Carbapenemase-Producing Klebsiella pneumoniae in COVID-19 Intensive Care Patients: Identification of IncL-VIM-1 Plasmid in Previously Non-Predominant Sequence Types

During the COVID-19 pandemic, intensive care units (ICUs) operated at or above capacity, and the number of ICU patients coinfected by nosocomial microorganisms increased. Here, we characterize the population structure and resistance mechanisms of carbapenemase-producing Klebsiella pneumoniae (CP-Kpn) from COVID-19 ICU patients and compare them to pre-pandemic populations of CP-Kpn. We analyzed 84 CP-Kpn isolates obtained during the pandemic and 74 CP-Kpn isolates obtained during the pre-pandemic period (2019) by whole genome sequencing, core genome multilocus sequence typing, plasmid reconstruction, and antibiotic susceptibility tests. More CP-Kpn COVID-19 isolates produced OXA-48 (60/84, 71.4%) and VIM-1 (18/84, 21.4%) than KPC (8/84, 9.5%). Fewer pre-pandemic CP-Kpn isolates produced VIM-1 (7/74, 9.5%). Cefiderocol (97.3–100%) and plazomicin (97.5–100%) had the highest antibiotic activity against pandemic and pre-pandemic isolates. Sequence type 307 (ST307) was the most widely distributed ST in both groups. VIM-1-producing isolates belonging to ST307, ST17, ST321 and ST485, (STs infrequently associated to VIM-1) were detected during the COVID-19 period. Class 1 integron Int1-blaVIM-1-aac(6′)-1b-dfrB1-aadAI-catB2-qacEΔ1/sul1, found on an IncL plasmid of approximately 70,000 bp, carried blaVIM-1 in ST307, ST17, ST485, and ST321 isolates. Thus, CP-Kpn populations from pandemic and pre-pandemic periods have similarities. However, VIM-1 isolates associated with atypical STs increased during the pandemic, which warrants additional monitoring and surveillance.


Introduction
Coronavirus disease of 2019 (COVID- 19), the disease caused by infection with the SARS-CoV-2 virus, has caused the worst pandemic since the 1918 influenza. Through the
We then compared pandemic-period COVID CP-Kpn isolates with Madrid-CARB-ES-19 and ICU-CARB-ES-19 isolates, as described above. Five clusters included isolates from all three study groups; these clusters included ST307, CC11, ST15, ST147, and ST392 isolates. One additional cluster included eight ST17 isolates from the pandemic period and one isolate from the ICU-CARB-ES-19 group, and other cluster included four ST485 isolates from pandemic-period COVID-19 patients (Figure 2).
Applying a threshold of 10 alleles [10], we identified four groups (n > 3 isolates per group) of related isolates from pandemic-period COVID-19 and pre-pandemic CARB-ES-19 groups: two groups in the CC11 cluster with OXA-48-producers, one group in the . Grey ovals represent clusters. Where a circle corresponds to more than one isolate, the number of isolates is indicated in bold font. Gray shadows represent groups of strains; a threshold of 10 alleles was applied.
We then compared pandemic-period COVID CP-Kpn isolates with Madrid-CARB-ES-19 and ICU-CARB-ES-19 isolates, as described above. Five clusters included isolates from all three study groups; these clusters included ST307, CC11, ST15, ST147, and ST392 isolates. One additional cluster included eight ST17 isolates from the pandemic period and one isolate from the ICU-CARB-ES-19 group, and other cluster included four ST485 isolates from pandemic-period COVID-19 patients ( Figure 2). ST307 cluster included KPC-3-producers, and one group in the ST15 cluster included OXA-48-producers ( Figure 2). Three groups were identified that included only pandemicperiod isolates from COVID-19 patients; one of these groups included eight ST307 isolates that produced OXA-48 and VIM-1, whereas the other two groups included four ST485 and six ST17 VIM-1-producers, respectively ( Figure 2).  . Grey ovals represent clusters. For circles that correspond to more than one isolate, the number of isolates is indicated in bold font. Gray shadows represent groups of strains; a threshold of 10 alleles was applied.
Applying a threshold of 10 alleles [10], we identified four groups (n > 3 isolates per group) of related isolates from pandemic-period COVID-19 and pre-pandemic CARB-ES-19 groups: two groups in the CC11 cluster with OXA-48-producers, one group in the ST307 cluster included KPC-3-producers, and one group in the ST15 cluster included OXA-48producers ( Figure 2). Three groups were identified that included only pandemic-period isolates from COVID-19 patients; one of these groups included eight ST307 isolates that produced OXA-48 and VIM-1, whereas the other two groups included four ST485 and six ST17 VIM-1-producers, respectively ( Figure 2).
Comparing all VIM-1-producing isolates, 18/84 pandemic-period isolates from five STs expressed VIM-1, whereas 7/74 pre-pandemic isolates from four STs expressed VIM-1. The predominant STs among the VIM-1-producing pandemic period isolates were ST307, ST17, ST485, and ST321 ( Figure 3). isolate, the number of isolates is indicated in bold font. Gray shadows represent groups of strains; a threshold of 10 alleles was applied.
Comparing all VIM-1-producing isolates, 18/84 pandemic-period isolates from five STs expressed VIM-1, whereas 7/74 pre-pandemic isolates from four STs expressed VIM-1. The predominant STs among the VIM-1-producing pandemic period isolates were ST307, ST17, ST485, and ST321 ( Figure 3).  19) and numbers indicate the sequence type (ST). For circles that correspond to more than one isolate, the number of isolates is indicated in bold font.
The most frequently identified extended-spectrum β-lactamase (ESBL) gene was  (Table 4). ESBL: extended-spectrum β-lactamase. * Only the most frequent variants found in our study population are detailed.

Figure 4.
Overview of the IncL plasmid harboring blaVIM-1 detected in a strain of ST17: The figure represents the homology between the IncL plasmid and a highly similar plasmid identified in the GenBank database (blue outer ring). The graph represents the reads mapped against this reference sequence with a depth of coverage ranging from 0 (red) to 500, with orange indicating values of 1 to 20 reads and green indicating values higher than 200 reads. Gray boxes represent the coding sequence from automatic annotation, with dark and light colors being used when they were found on the forward or the reverse strand, respectively. Colored stripes represent a more detailed annotation that includes antibiotic resistance genes in red, insertion sequences (IS) in light green, integrases in blue, and Rep genes in dark green. The homology between the reference plasmid and the assembled contigs is represented in the inner ring, with each contig colored according to its number. represents the homology between the IncL plasmid and a highly similar plasmid identified in the GenBank database (blue outer ring). The graph represents the reads mapped against this reference sequence with a depth of coverage ranging from 0 (red) to 500, with orange indicating values of 1 to 20 reads and green indicating values higher than 200 reads. Gray boxes represent the coding sequence from automatic annotation, with dark and light colors being used when they were found on the forward or the reverse strand, respectively. Colored stripes represent a more detailed annotation that includes antibiotic resistance genes in red, insertion sequences (IS) in light green, integrases in blue, and Rep genes in dark green. The homology between the reference plasmid and the assembled contigs is represented in the inner ring, with each contig colored according to its number. Antibiotics 2023, 12, x FOR PEER REVIEW 12 of 19 Figure 5. Overview of the IncL plasmid harboring blaVIM-1 detected in a strain of ST321: The figure represents the homology between the IncL plasmid and a highly similar plasmid identified in the GenBank database (blue outer ring). The graph represents the reads mapped against this reference sequence with a depth of coverage ranging from 0 (red) to 500, with orange indicating values of 1 to 20 reads and green indicating values higher than 200 reads. Gray boxes represent the coding sequence from automatic annotation, with dark and light colors being used when they were found on the forward or the reverse strand, respectively. Colored stripes represent a more detailed annotation that includes antibiotic resistance genes in red, insertion sequences (IS) in light green, integrases in blue, and Rep genes in dark green. The homology between the reference plasmid and the assembled contigs is represented in the inner ring, with each contig colored according to its number. Figure 5. Overview of the IncL plasmid harboring bla VIM-1 detected in a strain of ST321: The figure represents the homology between the IncL plasmid and a highly similar plasmid identified in the GenBank database (blue outer ring). The graph represents the reads mapped against this reference sequence with a depth of coverage ranging from 0 (red) to 500, with orange indicating values of 1 to 20 reads and green indicating values higher than 200 reads. Gray boxes represent the coding sequence from automatic annotation, with dark and light colors being used when they were found on the forward or the reverse strand, respectively. Colored stripes represent a more detailed annotation that includes antibiotic resistance genes in red, insertion sequences (IS) in light green, integrases in blue, and Rep genes in dark green. The homology between the reference plasmid and the assembled contigs is represented in the inner ring, with each contig colored according to its number.

Discussion
During 2020, ICU admissions were significantly elevated because of the escalating global SARS-CoV-2 pandemic. According to several sources, up to 5% of patients infected with SARS-CoV-2 were admitted to the ICU [11,12]. Some ICUs operated at or above capacity for several months, which could have contributed to increased spread of opportunistic pathogens, such as K. pneumoniae, resulting from overcrowding and excessive demand on the healthcare system. In addition, the overuse of antimicrobials in ICUs is known to promote the development of MDR bacteria [13,14]. Retrospective observational research in Italy detected an increase from 6.7% to 50% in CPE in ICUs between 2019 and April 2020 [15], and other studies in medical centers in New York [16] and Italy [17] also documented increased detection of CPE in patients with COVID-19. Beyond the quantitative variations, it is also important to assess whether modifications to healthcare best practices, made out of necessity during the first waves of the COVID-19 pandemic, may have qualitatively influenced the prevalence or nature of CP-Kpn in COVID patients admitted to ICUs.
This study shows that the population of CP-Kpn affecting COVID-19 patients admitted to the ICUs of five hospitals in Madrid during the first year of the pandemic was mainly made up of OXA-48-producing isolates belonging to ST307. Comparison with a previous collection of CP-Kpn isolates in 2019 [5], just a year before the start of the pandemic, reveals a similar scenario. However, we note here certain evolutionary trends that deserve monitoring to determine whether they will consolidate or whether they reflect specific and/or local epidemiological situations. For example, it is worth noting that the number of VIM-1-producing K. pneumoniae isolates increased during the pandemic and that these isolates were associated with previously rare STs, including ST17, ST321, and ST485.
The present study is important because it reports WGS analysis of CP-Kpn isolates colonizing or infecting seriously ill COVID-19 patients at the height of the pandemic in a region and at a time when healthcare services were extremely stressed. Furthermore, WGS data on COVID-19 isolates of CP-Kpn were directly compared with a pre-pandemic Spanish national collection of representative CP-Kpn isolates collected a few months before the start of the pandemic. A limitation of the present study may be that different protocol designs were used to collect CP-Kpn strains during the pandemic and pre-pandemic periods; justified by the difficulty in collecting cases of infection/colonization by CP-Kpn during the first phase of the pandemic.
Traditionally, and in general, VIM has been more frequent in Spain than in the rest of Europe. For example, in the European Survey on CPE (EuSCAPE) carried out in 2013-2014, 5.7% and 10.3% of all European CP-Kpn isolates and CP-Kpn from Spain, respectively, were VIM-producers [18]. However, the emergence and dissemination of OXA-48 as well as KPC and NDM has reduced the relative frequency of VIM-1 in Spain [5,19]. In the present study, a high frequency of VIM-1 linked to STs rarely associated with this type of carbapenemase (namely ST17, ST485, and ST307) has been detected in COVID-19 patients admitted to the ICU.
This work confirmed the predominance of the high-risk clone ST307 detected in previous studies [5,20]. However, in contrast to previous studies, four isolates in the present study carry the bla VIM-1 gene. The ST307 dispersion has been linked to the carbapenemases OXA-48 and KPC, with very infrequent previous reports of linkage between VIM-type carbapenemases and this ST [21,22]. ST17, ST485, and ST321 of K. pneumoniae, detected in this study carrying bla VIM-1 from COVID patients, are rare STs in CP-Kpn. Recently, the coexistence of mcr-1, bla NDM-5 , and bla CTX-M-55 in a K. pneumoniae ST485 isolate was communicated [23], but there are no published reports of outbreaks due to carbapenemase-producing ST485. Regarding ST17 isolates, they were recently linked to the production of OXA-181 carbapenemase [22,24] and to sporadic cases of hypervirulent isolates [25,26], but they were not previously linked to production of VIM-1. In this study, no hypervirulent isolates were detected. Five VIM-1-producing ST321 isolates were recently detected in long-term care facilities in the Northern Italian region [27].
Relative to the pre-pandemic population diversity in CP-Kpn, the SDI was lower, indicating less diversity in the COVID-19 period than in the pre-COVID period, especially relative to ICU-CARB-ES-19 isolates of CP-Kpn. This fact could reflect the dissemination of intra-ICU-specific clones, facilitated by the large increase in ICU admissions during the pandemic [11,12].
Regarding the level of resistance to carbapenem antibiotics as the main target of carbapenemases, it should be noted that the profile of meropenem and/or imipenem susceptibility with ertapenem resistance was frequently detected in the three patient groups, with minor differences between them. This profile was conferred by and is mainly due to highly prevalent OXA-48 isolates of CP-Kpn [5,19], although it is also observed in patients with VIM-1-producing isolates [19,28]. It is worth noting the difference in susceptibility to meropenem (37.6%) and meropenem/vaborbactam (87.1%) in a collection in which the VIM-1-and OXA-48-producers predominated, carbapenemases that are not inhibited by vaborbactam. This fact is mainly because predominated isolates with meropenem MICs of 4-8 mg/L, and they were characterized as Susceptible, increased exposure (I); these MICs in the case of meropenem/vaborbactam were considered susceptible, according to EUCAST criteria. On the other hand, new antibiotics, such as cefiderocol, plazomicin, meropenem/vaborbactam, and imipenem/relebactam, have significantly improved the treatment options for CPE infections [13]. In our study, all CP-Kpn isolates showed > 73% susceptibility to these antibiotics with non-significant differences between the three groups. Minor differences among the three groups were mainly justified by the predominant type of carbapenemases in each group; and, specifically, different susceptibilities in aztreonam and ceftazidime/avibactam reflect different proportion of metallo-beta-lactamases by groups.
Modifications in the profile of antibiotic use in general, and in particular against infections produced by CP-Kpn, can contribute to the selection of different types of carbapenemases and clones that are prone to carry them. Both, the COVID-19 pandemic and the marketing of new antibiotics against this type of bacteria, could have been factors that may have contributed to change the use of antibiotics in ICUs [29,30].
Although chloramphenicol resistance genes were less frequent in pandemic-period isolates (40.5%) than in pre-pandemic isolates (70.5% and 70% in Madrid-CARB-ES-19 and ICU-CARB-ES-19 groups, respectively), no clear pattern was observed to justify this difference. In general, the absence of chloramphenicol resistance genes occurred mainly in OXA-48-producing strains of different STs in the three study groups. The catB2 gene was mainly associated with VIM-1-producing isolates linked to a class 1 integron in COVID-19 patients (20.2%).
It is worth highlighting the presence of the same class 1 In624-like integron [31] and the IncL plasmid carrying VIM-1 in all emerging STs with this type of enzyme among CP-Kpn isolates in the COVID-19 group. Class 1 integron In624-like has been previously described in Enterobacter cloacae [31], Citrobacter freundii [32], and Serratia marcescens [33] in Spain, suggesting that it plays an important role in the interspecies transfer of bla VIM-1 .
IncL plasmids detected in this study are closely related to plasmids previously shown to be responsible for the worldwide spread of OXA-48 [34]. The main difference between the two is the presence of a class I integron with the bla VIM-1 carbapenemase in the former, instead of the bla OXA-48 transposon Tn1999 in the latter [33]. The great biological success of the IncL plasmid carrying OXA-48 [34] should alert us to the possible future dissemination of the IncL plasmid harboring VIM-1. This IncL-VIM-1 plasmid has been recently described in multidrug-resistant strains of K. pneumoniae [35] and S. marcescens [33] in Spain. The simultaneous presence of this plasmid in different emerging STs supports this hypothesis and requires surveillance.
High correlations between K-loci and STs have been described previously [5], including the predominant combinations KL24/ST11 and KL102/ST307.
Looking to the future, strategies to manage patients with COVID-19 should include approaches for mitigating the impact of MDR infections in this population. Updated knowledge about carbapenemase-producing Enterobacterales will allow for early detection of emerging mechanisms of resistance and the clones or mobile genetic elements that carry them and facilitate their spread. In this regard, the emergence of new VIM-1-producing K. pneumoniae clones linked to successful IncL plasmids and a class 1 integron, as reported here, is a matter of concern that requires continuous monitoring.

Study Design and CP-Kpn Isolates
This study was performed by the unrestricted national Spanish Antibiotic Resistance Surveillance Programme, operated by the official Spanish Public Health Institute (Instituto de Salud Carlos III). The study characterized 85 CP-Kpn isolates collected from individual COVID-19 patients in ICUs of five hospitals in Madrid. These isolates were collected between 1 April 2020 and 30 April 2021. For comparison, two groups of CP-Kpn isolates obtained before the COVID-19 pandemic began, during the CARB-ES-19 national multicenter study, were also analyzed. The first of these two pre-pandemic groups included 34 CP-Kpn isolates collected in Madrid, while the second pre-pandemic group included 40 CP-Kpn isolates from Spanish ICU patients obtained during CARB-ES-19. The overall results of the CARB-ES-19 study were recently published [5]. Briefly, 71 hospitals representing all 50 Spanish provinces participated in CARB-ES-19, whose goal was to collect the first ten non-duplicate consecutive isolates of carbapenem non-susceptible Kpn isolates from clinical samples from individual patients between February and May 2019. The CARB-ES-19 study included four hospitals in Madrid that collected 34 CP-Kpn isolates [5].

Genomic Library Preparation and DNA Sequence Analysis
Genomic DNA paired-end libraries were generated using the Nextera XT DNA Sample Preparation Kit (Illumina, Inc., San Diego, CA, USA). These libraries were sequenced using the Illumina HiSeq 500 and NextSeq 500-500 high output v2.5 next-generation sequencers with 2 × 150 bp paired-end reads (Illumina, Inc.) Raw sequence data were submitted to the European Nucleotide Archive (PRJEB57245 and PRJEB50822 for isolates from COVID-19 patients and CARB-ES-19 isolates, respectively). Quality of short reads was assessed using FASTQC, and they were assembled into contigs with Unicycler 0.4.8 [37]. The quality of the assembly was assessed with QUAST (http://quast.bioinf.spbau.ru/, accessed on 3 December 2022). Prokka v1.14-beta [38] was used for automatic de novo assembly annotation.

Phylogenetic Analyses
STs were calculated according to multilocus sequence typing (MLST) schemes of the Institut Pasteur using Ariba v2.6.2 [39]. A simple diversity index (SDI) [40] was applied to analyze population diversity. A core genome multilocus sequence typing (cgMLST) that relies on species-specific schemes with a fixed number of chromosomal target genes was applied, consisting of 2538 K. pneumoniae targets provided by SeqSphere+ 3.5.0 (Ridom, Münster, Germany). A relatedness threshold of ≤10 alleles was applied for detecting related isolates, as recommended [10].

Characterization of Plasmids Carrying Carbapenemase Genes
To reconstruct the plasmids carrying the bla VIM genes, an in-house script (PlasmidID, https://github.com/BU-ISCIII/plasmidID, accessed on 3 December 2022) was used. The aims were to (i) map reads over a curated plasmid database, to find those with higher coverage and to assemble these reads de novo; (ii) make local alignments to localize resistance and replicative genes; and (iii) generate a graphic representation of the plasmids identified.
Supplementary Materials: The following supporting information can be downloaded at: https://www. mdpi.com/article/10.3390/antibiotics12010107/s1: Table S1: Identification and antibiotic resistance and virulence genes of Klebsiella pneumoniae from COVID-19 and pre-pandemic time patients. Funding: This research was funded by grants from the Instituto de Salud Carlos III (PI18CIII/00030 and PI21CIII/00039). This research was also supported by CIBER-Consorcio Centro de Investigación Biomédica en Red (CB21/13/00095; CIBERINFEC), Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea-NextGenerationEU. This work was supported by Plan Nacional de I+D+i 2013-2016 and Instituto de Salud Carlos III, Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Economía, Industria y Competitividad, Spanish Network for Research in Infectious Diseases (REIPI RD16CIII/0004/0002) and co-financed by the European Development Regional Fund (EDRF), "A way to achieve Europe", Operative program Intelligent Growth, 2014-2020.
Institutional Review Board Statement: Ethical review and approval were waived for this study due to it was a purely microbiological study involving only bacterial strains.

Data Availability Statement:
The datasets presented in this study can be found in the European Nucleotide Archive (PRJEB57245 and PRJEB50822 for isolates from COVID-19 patients and CARB-ES-19 isolates, respectively).