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Genetic determinants of silver nanoparticle resistance and the impact of gamma irradiation on nanoparticle stability

BMC Microbiology volume 25, Article number: 18 (2025) Cite this article

Abstract

Background

One of the main issues facing public health with microbial infections is antibiotic resistance. Nanoparticles (NPs) are among the best alternatives to overcome this issue. Silver nanoparticle (AgNPs) preparations are widely applied to treat multidrug-resistant pathogens. Therefore, there is an urgent need for greater knowledge regarding the effects of improper and excessive use of these medications. The current study describes the consequences of long-term exposure to sub-lethal concentrations of AgNPs on the bacterial sensitivity to NPs and the reflection of this change on the bacterial genome.

Results

Chemical methods have been used to prepare AgNPs and gamma irradiation has been utilized to produce more stable AgNPs. Different techniques were used to characterize and identify the prepared AgNPs including UV-visible spectrophotometer, Fourier Transform Infrared (FT-IR), Dynamic light scattering (DLS), and zeta potential. Transmission electron microscope (TEM) and Scanning electron microscope (SEM) showed 50–100 nm spherical-shaped AgNPs. Eleven gram-negative and gram-positive bacterial isolates were collected from different wound infections. The minimum inhibitory concentrations (MICs) of AgNPs against the tested isolates were evaluated using the agar dilution method. This was followed by the induction of bacterial resistance to AgNPs using increasing concentrations of AgNPs. All isolates changed their susceptibility level to become resistant to high concentrations of AgNPs upon recultivation at increasing concentrations of AgNPs. Whole genome sequencing (WGS) was performed on selected susceptible isolates of gram-positive Staphylococcus lentus (St.L.1), gram-negative Klebsiella pneumonia (KP.1), and their resistant isolates St.L_R.Ag and KP_R.Ag to detect the genomic changes and mutations.

Conclusions

For the detection of single-nucleotide polymorphisms (SNPs) and the identification of all variants (SNPs, insertions, and deletions) in our isolates, the Variation Analysis Service tool available in the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) was used. Compared to the susceptible isolates, the AgNPs-resistant isolates St.L_R.Ag and KP_R.Ag had unique mutations in specific efflux pump systems, stress response, outer membrane proteins, and permeases. These findings might help to explain how single-nucleotide variants contribute to AgNPs resistance. Consequently, strict regulations and rules regarding the use and disposal of nano waste worldwide, strict knowledge of microbe-nanoparticle interaction, and the regulated disposal of NPs are required to prevent pathogens from developing nanoparticle resistance.

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Introduction

Antimicrobial resistance (AMR) represents a top global threat to healthcare systems and national economies in the 21st century [1]. The fact that AMR was responsible for 1.27 million deaths worldwide in 2019 [2]. Several groups are at higher risk including, immunocompromised patients or those with underlying conditions such as diabetes, cancer, autoimmune disease, respiratory disorders, Human immune deficiency disease HIV, or aging [3,4,5]. The World Health Organization (WHO) adopted a strategy to raise awareness of AMR by launching surveillance systems [6] and implementing antimicrobial stewardship programs to cut down inappropriate use of antibiotics and improve access to appropriate treatment. The 2022 Global Antimicrobial Resistance and Use Surveillance System highlights alarming resistance rates among pathogenic bacteria including methicillin-resistant Staphylococcus aureus, cephalosporin-resistant Escherichia coli, and multidrug-resistant Klebsiella pneumoniae [7]. Multiple antibiotic discoveries have been reported since the use of the first antibiotic, penicillin. Regretfully, the emergence of antimicrobial resistance outpaces the reveal or development of novel antimicrobial treatments [8].

Nanomaterials have recently emerged as a weapon against bacteria resistant to many drugs. Metal and metal oxide nanoparticles (NPs) are one of the most studied nanomaterials against multidrug-resistant bacteria [9]. Metals such as silver, titanium, gold, aluminum, copper, and zinc can be used to create such NPs. Numerous evaluations have emphasized the significance of nanotechnology, which is undoubtedly incredibly versatile and has great potential in combating microbial diseases [10, 11]. The healthcare industry has been greatly impacted by the antimicrobial ability of AgNPs, which are used to create bactericidal coatings for medical equipment. Additionally, they can be found in cosmetics, packaging materials, and textiles [12].

The preparation of AgNPs was conducted through physical and chemical procedures [13]. The utilization of gamma radiation-induced techniques for NP synthesis offers distinct advantages over traditional chemical methods [14]. These advantages include the ability to control the shape and size of NPs, the use of non-toxic or low-toxic precursors along with environmentally friendly solvents, reduced reliance on chemical reagents, minimal generation of hazardous waste, and limited formation of reaction byproducts. This radiation-induced approach presents a more environmentally friendly pathway for NP preparation [15].

A significant proportion of antibiotic resistance mechanisms become redundant due to the direct binding of NPs to bacterial cell walls, inducing the bactericidal effect without the need to breach the cell membrane. Consequently, the effectiveness of NPs against bacteria is more likely to surpass that of antibiotics [16]. One of three models explains the antibacterial mechanism of action of NPs against bacterial isolates, oxidative stress induction [17], nonoxidative processes [18] and metal ion release [19]. Nevertheless, prolonged exposure to sub-lethal biocidal levels may induce efflux pump over-expression and the emergence of bacterial resistance [20]. Numerous harmful bacteria have already been found to be resistant to silver ions. Regretfully, current research has shown that the development of microbial resistance has also been facilitated by the chemical adaptability of NPs [21, 22].

Next generation sequencing (NGS) technology is becoming more and more common for WGS. With a unified, efficient workflow, NGS offers a fast, high throughput technology. One can utilize this technique to identify single-base pair mutations in bacteria belonging to the same species [23]. By offering a comprehensive database of genetic polymorphisms, especially single-nucleotide polymorphisms (SNPs), this method offers higher sequence resolution than conventional techniques. Additionally, WGS links pathogen biology, genome structure, genome evolution, and gene content to epidemiology. This connection sheds light on biological markers including virulence factors and antibiotic resistance [24].

Finding SNPs in bacterial genomes is important for tracking the evolution of resistant clinical isolates and establishing the relationship between them. Furthermore, genome sequencing simplifies the process of screening for specific changes or alterations within resistant genes when comparing them to susceptible or control strains of the same bacterial species [25, 26].

Unfortunately, recent research has shown that the chemical adaptability of NPs has also played a role in the rise of microbial resistance [21]. This study provides insights into the emerging microbial diseases that can induce resistance to NPs and pose a serious risk to human health. This study scrutinized single-nucleotide alterations within AgNPs-resistant and nonresistant gram-positive and gram-negative bacterial isolates. The nsSNPs identified in the AgNPs-resistant isolates have the potential to change the amino acid sequence, potentially impacting the function of the resulting protein expression. This alteration can provoke diverse resistance mechanisms.

Materials and methods

Preparation of AgNPs

Silver nanoparticles were produced by chemical reduction as previously described by Turkevich, Lee, and Meisel [27, 28]. A solution of 5 × 10− 3 M silver nitrate AgNO₃ (100 mL) was used as Ag⁺₁ ions precursor. It was added portion-wise to 300 mL of vigorously stirred ice-cold 2 × 10− 3 M NaBH4 (Sodium borohydride) as a mild reducing agent. A solution of 1% polyvinyl pyrrolidone (PVP) (50 mL) was added during the reduction as a stabilizing agent. The mixture was then boiled for 1 h to decompose any excess of NaBH4. The final volume was adjusted to 500 mL. As the Ag⁺ ions were reduced to Agº NPs, the solution’s color gradually changed to a yellowish-brown.

Effect of gamma irradiation on AgNPs

Silver nanoparticles were irradiated with 5 KGy and 10 KGy gamma irradiation using a Cobalt 60 source (Gamma cell 4000-A-India) at room temperature. A non-irradiated sample was used as a control. The irradiation procedure was done at the National Center for Radiation Research and Technology (NCRRT).

Characterization of AgNPs

After gamma irradiation, physicochemical characterization was performed using UV-visible spectrophotometer (JASCO V-560 UV/Vis, Japan) as a function of wavelength in the range of 200–900 nm, operating at a resolution of 1 nm. Additionally, Fourier Transform Infrared Spectroscopy (FT-IR) spectra were recorded using an infrared spectrometer (JASCO FT/IR-3600, Japan) in the range of 500–4000 cm− 1 using the KBr pellet technique. The FT-IR analysis examined the changes in AgNPs before and after exposure to gamma irradiation. The average particle size, size distribution, and zeta potential were evaluated by the PSS-NICOMP 380-ZLS particle sizing system (St. Barbara, California, USA) at NCRRT. The size and shape of the prepared NPs were documented by using the transmission electron microscope (TEM) model JEOL electron microscope (JEM-100 CX, Japan), at NCRRT. Drop-coating NPs onto carbon-coated TEM grids was used to prepare the grids for TEM. After allowing the film on the TEM grids to dry, the excess solution was wiped off with blotting paper. The surface morphologies and size of the NPs were examined by Scanning Electron Microscope (SEM) (ZEISS-EVO-MA10, Germany) attached with energy-dispersive X-ray spectra (EDX-BRUKER Nano GmbH, D-12489,410-M, Berlin, Germany) to detect the basic makeup of the prepared AgNPs.

Bacterial isolation and identification

Eleven bacterial isolates were recovered from wound infections. Protein fingerprinting was performed using Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) with the Microflex MALDI-TOF MS system (Bruker Daltonics, Bremen, Germany) at 57,357 Hospital in Cairo, Egypt. The analysis and comparison were conducted using MALDI BioTyper 2.0 software and the MALDI BioTyper database, with species-level identification determined by a score of ≥ 2.0 according to the manufacturer’s criteria. Isolates were preserved in Muller Hinton Broth with 30% v/v glycerol and stored at -80ºC until needed [29, 30].

MIC determination of AgNPs against the tested bacterial isolates

The minimum Inhibitory Concentration of AgNPs was determined by the Agar Dilution method according to the Clinical and Laboratory Standard Institute CLSI 2011 & 2018 [31, 32]. Bacterial isolates were grown overnight on Muller Hinton Agar (MHA) (HiMedia) plates at 35 °C before being used. Two-fold serial dilutions of AgNPs (0.1–100 µg/ml) were prepared and incorporated into the agar medium, with each plate containing a different concentration of the AgNPs. 0.1 µL were spot inoculated over the circles marked on agar plates from an initial bacterial density of each microbial isolate 1 × 108 CFU/ml. After incubation for 24 h at 37˚C, the MIC was visually estimated on the surface of MHA plates. The MIC is the lowest concentration of antimicrobial agents that completely visually inhibits the 99% growth of the microorganisms. All the experiments were done in triplicates on three different days. All isolates were utilized as positive controls on MHA media without AgNPs.

Induction and development of bacterial resistance to AgNPs

Induction of bacterial resistance was attempted by repeatedly culturing the isolates in growth media with sub-lethal doses of AgNPs, at concentrations sub-MIC where growth was detected. Each bacterial isolate underwent twenty successive cultivation steps in media containing sub-MIC of AgNPs. AgNPs stock solutions were prepared at concentrations ranging from 1.25 to 100 µg/ml, and long-term exposure involved gradually increasing the MIC of AgNPs. The MIC values after the 20th passage were visually estimated on the surface of MHA plates after 24 h of incubation and compared to the MIC values before the passages. The stability of AgNPs resistance after the 20th passage was assessed by subculturing the resistant isolates daily for more five passages. All isolates were used as negative controls in each passage, using MHA media without AgNPs.

DNA extraction and whole genome sequencing

DNA of four bacterial isolates (gram-positive Staphylococcus lentus St.L.1, gram-negative Klebsiella pneumonia KP.1, and their AgNPs resistant isolates St.L_R.Ag and KP_R.Ag, respectively) were extracted using QIAamp DNA Mini Kit (Qiagen, Germany) according to the manufacturer’s protocol. The concentration of the extracted DNA was determined with a Qubit 3.0 Fluorometer and the HSDNA Qubit™ Assay Kit (Q32854, ThermoFisher Scientific Inc, USA). Bacterial DNA samples at a concentration of 20 ng/µl were done at Clinilab (Cairo, Egypt) for whole-genome sequencing.

Sequencing, preprocessing, assembly, and genome annotation

The extracted DNAs were sequenced using the Ion torrent proton platform, Thermofischer Scientific Inc, USA. Single–end chemistry was used with an average library insert size 150–200 bp. The DNA libraries preparation from the extracted DNAs were performed using Ion Xpress™ plus fragment Library Kit, cat no. 4,471,269, Thermofischer Scientific Inc, USA as per the manufacturer’s instructions. Adapter sequences and low-quality reads were removed with a quality score filter of > 30. DNA libraries were quantified using Ion Library TaqMan™ Quantification kit, cat no. 4,468,802. Template preparation kit and sequencing were performed using Ion PI™ HI-Q™ Chef Kit (cat. No. A27198), Thermofischer Scientific Inc, USA.

High-quality sequence reads were de novo assembled using SPAdes assembler (v3.12.0), which is part of the Bacterial and Viral Bioinformatics Resource Center (BV-BRC/ PATRIC database), (https://www.bv-brc.org/) [33] with a minimum contig length of 300 bp.The assemblies were mapped against the control isolate to evaluate the core genome average identities and completeness. Assembled FASTA files were annotated by the BV-BRC (version 3.27.0) annotation service which uses the RASTtk (Rapid Annotation using Subsystem Technology) algorithm server for gene predictions and annotations [34, 35]. The prediction relied on the existing annotation resources such as Coding DNA Sequences (CDS) and proteins.

Genome comparisons and analysis of single nucleotide polymorphisms

The Proteome Comparison Service available in BV-BRC was used to perform protein sequence-based genome comparison between the AgNPs resistant isolates and their corresponding reference genomes using bidirectional BLASTP. The proteome comparison results are displayed as an interactive circular genome view with color-coding for protein percent identity relative to the best hit on the reference genome.

For the detection of SNPs and the identification of all variants (SNPs, insertions, and deletions) in the tested isolates, we used the Variation Analysis Service tool available in BV-BRC. The sequencing reads of the AgNPs resistant isolates KP_R.Ag and St.L_R.Ag were mapped to their corresponding reference genome KP.1 and St.L.1 respectively, using LAST software (Frith et al. 2010). High-confidence SNP variants data sets were created by FreeBayes SNP caller (Marth et al. 1999) by applying a series of filters. The variants were identified and extracted using the following Parameters: the raw SNPs are filtered by SNP quality (QUAL > 10) and read depth (DP > 5) to keep only the high-quality SNPs.

Data Availability

For the two Klebsiella pneumonia isolates (KP.1 & KP_R.Ag) and the two Staphylococcus lentus isolates (St.L.1 & St.L_R.Ag) used in this study, their genome assemblies have been deposited in the National Center for Biotechnology Information (NCBI) under the Bioproject accession number: PRJNA1108055. All raw sequences were deposited in the Sequence Read Archive database under the Bioproject accession number PRJNA1109764 (https://www.ncbi.nlm.nih.gov/sra/PRJNA1109764).

Statistical methods

The mean MIC and results from antimicrobial susceptibility testing were imported into the Statistical Package for the Social Sciences (SPSS) software, version 20.0 (SPSS Inc., Chicago, IL, USA).

Results

Preparation, irradiation using gamma radiation, and characterization of AgNPs

The chemical synthesis of AgNPs resulted in a yellowish-brown solution. AgNPs were exposed to 5 kGy and 10 kGy gamma irradiation exposure levels. The structural assessment of AgNPs was done by analyzing the NPs before and following exposure to gamma irradiation using UV-visible spectrophotometry and FTIR analysis techniques. The UV-visible spectrophotometric analysis of unirradiated and irradiated AgNPs showed a wavelength peak value near 400 nm (Fig. 1). After gamma irradiation, the UV analysis of AgNPs was characterized by a strong Plasmon band at 1.7 and 1.9 after 5 kGy and 10 kGy, respectively. The high Plasmon band after exposure to gamma irradiation indicated an increase in the concentration of the NPs. The chemical groups that are near AgNPs and contribute to their stability were examined by FTIR analysis. It also made it possible for us to ascertain whether the radiolytic reduction brought on by gamma irradiation had altered the functional groups in any way. The FTIR spectrum of AgNPs (Supplementary Figure S1a) showed inorganic bands 1500 –500 cm− 1 indicating an incomplete reduction of Ag+ ions in the solution. After gamma irradiation, no functional transformation was found and the inorganic band at 588 cm− 1 indicated a complete decrease of Ag+ ions to Agº and a complete stabilization of AgNPs (Supplementary Figures S1b & S1c).

Fig. 1
figure 1

A curve showing UV-visible spectrophotometer analysis of the prepared silver nanoparticles (AgNPs) before and after 5 kGy and 10 kGy gamma irradiation. All samples show wavelength peaks at 400 nm. High absorbance peaks after gamma irradiation showing 1.7 and 1.9 at 5 and 10 kGy respectively indicating increase in NPs concentrations

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The average particle size assessed by the Dynamic Light scattering DLS technique was detected to be 50–500 nm for AgNPs. AgNPs stability can be simply ascertained by logging the zeta potential value. The zeta potential value registered for AgNPs was – 24.4 mV as illustrated in Fig. 2. TEM examination of AgNPs demonstrated spherical-like particles with a nanoscale range from 50 to 100 nm with a diameter of 15 nm for AgNPs as depicted in Fig. 3.

Fig. 2
figure 2

Dynamic light scattering (DLS) and Zeta potential of the prepared silver nanoparticles (AgNPs): a) Particle size Distribution by DLS of the prepared AgNPs showing average particle size 50–500 nm b) Zeta potential for the prepared AgNPs showing – 24.4 mV indicating high stability

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Fig. 3
figure 3

Transmission Electron Microscope (TEM) images of the prepared silver nanoparticles AgNPs at different nanoscales show a spherical shape and an average diameter of 15 nm

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SEM image explained the surface morphology of AgNPs which were pseudo-spherical shaped, and their size varied from 15 nm Fig. 4a. The homogeneously dispersed and well-stabilized nature of the synthesized AgNPs is also evident from the SEM pictures. The EDX mapping gives an idea about the basic examination of the synthesized NPs (Fig. 4b and c). Additional peaks seen in the EDX profile were carbon biomolecules implicated in the capping of these NPs’ surfaces, and the profile highlighted a significant signal for the presence of silver atoms.

Fig. 4
figure 4

Scanning Electron Microscope (SEM), Energy-Dispersive X-ray spectra (EDX), and mapping of the prepared silver nanoparticles (AgNPs): (a) SEM images at different magnifications showing spherical shaped particles and average diameter 96 nm and 141 nm (b) EDX spectrum of the prepared NPs showing silver and carbon 100% carbon and silver mass (c) Elemental mapping of the prepared AgNPs showing silver and carbon signals

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Bacterial isolation and identification

A total of eleven bacterial isolates were recovered from wound infections and then identified by MALDI-TOF (Supplementary Table S1). Two Escherichia coli isolates (EC.1 and EC.2), two Staphylococcus lentus isolates (St.1 and St.2), two Klebsiella pneumonia isolates (KP.1 and KP.2), two Pseudomonas aeruginosa isolates (Ps.1 and Ps.2), Acinetobacter baumannii (AB), Stenotrophomonas maltophilia (St.M) and Staphylococcus aureus (St.A) were identified. For MALDI-TOF MS-based bacterial ID in Clinical Microbiology Laboratories, the MALDI Biotyper system was used. (Bruker Daltonics; https://www.bruker.com/en/products-and-solutions/mass-spectrometry/maldi-tof.html).

A scoring system was used to express the pattern-matching results. A score of less than 1.7 was considered an unreliable ID, while a score of more than 2.0 was considered a species-level result. All tested bacterial isolates proved to match species level score > 2.

MIC determination of AgNPs against the tested bacterial isolates

The antimicrobial effectiveness of AgNPs was determined by the standard methods of the CLSI 2011&2018. Discrete amounts of AgNPs were settled from 1.5 to 50 µg/ml. MIC was performed against eleven bacterial isolates by the agar dilution method. The experiment was done on three different days. The mean MIC range and standard deviation of the AgNPs fluctuated from 3.12 µg/ml to 8.3 µg/ml (Fig. 5).

Fig. 5
figure 5

Graph showing the mean Minimum Inhibitory Concentrations (MICs) of silver nanoparticles (AgNPs) in µg/ml against the tested bacterial isolates using the Agar Dilution method. All the values are averages of triplicates and expressed as ± SD values. Abbreviations: EC.1, Escherichia coli; EC.2, Escherichia coli; KP.1, Klebsiella pneumonia; KP.2, Klebsiella pneumonia; St.L.1, Staphylococcus lentus; St.L.2, Staphylococcus lentus; St.A, Staphylococcus aureus; Ps.1, Pseudomonas aeruginosa; Ps.2, Pseudomonas aeruginosa; AB, Acinetobacter baumannii; St.M, Stenotrophomonas maltophilia

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Induction and development of bacterial resistance to AgNPs

To find out if these isolates may develop resistance to AgNPs over time, they were tested against increasing concentrations of AgNPs, and the changes in bacterial sensitivity to AgNPs were determined. MICs were determined following each of the twenty consecutive steps of bacterial growth, which involved putting each tested isolate in cultivation media comprising subinhibitory doses of AgNPs (Table 1). The results clearly shows that the isolates developed resistance after the addition of AgNPs, and this resistance increased with increasing concentrations of AgNPs, stabilizing after the 20th passage. All isolates changed their susceptibility level to AgNPs to become resistant to high concentrations of AgNPs. These findings unequivocally demonstrate that following prolonged exposure every tested bacterial isolate became resistant to AgNPs. Both EC.1 & EC.2 changed sensitivity from 6.25 to > 30 µg /ml, St.L.1 & St.L.2 changed sensitivity from 3.12 µg/ml and 8.3 µg/ml to > 30 µg/ml, KP.1 & KP.2 changed sensitivity from 6.25 µg/ml and 7.2 µg/ml to > 30 µg/ml, and St. A changed susceptibility from 6.25 to > 30 µg/ml. Both Ps.1 & Ps.2 changed susceptibility from 6.25 to > 30 µg/ml and AB and St. M changed sensitivity from 5.2 µg/ml and 2.56 µg/ml to > 30 µg/ml. To verify the reasons for changing the variants’ sensitivity, whole genome sequencing was analyzed. Only two resistant isolates were chosen to be whole genome sequenced; KP.1 and St.L.1 were picked as representatives of gram-negative and gram-positive bacterial isolates, respectively, and were subjected to next-generation sequencing.

Table 1 Determination of Minimum Inhibitory Concentration (MIC) of silver nanoparticles (AgNPs) against tested gram-positive and gram-negative isolates after each of twenty consequent culture steps
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Genome sequencing, assembly, and annotation

The sequenced data were subjected to contamination screening and the genome sizes of final assemblies were 5,785,228 Kbp for KP.1 isolate and 2,863,362 Kbp for St.L.1 isolate. The de novo assembly of genome sequence data revealed that the number of contigs (> 200 bp) was 253 for KP.1 and 148 for St.L.1 isolate. More than 80% of the reads are above the Phred quality score of 30 indicating high-quality sequencing data. These contigs were aligned to the reference genome of each isolate. The Maximum contig sizes were 250,107 bp and 245,449 bp for KP.1 and St.L.1 respectively. The GC content was 56.58% for KP.1 and 32.63% for St.L.1. A summary of the genome sequence data and assembly are shown in Table 2.

Table 2 Genomic annotation analysis of the control isolates Klebsiella pneumonia (KP.1) and Staphylococcus lentus (St.L.1)
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Genome single nucleotide polymorphism

Figure 6 shows the circular map of the two AgNPs resistant isolates KP_R.Ag and St.L_R.Ag compared to the reference genome KP.1 and St.L.1 respectively. The inner circle represents the genome of the resistant AgNPs isolate, while the outer circle represents the genome of their corresponding control isolate. The shared identity of each isolate with the reference genome is represented in different colors, which denotes the BLASTP matches between 10 and 100% nucleotide identities. The blank regions in the rings represent the areas of non-coding regions, unannotated sequences, or regions with insufficient data coverage.

Fig. 6
figure 6

Circular genomic map of silver nanoparticles (AgNPs) resistant isolates Staphylococcus lentus (St.L_R.Ag) and Klebsiella pneumonia (KP_R.Ag) compared to their reference genomes St.L.1 and KP.1, respectively. The innermost circle represents the genomes of the AgNPs resistant isolates, while the outermost circle represents the genomes of their corresponding control isolates. Colors indicate BLASTP matches from 10–100% nucleotide identities. Blank regions denote non-coding areas

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We focused our analysis on identifying nonsense SNPs that result in premature termination of functioning genes. In addition, we also screened for point mutations that lead to the change of codons or nucleotide deletions or insertions that create frameshift mutations. In resistant isolates, we first looked for nsSNPs in comparison to their reference genome. nsSNPs were identified in KP_R.Ag and St.L_R.Ag isolates compared to their reference isolate. To probe nsSNPs in genes annotated to be associated with AgNPs resistance [36] or virulence factors [37], we selectively extracted the nsSNPs that existed in divergent NPs resistant genes of resistant isolates. Many of the polymorphic genes among the resistant isolates were correlated with virulence, metabolism, and Nucleic acid regulator genes involved in the repair process. In the St.L_R.Ag isolate (Fig. 7a), our analysis identified 40 nsSNPs coding for hypothetical proteins, 29 nsSNPs coding for efflux pump proteins, and 51, 77, and 148 nsSNPs coding for regulators, metabolism-related proteins, and nucleic acid regulators, respectively. Additionally, among the genes linked to AgNPs resistance, 24 stress response genes, 3 permease proteins, and 1 outer membrane protein were discovered.

The number of nsSNPs shared within a gene across KP_R.Ag isolates are depicted in Fig. 7b. For instance, KP_R.Ag isolate that codes for hypothetical proteins included 40 nsSNPs. AgNPs efflux pump proteins are coded for by 55 nsSNPs; nucleic acid regulators, metabolism, and regulators are coded for by 78, 74, and 55, respectively. Additionally, we also found out nsSNPs in genes responsible for resistance to AgNPs, including four permeases, ten outer membrane proteins, and 18 stress response genes. Collectively, these were discovered to influence cell wall permeability and contribute to nanoparticle resistance [38].

Focusing on permeases, outer membrane proteins, and efflux pumps, as shown in Table 3, the KP_R.Ag isolate possesses 26 nucleotide deletions, causing a frameshift change that truncates the protein products. Also, it was detected that 13 nucleotide insertions led to frameshift mutations, 5 nonsynonymous variations caused stop codon loss, and 26 nonsynonymous variations resulted in missense variants with moderate SNP impact. On the other hand, as described in Table 4, St.L_R.Ag possesses 1 nucleotide deletion with high SNP impact provoking a frameshift change and 31 nonsynonymous variants that lead to missense moderate impact. The thorough list of unique nsSNPs is marked in KP_R.Ag and St.L_R.Ag compared to AgNPs susceptible isolates is shown in Supplementary Tables S2 & S3.

Table 3 Key nsSNPs identified in Klebsiella pneumonia (KP_R.Ag) resistant isolate compared to KP.1 reference genome
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Table 4 Key nsSNPs identified in the Staphylococcus lentus (St.L_R.Ag) resistant isolate compared to St.L.1 reference genome
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Further examination unveiled the presence of mutations within the Adenosine triphosphate binding cassette (ABC) transport system encompassing different groups of proteins in KP_R.Ag isolate. Among these, mutations in the ATP binding proteins were identified in LivF, MdlB, OppF, Bacteriocin/Lantibiotic efflux along with clusters related to basic amino acids, glutamines, and opines while alterations in the substrate-binding proteins were observed in, ModA, MdxE, SsuA, ZnuA, GltI, Methionine, phosphate/phosphonate periplasmic component and clusters related to maltose, polyamine and iron. Additionally, mutations affecting the permease proteins were found in MdxF, N-acetyl-D-glucosamine, iron compound, and F+ 3 siderophore transport system along with clusters related to nickel, peptides, and opines. Furthermore, mutations were detected in proteins involved in specialized transport functions, such as FeoA for ferrous iron transport, YehX for osmoprotectant transport, UrtC for urea transport, and MlaB for phospholipid binding protein transport. These mutations collectively highlight the diverse genetic changes within the ABC transport system, potentially influencing various cellular transport processes. As for the St.L_R.Ag isolate, mutations were detected in genes of PotA, PotD, PotC, YbiT, OpuA, PstB, and MsmX, along with clusters related to maltose, basic amino acids, and iron.

Within the KP_R.Ag isolate, we identified mutations in various multidrug efflux transporter proteins belonging to the RND family such as CusA, CusB, CusC, AcrAB-TolC, AcrAD-TolC, AcrEF-TolC, putative heavy metals, and membrane fusion protein. These mutations are integral to the function of the multidrug efflux pump system, enhancing the KP_R.Ag isolate’s resistance mechanism. Additionally, mutations were detected in outer membrane proteins/porins, including OmpN, OprD, PhoE, OmpC, YaeT, OprB, FimD, outer membrane protein X, and outer membrane protective antigen. These mutations play a crucial role in altering membrane permeability, thereby contributing to the KP_R.Ag isolate’s enhanced resistance capabilities.

Furthermore, the St.L_R.Ag isolate exhibited the presence of mutations within the Adenosine triphosphate binding cassette (ABC) transport system. Mutations detected in the ATP binding proteins were PotA, MsmX, PstB, OpuA, MdlB, OppF, OppD, Methionine, along with clusters related to basic amino acids, maltose, polyamine, iron, while alterations in the substrate-binding proteins were observed in, PotD, MdxE, SitA.

Several stress response proteins and genes, indicative of SOS response-induced chromosomal mutations, were also identified in both the KP_R.Ag and St.L_R.Ag isolates. In the KP_R.Ag isolate, mutations were detected in genes such as DegQ, DegS, YdcZ, HSP, GrpE, YdaA, YciE, RecF, KatE, ZraP, CopD, CueR, RcsA coregulatory RcsB, superoxide dismutase protein, and universal stress response protein G (Supplementary Table S2). Conversely, the St.L_R.Ag isolate exhibited mutations in genes including RecA, LexA, CSP, HSP, TrxB, DnaK, DnaJ, ClpB, ClpP, ClpC, ClpX, ClpE, PhoH, YicC, FtsH, GlcU, AhpC, AhpF, HslO, adenylate kinase, arsenate reductase, superoxide dismutase, and MBL-fold metallohydrolase superfamily (Supplementary Table S3). In addition, mutations were detected in genes associated with antibiotic resistance in the KP_R.Ag isolate, including albicidin, fosmidomycin, and class A beta-lactamase. Conversely, mutations were found in genes encoding tetracycline and macrolide efflux proteins in the St.L_R.Ag isolate, indicating potential alterations in antibiotic resistance mechanisms.

Fig. 7
figure 7

Functional categories of enzymes/proteins affected by mutations in bacterial genomes: a) Number of proteins in Staphylococcus lentus (St.L_R.Ag) resistant isolate b) Number of proteins in Klebsiella pneumonia (KP_R.Ag) isolate

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Discussion

As NPs are relatively new, the risk should be properly evaluated when used as antimicrobial agents. To verify the unauthorized use of NPs, strict global regulations should be developed and followed. Strict norms and regulations are in place for the use, production, and disposal of nanowaste. Much like with antibiotics, exposing organisms over time to sub-lethal dosages of NPs may hasten the evolution of resistant bacteria [21]. Sub-lethal dosages of AgNPs have been linked to multiple studies showing genetic abnormalities, changes, and overproduction of proteins/enzymes [39, 40]. It is necessary to strictly adhere to the guidelines for the concentrations of NPs used in diverse circumstances.

In this work, in order to identify the genes involved in AgNPs resistance, resistance was induced in different bacterial isolates. The chemical reduction process was used to create AgNPs. The addition of silver nitrate solution to sodium borohydride caused the solution color to shift to dark brown, signifying the formation of AgNPs [41]. After exposure to gamma irradiation at 5 kGy and 10 kGy, the remaining Ag+ ions after chemical preparation were reduced to Agº giving more stable NPs in the solutions. UV-visible spectrophotometer and FTIR were performed before and after irradiation to confirm AgNPs stabilization. The UV-visible spectrophotometer was adopted to analyze the formation and stability of the AgNPs in the solution. The maximum absorbance peaks for AgNPs were 0.8 and 400 nm in wavelength for control. After exposure to gamma irradiation, the absorbance increased to 1.7 and 1.9 at 5 kGy and 10 kGy, respectively. This property is called the Surface Plasmon Resonance (SPR) of AgNPs [42]. High SPR of UV analysis after exposure to gamma irradiation indicates increased concentration of AgNPs. FTIR confirms the complete reduction of all Ag+ ions to Agº after gamma irradiation by the effect of radiolysis. The prepared AgNPs were spherical in shape with an average size of 50–500 nm and zeta potential (-24.4) indicating highly stable AgNPs. Increased particle size in DLS analysis than in TEM analysis is due to the hydrodynamic radius of water molecules around the prepared AgNPs in solution. The SEM, EDX, and mapping of AgNPs were used to analyze the morphological structure of the NPs [43].

Following the exposure of bacterial isolates to increasing concentrations of AgNPs, the changes in bacterial susceptibility to AgNPs were demonstrated. Meanwhile, there is no standard procedure to compare the activity of AgNPs on different strains of bacteria, as the physicochemical characteristics of the nanoparticle, the bacterial growth medium, and even the incubation conditions used, would influence its activity [44,45,46].

Focusing on one-gram negative bacteria (KP.1) and one-gram positive bacteria (St.L.1), MIC was increased from 6.25 to > 30 µg/ml and from 3.12 to > 30 µg/ml, respectively under the same conditions. Only KP.1, St.L.1, and their AgNPs resistant isolates (KP_R.Ag and St.L_R.Ag) were chosen to be whole genome sequenced. Our results are in agreement with Panáček et al. 2018 where they demonstrated the resistance of the Gram-negative isolates Escherichia coli and Pseudomonas aeruginosa to AgNPs after repeated exposures. They determined the MIC of AgNPs and their results focused on bacteria repeatedly exposed to sub-inhibitory concentrations of AgNPs, where pathogens were able to rapidly develop AMR [47].

In this case, we have looked into the genetic variety in Klebsiella pneumonia and Staphylococcus lentus hospital wound isolates by next-generation sequencing NGS and contrasting genomics. Utilizing the WGS technique to evaluate the isolates’ genome sequences (AgNPs-resistant) and contrasting the results with the reference genome allowed researchers to explore the genomic variance among the isolates with different resistance traits (AgNPs-susceptible).

Many nsSNPs are potentially significant in AMR, with new perspectives to expand our knowledge of the aspects influencing the hospital isolates’ resistance regime. Multiple processes of antimicrobial resistance in both Klebsiella pneumonia and Staphylococcus lentus isolates have been identified [48,49,50]. Mechanisms of antimicrobial resistance entail the following: changes in the antimicrobial agent target to alter the antimicrobial’s affinity, antimicrobial deactivation via synthetic alteration or deterioration, alterations in antimicrobial agent permeability via modifications affecting the bacterial cell surface (e.g., by altering the production of outer membrane proteins/porins), and active transport of antimicrobial agents from the bacterial cells.

In many instances, bacterial MDR results from several mechanisms; however, active efflux of the antimicrobial agent can achieve MDR. Antimicrobial efflux pumps can be categorized into many families according to the variations in their structural characteristics and energy requirements [51,52,53,54]. They enclose the following: RND (resistance-nodulation division), ABC (ATP-binding cassette), MATE (multidrug and toxic compound extrusion), MFS (major facilitator superfamily), SMR (small multidrug resistance), PACE (proteobacterial antimicrobial compound efflux), and CDF (cation diffusion facilitator) transporters [9, 53]. As far as secondary transporters go, MF is the biggest and most varied superfamily currently identified [55]. In this study, we identified variants of RND transporters, the ABC efflux complexes, the SMR family, the MF family, and the MATE superfamily [56, 57].

The RND efflux pump family consists of tripartite efflux pumps, which are composed of three main components. These components include an outer membrane protein or outer membrane factor (OMP, an inner membrane transporter protein (efflux protein), and a periplasmic adapter protein (PAP), also known as the membrane fusion protein (MFP), which acts as a connector between the OMP and the RND protein [58, 59]. In our study different mutations were detected in the RND family proteins member such as AcrAB-TolC/drug antiporter AcrB, AcrAD-TolC/drug antiporter AcrD, AcrEF-TolC/drug antiporter AcrF were identified in KP_R.Ag isolate. These proteins play a crucial role in the efflux of antimicrobial drugs, decreasing the intracellular concentration of it in the bacterial cell and consequently playing a role in AgNPs resistance acquisition. The same results were obtained by Jianhua et al. and Yang et al. after exposure of NPs on Pseudomonas aeruginosa [60, 61].

The Cus system is the silver resistance mechanism that can transport silver ions into the extracellular space [47, 62]. Mutations in Copper/silver efflux RND transporters proteins CusA, CusB, CusC, and CusS have been identified in KP_R.Ag isolate and have been known to be associated with silver resistance (Table 3). Mutation in CusS protein, involved in silver resistance, raises cusCFBA expression which is an efflux transporter required for silver resistance [63], and ultimately raises Ag + efflux [64].

According to genetic studies, ABC transporters are one of the most recognized protein families in prokaryotes and may be crucial to the physiology of both gram-positive and gram-negative bacteria [65]. Numerous cellular activities are mediated by bacterial ABC transporters such as MDR, biofilm formation, adhesion, attainment of necessary nutrients, formation of spores, conjugation, and toxin release [66]. Despite the fact that many vital ABC importers remain unknown, such proteins play an important role in transportation of metals and amino acids [67]. The data obtained showed that various mutations in ABC transporters were identified in both AgNPs resistant isolates, which may play a role in AgNPs resistance. Fe + 3 siderophore transport system, iron compound transporter, and ZnuA zinc transporter were identified as metal ABC transporters in KP_R.Ag isolate. Also, mutations in amino acid and protein ABC transporters were MlaB, OppF, CcmB, MdxE, LivF, SsuA, GltI, YehX, MdlB, MdxF, ModA, UrtC, methionine, phosphate/phosphonate transporter, substrate-binding protein, N-acetyl-D-glucosamine along with clusters related to maltose/polyamine/glutamine/opines/nickel and peptides. On the other hand, mutations in iron transporter and manganese transporter SitA were identified in St.L_R.Ag isolate as metal ABC transporters. PotA, PotC, PotD, MsmX, MdxE, PstB, OpuA, MdlB, OppF, OppD, YbiT, heterodimeric, methionine, and ABC excinuclease along with clusters related to maltose and basic amino acid, were marked as mutations in protein and amino acid ABC transporters in St.L_R.Ag isolate. Our results are in agreement with Jiya Jose et al. which demonstrated complete resistance of Staphylococcus aureus to AgNPs and induce complete mortality of Staphylococcus aureus when treated with Verapamil, (an efflux pump inhibitor) [68].

Different mutations were also identified as part of the efflux system in KP_R.Ag, such as MdtL, MdtM, EmrD, uncharacterized MFS transporters, and 3-(3-hydroxyphenyl) propionate transporters as part of the major facilitator superfamily (MFS) in KP_R.Ag isolate. Alterations of bacterial efflux pumps of the MFS restored the clinical utility of antimicrobial agents according to Kumar et al. and thus may play a role in AgNPs resistance in this study [69]. Mutations were also identified in Multidrug resistance proteins such as MdtG, MdtN, MdtO, MdtP, and MdtQ in KP_R.Ag isolate which had been identified in Klebsiella pneumonia resistance to antibiotics [70] and thus may play a role in AgNPs resistance in this study.

Permease proteins are membrane transport proteins that allow the diffusion of a specific molecule in or out of the cell. Mutations in permease proteins such as cytosine/ purine/uracil/thiamine/allantoin permease family proteins, fucose permease, and YbiR were detected in KP_R.Ag isolate which might be involved in AgNPs resistance. Contrarily, mutations in macrolide permease protein, YdaO, and AapA were detected in St.L_R.Ag isolate. OmpN, OprD, PhoE, OmpC, YaeT, OprB, FimD, outer membrane protein x precursor, and outer membrane protein/protective antigen were also recognized as outer membrane proteins in KP_R.Ag isolate alters the bacterial membrane permeability and thus plays a role in AgNPs resistance in agreement with TiO2 NPs resistance by Christophe Pagnout [71].

Among the Gram-negative bacteria, the most studied MATE superfamily transporters pump is the NorM efflux pump in Neisseria gonorrhoeae and Vibrio cholera [72]. The NorM efflux pump exports substrates including antimicrobial cationic compounds (quaternary ammonium compounds) and antimicrobials such as ciprofloxacin and solithromycin in N. gonorrhoeae [73]. In this study, mutations identified in MdtK/NorM as part of the MATE family which might be involved in AgNPs bacterial resistance [74].

According to Baharoglu et al. 2013, sub-MICs of antimicrobial reagents can elevate the horizontal transfer of antimicrobial resistance genes by increasing reactive oxygen species (ROS) formations, subsequent induction of multidrug efflux systems, and ROS-induced DNA mutagenesis [75]. In this study, long-term exposure to a sub-MIC of AgNPs altered the activity of certain proteins involved in oxidative stress and SOS response pathways. This is a global response to DNA damage in which DNA repair is induced, leading to a rise in the rate of the genome-wide mutation [76]. Mutations in variants of stress response proteins such as superoxide dismutase, universal stress protein G, DegS, DegQ, YdcZ, YdaA, YciE, HSP, GrpE, Zrap, RecF, CopD, CueR, and RcsA coregulator with RcsB were identified in KP_R.Ag isolate. Adenylate kinase, arsenate reductase, superoxide dismutase, thioredoxin reductase, MBL-fold metallohydrolase superfamily, CSP, HSP, GroEL, DnaK, DnaJ, ClpB, ClpP, ClpC, ClpX, ClpE, PhoH, YicC, FtsH, GlcU, AhpC, AhpF, and HslO were identified in St.L_R.Ag isolate [77]. Furthermore, SOS response proteins KatE and RecF in KP_R.Ag, RecA, and LexA in St.L_R.Ag had been detected in both isolates (Supplementary Tables S2 & S3), respectively. Bacteria exposed to AgNPs activate proteins responsible for safeguarding against oxidative stressors such as KatE which converts hydrogen peroxide into oxygen later on [78]. Also, it activates proteins such as superoxide dismutase which breaks down superoxide into hydrogen peroxide. Our findings are in agreement with the induced formation of free radicals produced by metals which might cause oxidative stress and trigger the SOS response [79].

According to Kamat and Kumari 2023, intracellular stress brought on by NPs modifies multidrug-resistant proteins and/or genes. This, in turn, sets off a chain reaction that results in the overexpression of membrane porin/protein genes and multidrug resistance efflux genes, ultimately fostering adaptive pathogenic evolution [3].

Conclusion

Nowadays, NPs are applied in many fields, including agriculture, medicine, and the environment. The current work has exhibited that bacteria can quickly become resistant to the antimicrobial effects of AgNPs when they are exposed to sub-inhibitory doses of the particles regularly. Understanding the mechanism of acquiring nanoparticle resistance is crucial to overcome the current issue of resistance to NPs produced by bacteria. Resistance could be related to a mix of mutations that leads to the overexpression of several transporters, multidrug efflux pumps, and alterations of expression of enzymes and proteins incorporated in outer membrane permeability. Despite being a relatively new phenomenon, stringent regulations and rigorous adherence to the guidelines for the usage and disposal of nano wastes are needed to stop this issue from spreading as far as antibiotic resistance.

Data availability

Data of whole genome sequencing are available on NCBI under the Bioproject accession number: PRJNA1108055 and PRJNA1109764. All other data are available on request.

Abbreviations

AgNPs:

Silver nanoparticles

MIC:

Minimum inhibitory concentrations

WGS:

Whole genome sequencing

SNP:

Single nucleotide polymorphism

BV-BRC:

The Bacterial and Viral Bioinformatics Resource Center

AMR:

Antimicrobial resistance

NGS:

Next generation sequencing

HIV:

Human immune deficiency virus

WHO:

The World Health Organization

PVP:

Polyvinyl pyrrolidone

FT-IR:

Fourier Transform Infrared Spectroscopy

DLS:

Dynamic light scattering

TEM:

Transmission electron microscope

SEM:

Scanning electron microscope

EDX:

Energy-dispersive X-ray

MALDI-TOF MS:

Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry

MHA:

Muller Hinton agar

NCBI:

National Center for Biotechnology Information

SPSS:

Statistical Package for the Social Sciences

CLSI:

The Clinical and Laboratory Standards Institute

EC.1:

Escherichia coli

EC.2:

Escherichia coli

KP.1:

Klebsiella pneumonia

KP.2:

Klebsiella pneumonia

AB:

Acinetobacter baumannii

St.L.1:

Staphylococcus lentus

St.L.2:

Staphylococcus lentus

Ps:

Pseudomonas aeruginosa

St.M:

Stenotrophomonas maltophilia

St.A:

Staphylococcus aureus

KP.Ag.R:

AgNPs resistant Klebsiella pneumonia

St.Ag.R:

AgNPs resistant Staphylococcus lentus

ABC:

Adenosine triphosphate binding cassette

RND:

Resistance-nodulation division

MATE:

Multidrug and toxic compound extrusion

SMR:

Small multidrug resistance

MFS:

Major facilitator superfamily

PACE:

Proteobacterial antimicrobial compound efflux

CDF:

Cation diffusion facilitator

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Acknowledgements

The authors thanks National Center for Radiation Research and Technology (NCRRT), Egyptian Atomic Energy Authority (EAEA), Cairo, Egypt for the possibility to use their equipment and facilities during gamma irradiation process.

Funding

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

This research received no external funding.

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Authors and Affiliations

  1. Department of Drug Radiation Research, Division of Biotechnology, Laboratory of Drug Microbiology, National Center for Radiation Research and Technology (NCRRT), Egyptian Atomic Energy Authority (EAEA), Cairo, Egypt

    Amira M. Mahfouz & Hala Nour El Din El Hifnawi

  2. Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Kasr El-Aini Street, Cairo, 11562, Egypt

    Walaa A. Eraqi, Alaa El Din Shawky, Reham Samir & Mohamed A. Ramadan

Authors
  1. Amira M. Mahfouz
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  2. Walaa A. Eraqi
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  5. Reham Samir
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  6. Mohamed A. Ramadan
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Contributions

A.M.M: carried out the practical and experimental part, analyzed the data, wrote the main manuscript draft, data representation and editing of manuscript. W.A.E: analyzed the data, prepared figures and revised the manuscript. H.N: participated in research methodology and manuscript revising. R.S: suggested the research topic, investigated the articles, planned the research methodology and participated in the data representation and manuscript revising. M.A.R: revised the manuscript. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Amira M. Mahfouz or Walaa A. Eraqi.

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Mahfouz, A.M., Eraqi, W.A., El Hifnawi, H.N.E.D. et al. Genetic determinants of silver nanoparticle resistance and the impact of gamma irradiation on nanoparticle stability. BMC Microbiol 25, 18 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12866-024-03682-x

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12866-024-03682-x

Keywords

BMC Microbiology

ISSN: 1471-2180

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