Comprehensive Genomic Analysis of Klebsiella pneumoniae and Its Temperate N-15-like Phage: From Isolation to Functional Annotation

Comment

Introduction has information but it is unstructured and did not provide a theoretical framework listing information that seems discussion or describe the results.

Response

Thank you for your important comment, the introduction part has been restructured in the main manuscript.

Comment

Delete short title

Response

Thank you for your clarification. Short titles are not permissible, so we have removed them accordingly.

Comment

Line 22, change E coli in italics

Response

Thank you for your notice, we have italicized all scientific names through the main manuscript.

Comment

lines 35-44, paragraph too long, please resume for the abstract.

Response

We sincerely appreciate your insightful feedback. As suggested, we have revised the abstract to ensure conciseness while emphasizing the study’s objectives and key findings.

Comment

Author summary is not required.

Response

Thank you for your clarification.  Author summary are not permissible, so we have removed them accordingly.

Comment

Please use the same font along the text. In some lines the format is distinct.

Response

Thank you for your observation, the fonts were adjusted in the manuscript.

Comment

line 64, please avoid contractions and along the text, this is informal

Response

Thank you for this correction, the sentence was replaced by formal form: The capacity of K. pneumoniae to acquire and disseminate antibiotic resistance genes through horizontal gene transfer routes, such as plasmids, transposons, and prophages, has significantly contributed to its reputation as a significant nosocomial pathogen.

Comment

line 76, the verb mix is not clear to mention phage integration:

Response

Thank you for your notice, the word mix was changed to integrate.

Comment

line 132-133 and 285-286, information of bioproject and accession numbers should be provided in material and methods.

Response

Thank you for your comment, the information’s of bioproject and accession numbers were removed to material and methods.

Comment

Figure 1, phylogenetic tree was done with 16S rRNA sequence or complete genome?

Response

Thank you for raising this important point. The phylogenetic tree in Figure 1 was constructed using 16S rRNA gene sequences, not complete genomes. The caption has now been revised to explicitly state this, ensuring clarity for readers. While 16S rRNA is a widely used marker for phylogenetic analysis at the species level, we acknowledge its limitations in resolving fine-scale differences among closely related strains within Klebsiella pneumoniae. To strengthen our interpretation, we emphasize that the observed clustering patterns align with geographic and clinical/environmental metadata, supporting the plausibility of the inferred relationships. Future studies incorporating whole-genome sequencing or multi-locus sequence typing (MLST) could further refine these phylogenetic insights. The methodological details, including the use of the Tamura-Nei model and bootstrap validation, remain appropriate for 16S rRNA-based analyses.

Comment

Results regarding MIC are too long, please show the most important results.

Response

Thank you for your comment, antibiotic data were reduced to the most important ones.

Comment

Table 3, edit genes in italics.

Response

Thank you for your observation, all gene names through the manuscript were revised and italicized.

Comment

lines 289-292, information is repetitive.

Response

Thank you for your observations. Those lines were removed.

Comment

information of phylogenetic analyses is repetitive.

Response

Thank you for your feedback. We have streamlined the text to eliminate redundancy in the description of Figure 4. The caption is now as follows: Figure 4. The phylogenetic analysis of Klebsiella phage Kpn_R1 was conducted using ViPTree, a web server that generates viral proteomic trees based on genome-wide sequence similarities computed by tBLASTx. The circular proteomic tree illustrates the evolutionary relationships of Kpn_R1, highlighting its closest related phages forming distinct clusters (gray).

Comment

line 381, what were the criteria to define morons, AMG and host takeover?

Response

We sincerely appreciate the reviewer’s insightful comments and the opportunity to clarify our approach to defining morons, auxiliary metabolic genes (AMGs), and host takeover genes in our stud. Below, we provide detailed responses to each point raised.

Criteria for Identifying Morons, AMGs, and Host Takeover Genes in the Phage Genome

1. Morons
• Defined as accessory genes located within intergenic regions of the phage genome, typically flanked by phage promoters and terminators, and not essential for the viral replication cycle.
• Identified by scanning for ORFs with unique functional annotations absent in core phage structural and replication modules.
2. Auxiliary Metabolic Genes (AMGs)
• Characterized based on homology to known metabolic genes that enhance host metabolic functions, potentially benefiting the phage replication process.
• AMGs were identified using functional annotation pipelines and were further classified based on their role in influencing host metabolism.
3. Host Takeover Genes
• Defined as phage-encoded genes that manipulate host processes to favor viral replication, such as inhibition of host defense mechanisms or redirection of cellular metabolism.
• Identified by comparative genomics against known host takeover genes from reference phages and validated through protein domain searches.

Comment

In methods authors mention phageTerm analysis but the results are not described in the text

Response

Thank you for your observation, we included “The linearity of the phage genome was confirmed by PhagTem” in the text (The linearity of the phage genome was confirmed by PhageTem.)

Comment

In discussion, many results are mentioned but it is poorly discussed about the biological significance, and I considered a reestructuration of discussion is needed.

Response

Thank you for this important issue, the discussion has been restructured.

Comment

line 603, what is the source of Klebsiella strains? can authors provide citation?

Response

Thank you for raising this important point. The multidrug-resistant (MDR) K. pneumoniae strains analyzed in this study are part of our institution’s bacterial repository, established under ethical approval for antimicrobial resistance surveillance. For comparative host range testing, we also included the following reference strains:

• Escherichia coli ATCC 25922 (ATCC® 25922™, Manassas, VA, USA)
• K. pneumoniae ATCC 13883 (ATCC® 13883™)
• Pseudomonas aeruginosa ATCC 9027 (ATCC® 9027™)

The bacteriophage specificity assays confirmed that the phage lysed only the ST147 Kpn-R1 isolate, with no activity against other tested K. pneumoniae or the ATCC reference strains.

Comment

line 612-624, what type of library was done? 2 x 150 bp?, what were the trimmomatic parameters for trimming?

Response

Thank you for raising this important point. The library was 2x150 bp. The Trimmomatic parameters were Trimmomatic (v0.39; parameters: ILLUMINACLIP:TruSeq3-PE-2.fa:2:30:10, LEADING:20, TRAILING:20, SLIDINGWINDOW:4:20, MINLEN:50). These lines were added to the material section.

Comment

5.4 and 5.5 section can be merge and avoid repetitive information and sections 5.4, 5.5 and 5.6 have mix information, I suggest to mention a section specific for DNA isolation and sequencing for bacteria, and other section for phage.

Response

Thank you for your constructive feedback regarding the organization of Sections 5.4, 5.5, and 5.6. We agree that merging overlapping content and separating bacterial and phage workflows will improve clarity. Below are the revised sections, restructured to address redundancy and enhance methodological transparency:

5.4. Bacterial DNA Isolation, Sequencing and Bioinformatics Analysis

The bacterial genomic DNA of K. pneumoniae ST147 Kpn-R1 was isolated using the Qiagen Blood and Tissue DNA Extraction Kit, following the manufacturer’s protocol. DNA purity and concentration were verified using a Nanodrop spectrophotometer (Thermo Fisher Scientific, USA). Whole-genome sequencing (WGS) was performed by Macrogen Korea on the Illumina NovaSeq 6000 platform (2×150 bp paired-end reads). Libraries were prepared using the TruSeq Nano DNA Kit (350 bp insert size), with library quality assessed via the Agilent 2100 Bioanalyzer and TapeStation D1000 Screen Tape. Raw sequencing reads were trimmed with Trimmomatic (v0.39) to remove adapters and low-quality bases (parameters: ILLUMINACLIP:TruSeq3-PE-2.fa:2:30:10, LEADING:20, TRAILING:20, SLIDINGWINDOW:4:20, MINLEN:50) (89). The cleaned reads were assembled into contigs using SPAdes (v3.15.5) with default settings (90). Raw data from whole-genome sequencing (WGS) were integrated using Proksee Assemble (v1.3.0) (102).Genome annotation was performed using Prokka (v1.2.0), which identified open reading frames (ORFs), tRNA, rRNA, and other genomic features (103). Map Builder (v2.0.5) generated a CGView JSON file for showing the completed genome from GenBank formats. To rank BLAST tracks based on similarity and color BLAST features based on percent identity, the BLAST Formatter (v1.0.3) was used, assisting in the identification of conserved and divergent regions.     
Alien Hunter (v1.1.0) was used to forecast likely horizontal gene transfer (HGT) events based on atypical nucleotide compositions that indicate alien DNA acquisition (104). To compare the genome with closely related species and determine taxonomic connections, the whole-genome average nucleotide identity (ANI) was calculated using FastANI (v1.1.0) (105). The Comprehensive Antibiotic Resistance Database (CARD) Resistance Gene Identifier (RGI) (v1.2.1) was used to identify antibiotic resistance genes. Based on the CARD database, this tool anticipates resistance genes and mutations, giving information on the genome's antibiotic resistance profile (106).        
VirSorter (v1.1.1) was used to find viral genomes (107). Phigaro (v1.0.1) has been annotated in prophage regions (108). Mobile OG-db (v1.1.3), a database and tool designed for the identification of Mobile Genetic Elements (MGEs), including plasmids, transposons, and integrons (109). Using the CRISPR/Cas Finder (v1.1.0) tool, was used to locate CRISPR arrays and associated Cas proteins, offering insights into the genome's adaptive immune system (110). The Proksee tool displayed and organized all genetic traits. All visible tracks on the genome map were documented in a detailed figure caption created using the Track List Caption (v1.2.0) (102).

Using Kaptive Web (111), capsule (K) and lipopolysaccharide (O) serotypes in K. pneumoniae genomes were predicted. Sequence-based typing and known Klebsiella strain comparisons using the PubMLST Klebsiella database (112). Virulence factors are identified using the 2019 Virulence Factor Database (VFDB) (113). Barrnap helped to pull out the 16S rRNA gene sequence (114). By use of NCBI BLASTn database comparison, closely similar species were identified. A phylogenetic tree based on the 16S rRNA sequence and other conserved markers was built using MEGA 12 (115), therefore exposing the evolutionary links of the isolate, with the final genome deposited in GenBank under BioProject PRJNA1217456.

5.5. Phage DNA Isolation, Sequencing and Bioinformatics Analysis

Phage DNA was extracted from purified lysates using the Norgen Biotek Phage DNA Isolation Kit . Sequencing libraries were prepared identically to bacterial methods (TruSeq Nano DNA Kit, Illumina NovaSeq 6000). Raw reads were processed with Trimmomatic (same parameters as above) and assembled using SPAdes (v3.15.5). Genome completeness was ascertained using CheckV (v1.0.1) (91), and structural features were projected using PhageTerm (v4.0.0) (92). Functional annotations included phage lifestyle prediction using Bacphlip (v0.9.6) (93)and protein classification using PhANNs (94). Comparative genomics was run using Pyani (v0.2.12) (95) and Clinker (v0.0.24) (96). AMRFinderPlus (v3.12.8) (97) and VirulenceFinder (v2.0.4) (98) separately verified antimicrobial resistance and virulence genes. MASH distances were used to show the genome in CGView (v1.1.1) (99) against the Millardlab Phage Database (100). Phylogenetic trees was generated using Viptree (101). Every tool is open source, hence once released data will be available in public repositories.The phage genome was deposited in GenBank under accession numbers PQ800144.1–PQ800159.1.

Comment

Section 5.6 is long but no specific information about statistical tests is provided.

Response

Thank you for your comment, we clarified statistical analysis as follow: Statistical analyses were conducted using R (v4.3.1) and Python (v3.10) to evaluate genomic data. Descriptive statistics summarized key metrics (e.g., genome size, GC content, gene coverage). Comparative genomic analyses included average nucleotide identity (ANI) calculations using FastANI and MASH distances for phylogenetic comparisons. Multiple testing corrections (Benjamini-Hochberg method, FDR < 0.05) were applied where applicable. For phylogenetic analyses, branch support was assessed via 500 bootstrap replicates in MEGA12. Correlation analyses between genetic features (e.g., plasmid replicons, prophage regions) and antibiotic resistance profiles used logistic regression models (R stats package). MASH distances were used to show the genome in CGView (v1.1.1) (99) against the Millardlab Phage Database (100). Phylogenetic trees and Genomic similarity matrices were computed using Viptree and Clinker for synteny analysis (101).

Comment

Improved the format of tables. Extensive tables can be included as supplementary information, not in the manuscript.

Response

Thank you for this important point, all tables’ formats were revised and table 3 were moved to supplementary materials.

Comment:

Comment: Are short titles permissible?

Response:

Response: Thank you for your clarification. Short titles are not permissible, so we have removed them accordingly.

Comment:

The abstract is overly lengthy. It should be condensed and include a clear summary of the study's objectives and findings.         

Response:

We sincerely appreciate your insightful feedback. As suggested, we have revised the abstract to ensure conciseness while emphasizing the study’s objectives, methodology, and key findings. The updated abstract now reads as follows: 
This research delineated an extensively drug-resistant (XDR) Klebsiella pneumoniae strain obtained from an ICU patient and telomeric temperate phage derived from hospital effluent. The bacteria showed strong resistance to multiple antibiotics, including penicillin (≥16 μg/mL), ceftriaxone (≥32 μg/mL), and meropenem (≥8 μg/mL), which was caused by SHV-11 beta-lactamase, NDM-1 carbapenemase, OmpK37 porin mutations and MdtQ efflux pump. The strain was categorized as K46 and O2a types and carried virulence genes involved in iron acquisition, adhesion, and immune evasion, as well as plasmids (IncHI1B_1_pNDM-MAR, IncFIB) and eleven prophage regions, reflecting its genetic adaptability facilitating and resistance dissemination.        
The 171,025 bp linear genome and 46.3% GC content of the N-15-like phage showed strong genomic similarities to phages of the Sugarlandvirus genus, especially those that infect K. pneumoniae. There were structural proteins (11.8 %), DNA replication and repair enzymes (9.3 %), and a toxin-antitoxin system (0.4%) encoded by the phage genome. A protelomerase and ParA/B partitioning proteins indicate that the phage is replicating and maintaining itself in a manner similar to the N15 phage, which is renowned for maintaining a linear plasmid prophage throughout lysogeny. Understanding the dynamics of antibiotic resistance and pathogen development requires knowledge of phages like this one, which are known for their temperate nature and their function in altering bacterial virulence and resistance profiles. The regulatory and structural proteins of the phage also provide a model for research into the biology of temperate phages and their effects on microbial communities. The importance of temperate phages in bacterial genomes and their function in the larger framework of microbial ecology and evolution is emphasized in this research.

Comment:

Some information in the introduction lacks references.

Response:

Thank you for your feedback. We have carefully reviewed the introduction, inserted the missing references, and reduced its length. The revised section is now included in the manuscript.

Comment:

Please add references for each finding in Table 1, placing them in a separate column, if the authors have not already done so.

Response:

Thank you for your suggestion. We have added references for each finding in Table 1 and placed them in a separate column as requested. The changes have been marked in red in the main manuscript for easy review.

Comment:

For lines 189, 193, and 196, please insert "and" between the gene names.

Response:

We have inserted "and" between the gene names in lines 189, 193, and 196 as requested.

Comment:

Table 3 is not sufficiently informative. The author should provide additional details in a separate column.

Response:

We have revised Table 3 by adding a separate column to provide additional details, improving its informativeness and clarity. The updated table is now included in the manuscript. This table was removed to supplementary tables S1.

Comment:

Similarly, Table 4 requires references, as does Table 7.

Response:

Thank you for your suggestion. We have combined Figures 2A and 2B into a single TIFF file as requested and have updated the manuscript accordingly, all changed were marked in red in the manuscript.

Comment:

Improve the resolution of Figure 5.

Response:

Thank you for your suggestion. We have replaced Figure 5 with a higher-resolution version to improve clarity and visual quality.

Comment:

Please make Figure 3 in color.

Response:

Thank you for your feedback. We have updated Figure 3 to a multicolor format to enhance clarity and visual representation. The revised figure is now included in the manuscript.

Comment:

Combine Figures 2A and 2B into a single TIFF file.

Response:

Thank you for your suggestion. We have combined Figures 2A and 2B into a single TIFF file as requested and have updated the manuscript accordingly.

Comment:

What bootstrap value was used in constructing the phylogenetic trees (Figures 1 and 4)?

Response:

For figure (3), Thank you for your valuable comment, the phylogenetic tree was recreated with 500 bootstraps and the caption was replaced as follows: Figure 1. Circular phylogenetic tree illustrating the evolutionary relationships of Klebsiella pneumoniae Kpn_R01 and its 34 closest strains. The Maximum Likelihood (ML) tree highlights the phylogenetic placement of Kpn_R01 (marked with a red dot) among closely related strains. Clustering patterns indicate potential global dissemination, with strains originating from diverse geographic locations. The close association between clinical and environmental isolates underscores the role of environmental reservoirs in bacterial transmission. The tree was inferred using the ML method with the Tamura-Nei model (21), and branch support was assessed with 500 bootstrap replicates (22). The initial heuristic search compared a Neighbor-Joining (NJ) tree (23) and a Maximum Parsimony (MP) tree, selecting the one with the best log-likelihood score. Evolutionary analyses were conducted in MEGA12 (24).

For figure (4), thank you for catching this oversight. You are absolutely correct—the original description of Figure 4 erroneously attributed the phylogenetic analysis to the maximum likelihood method. In fact, the analysis was conducted using ViPTree, a web server that generates viral proteomic trees based on genome-wide sequence similarities computed by tBLASTx. We have revised the figure caption to accurately reflect the methodology used, and the corrected version now reads: Figure 4: The phylogenetic analysis of Klebsiella phage Kpn_R1 was conducted using ViPTree, a web server that generates viral proteomic trees based on genome-wide sequence similarities computed by tBLASTx. The circular proteomic tree illustrates the evolutionary relationships of Kpn_R1, highlighting its closest related phages forming distinct clusters (gray). Kpn_R1 shares 92.8% identity across 31.5% of its genome with Klebsiella phage vB_Kpn_IME260 and 92.3% identity across 30.1% of its genome with Klebsiella phage Sugarland. The comparison also identified Escherichia phage N15 with a lower mean identity (69.8% across 14% of the genome), suggesting evolutionary divergence. Seq1 (marked with a red branch) represents Klebsiella phage Kpn_R1. 
We sincerely apologize for the error and have carefully reviewed the manuscript to ensure consistency in methodological descriptions. Please let us know if further clarification is needed.

Comment:

The authors did not clearly articulate the novel contribution of their work compared to existing genomic studies of K. pneumoniae ST147 and temperate phages, particularly N-15-like phages. It remains unclear how this study significantly advances current knowledge or differs from numerous prior genomic characterizations.

Recommendation: Explicitly state how the findings differ from previously published research. Clarify how the results could practically impact clinical practice, infection control, or therapeutic strategies.

Response:

 We thank the reviewer for highlighting the need to clarify the novel contributions and translational implications of our work. Below, we address these points explicitly:

Novel Contributions

1. First Characterization of an N15-Like Phage in ST147 K. pneumoniae:
• While N15-like phages are well-studied in Escherichia coli and Klebsiella oxytoca, this is the first report of an N15-like phage (Kpn_R1) integrated into the high-risk K. pneumoniae ST147 clone. Unlike prior studies, we identified a unique toxin-antitoxin (TA) system (RelE/ParE) within the phage genome, a feature absent in other N15-like phages (e.g., E. coli phage N15 or K. oxytoca pKO2). This system may enhance bacterial stress adaptation and prophage stability, offering new insights into phage-mediated evolution of XDR pathogens.
2. Regional and Environmental Insights:
• Our study bridges clinical and environmental reservoirs by isolating the ST147 strain from an ICU patient and the N15-like phage from hospital wastewater. This dual-source approach reveals potential pathways for resistance gene dissemination in healthcare settings, a dimension underexplored in prior genomic studies of ST147.
3. Unique Genetic Context of Resistance:
• The ST147 strain harbors a hybrid plasmid (IncHI1B_1_pNDM-MAR + IncFIB) carrying blaNDM-1* and colicin genes, a combination not previously reported in Middle Eastern ST147 lineages. This highlights region-specific plasmid evolution driving carbapenem resistance.
4. CRISPR Inactivation and Prophage Diversity:
• We demonstrate that CRISPR-Cas inactivation in this strain correlates with extensive prophage diversity (11 regions) and plasmid uptake, a mechanism less emphasized in global ST147 studies. This finding aligns with emerging evidence linking CRISPR loss to enhanced horizontal gene transfer in nosocomial pathogens.

Practical Implications

1. Phage Engineering for Therapeutics:
• The N15-like phage’s linear plasmid replication system (protelomerase, ParA/B) and TA system provide a template for engineered phages to deliver CRISPR-Cas systems or disrupt resistance/virulence genes. This could advance precision phage therapy against XDR K. pneumoniae.
2. Infection Control and Surveillance:
• Detection of the N15-like phage in wastewater underscores the need to monitor environmental reservoirs in hospitals to curb resistance spread. Our data suggest wastewater surveillance could act as an early warning system for emerging XDR clones.
3. Diagnostic and Therapeutic Targets:
• The hybrid plasmid’s structure and prophage-carried TA system offer new molecular targets for rapid diagnostics (e.g., PCR probes for blaNDM-1* + colicin markers) or small-molecule inhibitors to disrupt phage-mediated stress adaptation.
4. Regional Antibiotic Stewardship:
• The strain’s resistance to last-resort agents (e.g., colistin, fosfomycin) and biocides highlights the urgency for region-specific stewardship programs in Saudi Arabia to limit empirical use of polymyxins and quaternary ammonium compounds.

Differentiation from Prior Studies

While genomic studies of ST147 (e.g., Di Pilato et al., 2022; Talat et al., 2024) focus on clinical isolates and resistance gene cataloging, our work uniquely:

• Links clinical K. pneumoniae ST147 to environmental phage dynamics.
• Identifies a phage-encoded TA system as a novel driver of bacterial persistence.
• Provides actionable data for phage-based interventions and environmental surveillance in endemic regions.

Comment:

Phage Analysis and Host Range

Host range predictions based entirely on genomic similarity are insufficient to conclude specificity or infectivity. Experimental validation of host specificity or cross-infectivity was not provided.

Recommendation: Acknowledge limitations of solely bioinformatic predictions… Experimental validation approaches (?)

Response:

Thank you for raising this important point. The multidrug-resistant (MDR) K. pneumoniae strains analyzed in this study are part of our institution’s bacterial repository, established under ethical approval for antimicrobial resistance surveillance. For comparative host range testing, we also included the following reference strains:

• Escherichia coli ATCC 25922 (ATCC® 25922™, Manassas, VA, USA)
• K. pneumoniae ATCC 13883 (ATCC® 13883™)
• Pseudomonas aeruginosa ATCC 9027 (ATCC® 9027™)

The bacteriophage specificity assays confirmed that the phage lysed only the ST147 Kpn-R1 isolate, with no activity against other tested K. pneumoniae or the ATCC reference strains.

Comment:

CRISPR-Cas Systems and Prophage Analysis

The biological or clinical implications of CRISPR arrays and prophages remain largely speculative, especially regarding their roles in horizontal gene transfer.

Recommendation: Clearly state hypotheses about how identified prophages and CRISPR-Cas systems might contribute to genomic plasticity, antibiotic resistance dissemination, or strain persistence.

Response:

 Thank you for your insightful comment. We have revised the manuscript to clearly articulate the biological and clinical implications of CRISPR-Cas systems and prophages in XDR K. pneumoniae ST147, particularly regarding their roles in genomic plasticity, horizontal gene transfer (HGT), and strain persistence and updated the discussion section.

Our hypothesis is that:

1. CRISPR-Cas and Resistance Gene Acquisition:
• The presence of a CRISPR-Cas system in this XDR strain does not significantly limit the acquisition of resistance plasmids, suggesting that HGT remains a dominant mechanism in its evolution.
• This supports the notion that certain K. pneumoniae ST147 lineages may have non-functional or weakly active CRISPR systems, allowing them to accumulate multiple antibiotic resistance genes (ARGs).
2. Prophages and Genomic Plasticity:
• The identified N15-like phage may serve as a genetic vehicle for horizontal gene transfer, contributing to the host strain's adaptability.
3. Implications for Infection Control and Therapeutics:
• The observation that CRISPR-Cas does not prevent phage infection suggests that phage therapy remains a viable strategy against XDR K. pneumoniaeST147.
• A deeper understanding of prophage–host interactions could lead to novel interventions, such as CRISPR-based genome editing or synthetic biology approaches to engineer phages for targeted bacterial eradication.

Comment:

Conclusions

The conclusions section remains somewhat general and lacks direct implications or actionable insights derived from the research findings.

Recommendation: Summarize key findings explicitly, emphasizing practical impacts on public health, clinical practice, or phage therapy development. Highlight clear future directions or unanswered questions emerging from the study.

Response:

Thank you for your emphasizing comment. We have changed the conclusion section as follows: This study presents the genomic interaction between a novel N15-like temperate phage sourced from hospital wastewater and an extremely drug-resistant K. pneumoniae ST147 strain isolated from an ICU patient, thereby revealing significant new insights into resistance dissemination and phage-mediated evolution. The ST147 strain's hybrid plasmid (IncHI1B_1_pNDM-MAR/IncFIB), which carries blaNDM-1 and colicin genes, along with CRISPR-Cas inactivation and 11 prophage regions, highlights its genetic plasticity and potential nosocomial threat. The linear plasmid-like replication system of the phage, along with protelomerase and a novel RelE/ParE toxin-antitoxin (TA) system—previously unreported in temperate Klebsiella phages—highlights mechanisms that enhance resistance traits and promote phage survival.
Tracking phage-mediated resistance gene transfer between clinical and environmental reservoirs helps us show how wastewater monitoring may prevent outbreaks. By suggesting actionable plans, this work goes beyond current genomic cataloging of ST147: the phage's replication machinery provides a template for engineered therapies (e.g., CRISPR-Cas delivery), while the strain's regional resistance profile calls for tailored antibiotic stewardship to reduce last-resort drug misuse. Emphasizing phage-bacterial interactions as a frontier in the fight against XDR infections, our results change the paradigm from passive genomic monitoring to proactive, ecology-driven therapies. Future research should confirm the functional significance of the TA system and investigate phage-based diagnostics to interfere with resistance transfer in healthcare environments.

Comment:

L1, L22, and throughout the manuscript: Please ensure that all bacterial names are italicized.

Response:

Thank you for your notice, all scientific names were italicized.

Comment:

The introduction is excessively long and should be shortened.

Response:

Thank you for your suggestion. We have shortened the introduction as requested. The revised version is now included in the manuscript.

Comment:

L156: On what criteria was this strain identified as XDR? Please provide a supporting reference.

Response:

Thank you for your comment, the following was added to text: Klebsiella pneumoniae Kpn_R01 is categorized as extensively drug-resistant (XDR) owing to its resistance to multiple antibiotic classes. This classification is supported by minimum inhibitory concentration (MIC) testing, as presented in Table 1, and is further validated through resistance gene analysis utilizing the CARD database. Extensively drug-resistant (XDR) bacteria are defined globally as exhibiting resistance to at least one agent in all but one or two categories of antimicrobials (Magiorakos et al., 2012). This strain qualifies for XDR designation as it exhibits resistance to beta-lactams, cephalosporins, carbapenems, monobactams, fluoroquinolones, aminoglycosides, tetracyclines, macrolides, polymyxins, sulfonamides, trimethoprim, phenicols, rifamycins, and fosfomycin. This strain demonstrates resistance to a wide array of antibiotics; however, additional research is required to ascertain whether drugs continue to be effective in addressing pandrug resistance (PDR) criteria.

Comment:

L162: The sentence “Aztreonam resistance (≥32 μg/ml) is similarly attributed to NDM-1” is incorrect. NDM-1 does not confer resistance to monobactams. Please revise and correct.

Response:

Thank you for your comment, this was revised and corrected in table 1 and in the corresponding text (Aztreonam resistance (≥32 μg/ml) is attributed to low permeability caused by Outer Membrane Porinmutations in OmpK37and MdtQ.

Comment:

L156–L181, Table 2, and throughout the manuscript: All gene names must be italicized. Additionally, the authors must clearly distinguish between genes, their encoded enzymes, proteins, and efflux pumps. For example, bla_NDM-1 refers to a gene, while NDM-1 refers to the enzyme. Proper notation is critical. Since it seems that the authors may not microbiologists, it is strongly recommended that they consult a microbiologist before resubmission.

Response:

Thank you for your detailed feedback. We have italicized all gene names throughout the manuscript, including L156–L181 and Table 2. Additionally, we have carefully distinguished between genes, their encoded enzymes, proteins, and efflux pumps, ensuring proper notation. These revisions have been made with careful consideration of microbiological conventions.

Comment:

L239: What was the purpose of performing the CRISPR-Cas Finder analysis in this study? Please clarify.

Response:

Thank you for your inquiry. The CRISPR-Cas Finder analysis in this study aimed to assess the role of CRISPR-Cas systems in the genetic adaptability of the XDR K. pneumoniae ST147 strain. Our findings highlight the following key points:

• The strain’s extensive resistance profile suggests that CRISPR-Cas does not significantly restrict plasmid acquisition, allowing the accumulation of multiple resistance genes.
• Horizontal gene transfer (HGT) remains a major driver of its adaptability, further supporting its classification as a high-risk clone.
• The presence of a temperate N15-like phage in the strain suggests that CRISPR-Cas does not prevent phage infection, implying that phage therapy remains a viable treatment option.

The CRISPR spacer profile provides insights into the strain’s evolutionary history and epidemiological trends, aiding in understanding the genetic plasticity of ST147 in hospital settings.

Comment:

The discussion is too long and should primarily focus on interpreting the study’s significant findings.

Response:

Thank you for your feedback. We have restructured the discussion to focus primarily on interpreting the study’s significant findings. The revised version is now included in the manuscript.