antibiotics showed greater promise compared with either therapy alone. Moreover, combination therapy can also prevent the development of resistant mutants that would otherwise develop rapidly when exposed to antibiotics or phages. This demonstrates that using phages as an adjuvant with a sublethal concentration of antibiotics is an effective therapeutic strategy.

Acknowledgements

This work was supported by Fundamental Fund (2021), Thailand Science Research and Innovation (TSRI) (grant number 031/2564), and graduate school fund, Faculty of Science, Srinakarinwirot University.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Appendix A

Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jksus.2024.103111.

Appendix A

Supplementary data

The following are the Supplementary data to this article:

Supplementary data 1

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