Skip to main content
Download PDF

Genomic and immunocyte characterisation of bloodstream infection caused by Klebsiella pneumoniae

Annals of Clinical Microbiology and Antimicrobials volume 23, Article number: 56 (2024) Cite this article

Abstract

Objectives

The aim of this study was to evaluate the characteristics of immunocyte associated with bloodstream infection (BSI) caused by Klebsiella pneumoniae (Kpn).

Methods

Patients with BSI-Kpn were included from 2015 to 2022 in our hospital. Immunocyte subpopulations of enrolled BSI-Kpn patients were tested on the same day of blood culture using multicolor flow cytometry analysis. Antibiotic susceptibility test was determined by agar dilution or broth dilution method. All included isolates were subjected to whole genome sequencing and comparative genomics analysis. Clinical and genetic data were integrated to investigate the risk factors associated with clinical outcome.

Results

There were 173 patients with non-duplicate BSI-Kpn, including 81 carbapenem-resistant Kpn (CRKP), 30 extended-spectrum β-lactamases producing Kpn (ESBL-Kpn), 62 none CRKP or ESBL-Kpn (S-Kpn). Among 68 ST11-CRKP isolates, ST11-O2v1:KL64 was the most common serotypes cluster (77.9%, 53/68), followed by ST11-OL101: KL47 (13.2%, 9/68). Compared with CSKP group, subpopulations of immunocyte in patients with CRKP were significantly lower (P < 0.01). In patients with ST11-O2v1:KL64 BSI-Kpn, the level of cytotoxic T lymphocytes (CD3 + CD8 +) is the highest, while the B lymphocytes (CD3-CD19 +) was the least. In addition, the level of immunocyte in patients with Kpn co-harbored clpV-ybtQ-qacE were lower than that in patients with Kpn harbored one of clpV, ybtQ or qacE and without these three genes. Furthermore, co-existence of clpV-ybtQ-qacE was independently associated with a higher risk for 30-day mortality.

Conclusions

The results demonstrate that patients with BSI-CRKP, especially for ST11-O2v1:KL64, exhibit lower leukomonocyte counts. In addition, BSI-Kpn co-harbored clpV-ybtQ-qacE is correlated to higher 30-day mortality.

Introduction

Klebsiella pneumoniae (Kpn) is one of significant pathogens for community-acquired and hospital-acquired infections, especially for bloodstream infection (BSI). In the last decade, the rate of BSI caused by carbapenem-resistant K. pneumoniae (CRKP) is trending upwards from 7.0% in 2014 to 19.6% in 2019 [1]. In addition, BSI-CRKP were associated with high mortality due to few therapeutic options [2, 3]. Recently, several novel antibiotics are available to combat CRKP, however, there have been reports of resistance to novel ß-lactams and ß -lactamase inhibitors [4, 5]. Therefore, clinical treatment for BSI-Kpn could not just rely upon antibiotics, and the interaction between CRKP and the host immune response needs to be further investigated.

Recent studies demonstrated that Kpn could enhance resistance by mediating cytokine levels and immune cell recruitment in host, resulting in disease-tolerant immune response [6,7,8]. In addition, several other evidence demonstrated that Kpn, especially for ST258 CRKP could actively subvert host defence by different immune evasion strategies, such as limiting C3b deposition, triggering apoptosis in macrophages and secretion of several siderophores [6]. Notably, ablating host defence by Kpn could cause a more pronounced bacteremia and accelerated mortality in infected mice [9, 10]. However, the majority of evidence on the interplay between Kpn and host immune response were obtained by infecting rodents, chiefly by mice [8,9,10]. Few studies addressed the response of immune cells to counteracting BSI- Kpn, especially for ST11 CRKP. Therefore, this present study was conducted to elucidate the immune cells response against different BSI-Kpn in clinic. In addition, clinical and genetic data were integrated to further investigate the risk factors associated with clinical outcome.

Methods

Patients and clinical data

A retrospective study was conducted to obtain profiles of the immune response in patients with BSI-Kpn and identify the risk factors associated with 30-day mortality. Clinical diagnosis of BSI-Kpn was screened by positive blood culture at The First Affiliated Hospital, Zhejiang University School of Medicine from 2015 to 2022. Meanwhile, patients tested immunocyte subpopulations on the same day of blood culture. The medical records of included patients were reviewed. The detailed analysis data and definitions were obtained as described in our previous study [11, 12]. The 30-day mortality was used as treatment outcomes. This study was approved by the recommendations of the Ethics Committee of The First Affiliated Hospital, Zhejiang University School of Medicine.

Analysis of immunocyte subpopulations with flow cytometry

The immunocyte subpopulations in the whole blood, including mature peripheral T lymphocytes (CD3 +), helper T lymphocytes (CD3 + CD4 +), cytotoxic T lymphocytes (CD3 + CD8 +), B lymphocytes (CD3-CD19 +), and natural killer cells (CD3-CD16 + CD56 +), were tested by multicolor flow cytometry as a previous study [13]. Heat map analysis for cytokine data was performed using TBtools [14].

Strain collection and antibiotic susceptibility test

A total of 173 BSI-Kpn strains were collected in the study. The minimal inhibitory concentration (MIC) of 20 antibiotics against BSI-Kp isolates were determined by agar dilution method, while antimicrobial sensitivity of tigecycline and polymyxin B was done by broth dilution method. Extended-spectrum-β-lactamase (ESBL)-producing isolates were confirmed for ESBLs production by disk synergy test [15]. CRKP was defined as Kpn strain resistant to imipenem or meropenem or ertapenem. Non-CRKP or non-ESBL-Kpn was considered as “susceptible” Kpn (S-Kpn). ESBL-Kpn and S-Kpn belong to carbapenem-sensitive K. pneumoniae (CSKP). The details of antibiotics were consistent with our previous study [16]. The results for test antibiotics were interpreted according to Clinical and Laboratory Standards Institute (CLSI) guidelines [15].

Genome sequencing and comparative genomics analysis

The genomic DNA of isolates was extracted by QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). Whole-genome sequencing (WGS) was performed on HiSeq 2000 platform (Illumina, USA) by the Beijing Novogene Institute (Beijing, China). Illumina raw reads were assembled and annotated using SPAdes v3.14.1 and Prokka v 1.10, respectively [17, 18].

Antimicrobial resistance genes, and virulence genes were identified using Resfinder and VFDB databases, respectively. Phylogenetic trees were built from core genome single nucleotide polymorphisms using kSNP4.1 [19]. K/O-type was determined using Kaptive v1.0 [20].

All sequence data has been deposited under BioProject accession No. PRJNA778807 and PRJNA1056658.

Statistical analysis

The results for abnormal distribution of continuous variables were presented as median (interquartile range) and analyzed using chi-square test. Multivariate analysis was performed after identifying variables with a P-value of < 0.05 in the univariate analysis. A two-tailed P value < 0.05 was considered to be statistically significant. GraphPad Prism software (V8.0) and SPSS 23.0 for Windows (SPSS Inc., Chicago, IL, USA) were used to analyze data. The 30-day mortality was established basing on the regression model by employing the R v4.1.2 package.

Results

Clinical characteristics in patients with BSI-Kpn

There were 173 patients with non-duplicate BSI-Kpn, including 81 CRKP, 30 ESBL, 62 S-Kpn, were included in this study. The clinical characteristics of all patients are shown in Table 1. There were no significant differences in gender and age. Organ transplant patients were more likely to be infected with CPKP. In addition, CRKP patients also underwent more invasive procedures. The levels of albumin and procalcitonin in patients with CRKP were lower than that in patients with CSKP. More patients in CRKP group received aminoglycoside, fosfomycin, tigecycline, polymyxin B, and ceftazidime-avibactam. APACHE-II score and SOFA score in CRKP were higher than that in CSKP (P < 0.05). Furthermore, the 30-day mortality in CRKP was significantly higher than that in CSKP (P < 0.000).

Table 1 Clinical characteristics of all patients with BSI-Kpn
Full size table

Antibiotic resistance and virulence profiles

A summary of 22 antibiotics MIC against BSI-Kpn is shown in Table 2. The lowest non-sensitive rates in the CRKP group were for tigecycline (4.9%) and polymyxin B (8.6%). The blaKPC (96.3%, 78/81) (77 blaKPC-2 and 1 blaKPC-3) were the major carbapenemase genes (Supplementary Table 1). There were three isolates were negative for carbapenemase genes, of which two isolates harbored blaSHV-182 and blaSHV-67, and other one isolate co-harbored blaSHV-182, blaCTX-M-15 and blaCTX-M-65.

Table 2 Minimum inhibitory concentrations of 22 antibiotics against BSI-Kpn
Full size table

In total, all ESBL-Kpn isolates were susceptible to imipenem, meropenem, fosfomycin. The susceptible rates of amoxicillin-clavulanic acid, piperacillin-tazobactam and cefoperazone-sulbactam for ESBL-Kpn were less than 40%. blaCTX-M genes were detected in 22 of 62 ESBL-producing isolates: 10 (45.5%) were blaCTX-M-3, 6 (27.3%) were blaCTX-M-15, 3 (13.6%) were blaCTX-M-14, 2 were (9.1%) blaCTX-M-27, and 1 (4.5%) was blaCTX-M-55 (Supplementary Table 1).

Among 62 S-Kpn isolates, more than 90% isolate showed susceptibility to aztreonam, moxalactam, third-generation cephalosporins, carbapenems, cefoperazone-sulbactam, amikacin, fosfomycin, tigecycline and polymyxin B. A portion of S-Kpn isolates (90.3%, 56/62) harbored blaSHV genes, of which 9 harbored blaSHV-190, 9 harbored blaSHV-98, and 6 harbored blaSHV-67 (Supplementary Table 1).

Virulence genes, such as all, clb, clbK, ompA, wcaJ, ybtT, were more common in CSKP isolates, while rmpA2, sciN, iucA-D, clpV, icmF, hcp, fimB, fepC, ybtQ, qacE were identified in more CRKP isolates (P < 0.05) (Supplementary Table 1).

Phylogenetic analysis

Among 81 BSI-CRKP isolates, ST11 was the predominant clone, accounting for 84.0% (N = 68), by ST15 (8/81, 9.9%). However, BSI-CSKP was sporadic and ST23 was the most common clone (12/92, 13.0%). There were five O-loci (Ols, outer lipopolysaccharide synthesis loci) in CRKP group, of which O2v1 (60/81, 74.1%) was the most prevalent, followed by O2v2 (9/81, 11.1%) and OL101 (9/81, 11.1%). By contrast, O2v2 (54/92, 58.7%) was the predominant OL in CSKP group. CRKP group included 9 K-loci (KLs, capsule synthesis loci), KL64 (54/81, 66.7%) was predominant, followed by KL47 (10/81, 12.3%). The two most common KLs in CSKP group were KL2 (24/92, 26.1%) and KL1 (14/92, 15.2%).

Among 68 ST11-CRKP isolates, ST11-O2v1:KL64 was the most common serotypes cluster (77.9%, 53/68), followed by ST11-OL101: KL47 (13.2%, 9/68). Except for one isolate belonged to ST15-O2v1:KL19, other seven isolates were ST15-O2v2:KL19 in ST15-CRKP. All ST11-O2v1:KL64 isolates were clustered in one highly related clade of the phylogenetic tree, which is also clustered with one sublineage of ST11-OL101: KL47 and one sublineage ST11-O2v1:KL21. ST15-O2v2:KL19 in CRKP was roosted with ST15-CSKP (Fig. 1). Among CSKP, ST23-O2v2:KL1 was the predominant serotypes cluster, followed by ST25-O2v2:KL2 and ST65-O2v2:KL2, which ST25-O2v2:KL2 and ST65-O2v2:KL2 clustered together to form a branching clade and ST23-O2v2:KL1 clustered into another sublineage.

Fig. 1
figure 1

Phylogenetic analysis of 173 BSI-Kpn isolates collected in this study

Full size image

Subpopulations of immunocyte

Absolute number of leukomonocyte (CD45 +) in CRKP and CSKP were 309.0 (161.0–514.0) and 600.5 (226.5–934.3) cells/μl, respectively (Supplementary Table 2). The absolute numbers of mature peripheral T lymphocytes (CD3 +), helper T lymphocytes (CD3 + CD4 +), cytotoxic T lymphocytes (CD3 + CD8 +), and natural killer cells (CD3-CD16 + CD56 +) in patients with CRKP were significantly lower than that in CSKP (P < 0.01) (Fig. 2). The proportion of natural killer cells in the death group decreased more significantly (P = 0.041) (Supplementary Fig. 1). Among CRKP isolates, the level of cytotoxic T lymphocytes (CD3 + CD8 +) in ST11-O2v1:KL64 is higher than other serotypes and STs combinations (Supplementary Table 3). The B lymphocytes (CD3-CD19 +) showed the lowest level in ST11-O2v1:KL64. However, the difference of B lymphocytes (CD3-CD19 +) level between the death group and the survival group is not significant whether in CRKP or CSKP. The level of immunocyte in isolates co-harbored clpV-ybtQ-qacE were lower than that in isolates harbored one of clpV, ybtQ or qacE and without these three genes (Fig. 3 and Supplementary Table 4).

Fig. 2
figure 2

Subpopulations of immunocyte between CRKP and CSKP groups. N, Normal; D, decrease

Full size image
Fig. 3
figure 3

Overview of immunocyte, carbapenem resistance, and virulence genes among BSI-Kpn patients

Full size image

Risk factors for 30-day mortality in enrolled patients

A total of 42 BSI-Kpn patients died, including 12 CSKP and 30 CRKP. The results of univariate analysis and logistic regression was shown in Table 3 and Supplementary Table 5. Compared to the survival group, BSI-Kpn patients with resistance genes (blaKPC-like, blaTEM-1B, rmtB, dfrA-like, aadA, ramR) and virulence genes (AAA92657, clpV, ybtQ, ybtU) caused higher mortality (P < 0.05). Notably, BSI-Kpn isolates co-harbored clpV, ybtQ and qacE resulted in higher 30-day mortality than isolates carried one of three or none of them (Fig. 4).

Table 3 Logistic regression model of isk factors for 30-day mortality
Full size table
Fig. 4
figure 4

Kaplan–Meier survival estimates for patients with BSI-Kpn co-harbored clpV-ybtQ-qacE, harbored one of clpV, ybtQ or qacE, and without these three genes. A significant difference was found in the 30-day mortality between the 3 groups (P < 0.0001)

Full size image

Lower count of white blood cell, hemoglobin, platelet, and cholinesterase showed significant associations with 30-day mortality in a univariate analysis. In addition, use of glucocorticoid and immunosuppressant before BSI-Kpn are risk factors for 30-day mortality. Patients with longer ICU stay and more invasive procedures, such as mechanical ventilation, hemodialysis, urinary catheterization, arterial catheterization and stomach tube, had a higher mortality rate (P < 0.05). Tigecycline and combination therapy after diagnosis led to increased 30-day mortality. Further logistic regression established multivariate predictive model, demonstrating length of ICU stay, hemodialysis, urinary catheterization, platelet count, APACHE-II score and co-existence of clpV-ybtQ-qacE independently associated with a higher risk for 30-day mortality.

Discussion

Although novel antibiotics have shown promising efficacy against multidrug-resistant bacterial infections, the mortality rate in BSI-CRKP remains high [2, 3]. Therefore, relying on antibiotics is not enough. Clearance of Kpn requires a complex, multi-faceted response of innate immune cells and ultimately resolved by adaptive immune cells [6, 21]. Therefore, the role of host immune responses and the interaction between BSI-Kpn and immunocyte in treating deadly infections deserves attention.

Kpn display a population structure characterized by genetic diversity, however, highly successful clonal genetic lineages were observed in CRKP, such as ST258 and ST11 [22, 23]. However, a previously prevalent subclone OL101:KL47 was replaced by O2v1:KL64 in the predominant clone ST11 [23]. In the present study, we also found ST11-O2v1:KL64 was the most common serotypes cluster in BSI-CRKP, which clustered with one sublineage of ST11-OL101: KL47 as well. The abundant genetic diversity between CRKP and CSKP may result in heterogeneity of interaction with host immune responses [24].

Several studies demonstrated that Kpn, especially for CRKP, could frustrate normal immune responses, capitalize upon states of immunocompromise, and cause infections with high mortality [21, 25]. Our results demonstrated the absolute numbers of tested immunocyte in patients with CRKP were significantly lower than that in CSKP (P < 0.01). Previous study found Kpn stimulated highly purified human blood B cells [26]. Our study further demonstrated the B lymphocytes (CD3-CD19 +) in ST11-O2v1:KL64 showed the lowest level. Therefore, genetic diversity of BSI-Kpn impacts the outcomes of the interactions between the Kpn and each of these host immunocyte responses. Previous studies revealed bacterial factors of hypervirulent Kpn, such as capsule polysaccharides, lipopolysaccharide, type VI secretion system (T6SS) resulted in a common evasion strategy based on phagocytosis evasion, while CRKP showed heterogeneous evasion strategies, leading to prolong intracellular survival [7, 9, 27]. However, few studies have addressed the relationship between genetic diversity of Kpn and inflammatory response. To obtain comprehensive information, it will be necessary to assess the mechanism of common and unique interaction between BSI-Kpn heterogeneity and immune cells.

Although some studies have demonstrated CRKP infections were associated with BSI mortality in several clinical series, the risk factors remain inconsistent [2, 3, 28]. CD4 + /CD8 + T lymphocytes ratio < 1 was identified as independent risk factors for ICU admission patients with CRKP infections [28]. Similarly, we found the level of CD8 + in ST11-O2v1:KL64 among patients with CRKP was higher than that in other serotypes and STs combinations. The level of immunocyte in isolates co-harbored clpV-ybtQ-qacE were lower than that in isolates harbored one of clpV, ybtQ or qacE and without these three genes. Furthermore, co-existence of clpV-ybtQ-qacE was independently associated with a higher risk for 30-day mortality. Previous studies reported T6SS core component (clpV) used by Salmonella to survive within host macrophages [29]. ybtQ, encoding a transporter for the siderophore yersiniabactin, played an important role for the ability of Kpn to maintain infection in a mammalian host [30]. qacE, as disinfectant resistance gene, reduced biocide susceptibility [31]. Taken together, these data show correlation among virulence, antibiotic resistance and inflammatory response, which could affect the ability to clear Kpn and increase the risk of death.

This study firstly provides an insight into interactions between different phylogenetic BSI-Kpn and immunocyte subpopulations in clinic. However, there were also several limitations in the present study. First, the immune cells were not dynamically observed during the infections. Therefore, it is unable to fully elucidate the changes in host inflammatory response throughout the entire BSI process. In addition, the number of isolates in this study remains not enough. Above all, there is a pressing need to focus on the dynamics and outcomes of the interactions between BSI-Kpn heterogeneity and host immune response.

Conclusions

In conclusion, BSI-CRKP, especially for ST11-O2v1:KL64, was associated with 30-day mortality. In addition, subpopulations of immunocyte in patients with CRKP were lower than that in other BSI-Kpn. Furthermore, co-existence of clpV-ybtQ-qacE in BSI-Kpn not only showed lower immunocyte count, but it also resulted in high mortality rates. Therefore, further better understanding of BSI-Kpn-host interactions is needed to develop new therapeutics.

Data availability

All sequence data has been deposited under BioProject accession No. PRJNA778807 and PRJNA1056658.

References

  1. Chen Y, Ji J, Ying C, Liu Z, Yang Q, Kong H, Xiao Y, Blood Bacterial Resistant Investigation Collaborative System (BRICS) Study Group. Blood bacterial resistant investigation collaborative system (BRICS) report: a national surveillance in China from 2014 to 2019. Antimicrob Resist Infect Control. 2022;11(1):17. https://doi.org/10.1186/s13756-022-01055-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Kern WV, Rieg S. Burden of bacterial bloodstream infection-a brief update on epidemiology and significance of multidrug-resistant pathogens. Clin Microbiol Infect. 2020;26(2):151–7. https://doi.org/10.1016/j.cmi.2019.10.031.

    Article  CAS  PubMed  Google Scholar 

  3. Kohler PP, Volling C, Green K, Uleryk EM, Shah PS, McGeer A. Carbapenem resistance, initial antibiotic therapy, and mortality in Klebsiella pneumoniae bacteremia: a systematic review and meta-analysis. Infect Control Hosp Epidemiol. 2017;38(11):1319–28. https://doi.org/10.1017/ice.2017.197.

    Article  PubMed  Google Scholar 

  4. Kanj SS, Bassetti M, Kiratisin P, Rodrigues C, Villegas MV, Yu Y, van Duin D. Clinical data from studies involving novel antibiotics to treat multidrug-resistant Gram-negative bacterial infections. Int J Antimicrob Agents. 2022;60(3): 106633. https://doi.org/10.1016/j.ijantimicag.2022.106633.

    Article  CAS  PubMed  Google Scholar 

  5. Yu W, Shen P, Chen Y, Zhou K, Chi X, Xiao Y. Epidemiology and genomic characteristics of bloodstream infection caused by carbapenem-resistant Klebsiella pneumoniae with decreased susceptibility to aztreonam/avibactam in China. Front Cell Infect Microbiol. 2022;12: 926209. https://doi.org/10.3389/fcimb.2022.926209.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Bengoechea JA, Sa PJ. Klebsiella pneumoniae infection biology: living to counteract host defences. FEMS Microbiol Rev. 2019;43(2):123–44. https://doi.org/10.1093/femsre/fuy043.

    Article  CAS  PubMed  Google Scholar 

  7. Wong Fok Lung T, Charytonowicz D, Beaumont KG, Shah SS, Sridhar SH, Gorrie CL, Mu A, Hofstaedter CE, Varisco D, McConville TH, Drikic M, Fowler B, Urso A, Shi W, Fucich D, Annavajhala MK, Khan IN, Oussenko I, Francoeur N, Smith ML, Stockwell BR, Lewis IA, Hachani A, Upadhyay Baskota S, Uhlemann AC, Ahn D, Ernst RK, Howden BP, Sebra R, Prince A. Klebsiella pneumoniae induces host metabolic stress that promotes tolerance to pulmonary infection. Cell Metab. 2022;34(5):761-774.e9. https://doi.org/10.1016/j.cmet.2022.03.009.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ahn D, Bhushan G, McConville TH, Annavajhala MK, Soni RK, Wong Fok Lung T, Hofstaedter CE, Shah SS, Chong AM, Castano VG, Ernst RK, Uhlemann AC, Prince A. An acquired acyltransferase promotes Klebsiella pneumoniae ST258 respiratory infection. Cell Rep. 2021;35(9):109196. https://doi.org/10.1016/j.celrep.2021.109196.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Feriotti C, Sá-Pessoa J, Calderón-González R, Gu L, Morris B, Sugisawa R, Insua JL, Carty M, Dumigan A, Ingram RJ, Kissenpfening A, Bowie AG, Bengoechea JA. Klebsiella pneumoniae hijacks the Toll-IL-1R protein SARM1 in a type I IFN-dependent manner to antagonize host immunity. Cell Rep. 2022;40(6): 111167. https://doi.org/10.1016/j.celrep.2022.111167.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Dolgachev VA, Yu B, Sun L, Shanley TP, Raghavendran K, Hemmila MR. Interleukin 10 overexpression alters survival in the setting of gram-negative pneumonia following lung contusion. Shock. 2014;41(4):301–10. https://doi.org/10.1097/SHK.0000000000000123.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Chen Y, Ying S, Jiang L, Dong S, Dai J, Jin X, Yu W, Qiu Y. A Novel nomogram for predicting risk factors and outcomes in bloodstream infections caused by Klebsiella pneumoniae. Infect Drug Resist. 2022;15:1317–28. https://doi.org/10.2147/IDR.S349236.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Pan H, Lou Y, Zeng L, Wang L, Zhang J, Yu W, Qiu Y. Infections caused by carbapenemase-producing Klebsiella pneumoniae: microbiological characteristics and risk factors. Microb Drug Resist. 2019;25(2):287–96. https://doi.org/10.1089/mdr.2018.0339.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Guo W, Lian X, Li H, Jiang L, Chen Y, Shen P, Yu W. Characteristics of immunocytes and cytokines in patients with bloodstream infections caused by carbapenem-resistant Klebsiella pneumoniae in China. Infect Drug Resist. 2024;17:719–25. https://doi.org/10.2147/IDR.S431207.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, He Y, Xia R. TBtools: an integrative toolkit developed for interactive analyses of big biological data. Mol Plant. 2020;13(8):1194–202. https://doi.org/10.1016/j.molp.2020.06.009.

    Article  CAS  PubMed  Google Scholar 

  15. Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing. 32th informational supplement 2022. 2022. http://www.clsi.org/.

  16. Yu W, Luo Q, Shen P, Chen Y, Xu H, Xiao Y, Qiu Y. New options for bloodstream infections caused by colistin- or ceftazidime/avibactam-resistant Klebsiella pneumoniae. Int J Antimicrob Agents. 2021;58(6): 106458. https://doi.org/10.1016/j.ijantimicag.2021.106458.

    Article  CAS  PubMed  Google Scholar 

  17. Prjibelski A, Antipov D, Meleshko D, Lapidus A, Korobeynikov A. Using SPAdes De Novo assembler. Curr Protoc Bioinformatics. 2020;70(1): e102. https://doi.org/10.1002/cpbi.102.

    Article  CAS  PubMed  Google Scholar 

  18. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30(14):2068–9. https://doi.org/10.1093/bioinformatics/btu153.

    Article  CAS  PubMed  Google Scholar 

  19. Gardner SN, Slezak T, Hall BG. kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome. Bioinformatics. 2015;31(17):2877–8. https://doi.org/10.1093/bioinformatics/btv271.

    Article  CAS  PubMed  Google Scholar 

  20. Wyres KL, Wick RR, Gorrie C, Jenney A, Follador R, Thomson NR, Holt KE. Identification of Klebsiella capsule synthesis loci from whole genome data. Microb Genom. 2016;2(12): e000102. https://doi.org/10.1099/mgen.0.000102.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Gonzalez-Ferrer S, Peñaloza HF, Budnick JA, Bain WG, Nordstrom HR, Lee JS, Van Tyne D. Finding order in the chaos: outstanding questions in Klebsiella pneumoniae pathogenesis. Infect Immun. 2021;89(4):e00693-e720. https://doi.org/10.1128/IAI.00693-20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Wyres KL, Lam MMC, Holt KE. Population genomics of Klebsiella pneumoniae. Nat Rev Microbiol. 2020;18(6):344–59. https://doi.org/10.1038/s41579-019-0315-1.

    Article  CAS  PubMed  Google Scholar 

  23. Zhou K, Xue CX, Xu T, Shen P, Wei S, Wyres KL, Lam MMC, Liu J, Lin H, Chen Y, Holt KE, Xiao Y, BRICS Working Group. A point mutation in recC associated with subclonal replacement of carbapenem-resistant Klebsiella pneumoniae ST11 in China. Nat Commun. 2023;14(1):2464. https://doi.org/10.1038/s41467-023-38061-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gomez-Simmonds A, Uhlemann AC. Clinical implications of genomic adaptation and evolution of carbapenem-resistant Klebsiella pneumoniae. J Infect Dis. 2017;215(suppl_1):S18–27. https://doi.org/10.1093/infdis/jiw378.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Ernst CM, Braxton JR, Rodriguez-Osorio CA, Zagieboylo AP, Li L, Pironti A, Manson AL, Nair AV, Benson M, Cummins K, Clatworthy AE, Earl AM, Cosimi LA, Hung DT. Adaptive evolution of virulence and persistence in carbapenem-resistant Klebsiella pneumoniae. Nat Med. 2020;26(5):705–11. https://doi.org/10.1038/s41591-020-0825-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Gross WL, Rucks A. Klebsiella pneumoniae stimulate highly purified human blood B cells to mature into plaque forming cells without prior proliferation. Clin Exp Immunol. 1983;52(2):372–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Beceiro A, Tomás M, Bou G. Antimicrobial resistance and virulence: a successful or deleterious association in the bacterial world? Clin Microbiol Rev. 2013;26(2):185–230. https://doi.org/10.1128/CMR.00059-12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Li Y, Shen H, Zhu C, Yu Y. Carbapenem-resistant Klebsiella pneumoniae infections among ICU admission patients in central China: prevalence and prediction model. Biomed Res Int. 2019;2019:9767313. https://doi.org/10.1155/2019/9767313. (eCollection 2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Blondel CJ, Jiménez JC, Leiva LE, Alvarez SA, Pinto BI, Contreras F, Pezoa D, Santiviago CA, Contreras I. The type VI secretion system encoded in Salmonella pathogenicity island 19 is required for Salmonella enterica serotype Gallinarum survival within infected macrophages. Infect Immun. 2013;81(4):1207–20. https://doi.org/10.1128/IAI.01165-12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lawlor MS, O’connor C, Miller VL. Yersiniabactin is a virulence factor for Klebsiella pneumoniae during pulmonary infection. Infect Immun. 2007;75(3):1463–72. https://doi.org/10.1128/IAI.00372-06.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Paulsen IT, Littlejohn TG, Rådström P, Sundström L, Sköld O, Swedberg G, Skurray RA. The 3′ conserved segment of integrons contains a gene associated with multidrug resistance to antiseptics and disinfectants. Antimicrob Agents Chemother. 1993;37(4):761–8. https://doi.org/10.1128/AAC.37.4.761.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

None.

Funding

This work was supported by the Zhejiang Provincial Natural Science Foundation of China under Grant No. LTGY24H190002 and Independent Task of State Key Laboratory for Diagnosis and Treatment of Infectious Diseases (No. 2022zz01). The funder had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. Wei Yu and Chen Huang have contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

    Wei Yu, Lushun Jinag, Ping Shen & Yonghong Xiao

  2. Department of Respiratory Medicine, Ningbo Medical Center Lihuili Hospital, Ningbo, China

    Chen Huang

  3. Department of Infectious Diseases, The Affiliated Xiangshan Hospital of Wenzhou Medical University, Xiangshan First People’s Hospital Medical and Health Group, Ningbo Fourth Hospital, Ningbo, China

    Xiang Lian & Hong Li

Authors
  1. Wei Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chen Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiang Lian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lushun Jinag
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ping Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yonghong Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agree to be accountable for all aspects of the work.

Corresponding authors

Correspondence to Ping Shen or Yonghong Xiao.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the recommendations of the Ethics Committee of The First Affiliated Hospital, Zhejiang University School of Medicine with written informed consent from all subjects (Reference Number: 2021789).

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yu, W., Huang, C., Lian, X. et al. Genomic and immunocyte characterisation of bloodstream infection caused by Klebsiella pneumoniae. Ann Clin Microbiol Antimicrob 23, 56 (2024). https://doi.org/10.1186/s12941-024-00721-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12941-024-00721-3

Keywords

Annals of Clinical Microbiology and Antimicrobials

ISSN: 1476-0711

Contact us