Category: 7. Science

In 2006, Pluto was famously demoted from a planet to a dwarf planet. It remains the most famous dwarf planet today, but there are others in our solar system, including potentially hundreds that haven’t been discovered yet.

But what, exactly, is a dwarf planet? And how many dwarf planets are there?

Introduction

The emergence of carbapenem-resistant Klebsiella pneumoniae (CRKP) challenges clinical management and global public health. The main issue is the extremely limited antibiotic treatment options, which makes CRKP infections difficult to treat and threatens patient outcomes and the healthcare system.¹ Carbapenem resistance in K. pneumoniae mainly results from carbapenemases (β-lactamase enzymes), particularly Klebsiella pneumoniae carbapenemase (KPC; class A serine enzymes) and New Delhi metallo-β-lactamase (NDM; metallo-β-lactamases requiring zinc).² What is even more alarming is that K. pneumoniae strains co-existing with blaKPC and blaNDM can obtain or spread extra antimicrobial resistance genes, such as extended-spectrum β-lactamase (ESBL) genes, fluoroquinolone resistance genes, tetracycline resistance genes and aminoglycoside resistance genes. This results in a high level of resistance to most of the routinely employed antibiotics, creating serious obstacles for therapeutic treatment.³

Healthcare-associated infections remain a significant challenge, particularly due to the increasing prevalence of multidrug-resistant (MDR) organisms. KPC-producing and NDM-producing K. pneumoniae (KPC-Kp and NDM-Kp) are undoubtedly concerning pathogens, characterized by limited treatment options, high mortality rates, and the capacity to trigger outbreaks in healthcare settings.⁴ A previous investigation of an NDM outbreak indicated that the losses caused by ward closures, temporary admission restrictions, or delayed discharges due to such outbreaks were enormous.⁵

In this study, we identified a multidrug-resistant K. pneumoniae strain (KP3T58) isolated from a clinical patient, exhibiting resistance to nearly all antibiotics except polymyxin. Whole-genome sequencing (WGS) revealed the coexistence of bla_KPC-2 and bla_NDM-5 alongside three critical plasmids. Through conjugation assays, we confirmed the transferability of these high-risk genetic determinants and further investigated the virulence phenotype of KP3T58. This work comprehensively characterizes a clinical CRKP co-producing KPC and NDM, highlighting the urgent threat posed by such dual-carbapenemase strains.

Materials and Methods

Bacterial Isolates and Case Report

A 70-year-old male was admitted to the intensive care unit (ICU) of The Second Affiliated Hospital of Xiamen Medical College due to brainstem hemorrhage. Upon admission, chest CT findings indicated that the patient concurrently suffered from chronic bronchitis and emphysema. During hospitalization at this tertiary care center, K. pneumoniae was detected in the patient’s sputum. To control the infection, piperacillin – tazobactam was initiated at a dosage of 4.5 grams every 12 hours. However, after three weeks of treatment, sputum culture following bronchoscopy still yielded K. pneumoniae, with the isolate showing intermediate susceptibility to piperacillin-tazobactam (MIC = 16 μg/mL). Therapy was subsequently changed to ceftazidime (1 gram every 8 hours) and linezolid (0.6 gram every 8 hours) for one week. Due to deteriorating pulmonary status, meropenem (2 grams every 8 hours) was administered. During meropenem treatment, bronchoalveolar lavage fluid culture was positive for a CRKP isolate (KP3T58). This isolate exhibited resistance to ceftazidime-avibactam, tigecycline, and carbapenems. The patient died of respiratory failure caused by severe pulmonary infection three weeks after KP3T58 detection. Figure 1 summarizes the microbiological details, timeline, and antibiotic regimens.

Figure 1 The patient’s treatment and infection timeline.

Antimicrobial Susceptibility Testing

Isolates were identified by matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS, BioMérieux, France). Antimicrobial susceptibility testing was performed using the Vitek-2 system (Vitek-AST-N334/N335 cards), with ceftazidime-avibactam (CZA) susceptibility determined by broth microdilution. Tigecycline breakpoints followed FDA criteria (susceptible ≤2 mg/L, intermediate 4 mg/L, resistant ≥8 mg/L); polymyxin breakpoints followed EUCAST 2023 standards (https://www.eucast.org); all other breakpoints adhered to CLSI M100 guidelines. Escherichia coli ATCC 25922 served as the quality control strain.

Whole-Genome Sequencing and Bioinformatics Analysis

Genomic DNA from KP3T58 was extracted using the Qiagen DNA extraction Kit (Qiagen, Germany). Genome sequencing was performed on the PacBio HiFi and Illumina NovaSeq 6000 platforms. Long-read data (third-generation sequencing) was assembled using hifiasm (v0.19.5). The assembly was error-corrected using pilon (v1.24) and the clean short-read (second-generation) sequencing data. We used Kleborate (https://github.com/katholt/Kleborate/) for multilocus sequence typing (MLST) and serotype analysis.⁶ ResFinder 4.6.0 was used to identify chromosomal mutations and acquired resistance genes.⁷ PlasmidFinder (v2.1) identified plasmid replication origins, resistance genes, and virulence factors.⁸ OriTfinder analyzed plasmid conjugative and mobilizable capabilities.⁹ Additionally, VRprofile was used for analysis and annotation of insertion sequences (ISs) and transposons (Tns).¹⁰

Multilocus Sequence Typing (MLST)

MLST was performed on the first two K. pneumoniae isolates (KP3P34 and KP3R15) recovered from patient sputum samples. PCR amplification and sequencing of seven housekeeping genes (gapA, infB, mdh, pgi, phoE, rpoB, and tonB) were conducted as previously described.¹¹ Allele numbers and sequence types (STs) were assigned using the Pasteur Institute’s Klebsiella pneumoniae MLST database (http://bigsdb.pasteur.fr/klebsiella/).

Phylogenetic Analysis

Genomic sequences and metadata of 35 K. pneumoniae strains (34 public isolates from China co-harboring blaKPC and blaNDM, plus clinical strain KP3T58) were obtained from NCBI. Core genome SNP (cgSNP) analysis was performed using Parsnp v1.2 with KP3T58 as the reference genome, and the resulting phylogenetic tree was visualized and annotated via iTOL (https://itol.embl.de/).

Comparative Genomic Analyses

Sequence alignment was performed using BLASTn. For plasmid comparison, Proksee (https://proksee.ca/) was employed used to generate circular maps comparing KP3T58 plasmids with other representative plasmids. The genetic environments surrounding antibiotic resistance genes were investigated using Easyfig (version 2.25). Nucleotide sequences were aligned using ClustalW in Jalview 2.11.4.0. Amino acid sequence alignment of Tet(A) was performed using ESPript 3.0.¹²

Conjugation Assay

Conjugation assays assessed transfer of resistance plasmids from K. pneumoniae KP3T58 (donor) to E. coli EC600 (recipient). Donor and recipient strains, grown to logarithmic phase, were mixed (1:1 ratio), centrifuged (8,000g, 1 min), and resuspended in 20 µL of 10 mM MgSO₄. The mixture was spotted onto Luria-Bertani (LB) agar and incubated overnight at 37°C. Serial dilutions were plated on LB agar supplemented with selective antibiotics: tetracycline (10 mg/L; tet(A)), bleomycin (10 mg/L; ble), gentamicin (15 mg/L; rmtB), and for the recipient, rifampicin (600 mg/L).

Transconjugants were identified by MALDI-TOF MS. The presence of tet(A), rmtB, bla_NDM-5, and bla_KPC-2 in transconjugants was confirmed by PCR using primers listed in Table 1. Conjugation frequency (CF) was calculated as: CF = [Number of transconjugants (CFU/mL)] / [Number of donor cells (CFU/mL)].

Table 1 Oligonucleotides for PCR

Plasmid Stability Testing and Growth Assays

Plasmid stability in transconjugants was evaluated as described previously.¹³ Fitness was assessed by growth curve analysis. Transconjugants and the recipient strain were cultured overnight in LB, diluted to an OD600 of 0.01, and incubated at 37°C for 24h. OD600 was measured every 30 minutes.¹⁴

Serum Killing Assay

To evaluate the capacity of strains to withstand serum-mediated killing, a serum resistance assay was conducted following previously published procedures.¹⁵ Briefly, mid-log phase bacterial cells at a concentration of colony-forming units (CFU) per milliliter were combined with normal human serum, sourced from healthy human volunteers, in a 1:3 ratio. The mixture was then incubated at 37°C for 2 hours. Subsequently, after serial dilution, the bacteria were plated onto LB agar and incubated overnight at 37°C to enumerate the viable bacteria. Informed consent was obtained from the donors prior to using their serum.

Quantitative Siderophore Production Assay

To assess the capacity of bacterial supernatants to chelate iron, the researchers employed the chrome azurol S (CAS) assay in accordance with the standardized procedures.¹⁶ Briefly, 1 μL of stationary-phase, iron-chelated cultures was placed onto CAS plates. After incubation at 37°C for 48 hours, the formation of orange halos was used as an indicator to detect siderophore production.

Capsule Quantification

To evaluate the mucoviscosity of K. pneumoniae KP3T58, uronic acid extraction and quantification were carried out following a previously reported protocol.¹⁵ Specifically, an overnight culture in LB medium underwent dilution at a ratio of 1:100 into fresh medium and was incubated at 37°C for 6 h. Then, 500 μL of the culture was combined with 100 μL of 1% Zwittergent 3–12 detergent. The mixture was heated at 50°C for 20 min and subsequently centrifuged at 13,000×g for 5 min. Next, 300 μL of the supernatant was mixed with 1.2 mL of absolute ethanol and centrifuged again at 13,000×g for 5 min. The obtained pellet was dried and resuspended in 200 μL of sterile water. Subsequently, 1.2 mL of tetraborate solution (12.5 mM sodium tetraborate in sulfuric acid) was added. The solution was incubated at 100°C for 5 min, followed by rapid cooling on ice for a minimum of 10 min. Finally, 20 μL of hydroxyphenyl reagent was added. After a 5 – minute incubation at room temperature, the optical density (OD) was measured at 520 nm.

G. Mellonella in vivo Infection Model

To assess the pathogenicity of K. pneumoniae strains KP3T58, Galleria mellonella infection assays were conducted following established protocols.¹⁷ First, the caterpillars were stored at 4°C; those weighing between 150 and 200mg were then carefully selected. Two groups were established: a treatment group and a control group. The treatment group was inoculated with 10 μL of a bacterial suspension at a concentration of 1 × 10⁶ colony-forming units (CFU)/mL, while the control group received 10 μL of normal saline.

Each treatment group consisted of at least 30 caterpillars, which were evenly divided into three Petri dishes. All setups were kept at 37°C. Caterpillar survival rates were documented through daily observations over a three-day period.

Statistical Analysis

Data analyses were conducted using GraphPad Prism 8.0.2 software. The results were presented with a two-tailed non-parametric Student’s t-test. For the survival data obtained from in vivo and in vitro experiments, the Log Rank test (Mantel-Cox) was employed for analysis. P-values < 0.05 were considered significant.

Nucleotide Accession Number

The complete genome sequence of K. pneumoniae KP3T58 has been deposited in the GenBank database of the National Center for Biotechnology Information (NCBI), with the accession number PRJNA1206428.

Result

K. Pneumoniae KP3T58 Was a MDR Strain

K. pneumoniae KP3T58 exhibited high-level resistance to ceftazidime/avibactam and tigecycline, carbapenems (ertapenem, meropenem, and imipenem), β-lactam inhibitors (amoxicillin/clavulanic acid,piperacillin/tazobactam, ticarcillin/clavulanic acid, cefoperazone/sulbactam), β-lactam antimicrobials (cefuroxime, ceftazidime,ceftriaxone, cefepime, aztreonam), aminoglycosides (amikacin, tobramycin), quinolones (ciprofloxacin, levofloxacin), tetracyclines (doxycycline, minocycline), it exhibited susceptibility solely to colistin (Table 2).

Table 2 Antimicrobial Drug Susceptibility Profiles

Genomic Characteristics of K. Pneumoniae KP3T58

WGS analysis using Kleborate typed strain KP3T58 as sequence type ST11 and capsule type KL64. Hybrid assembly with Circos revealed a circular chromosome of 5,534,638 bp (accession no. CP177330) with a GC content of 57.0%. Strain KP3T58 carried 23 resistance determinants associated with its MDR phenotype (Table 3). Chromosomal resistance genes included bla_SHV-11, aadA2, and qacE. Notably, three point mutations were identified in the OmpK37 porin (I70M, I128M, N230G), and seven mutations were detected in the transcriptional repressor AcrR (P161R, G164A, F172S, R173G, L195V, F197I, K201M), which regulates the OqxAB efflux pump. Virulome analysis showed that KP3T58 carried multiple virulence-associated factors, such as iron uptake systems (yersiniabactin and Ent siderophore), type 1 and type 3 fimbriae, capsule, and type 6 secretion systems (T6SS-I). However, the isolate lacked multiple virulence genes involved in siderophore biosynthesis, including iucABCD, iroBCD, and rmpA.

Table 3 Genomic Information of the K. Pneumoniae KP3T58

Plasmid Characteristics of K. Pneumoniae KP3T58

Genomic analysis indicated that plasmid pKP3T58_1 (323,738 bp, CP177331), classified as an IncFIB(K)/IncFII(pKP91)/IncR plasmid with a GC content of 52%. It carried multiple resistance genes, including tet(A),qnrS1,bla_CTX-M-14,bla_TEM-1,bla_LAP-2,aph(3”)-Ib and aph(6)-Id (Table 3). OriTfinder analysis indicated that pKP3T58_1 was conjugative, as it contained a complete conjugative apparatus (oriT site, relaxase, type-4 secretion system (T4SS), and type-4 coupling protein (T4CP)).

The resistance gene bla_NDM-5 was located on plasmid pKP3T58_2 (108,400 bp, CP177332), an IncI1-I type plasmid. This plasmid also contained the sul1 and ble drug-resistance genes. Bioinformatics analysis further confirmed pKP3T58_2 as aconjugative plasmid.

Plasmid pKP3T58_3 (56,083 bp, CP177333), assigned to the IncFII type, exhibited a 52% GC content and contained four resistance genes: bla_{KPC – 2}, rmtB, bla_{TEM – 1B}, and bla_{CTX – M – 65}. In contrast to pKP3T58_1 and pKP3T58_2, pKP3T58_3 lacked autonomous conjugative ability, due to an incomplete conjugation system, specifically the absence of oriT, a relaxase, and T4CP.

Plasmid pKP3T58_4 (11,970 bp, CP177334), with a GC content of 56%, was devoid of resistance or virulence genes and belonged to the ColRNAI type.

MLST Confirms ST11 Clonal Persistence

MLST analysis assigned both carbapenem-susceptible isolates (KP3P34, KP3R15) and the carbapenem-resistant isolate KP3T58 to ST11 (Pasteur scheme), confirming clonal persistence within the patient.

KP3T58 Clusters Within Dominant Epidemic ST11 Clade

Phylogenetic analysis of 34 K. pneumoniae strains co-harboring blaKPC and blaNDM carbapenemase genes from nationwide surveillance and the clinical isolate KP3T58 revealed that KP3T58 clustered within the dominant epidemic ST11-KL64 clade, indicating it is a prevalent ST11-KL64 clone circulating in China (Figure 2).

Figure 2 Phylogeny of 35 K. pneumoniae isolates co-harboring blaKPC and blaNDM based on core genome SNP analysis. The tree includes 34 public isolates from China and the clinical strain KP3T58. Annotations indicate multilocus sequence typing (MLST; ST), capsular serotype (KL), Chinese provinces of origin, and distributions of antimicrobial resistance genes and virulence genes.

Comparative Genomic and Linear Comparison

Comparative analysis showed that plasmid pKP3T58_ 1 had 80–84% coverage and 99.9–100% identity with punnamed1 (CP040176.1) of K. pneumoniae strain 2e from Chongqing, p82_1 (CP101547.1) of KP82 from Yunnan, and pKP309 (CP089881.1) of KP309 from Shanghai, all isolated from within China (Figure 3A).

Figure 3 Comparative analysis of pKP3T58_ 1, pKP3T58_ 2 and pKP3T58_ 3 with other reference plasmids. (A) Genome alignment was performed with pKP3T58_ 1(CP177331), plasmid unnamed1 (CP040176.1), p82_1 (CP101547.1) and pKP309 (CP089881.1). (B) Alignment of the genetic environment surrounding blaTEM-1B with pF16KP0064-1(CP052173.1) and plasmid unnamed2(NZ_CP061963.1). (C) Nucleotide and amino acid sequence alignments between the tet(A) of pKP3T58_1 and the wild – type. (D) Genome alignment was performed with pKP3T58_ 2(CP177332), pZYST1C2 (NZ_CP031615.1), pKP11 – 2 (OW848878.1), and pKP – NDM – 5 (NZ_CP084746.1). (E) Comparison of the genetic environment surrounding blaKPC−2.

Further analysis revealed pKP3T58_1 contained two large antibiotic resistance gene clusters.The bla_TEM-1B gene, together with other resistance genes (sul2,aph(3”)-Ib,aph(6)-Id,bla_LAP-2,qnrS1), formed a 17,803-bp antimicrobial resistance (AMR) region. The genomic context upstream of bla_TEM-1B was homologous to plasmid pF16KP0064-1 (CP052173.1) from Seoul, South Korea. A similar genetic environment for qnrS1 was observed when comparing pKP3T58_1 with the JNK002 plasmid unnamed2 (NZ_CP061963.1) (Figure 3B). The presence of multiple insertion sequences (ISs) and recombinase genes suggested this AMR region likely arose from successive insertion and recombination events. Furthermore, comparative analysis identified a point mutation (Leu294Val) in the tet(A) gene of pKP3T58_1 (Figure 3C).

Comparative analysis of plasmid pKP3T58_2 revealed potential evolutionary pathways for antibiotic resistance gene acquisition.pZYST1C2 (NZ_CP031615.1) from Heilongjiang, China, pKP11-2 (OW848878.1) from Catalan, Spain, and pKP-NDM-5 (NZ_CP084746.1) from Zhejiang, China, respectively, exhibited 80–98% coverage and 99.9–100% identity with pKP3T58 _ 2 (Figure 3D).

Structural analysis of the bla_KPC-2 locus identified ISkpn27 and ISkpn6 flanking the gene upstream and downstream, respectively. Notably, this resistance cassette was entirely embedded within an IS26-bounded region. A complete T4SS was detected downstream of bla_KPC-2, containing essential conjugation genes such as traA, traB, traE, traK, and traM (Figure 3E).

The Non-Conjugative Plasmid pKP3T58_3 Was Mobilized with the Assistance of Conjugative Plasmid pKP3T58_2

Given the three key resistance plasmids and their potential for interbacterial transfer, we assessed the dissemination risk of antimicrobial resistance associated with strain KP3T58. Conjugation assays demonstrated that conjugative plasmids pKP3T58_1 and pKP3T58_2 could transfer individually or together to E. coli EC600. Notably, pKP3T58_2 exhibited an exceptionally high conjugation frequency (1.1 × 10⁻² – 1.8 × 10⁻²). Contrary to expectations, pKP3T58_3 (lacking complete conjugative elements) was mobilized from KP3T58 to E. coli EC600 at a lower frequency (4.2 × 10⁻⁶ – 5.8 × 10⁻⁵) with the help of the conjugative helper plasmid pKP3T58_2. Antimicrobial susceptibility profiles of recipient cells and transconjugants are summarized in Table 1. PCR and agarose gel electrophoresis confirmed the presence of resistance genes in all transconjugants.

Plasmid stability assays showed that all KP3T58-derived plasmids were stably maintained in transconjugants during serial passages. Furthermore, E. coli EC600 harboring these drug-resistant plasmids showed no significant growth defect, ensuring their persistent maintenance in bacterial populations.

In vitro and in vivo Virulence of KP3T58

Subsequently, we aimed to investigate whether KP3T58 possesses hypervirulent traits. For this purpose, K. pneumoniae strain HS11286 (classical strain, ST11)¹⁸ served as the virulence-negative control, while K. pneumoniae NTUH-K2044 (ST23, KL1)¹⁹ was used as the virulence-positive control.

Quantitative siderophore production assays revealed that KP3T58 produced significantly fewer siderophores (13 mm halo diameter) than the positive control NTUH-K2044 (22 mm), comparable to the negative control HS11286 (12 mm) (Figure 4A).

Figure 4 The virulence phenotypes and levels of KP3T58. (A) Siderophores production determined by CAS agar plate. (B) The production of capsule measured based on uronic acid levels. (C) The survival rate (%) evaluated by serum resistance assay. (D) The survival curves of G. mellonella infected by KP3T58, NTUH-K2044 and HS11286. Note:NS (normal saline). Unpaired two-sided Student’s t-tests were performed for uronic acid production and the survival rate in the serum resistance assay. ***P < 0.001; ****P < 0.0001. A log – rank (Mantel–Cox) test was employed for the assessment of the survival curves. A significant difference (P<0.0001) was observed between these groups.

Capsule quantification via uronic acid measurement demonstrated that KP3T58 produced less uronic acid than NTUH-K2044, but slightly more than HS11286 (Figure 4B). Similar trends were observed in serum resistance assays (Figure 4C).

Pathogenicity assessment using the Galleria mellonella infection model showed that KP3T58-infected larvae exhibited a 63% survival rate at 72 hours post-infection, significantly lower than the negative control HS11286 (96%), but substantially higher than the positive control NTUH-K2044 (6%) (Figure 4D).

Discussion

Over the past decade, the global prevalence of MDR K. pneumoniae, particularly carbapenem-resistant variants (CRKP), has escalated significantly, posing a critical public health challenge.^20,21 To elucidate the origin of such high-risk strains, we investigated the clonal and epidemiological context of KP3T58. MLST analysis confirmed that both carbapenem-susceptible isolates (KP3P34, KP3R15) and the carbapenem-resistant isolate KP3T58 from the same patient belong to ST11. This suggests that resistance in KP3T58 likely evolved through acquired resistance mechanisms—such as plasmid acquisition or horizontal gene transfer—rather than new clonal invasion. The ST11 clone demonstrated prolonged persistence within the host, developing resistance under antibiotic pressure. Phylogenetic analysis of 35 K. pneumoniae strains co-harboring KPC and NDM carbapenemases from nationwide surveillance further revealed that KP3T58 clustered within a predominant epidemic subclade characterized by co-production of KPC and NDM carbapenemases in ST11-KL64 clones circulating in China. This clustering pattern, combined with the prevalence of ST11-KL64 among dual-carbapenemase producers in the national dataset, suggests that the ST11-KL64 lineage may serve as a key epidemiological vehicle for the acquisition and dissemination of the KPC-NDM co-production phenotype in China. Its dominance positions KP3T58 within a high-risk transmission network potentially driven by this successful clone.

KP3T58 exhibited near-pan-resistance to clinically used antibiotics, including ceftazidime-avibactam (CZA) and tigecycline. CZA, a β-lactam/β-lactamase inhibitor combination effective against KPC-producing CRKP, is compromised by NDM enzymes due to their zinc-dependent hydrolysis mechanism, which avibactam cannot inhibit.^22–24 Critically, unlike KPC-variant-mediated CZA resistance, NDM production does not restore carbapenem susceptibility. Moreover, the stable CZA resistance phenotype in such strains may facilitate horizontal dissemination of resistance genes within bacterial populations.

Plasmid pKP3T58_1, harboring three replicons (IncFIB, IncFII, and IncR), circumvented incompatibility through its multi-replicon configuration, enabling stable coexistence with other plasmids. This large conjugative plasmid carried multiple resistance genes, including qnrS1, tet(A), and diverse β-lactamases. The qnrS1 gene was embedded within a complex AMR region (ΔIS3–ISKpn19) alongside other determinants (IS5075-aph(3”)-Ib-aph(6)-Id- bla_TEM-1-IS26-bla_LAP-2). Comparative analysis with plasmids pF16KP0064-1 and pJNK002 indicated that this region arose from successive insertion and recombination events. Functionally, qnrS1 acquisition elevated levofloxacin MICs in transconjugants, while chromosomal acrR mutations (mediating fluoroquinolone resistance via RND efflux pump dysregulation) synergistically enhanced resistance.²⁵ Although qnrS1 alone confers low-level resistance, it expands the mutant selection window, promoting high-level resistance emergence.^26,27

Tigecycline resistance in KP3T58 likely stems from efflux pump upregulation. While rpsJ mutations and tet(A) variants are established tigecycline resistance mechanisms,^28–31 comparative analysis excluded rpsJ alterations. However, we identified a Leu294Val substitution in tet(A), which—combined with RND efflux activity—may explain the reduced tigecycline susceptibility in transconjugants. Prior studies corroborate that such mutations diminish tigecycline sensitivity and potentiate MDR phenotypes.³²

Conjugation assays revealed exceptionally high transfer efficiency of pKP3T58_2 (IncI1-I), consistent with its phylogenetic clustering within an epidemic subclade and suggesting conserved dissemination mechanisms. Comparative genomics indicated high sequence similarity with plasmid pKP-NDM-5 from Zhejiang Province, implying regional spread of this plasmid lineage. In East Asia, bla_KPC-2 frequently localizes to IncFII-type plasmids,³³ creating an ecological niche for co-dissemination with pKP3T58_2. Critically, KPC-NDM co-production confers elevated resistance to carbapenems and CZA, demanding urgent surveillance of pKP3T58_2-like plasmids.

The blaKPC gene resided on an IncFII-type plasmid, the primary vector for bla_KPC-2 spread in ST11.³⁴ Structural analysis revealed a unique genetic environment flanked by ISKpn27 and IS26, with a truncated ISKpn6 and an incomplete recombinase gene upstream. Notably, no ΔTn3 homolog was detected downstream; instead, a complete T4SS was present. This architecture—distinct from predominant Tn1721 transposons in Chinese isolates—highlights how IS accumulation enhances plasticity around bla_KPC-2, facilitating carbapenem resistance dissemination.^35,36

Previous studies define mobilizable plasmids as those incapable of autonomous transfer due to defective conjugative machinery, yet capable of horizontal transfer via “hitchhiking” with helper conjugative plasmids. Conventional knowledge dictates that such plasmids retain, at minimum, an oriT site to enable co-transfer. In our conjugation assays, plasmid pKP3T58_3—containing only a partial T4SS—was successfully co-transferred with the conjugative plasmid pKP3T58_2. This unconventional finding expands the mechanistic paradigm of plasmid dissemination. Notably, mobilizable plasmids may possess greater dissemination potential and broader host ranges than conjugative plasmids, potentially attributable to fewer protospacer sequences vulnerable to CRISPR-Cas targeting.^37,38 Consequently, the observed co-transfer of pKP3T58_3 raises significant concerns regarding the accelerated dissemination of antimicrobial resistance genes.

Although KP3T58 lacked hallmark hypervirulence genes (iucABCD, iroBCD, rmpA) and assays confirmed atypical hypervirulence, its yersiniabactin system poses substantial risks. This siderophore enhances respiratory colonization and pneumonia development, potentially enabling acquisition of additional virulence determinants.^39,40 While reports of carbapenem-resistant hypervirulent K. pneumoniae (hv-CRKP) are increasing,¹⁷ most global CRKP infections remain opportunistic healthcare-associated infections (HAIs).⁴¹ High-risk groups (neonates, elderly, immunocompromised) in ICUs—where CRKP mortality reaches 48.9%⁴²—are particularly vulnerable. Critically, the within-host evolution of resistance in ST11 underscores the need for decolonization protocols targeting susceptible carriers pre-resistance emergence. Antibiotic pressure concurrently drives convergence of MDR and hypervirulence, exacerbating therapeutic challenges.⁴³

Conclusion

In summary, this study systematically characterized the resistome of the clinical isolate and conducted in-depth genomic analysis of key resistance gene contexts. MLST analysis confirmed clonal persistence of the ST11 lineage within the host, while phylogenetic positioning revealed KP3T58’s clustering within a dominant epidemic subclade circulating in China. Critically, we experimentally demonstrated that mobilizable plasmids retaining only a T4SS—despite lacking core conjugative machinery—can achieve horizontal transfer when assisted by conjugative plasmids. This discovery fundamentally reshapes our understanding of plasmid dissemination mechanisms. Given these novel insights into plasmid transmission, coupled with the high-risk epidemiological context of the strain, and considering the potential role of the ST11-KL64 clone as a major disseminator of the KPC-NDM co-production phenotype in China, we conclude that the spread of CRKP co-producing KPC and NDM carbapenemases demands enhanced surveillance. Targeted monitoring of this high-prevalence, genetically adaptable lineage may be critical for understanding and interrupting the transmission dynamics of dual-carbapenemase resistance.

Ethics

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Second Affiliated Hospital of Xiamen Medical College (2025010). Written informed consent was obtained from the deceased patient’s next-of-kin for the publication of this case report and associated data.

Author Contributions

All authors made a significant contribution to the work reported, whether in the conception, study design, execution, acquisition of data, analysis, and interpretation, or in all these areas, took part in drafting, revising, or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This work was supported by the Joint Special Fund for Applied Basic Research of Kunming Medical University (No. 202201AY070001-182).

Disclosure

The authors report no conflicts of interest in this work.

References

1. Ernst CM, Braxton JR, Rodriguez-Osorio CA, et al. Adaptive evolution of virulence and persistence in carbapenem-resistant Klebsiella pneumoniae. Nature Med. 2020;26(5):705–711. doi:10.1038/s41591-020-0825-4

2. Kelly AM, Mathema B, Larson EL. Carbapenem-resistant Enterobacteriaceae in the community: a scoping review. Int J Antimicrob Agents. 2017;50(2):127–134. doi:10.1016/j.ijantimicag.2017.03.012

3. Hu R, Li Q, Zhang F, Ding M, Liu J, Zhou Y. Characterisation of blaNDM-5 and blaKPC-2 co-occurrence in K64-ST11 carbapenem-resistant Klebsiella pneumoniae. J Global Antimicrob Resist. 2021;27:63–66. doi:10.1016/j.jgar.2021.08.009

4. Zhang P, Shi Q, Hu H, et al. Emergence of ceftazidime/avibactam resistance in carbapenem-resistant Klebsiella pneumoniae in China. Clin Microbiol Infect. 2020;26(1):124.e1–124.e4. doi:10.1016/j.cmi.2019.08.020

5. Mollers M, Lutgens SP, Schoffelen AF, Schneeberger PM, Suijkerbuijk AWM. Cost of nosocomial outbreak caused by NDM-1–containing Klebsiella pneumoniae in the Netherlands, October 2015–January 2016. Emerg Infect Dis. 2017;23(9):1574–1576. doi:10.3201/eid2309.161710

6. Smillie C, Garcillán-Barcia MP, Francia MV, Rocha EPC, de la Cruz F. Mobility of plasmids. Microbiol Mol Biol Rev. 2010;74(3):434–452. doi:10.1128/mmbr.00020-10

7. Florensa AF, Kaas RS, Clausen P, Aytan-Aktug D, Aarestrup FM. ResFinder – an open online resource for identification of antimicrobial resistance genes in next-generation sequencing data and prediction of phenotypes from genotypes. Microb Genom. 2022;8(1). doi:10.1099/mgen.0.000748

8. Carattoli A, Zankari E, García-Fernández A, et al. In silico detection and typing of plasmids using plasmidfinder and plasmid multilocus sequence typing. Antimicrob Agents Chemother. 2014;58(7):3895–3903. doi:10.1128/aac.02412-14

9. Li X, Xie Y, Liu M, et al. oriTfinder: a web-based tool for the identification of origin of transfers in DNA sequences of bacterial mobile genetic elements. Nucleic Acids Res. 2018;46(W1):W229–W234. doi:10.1093/nar/gky352

10. Li J, Tai C, Deng Z, Zhong W, He Y, Ou H-Y. VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria. Briefings Bioinf. 2017. doi:10.1093/bib/bbw141

11. Diancourt L, Passet V, Verhoef J, Grimont PA, Brisse S. Multilocus sequence typing of Klebsiella pneumoniae nosocomial isolates. J Clin Microbiol. 2005;43(8):4178–4182. doi:10.1128/jcm.43.8.4178-4182.2005

12. Robert X, Gouet P. Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res. 2014;42(W1):W320–W324. doi:10.1093/nar/gku316

13. Johnson TJ, Danzeisen JL, Youmans B, et al. Separate F-type plasmids have shaped the evolution of the H30 subclone of Escherichia coli sequence type 131. mSphere. 2016;1(4). doi:10.1128/mSphere.00121-16

14. Liu D, Liu Z-S, Hu P, et al. Characterization of surface antigen protein 1 (SurA1) from Acinetobacter baumannii and its role in virulence and fitness. Vet Microbiol. 2016;186:126–138. doi:10.1016/j.vetmic.2016.02.018

15. Wang W, Tian D, Hu D, Chen W, Zhou Y, Jiang X. Different regulatory mechanisms of the capsule in hypervirulent Klebsiella pneumonia: “direct” wcaJ variation vs. “indirect” rmpA regulation. Front Cell Infect Microbiol. 2023. doi:10.3389/fcimb.2023.1108818

16. Tian D, Wang W, Li M, et al. Acquisition of the conjugative virulence plasmid from a CG23 hypervirulent Klebsiella pneumoniae strain enhances bacterial virulence. Front Cell Infect Microbiol. 2021;11. doi:10.3389/fcimb.2021.752011

17. Zhou Y, Wu X, Wu C, et al. Emergence of KPC-2 and NDM-5-coproducing hypervirulent carbapenem-resistant Klebsiella pneumoniae with high-risk sequence types ST11 and ST15. mSphere. 2024;9(1):e0061223. doi:10.1128/msphere.00612-23

18. Liu P, Li P, Jiang X, et al. Complete genome sequence of Klebsiella pneumoniae subsp. pneumoniae HS11286, a multidrug-resistant strain isolated from human sputum. J Bacteriol. 2012;194(7):1841–1842. doi:10.1128/jb.00043-12

19. Chou H-C, Lee C-Z, Ma L-C, Fang C-T, Chang S-C, Wang J-T. Isolation of a chromosomal region ofKlebsiella pneumoniaeAssociated with allantoin metabolism and liver infection. Infect Immun. 2004;72(7):3783–3792. doi:10.1128/iai.72.7.3783-3792.2004

20. Magiorakos AP, Srinivasan A, Carey RB, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268–281. doi:10.1111/j.1469-0691.2011.03570.x

21. Lan P, Jiang Y, Zhou J, Yu Y. A global perspective on the convergence of hypervirulence and carbapenem resistance in Klebsiella pneumoniae. J Global Antimicrob Resist. 2021;25:26–34. doi:10.1016/j.jgar.2021.02.020

22. Zhang J, Xu J, Shen S, et al. Comparison of three colloidal gold immunoassays and GeneXpert Carba-R for the detection of Klebsiella pneumoniae bla(KPC-2) variants. J Clin Microbiol. 2024;62(7):e0015424. doi:10.1128/jcm.00154-24

23. Antinori E, Unali I, Bertoncelli A, Mazzariol A. Klebsiella pneumoniae carbapenemase (KPC) producer resistant to ceftazidime–avibactam due to a deletion in the blaKPC3 gene. Clin Microbiol Infect. 2020;26(7):946.e1–946.e3. doi:10.1016/j.cmi.2020.02.007

24. Zhou P, Gao H, Li M, et al. Characterization of a novel KPC-2 variant, KPC-228, conferring resistance to ceftazidime-avibactam in an ST11-KL64 hypervirulent Klebsiella pneumoniae. Int J Antimicrob Agents. 2024. doi:10.1016/j.ijantimicag.2024.107411

25. Su CC, Rutherford DJ, Yu EW. Characterization of the multidrug efflux regulator AcrR from Escherichia coli. Biochem Biophys Res Commun. 2007;361(1):85–90. doi:10.1016/j.bbrc.2007.06.175

26. Drlica K. The mutant selection window and antimicrobial resistance. J Antimicrob Chemother. 2003;52(1):11–17. doi:10.1093/jac/dkg269

27. Rodríguez-Martínez JM, Velasco C, García I, Cano ME, Martínez-Martínez L, Pascual A. Mutant prevention concentrations of fluoroquinolones for Enterobacteriaceae expressing the plasmid-carried quinolone resistance determinant qnrA1. Antimicrob Agents Chemother. 2007;51(6):2236–2239. doi:10.1128/aac.01444-06

28. Lv L, Wan M, Wang C, et al. Emergence of a plasmid-encoded resistance-nodulation-division efflux pump conferring resistance to multiple drugs, including tigecycline, in Klebsiella pneumoniae. mBio. 2020;11(2). doi:10.1128/mBio.02930-19

29. Li R, Han Y, Zhou Y, et al. Tigecycline susceptibility and molecular resistance mechanisms among clinical Klebsiella pneumoniaeStrains isolated during non-tigecycline treatment. Microb Drug Resist. 2017;23(2):139–146. doi:10.1089/mdr.2015.0258

30. He F, Shi Q, Fu Y, Xu J, Yu Y, Du X. Tigecycline resistance caused by rpsJ evolution in a 59-year-old male patient infected with KPC-producing Klebsiella pneumoniae during tigecycline treatment. Infect Genet Evol. 2018;66:188–191. doi:10.1016/j.meegid.2018.09.025

31. Gu D, Lv H, Sun Q, Shu L, Zhang R. Emergence of tet(A) and blaKPC-2 co-carrying plasmid from a ST11 hypervirulent Klebsiella pneumoniae isolate in patient’s gut. Int J Antimicrob Agents. 2018;52(2):307–308. doi:10.1016/j.ijantimicag.2018.06.003

32. Akiyama T, Presedo J, Khan AA. The tetA gene decreases tigecycline sensitivity of Salmonella enterica isolates. Int J Antimicrob Agents. 2013;42(2):133–140. doi:10.1016/j.ijantimicag.2013.04.017

33. Wei D-W, Wong N-K, Song Y, et al. IS26 veers genomic plasticity and genetic rearrangement toward carbapenem hyperresistance under sublethal antibiotics. mBio. 2022;13(1):10.1128/mbio.03340–21.

34. Fu P, Tang Y, Li G, Yu L, Wang Y, Jiang X. Pandemic spread of bla((KPC-2)) among Klebsiella pneumoniae ST11 in China is associated with horizontal transfer mediated by IncFII-like plasmids. Int J Antimicrob Agents. 2019;54(2):117–124. doi:10.1016/j.ijantimicag.2019.03.014

35. Feng Y, Liu L, McNally A, Zong Z. Coexistence of three bla(KPC-2) genes on an IncF/IncR plasmid in ST11 Klebsiella pneumoniae. J Glob Antimicrob Resist. 2019;17:90–93. doi:10.1016/j.jgar.2018.11.017

36. Zeng L, Zhang J, Hu K, et al. Microbial characteristics and genomic analysis of an ST11 carbapenem-resistant Klebsiella pneumoniae strain carrying bla (KPC-2) conjugative drug-resistant plasmid. Front Public Health. 2021;9:809753. doi:10.3389/fpubh.2021.809753

37. Transmission of nonconjugative virulence or resistance plasmids mediated by a self-transferable IncN3 plasmid from carbapenem-resistant Klebsiella pneumoniae.

38. Zhang J, Xu Y, Wang M, et al. Mobilizable plasmids drive the spread of antimicrobial resistance genes and virulence genes in Klebsiella pneumoniae. Genome Med. 2023;15(1). doi:10.1186/s13073-023-01260-w

39. Bachman MA, Lenio S, Schmidt L, Oyler JE, Weiser JN, Hultgren SJ. Interaction of lipocalin 2, transferrin, and siderophores determines the replicative niche of Klebsiella pneumoniae during pneumonia. mBio. 2012;3(6). doi:10.1128/mBio.00224-11

40. Holt KE, Wertheim H, Zadoks RN, et al. Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health. Proc Natl Acad Sci U S A. 2015;112(27):E3574–81. doi:10.1073/pnas.1501049112

41. Podschun R, Ullmann U. Klebsiella spp. as nosocomial pathogens: epidemiology, taxonomy, typing methods, and pathogenicity factors. Clin Microbiol Rev. 1998;11(4):589–603. doi:10.1128/cmr.11.4.589

42. Xu L, Sun X, Ma X. Systematic review and meta-analysis of mortality of patients infected with carbapenem-resistant Klebsiella pneumoniae. Ann Clinic Microbiol Antimicrob. 2017;16(1). doi:10.1186/s12941-017-0191-3

43. Hennequin C, Robin F. Correlation between antimicrobial resistance and virulence in Klebsiella pneumoniae. Eur J Clin Microbiol Infect Dis. 2015;35(3):333–341. doi:10.1007/s10096-015-2559-7

In the wild, survival often depends on looks. Some insects evolve disguises that trick their predators into keeping a safe distance. One of the most fascinating examples of this is Batesian mimicry, where harmless species mimic dangerous ones.

Predators that are wary of painful stings, or toxic bites, learn to avoid the warning patterns on the bodies of these potential prey species.

But some other species evolve to copy these signals, despite being completely harmless themselves. This strange dance of deception shapes the appearance of many species worldwide.

Recently, researchers at the University of Nottingham pushed this idea further. They explored how advanced 3D printing technologies can unravel mysteries surrounding mimicry. Their results revealed surprising insights about evolution, predators, and survival strategies.

This study not only shines a light on insect mimicry but also offers a deeper look at the forces that mold nature’s endless forms.

How predators judge insect disguises

The Nottingham team, led by Dr. Tom Reader and Dr. Christopher Taylor, decided to take an experimental leap. They created life-size, 3D-printed models of insects to study how predators respond to different levels of mimicry.

By controlling every aspect of these models – such as shape, color, size, and patterns – they crafted accurate representations of real species. These included wasps that are known for their stings, and hoverflies that are famous mimics of wasps.

This approach allowed the scientists to explore a central question: Why do some mimics look almost identical to their models, while others resemble them only vaguely?

With 3D printing, they could manipulate every trait precisely and test how predators react to slight variations. This marked a significant step beyond previous studies that relied on natural specimens alone.

“In our study, we are asking a question about how evolution works and what determines where evolution reaches at a particular point in time,” Dr. Reader said.

“Our experiments looked at the competing influences which might ultimately shape what organisms look like. Insects and mimicry offer a powerful and accessible way to investigate questions that are relevant across the entire tree of life,” he explained.

Color and shape matter

The team employed cutting-edge imaging tools to scan real wasps and hoverflies. Then, using advanced morphing software, they modified these images to create insects with varying degrees of accuracy in terms of mimicry.

These experiments allowed the researchers to demonstrate the potential for using modern 3D imaging, along with computer morphing, to design insect models that displayed many different combinations of colors and patterns, shapes and sizes.

“The models enabled us to ask ‘what-if’ questions about these insects. What if they were better mimics because their color was more wasp-like?” said Dr. Taylor.

“It allowed us to play around with the insect’s appearance in a way you can’t with real specimens,” he said. “Which meant we could ask a much broader range of questions about what it is that makes a good or bad mimic.”

This experimental flexibility opened new doors for exploring mimicry. The researchers could fine-tune every trait independently and combine them in unexpected ways.

Their key aim was to understand how much precision a mimic needs in order to avoid being eaten. They also wanted to see why poor mimics still manage to survive in nature.

Birds demand better insect disguises

In their experiments, the scientists presented their models to real predators in controlled settings. Their main subjects were wild birds, particularly great tits, which rely heavily on sight to identify prey.

The results showed that birds responded strongly to variations in mimicry. They focused mainly on color and size, ignoring finer pattern details.

The birds were quick learners. They soon began to avoid models that looked more like wasps, even if those models were still rewarding to eat.

Interestingly, the team discovered that intermediate mimics, those blending traits of two different wasp models, gained no extra protection. Birds seemed to prefer clear signals over mixed ones, demanding accurate mimicry.

Sloppy mimics still survive

While birds proved strict judges, invertebrate predators reacted differently. The team tested crab spiders, jumping spiders, and mantises alongside birds to compare predator responses.

Invertebrates showed less concern about precise mimicry. They tolerated models with poor resemblance and attacked more broadly.

This revealed an important insight: invertebrates impose weaker pressure on mimics to evolve perfect disguises. Some insects can survive despite their sloppy mimicry if their main threats come from these predators.

This creates a fascinating evolutionary tension. Birds push for more accurate mimics, but invertebrates allow greater variation to persist.

How evolution shapes insect disguises

A major breakthrough in this study was the creation of an adaptive landscape for mimicry. By using their 3D printed models, the team could systematically map how changes in traits affected predator decisions.

They designed smooth transitions between models, allowing them to visualize shifts in predator responses as traits varied. The experiments showed that the landscape was steep for color and size, traits that birds select strongly for, but flatter for other features like pattern.

This landscape explained why some mimics evolve to look highly accurate, while others remain imperfect. It all depends on the types of predators in their environment.

In bird-heavy areas, precise mimicry becomes essential. In areas dominated by invertebrates, imperfect mimics can survive without major risks.

Simulating future disguises

3D modeling and visualization tools allow researchers to create life-size, full-color models of potential past or future hoverflies and then test them with real predators like birds and spiders to see how they respond to those traits.

“As an evolutionary biologist, you are constantly trying to understand something that happened in the past, and without a time machine you can’t know how a hoverfly ended up like it did, ” Dr. Reader said.

This study not only revealed the subtle pressures shaping insect disguises today but also hinted at how those forces may have operated throughout history.

By bridging technology and biology, the team has crafted a remarkable tool for studying evolution. Their work helps explain how nature fine-tunes survival strategies and keeps evolving in unexpected ways.

Their experiments brought new clarity to questions that have puzzled scientists for decades, showing how insect mimicry remains one of nature’s most astonishing tricks.

The study is published in the journal Nature.

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Should we expect shorter days soon?

The Earth is likely to spin slightly faster in July and August, which could lead to shorter days.

Notably, the Earth completes a little more than 365 full spins on its axis each year. That is the total number of days we have in a year.

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However, it was not always like this. Some studies show that in the past, Earth took between 490 and 372 days to complete one trip around the Sun.

So, which days in July and August might be the shortest? And what is the reason behind this change?

Let’s take a look:

Why and when Earth is predicted to spin faster

A scientist has warned that Earth’s rotation is speeding up unexpectedly, with the shortest day in history possibly just weeks away.

Graham Jones, an astrophysicist from the University of London, said the Earth’s spin may increase slightly on three specific days, July 9, July 22, and August 5, he told Daily Mail.

The difference will be very small, measured only in milliseconds.

On these days, the length of a day might drop by 1.30, 1.38, or 1.51 milliseconds, one after the other.

Experts say that even a slight change can impact satellite systems, GPS accuracy, and how we keep track of time.

Leonid Zotov, a researcher at Moscow State University, said: “Nobody expected this, the cause of this acceleration is not explained.”

Since 2020, scientists have observed the Earth turning slightly quicker than usual, but they are still unsure why this is happening.

Earlier, the planet had been slowing down gradually, mainly due to the moon’s pull, which over time helped shape our current 24-hour days.

Typically, the Earth takes 24 hours, or exactly 86,400 seconds, to complete one full spin, known as a solar day.

Judah Levine, a physicist at the National Institute of Standards and Technology, told Discover Magazine in 2021, “This lack of the need for leap seconds was not predicted.”

“The assumption was, in fact, that Earth would continue to slow down and leap seconds would continue to be needed. And so this effect, this result, is very surprising.”

If the Earth keeps rotating faster, timekeepers might need to make changes to official time, which could include removing a leap second for the first time ever in 2029.

Why is Earth spinning faster?

The Earth’s rotation is not perfectly steady. It can shift by a few milliseconds now and then.

This happens because natural forces, such as earthquakes and ocean movements, can change the planet’s spin slightly.

Other reasons include melting glaciers, changes in Earth’s molten core, and weather patterns like El Nino, which can either slow down or speed up rotation by small amounts.

Scientists use atomic clocks to track these tiny changes with high precision. The recent increase in spin has caught many of them off guard.

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According to reports, the fastest day so far was on July 5, 2024, when the Earth spun 1.66 milliseconds faster than the usual 24 hours.

Earthquakes are also known to affect the planet’s rotation. In March 2011, a magnitude 9.0 earthquake near Japan shifted the Earth’s axis and slightly shortened the length of a day.

Dr Richard Gross from Nasa’s Jet Propulsion Laboratory told Popular Mechanics in 2011, “Earthquakes can change the Earth’s rotation by rearranging the Earth’s mass. This is what a spinning ice skater does to make herself spin faster. She moves her arms closer to her body, she’s moving her mass closer to the axis about which she’s rotating.”

Understanding the causes of this spin change involves looking at what’s happening inside the Earth, from moving molten layers deep in the core to powerful ocean currents and winds high in the sky.

Earth’s interior is not solid all the way through. Its centre is made of hot, liquid metal that flows and shifts. This movement can change the planet’s balance, like a skater turning faster by pulling in their arms.

Currents in the ocean and jet streams, fast air flows high up in the atmosphere, also move mass around, leading to small changes in the speed of Earth’s rotation.

Scientists are looking at all of these, the moon’s pull, movement in the core, ocean flow, and wind, to understand what’s happening.

Topline

The full buck moon — the first full moon of summer in the Northern Hemisphere — will turn full on Thursday, July 10. It will be best seen at moonrise as it appears in the east during dusk that evening. It takes its name from the antlers that emerge from a buck’s forehead in summer. Occurring so soon after the solstice, like last June’s strawberry moon, it will also be one of the lowest-hanging full moons of the year.

Key Facts

Best Time To See The Full ‘buck Moon’ Rise

To find the best time to see it appear from where you are, consult a moonrise calculator. Here are some sample times :

• New York: sunset at 8:29 p.m. EDT, moonrise at 8:54 p.m. EDT on Thursday, July 10.
• Los Angeles: sunset at 8:07 p.m. PDT, moonrise at 8:33 p.m. PDT on Thursday, July 10.
• London: sunset at 9:16 p.m. BST, moonrise at 9:46 p.m. BST on Thursday, July 10.

The Iconic Image Of All Humans But One, From The ‘buck Moon’

On July 21, 1969, the late Michael Collins — Command Module Pilot on NASA’s Apollo 11 spacecraft — took this image of the lunar lander Eagle as it returned Neil Armstrong, Apollo 11 Mission Commander, and Buzz Aldrin, Lunar Module Pilot, from the moon’s surface where they had become the first humans to walk upon it. In the background is Earth, making Collins the only human not featured. Technically speaking, those on Earth’s night side aren’t in it, either, but it remains an iconic image. Collins took it while he orbited about 60 miles (97 km) above the moon in Apollo 11’s Columbia command module, where he had remained alone for 22 hours.

Background

The buck moon is the seventh of 12 full moons in 2025. A solar year is 365.24 days, while a lunar year is around 354.37 days, so sometimes there are 13 full moons in one calendar (solar) year — as in 2023 and next in 2028. Of the 12 full moons in 2025, three will be “supermoons” and two “blood moon” total lunar eclipses (the first happened on March 13-14, and the next lunar eclipse is on Sept. 7-8).

The next full moon is the sturgeon moon, which will occur on Saturday, Aug. 9. It will be the second full moon of summer in the Northern Hemisphere and winter in the Southern Hemisphere.

Further Reading

ForbesSee Two ‘Blood Moons,’ Three ‘Supermoons’ And The Biggest Full Moon Since 2019: The Moon In 2025By Jamie CarterForbesWhen To See June’s ‘Strawberry Moon,’ The Lowest Full Moon Since 2006By Jamie Carter

Saturday night presents a perfect opportunity to spot a “Golden Handle” shining brightly on the moon’s surface. It is a fleeting sight that appears when sunlight catches the peaks of a mountain range on the moon.

On July 5, the moon’s terminator, the line that separates lunar night from day, falls slightly to the west of the great circular plain Sinus Iridum (Latin for the ‘Bay of Rainbows’) in the northwest region of the lunar surface. At this time the sun is perfectly positioned to illuminate the eastern peaks of the vast Montes Jura mountain range bordering Sinus Iridum’s northernmost edge, giving rise to a spectacular golden arc that has since become known as the “Golden Handle”.