GC–IMS facilitates identification of carbapenem-resistant Klebsiella pneumoniae in simulated blood cultures

Abstract

This study aimed to identify carbapenem-resistant Klebsiella pneumoniae (CRKP) based on changes in levels of its volatile organic compounds (VOCs) in simulated blood cultures (BCs) using the gas chromatography–ion mobility spectrometry (GC–IMS) technique. A comprehensive analysis of volatile metabolites produced by Klebsiella pneumoniae (K. pneumoniae) in BC bottles was conducted using GC–IMS. Subsequently, the released VOCs were analyzed to examine differences in VOC release between CRKP and carbapenem-susceptible Klebsiella pneumoniae (CSKP). A total of 54 VOCs were detected, of which 18 (6 VOCs found in both monomer and dimer forms) were successfully identified. The VOCs produced by K. pneumoniae in BC bottles (BacT/ALERT® SA) were primarily composed of organic acids, alcohols, esters, and ketones. The content of certain VOCs was significantly different between CRKP and CSKP after the addition of imipenem (IPM). Moreover, the inclusion of carbapenemase inhibitors facilitated the identification of carbapenemase-producing K. pneumoniae based on the variations in VOCs. This study demonstrates the utility of GC–IMS technology in identifying CRKP, and reveals that changes in VOCs are closely related to the growth and metabolism of K. pneumoniae, indicating that they can be leveraged to promote early identification of CRKP bacteremia. However, further in-depth studies and experiments are needed to validate our findings.

Introduction

Bloodstream infection (BSI) is a systemic infectious disease that threatens human life and health. It has been shown to induce bacteremia, septicemia and sepsis. In some cases, it causes shock, disseminated intravascular coagulation (DIC), multiple organ failure, and even death (Kern and Rieg 2020; Tabah et al. 2023; Timsit et al. 2020). Epidemiologic data in China have demonstrated that Gram-negative bacteria, such as Escherichia coli and Klebsiella pneumoniae (K. pneumoniae), are the most commonly isolated pathogens associated with BSI, accounting for over 50% of BSI diseases (Chen et al. 2023). The widespread use of antibiotics and the prevalence of carbapenem-resistant Enterobacteriaceae (CRE) have made it difficult to treat these infections (Fang et al. 2023; Liu et al. 2021). Carbapenem-resistant Klebsiella pneumoniae (CRKP) is the most prevalent CRE associated with BSI. It is prevalent in developed and developing countries, with high drug resistance and mortality rates (Fang et al. 2023; Liu et al. 2021). Notably, CRKP accounts for 60–90% of all CRE isolates in China (Hu et al. 2022). In 2021, an annual report of the Blood Bacterial Resistance Investigation Collaborative System (BRICS) indicated that the isolation rate of CRKP was 15.8% (328/2076) (Chen et al. 2023). Generally, the management of CRKP BSI is challenging because of emergence of rapid spread of multidrug resistance strains, high mortality rate, and lack of antimicrobial agents. Therefore, it is important to identify CRKP BSIs and develop appropriate antimicrobial agents to improve patient treatment.

Currently, CRKP is primarily identified using conventional antimicrobial drug susceptibility testing methods. Although new methods, such as the widely employed carbapenem inactivation method (CIM), have increased the accuracy of detecting specific CRKP carbapenemase (CBPM) type, these supplementary tests are time-consuming and often necessitate overnight culture, which delays the initiation of clinical treatments (Luo et al. 2023; Yu et al. 2022). Therefore, investigating novel approaches for the rapid detection of CRKP is imperative.

Volatile organic compounds (VOCs) are a diverse collection of low-molecular-weight, low-boiling-point, high-vapor-pressure metabolites generated by bacteria (Kai et al. 2009). Accumulating evidence indicates that VOCs are potential biomarkers for bacterial identification (Chen et al. 2017b; Drees et al. 2019; Lu et al. 2022). Research conducted by our team on bacterial metabolomics has yielded significant findings with regard to the application of rapid mass spectrometry-based detection of bacteremia pathogens based on microbial VOC fingerprints (Chingin et al. 2015, 2016; Hang et al. 2017; Hu et al. 2016; Zhong et al. 2019).

To date, most studies have primarily investigated the involvement of VOCs in pathogenic bacteria identification. Only a handful of studies have identified strains by assessing alterations in VOCs based on the drug susceptibility and antibiotic resistance mechanisms of these pathogenic bacteria. In our previous study, we achieved early identification of CBPM-producing CRKP by examining changes in 3-methyl-1-butanol levels in trypticase soy broth (TSB) cultures (Luo et al. 2023). Furthermore, another study reported that carbapenem-susceptible Klebsiella pneumoniae (CSKP) can be differentiated from CRKP based on VOCs changes in TSB cultures (Filipiak et al. 2022). However, these studies employed gas chromatography–mass spectrometry (GC–MS), which has multiple pre-processing steps and long MS analysis time, making it unsuitable for widespread adoption. This calls for the development of more streamlined and rapid detection methods to facilitate early identification of CRKP.

Gas chromatography–ion mobility spectrometry (GC–IMS)—also referred to as gas electrophoresis (GEP) or plasma chromatography (PEC)—is a gas phase technique often used for the identification and characterization of VOCs. This technique leverages the differences in gas-phase ion mobility under a weak electric field, seamlessly merging the exceptional separation power of gas chromatography (GC) with the unmatched resolution, sensitivity, and accuracy of ion mobility spectrometry (IMS) (Drees et al. 2019). It has been widely investigated with regarding its ability to identify bacterial infections (Drees et al. 2019; Lacey et al. 2020; Lu et al. 2022).

In this study, we aimed to investigate differential VOCs between CSKP and CRKP using the GC–IMS method. VOCs were analyzed in simulated blood cultures (BCs) of both standards, under in vitro conditions, to identify metabolites associated with carbapenem resistance. The effects of imipenem (IPM) and CBPM inhibitors on VOCs were also examined.

Materials and methods

Bacteria strains and CBPM detection

The bacterial strains of K. pneumoniae ATCC BAA-1706 (CBPM-negative), ATCC BAA-1705 (bla Klebsiella pneumoniae carbapenemase (KPC)-positive), ATCC BAA-2146 (bla New Delhi metallo-β-lactamase (NDM)-positive), and ATCC BAA-2524 (bla oxacillinase-48 (OXA-48)-positive) were purchased from the American Type Culture Collection (ATCC) (Manassas, VA). Experiments involving these standard strains were performed in sextuplicate (one technical replicate was used in all samples).

Meanwhile, 69 K. pneumoniae isolates collected at the Second Affiliated Hospital of Nanchang University from January 1, 2016 to December 31, 2022 were analyzed. The isolates consisted of 25 CSKP isolates and 44 CRKP isolates (20 KPC-positive strains, 15 NDM-positive strains, 4 IPM-positive strains, and 5 CBPM-negative strains). The experiments involving these clinical strains were performed in triplicate for each strain.

All strains (standard and clinical strains) were kept in glycerol broth (15% glycerol) (Solarbio, China) in a − 80 °C freezer for further testing.

The identification of K. pneumoniae was conducted using the VITEK® 2 system (Bio-Merieux, Inc., France) or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) system (bioMérieux). Antibiotic susceptibility testing of K. pneumoniae was performed using a Kirby–Bauer (KB) test and the VITEK® 2 compact system, and the minimum inhibitory concentrations of ertapenem (ERT) and IPM were determined following the criteria set by the Clinical Laboratory Standards Institute (CLSI 2022). The assessment of CBPM production was conducted using two methodologies: the modified carbapenem inactivation method (mCIM) and the ethylenediaminetetraacetic acid (EDTA)-modified carbapenem inactivation method (eCIM). Moreover, the carbapenem resistance gene was characterized by polymerase chain reaction (PCR) amplification and sequencing.

Schematic diagram of GC–IMS

VOCs in each sample group were detected using the commercial GC–IMS equipment (GC–IMS; FlavourSpec®; G.A.S., Dortmund, Germany). The integration of GC and IMS in GC–IMS enables the simultaneous achievement of high-resolution pre-separation (GC) and high-sensitivity detection (IMS). As described in Additional file 3: Fig. S1, initially, molecules from the sample are separated by the GC component based on their interactions with the stationary phase coating on the chromatographic column wall. Subsequent to the separation of molecules by GC, ionization typically occurs through a tritium source. The ionized molecules are then propelled along the drift tube under the influence of an electric field. Highly pure nitrogen gas (N₂) introduced into the drift tube from the opposite direction causes molecules with varying mass and charge to exhibit different travel times to reach the Faraday plate. Finally, the combination of the retention time in the GC portion and the time of drift in the IMS section aids in the identification of compounds (Drees et al. 2019; Lu et al. 2022).

Culture conditions and sample preparation

The culture solutions utilized for experimentation were acquired from BacT/ALERT® SA (Ref. 259789; Biomérieux, Nürtingen, Germany) BC bottles. The medium consisted of pancreatic digest of casein (1.7% w/v), papain digest of legume-based food (0.3% w/v), sodium polyanethole sulfonate (0.035% w/v), pyridoxine hydrochloride (0.001% w/v), and a combination of various amino acids, as well as hydrocarbon digests in purified water.

As shown in Fig. 1, our preliminary findings demonstrated that the growth rate of K. pneumoniae exhibited its highest velocity at approximately 3 h after being subjected to the specified culture conditions (total volume: 6 mL; microbial concentration: 10⁷ colony forming units (CFU)/mL; culture medium: BacT/ALERT® SA; temperature: 37 °C; agitation: 200 rpm), subsequently transitioning into the end exponential growth phase around the 5 h mark.

Fig. 1

Growth curves of K. pneumoniae (standard strains)

The sample preparation process is presented in Additional file 3: Fig. S2. The experimental strains were inoculated on Columbia blood agar plates and incubated overnight at 37 °C. Subsequently, the bacterial suspensions were transferred to test tubes containing the culture medium (BacT/ALERT® SA), wherein the bacterial concentration was 10⁷ CFU/mL, with a total volume of 6 mL, and incubation was continued at 37 °C and 200 rpm agitation. About 500 mL of bacterial culture fluid for GC–IMS analysis was taken after incubation for 3 (T0), 4 (T1), 5 (T2), 6 (T3), and 7 (T4) h. A blank sterile medium served as a control.

To investigate the effect of IPM on CSKP and CRKP, a solution of IPM (Solarbio, China) was added to the bacterial suspension at the T0 time point, with a final concentration of 0.25 mg/mL (Luo et al. 2023). The incubation process was continued and all other conditions were maintained (Additional file 3: Fig. S2). Furthermore, subsequent experiments were undertaken to examine the influence of CBPM inhibitors on K. pneumoniae strains that produce CBPM. Similarly, the bacterial suspensions were simultaneously mixed with IPM and CBPM inhibitors [avibactam sodium or pyridine-2,6-dicarboxylic acid (DPA)] at T0, with avibactam sodium (Solarbio, China) concentration set at 1 mg/L (Luo et al. 2023) and DPA (Solarbio, China) concentration at 100 mg/L (Chen et al. 2017a).

GC–IMS measurements

GC–IMS equipped with an MXT-WAX column (a high-polar column, 15 m × 0.53 mm, 0.1 μm, RESTEK, Bellefonte, PA, America) was used. The experimental parameters utilized in the GC–IMS analysis are displayed in Additional file 1: Table S1 and the schematic representation of the experimental workflow is depicted in Additional file 3: Fig. S3. Briefly, a headspace vial comprising the test culture medium (500 µL) was positioned within an autosampler and agitated at 500 rpm for 3 min at 60 °C. Subsequently, 1 mL of headspace gas was extracted from the vial, and the specimen under examination was introduced into the GC–IMS detection apparatus for 10 min.

Data analysis

GC–IMS data were analyzed using the VOCal Version 0.1.3 software (G.A.S. mbH, Dortmund, Germany), employing C4–C9 ketones (2-butanone, 2-pentanone, 2-hexanone, 2-heptanone, 2-octanone, 2-nonanone) as reference standards. After data calibration, the VOCs were identified based on the retention index (RI) and drift time (reactant ion peak (RIP) relative) found in the GC–IMS library (NIST and IMS libraries) (Euler et al. 2022). Subsequently, the relative peak volume values (integrating peak intensities within specific regions after comparing calibrations) of VOCs were extracted from the software for statistical analysis. Given the limited number of VOCs (n = 54), potential VOCs exhibiting fold change (FC) values > 1.20 and a P-value < 0.05 were categorized as increased, whereas those with FC values < 0.83 and a P-value < 0.05 were categorized as decreased, in the context of inter-group comparisons (Mann–Whitney U test). Data processing and statistical analysis were conducted using R (version 4.2.1), while online tools ChiPlot (https://www.chiplot.online/) and OmicStudio (https://www.omicstudio.cn/tool), as well as Microsoft Office PowerPoint 2021 (Microsoft, Seattle, WA), were utilized for data visualization.

Results

Analysis of K. pneumoniae (standard strains) metabolites in the matrix components of BC bottles

A total of 54 VOCs (6 VOCs occurring as both monomers and dimers), including 4 organic acids, 3 alcohols, 3 esters, 4 ketones, 2 pyrazines, 2 benzene derivatives, and 30 unidentified compounds, were detected by GC–IMS (Table 1). Changes in the 54 VOCs throughout the time (T0–T4) were significant (Additional file 2: Table S2). K. pneumoniae reached the termination of its exponential growth phase at approximately 5 h (T2), and correspondingly, alterations in VOCs were no longer evident beyond T2 (Fig. 1). Hence, T2 was used for subsequent analysis.

Table 1 Information of the specific VOCs detected by GC–IMS

Changes in VOCs for each of the standard strains (ATCC BAA-1706, ATCC BAA-1705, ATCC BAA-2146, and ATCC BAA-2524) compared with the blank control group at T2 are shown in Fig. 2 and Additional file 2: Table S3. Compared with the blank control group, 26 VOCs were increased whereas 7 were decreased in the ATCC BAA-1706. For K. pneumoniae ATCC BAA-1705, 30 VOCs were increased whereas 8 were decreased. For K. pneumoniae ATCC BAA-2146, 30 VOCs were increased and 10 were decreased, and 30 VOCs were increased and 10 were decreased in the K. pneumoniae ATCC BAA-2524 (Fig. 3A).

Fig. 2

The heatmap of VOCs expression profile of each sample (after min–max normalization)

Fig. 3

The VOCs emitted by K. pneumoniae (standard strains, without IPM added). A The volcano plots of differential VOCs between the blank control group and the experimental groups. B The heatmap of the differentially expressed VOCs determined using the volcano plots (compared with the blank control group, after binarization). C The PCA of the sample groups (without IPM added)

Further analysis demonstrate that the principal VOCs released by K. pneumoniae (all standard strains) metabolites in the matrix components of BC bottles encompassed organic acids (3-methylbutanoic acid (monomer and dimer), 2-methylpropanoic acid (monomer and dimer), propionic acid (monomer and dimer), and acetic acid), alcohols (1,2-ethanediol and 3-methyl-1-butanol), ketones [isovalerone, butane-2,3-dione (diacetyl), and 3-hydroxy-2-butanone (acetoin)], and 2-methylpyrazine-M (monomer), compared with the blank control group. Meanwhile, benzaldehyde (monomer and dimer), butan-2-one, and 2-methylpyrazine-D (dimer) in K. pneumoniae standard strains were significantly reduced compared with those in the blank control group (Fig. 3B and Table 2). However, 13 VOCs exhibiting an upward trend and 3 VOCs displaying a downward trend were not accurately identified (Fig. 3B and Table 2).

Table 2 Volatile metabolic profiles of Klebsiella pneumoniae (standard strains) in the matrix components of BC bottles (at T2 time point)

The utility of VOCs in identifying CRKP based on standard strains

Next, K. pneumoniae ATCC BAA-1706 (CBPM-negative) was used as a negative control (CSKP), and K. pneumoniae ATCC BAA-1705 (bla KPC-positive), K. pneumoniae ATCC BAA-2146 (bla NDM-positive), K. pneumoniae ATCC BAA-2524 (bla OXA-48-positive) were used as a positive control (CRKP).

To investigate the potential of VOCs in distinguishing CRKP, a comprehensive analysis was conducted to examine the disparities in VOCs between CSKP and CRKP. Remarkably, 5 VOCs (unidentified-3, unidentified-21, unidentified-28, and butan-1-ol were increased, whereas unidentified-30 was decreased) differed significantly in the CRKP group compared with the CSKP group (Fig. 3B and Additional file 3: Fig. S4A). Subsequently, principal component analysis (PCA) showed that the 5 VOCs were effective in distinguishing between CSKP and CRKP in the T2 time point (Fig. 3C). Intriguingly, these differences disappeared with time (Additional file 3: Fig. S4B).

Differential VOCs between CSKP and CRKP (standard strains) after the addition of IPM

To assess the impact of IPM on VOC emission from K. pneumoniae, IPM was added to the test tubes at T0 to a concentration of 0.25 mg/mL (Additional file 3: Fig. S2). Subsequent growth curve analyses demonstrated that the introduction of IPM after a 3 h incubation period exclusively affects the growth of CBMP-negative strain (the bacteria were killed completely), while CBMP-positive strains exhibited a consistent growth pattern comparable to that observed in the absence of IPM supplementation (Figs. 1 and 4).

Fig. 4

The growth curves of K. pneumoniae standard strains after the addition of imipenem at time T0 (3 h of bacteria growth)

It was found that the introduction of IPM did not yield any new VOCs. However, notable alterations were observed in the content of certain VOCs of K. pneumoniae ATCC BAA-1706 in the T2 time point (after 2 h of IPM addition), which was maintained until the end of the study (Additional file 2: Table S4). Concurrently, VOCs of K. pneumoniae ATCC BAA-1705, ATCC BAA-2146, and ATCC BAA-2524 showed similar temporal change trends to those without IPM addition (Additional file 2: Table S4).

Further analysis revealed that compared with K. pneumoniae ATCC BAA-1706, K. pneumoniae ATCC BAA-1705 displayed a significant divergence of 26 VOCs (21 VOCs were increased and 5 were decreased), K. pneumoniae ATCC BAA-2146 showed a substantial variation of 24 VOCs (19 VOCs were increased and 5 were decreased), and K. pneumoniae ATCC BAA-2524 exhibited a marked distinction of 23 VOCs (19 VOCs were increased and 4 were decreased) at the T2 time point (Figs. 5 and 6A and Additional file 2: Table S5).

Fig. 5

The heatmap of the VOCs expression in all samples (treated with IPM, after min–max normalization)

Fig. 6

The VOCs emitted by K. pneumoniae (standard strains, with IPM added). A Volcano plots of differential VOCs between the CSKP group and CRKP strains. B The heatmap of the differentially expressed VOCs generated using volcano plots (compared with the CSKP group, after binarization). C The PCA of various sample groups (treated with IPM)

After a comprehensive analysis of these VOCs, the contents of 3-methylbutanoic acid (monomer and dimer), 2-methylpropanoic acid (monomer and dimer), acetic acid, butane-2,3-dione (diacetyl), and 3-hydroxy-2-butanone (acetoin) were significantly higher in the CRKP group than in the CSKP group, while the contents of benzaldehyde-D and butan-2-one were significantly lower. Meanwhile, 11 VOCs exhibiting an upward trend and 2 VOCs displaying a downward trend were not accurately identified (Fig. 6B). As shown in Additional file 3: Fig. S5, significant correlations were observed among the 22 increased VOCs and 6 decreased VOCs in the CRKP group. PCA further revealed that these differential VOCs were effective in discriminating between CRKP and CSKP (Fig. 6C). Interestingly, these differences persisted from T2 to T4 (Additional file 2: Table S4 and Additional file 3: Fig. S6).

Potential utility of VOCs in identifying CBPM-producing K. pneumoniae based on standard strains

To more comprehensively evaluate the significance of VOCs in the identification of CBPM-producing K. pneumoniae and determine its phenotypes, both IPM (final concentration, 0.25 mg/mL) and CBPM inhibitors (final concentration: avibactam sodium, 1 mg/L; or DPA, 100 mg/L) were added into the test tubes after a 3-h incubation period (T0). Moreover, changes in VOCs were assessed at the T2 time point before and after the addition of enzyme inhibitors.

Changes in the VOCs of the standard strains after the addition of CBPM inhibitors compared with those without CBPM inhibitors are presented in Additional file 2: Table S6. Results showed that the addition of avibactam sodium resulted in changes in the content of certain VOCs exclusively in K. pneumoniae ATCC BAA-1705, including 5 increased VOCs (benzaldehyde-D, 2,5-dimethylpyrazine-D, 2-methylpyrazine-D, butan-2-one, and unidentified-15) and 13 decreased VOCs (2-methylpropanoic acid (monomer and dimer), propionic acid (monomer and dimer), acetic acid, 3-hydroxy-2-butanone (acetoin), and 7 unidentified VOCs) (Fig. 7A). PCA results revealed that the addition of avibactam sodium lead to the identification of class A CBPM-producing K. pneumoniae (K. pneumoniae ATCC BAA-1705) via changes in VOCs (Fig. 7B). Similarly, the addition of DPA exerted the most significant influence on the contents of some VOCs in K. pneumoniae ATCC BAA-2146, including 5 increased VOCs (2,5-dimethylpyrazine-M, 2-methylpy,razine-D, butan-2-one and 2 unidentified VOCs) and 10 decreased VOCs (3-methylbutanoic acid-D, 2-methylpropanoic acid-D, benzaldehyde-M, 3-hydroxy-2-butanone (acetoin), butan-1-ol and 5 unidentified VOCs) (Fig. 8A). PCA further showed that the 15 differential VOCs after the addition of DPA were effective in identifying class B CBPM-producing K. pneumoniae (K. pneumoniae ATCC BAA-2146) (Fig. 8B). Additionally, Additional file 3: Fig. S7 confirmed that this experiment was repeated six times with high reproducibility.

Fig. 7

The VOCs emitted by K. pneumoniae after addition of avibactam sodium (standard strains, with IPM added). A The volcano plots displaying the differential VOCs between the pre- and post-inhibitor (avibactam sodium) addition stages for each strain. B The PCA of various sample groups (avibactam sodium unspiked and avibactam sodium spiked)

Fig. 8

The VOCs emitted by K. pneumoniae after addition of DPA (standard strains, with IPM added). A Volcano plots illustrating the differential VOCs between the pre- and post-inhibitor (DPA) addition stages for each strain. B The PCA of the sample groups (DPA unspiked and DPA spiked)

Potential application of VOCs in the identification of CRKP in clinical strains after the addition of IPM

The growth time curve of clinically isolated strains is shown in Additional file 3: Fig. S8, which was in line with the growth curves of standard strains. Using the T2 time point as the focal point, we further examined the disparity in VOCs between CSKP and CRKP.

The follow-up study encompassed 69 K. pneumoniae clinical isolates, comprising 25 CSKP strains and 44 CRKP strains. Experiments were performed in triplicates for each clinical isolate at the T2 time point utilizing GC–IMS. Moreover, the 44 CRKP strains included 20 KPC-positive strains, 15 NDM-positive strains, 4 IPM-positive strains, and 5 CBPM-negative strains. Given that CBPM-negative strains could not withstand a high concentration of IPM (0.25 mg/mL), the final concentration of IPM after a 3-h incubation period (T0) in the matrix components of BC bottles was adjusted to 16 µg/mL.

Changes in VOCs emitted by CRKP and CSKP at T2 are shown in Additional file 2: Table S7. Compared with the CSKP group, KPC-positive strains exhibited a notable disparity of 22 VOCs (15 increased and 7 decreased VOCs), NDM-positive strains displayed a significant divergence of 27 VOCs (16 increased and 11 decreased VOCs), IPM-positive strains demonstrated a substantial variation of 26 VOCs (14 increased and 12 decreased VOCs), and CBPM-negative strains had a marked distinction of 24 VOCs (5 increased and 19 decreased VOCs) (Fig. 9A and Additional file 3: Fig. S9). Further analysis of PCA results indicated that the differential VOCs with the addition of IPM were effective in identifying CBPM-producing Klebsiella pneumoniae (KPC-positive, NDM-positive, and IMP-positive strains); however, differential VOCs could not effectively distinguish between CSKP and CBPM-negative strains (Fig. 9B).

Fig. 9

The VOCs produced by K. pneumoniae (clinical strains, with IPM added). A The volcano plots of differential VOCs between the CSKP group and CRKP strains. B The PCA of the sample groups (with IPM added)

Potential utility of VOCs in identifying CBPM-producing K. pneumoniae based on clinical strains

Next, we investigated the importance of VOCs in identifying CBPM-producing K. pneumoniae and its phenotypes in clinical strains, following the same manipulation procedures as those applied to standard strains (CBPM-negative strains: IPM, final concentration, 16 µg/mL; avibactam sodium, 1 mg/L; DPA, 100 mg/L). Experiments were performed in triplicates for each clinical isolate at the T2 time point utilizing GC–IMS. Furthermore, considering that previous studies have shown that differential VOCs may differ between CSKP and CBPM-producing K. pneumoniae, changes in VOCs emitted by CSKP strains following the addition of CBPM inhibitors were not explored further.

Changes in VOCs emitted by CRKP strains after addition of CBPM inhibitors are shown in Additional file 2: Table S8. After the addition of avibactam sodium, only KPC-positive strains showed changes in the content of some VOCs, including 4 increased VOCs (benzaldehyde-D, 2,5-dimethylpyrazine-D, 2-methylpyrazine-D, and butan-2-one) and 8 decreased VOCs (3-hydroxy-2-butanone (acetoin), isovalerone, and 6 unidentified VOCs) (Fig. 10A). Moreover, a separation trend was observed in a three-dimensional PCA score plot after including the 12 potential biomarker VOCs, which were effective in identifying class A CBPM-producing K. pneumoniae (KPC-positive strains) after the addition of avibactam sodium (Fig. 10B). Subsequently, after the addition of DPA, there were significant changes in some VOCs, including 8 increased VOCs and 11 decreased VOCs in the NDM-positive strains. However, IMP-positive strains displayed comparable changes to NDM strains, characterized by an increase in 1,2-ethanediol and a decrease in 3-hydroxy-2-butanone (acetoin) and 4 unidentified VOCs (Fig. 11A). Finally, a three-dimensional PCA score plot revealed a separation trend after including these VOCs, which significantly facilitated the recognition of class B CBPM-producing K. pneumoniae strains, especially VOCs released by NDM-positive and IMP-positive strains. (Fig. 11B).

Fig. 10

The VOCs produced by K. pneumoniae after addition of avibactam sodium (clinical strains, with IPM added). A Volcano plots illustrating the differential VOCs between the pre- and post-inhibitor (avibactam sodium) addition stages for each strain. B The PCA of the sample groups (avibactam sodium unspiked and avibactam sodium spiked)

Fig. 11

The VOCs produced by K. pneumoniae after the addition of DPA (clinical strains, with IPM added). A The volcano plots illustrating the differential VOCs between the pre- and post-inhibitor (DPA) addition stages for each strain. B The PCA of the sample groups (DPA unspiked and DPA spiked)

Discussion

The rapid and accurate identification of BSIs caused by CRKP and the characterization of CBPMs are crucial in addressing the threat posed by the rapid global epidemic of multidrug-resistant bacteria, considering the escalating detection rate of CRKP in such infections (Chang et al. 2021; Chen et al. 2022). This study has the following main findings: (1) the identification of K. pneumoniae can be facilitated through the relative composition of VOCs (VOC fingerprints) in BC bottles (BacT/ALERT® SA). (2) The disparity in VOCs emitted by CSKP and CRKP following the addition of IPM was further substantiated, leading to the discovery of potential indicators for the discernment of CRKP in BC bottles. (3) The inclusion of CBPM inhibitors (avibactam sodium and DPA) resulted in discernible alterations in the composition of specific VOCs in the corresponding strains, thereby offering a novel approach to the detection and characterization of CBPM phenotypes.

In this study, simulated BCs were conducted, excluding peripheral blood, due to the significant variability in blood metabolism across environmental factors and individuals (Kim et al. 2014; Nicholson et al. 2011). Meanwhile, compared with fresh medium without blood, a previous study (Rees et al. 2016) confirmed a 20% increase in the total number of K. pneumoniae-associated volatiles in blood-containing media but VOCs already produced in the media without blood were unaffected; however, these findings warrant further validation. By focusing solely on the metabolism of K. pneumoniae without the confounding influence of blood, we provide a reference point for future studies. Further, to mitigate the influence of adsorbed beads (BacT/ALERT FA Plus, Biomérieux, Nürtingen, Germany), and limited by the inability to establish an anaerobic environment in vitro, we ultimately opted for the BacT/ALERT® SA culture medium. In addition, utilizing the alteration in VOCs of the standard strains as a benchmark and those of the clinical strains as a corroborative measure undoubtedly confers an additional significant advantage to the current study.

In recent years, VOCs have been increasingly utilized for strain characterization (Drees et al. 2019; Kunze et al. 2013; Lu et al. 2022). In addition, it is possible to differentiate CRKP and CSKP in TSB media using changes in VOCs (Filipiak et al. 2022). Nevertheless, we note that there are few studies employing commercial BC bottles emitting VOCs to identify CRKP and determine its CBPM phenotype, further emphasizing the strengths of the present study.

Fifty-four VOCs were isolated in the current study, of which 18 were successfully identified using the GC–IMS technique (6 VOCs existed as both monomers and dimers). Although 30 VOCs remained unidentified, valuable information regarding these compounds was obtained (Table 1). It is anticipated that the continuous advancement of technology and further research will results in identification of additional VOCs.

Previous studies have demonstrated a correlation between the growth metabolism of K. pneumoniae and VOCs, including propionic acid (BCs) (Julak et al. 2000), acetic acid (BCs/LB) (Julak et al. 2000), 3-methyl-1-butanol (sheep blood agar/TSB/LB) (Filipiak et al. 2022; Junger et al. 2012; Luo et al. 2023), butane-2,3-dione (diacetyl) (TSB) (Filipiak et al. 2022), and 3-hydroxy-2-butanone (malt extract agar and dichloran glycerol agar/TSB supplemented with 5% hemolyzed human blood) (Kiviranta et al. 1998; Rees et al. 2016). These findings align with the outcomes of the present study. Other identified VOCs released by K. pneumoniae, including 3-methylbutanoic acid, 2-methylpropanoic acid, 1,2-ethanediol, isovalerone, and 2-methylpyrazine-M, yielded varying outcomes in our study than in other studies maybe due to the dissimilar nutrient composition between commercial BC bottles and other media. Notably, variations in the employed detection methods have resulted in difference in the identified VOCs in the samples. Additionally, VOCs that were readily absorbed by K. pneumoniae and exhibited high concentrations within the blank medium undergo metabolic processes, leading to their transformation into different compounds, including benzaldehyde (TSB) (Filipiak et al. 2022), butan-2-one, and 2-methylpyrazine-D. However, it is noteworthy that butane-2,3-dione (diacetyl) and butan-2-one variations in the present study differed from that in previous studies (Boots et al. 2014; Rees et al. 2017). The results demonstrated that both substances were present at high levels in the blank medium, and due to the relatively small sample size, the results of these differential studies warrant further exploration. Interestingly, consistent with a previous study (Filipiak et al. 2022), the alterations observed in the VOCs (Additional file 2: Table S2) were generally congruent with the growth trend of K. pneumoniae (Fig. 1), as evidenced by the stabilization of VOC changes after 5 h of bacterial growth (T2), further supporting our decision to prioritize the examination of VOC changes at the T2 time point.

The catabolism of leucine by K. pneumoniae through the Ehrlich pathway was shown to generate 3-methyl-1-butanol (Luo et al. 2023; Smart et al. 2019). Similarly, the observed elevation in 1,2-ethanediol levels could potentially be attributed to the metabolic processes associated with fatty acids. Meanwhile, the synthesis of 2,3-butanedione occurs through the action of bacterial decarboxylases, which convert (2S)-2-hydroxy-2-methyl-3-oxobutanoic acid derived from pyruvate metabolism to 2,3-butanedione (Whiteson et al. 2014). The release of 3-hydroxy-2-butanone—another significant VOC—has been linked to glycolysis process (Chen et al. 2014). In the metabolic process of pyruvate, the final product of glycolysis and the carbon source for the citric acid cycle results in the production of acetylactate, which is subsequently transformed into 3-hydroxy-2-butanone through the action of α-acetolactate decarboxylase (Chen et al. 2014). In addition, the absorption of benzaldehyde may be affected by the enzymatic reduction of benzaldehyde by benzaldehyde dehydrogenase, which catalyzes the production of nicotinamide adenine dinucleotide phosphate (NADPH) during the growth of K. pneumoniae (Filipiak et al. 2022). However, due to the lack of precise knowledge regarding the specific constituents of the media in BC bottles coupled with the intricate nature of biochemical reactions, we did not determine the possible mechanisms underlying the remaining variations in differential VOCs.

In our study, we found that CRKP and CSKP can be differentiated without inclusion of IPM, but these differences disappear over time (Additional file 3: Fig. S4B), which is consistent with previous literature (Filipiak et al. 2022; Żuchowska and Filipiak 2023). In addition, 4 VOCs could not be identified and thus their significance is unknown. The bactericidal effects of IPM have been widely documented. For instance, several studies have demonstrated that it inhibits the biosynthesis of bacterial cell walls, leading to the lysis and subsequent death of bacteria (Pai Mangalore et al. 2022). Moreover, incorporation of IPM promoted the differentiation of CSKP from CRKP, with CRKP identified based on the differential VOCs, arising from killing of the susceptible cells, as reported in a previous study (Filipiak et al. 2022). Notably, the killing of sensitive bacteria by IPM caused a significant decrease in the amount of released VOCs and an increase in the number of absorbed VOCs compared to CRKP, and this difference remained unchanged over time (Fig. 4 and Additional file 3: Fig. S6). In addition, the incorporation of IPM exhibited different metabolic profiles between the standard and clinical strains, characterized by varying VOCs compared to the CSKP, and both strains could effectively differentiate between CRKP and CSKP based on specific differential VOCs. This may be as a result of the difference in origin of the two strains, clinical strains are susceptible to antibiotic-induced mutation and have different metabolism profiles from the standard strains (Filipiak et al. 2022). However, this study and our previous one (Luo et al. 2023) have consistently demonstrated the challenging nature of identifying carbapenemase-negative CRKP, which calls for further refinement of our experimental protocols.

The presence of VOCs in CRKP strains following the addition of IPM (4 h) has been documented (Filipiak et al. 2022). However, we did not obtain similar results, probably due to the limited duration of IPM addition and limitations of detection methodology, it provides valuable insights. Our findings suggest that alterations in VOCs may serve as a potential means to identify CRKP, opening new avenues for diagnosis and treatment options. Initially, we found that the inclusion of the enzyme inhibitor 3-aminophenylboronic acid (dissolved in dimethyl sulfoxide) increased the difficulty of identifying VOCs. Moreover, the alkaline nature (pH = 8.0) of EDTA also interfered with the outcomes. Consequently, avibactam sodium and DPA were selected as alternative components in the subsequent experiments. It has been demonstrated that avibactam is an effective inhibitor of class A, class C, and certain class D enzymes (Coleman 2011). In our study, the combination of averbactam sodium and IPM effectively eradicated K. pneumoniae strains that generate class A enzymes (standard and clinical strains). Furthermore, this treatment altered the levels of VOCs in class A enzyme-producing K. pneumoniae strains, which provided a reliable method for detecting it. However, our findings demonstrate that the addition of avibactam sodium was not effective in treating K. pneumoniae strains producing class D enzymes, which may be attributed to the inadequate avibactam sodium concentration. Pyridine-2,6-dicarboxylic acid (DPA), as an important type of Metallo-β-lactamases (MBL) inhibitor, can inhibit MBL by chelating, stripping, and binding Zn²⁺ in the active center of MBL (Chen et al. 2017a; Wang et al. 2020). Similar to the effects of avibactam sodium, DPA showed the capacity to selectively alter the VOCs of K. pneumoniae strains which produce class B enzymes, providing a novel approach for the identification of class B enzymes.

Although the findings presented in this preliminary study are interesting, several limitations should be acknowledged. The study mainly relied on clinical strains obtained from a single hospital which restricts the generalizability of the results to some extent. This limitation needs to be considered when interpreting the findings and their implications. In the future, we aim to expand the samples to detect more carbapenemase types of CRKP. Secondly, the experiments conducted to simulate blood cultures did not account for the impact of blood samples on the detection of VOCs. Studies have shown that incorporation of blood in these experiments increases the production of VOCs (Rees et al. 2016), and this needs to be further investigated. Thirdly, the use of single detection technique also limited the significance of our results. Although we successfully detected 54 VOCs, the identification was limited to 18 VOCs, of which 6 VOCs existed as both monomers and dimers. Therefore, it is imperative to incorporate additional detection methods to comprehensively analyze the fluctuations in VOCs. Lastly, the experimental designs and methods need to be further revised and improved. This will be the focus of our future investigations.

In conclusion, using GC–IMS technology, we identified CRKP strains by analyzing changes in VOC. In addition, we investigated the potential application of VOCs in the detection of phenotypes within CRKP strains. Moreover, we developed VOC fingerprints to facilitate the identification of relevant strains. Nevertheless, we acknowledge that these findings need to be further validated through large-scale, multi-center, prospective experiments.