Clinical characteristics of Elizabethkingia species infections

As shown in Table 1, the specimens were primarily isolated from the respiratory tract (85.9%, 61/71), including sputum (69.1%, 49/71), tracheal secretory fluid (14.1%, 10/71), and bronchoalveolar lavage fluid (2.8%, 2/71). There were only a few samples of sterile body fluids, including cerebrospinal fluid (4.3%, 3/71), ascites (1.4%, 1/71), drainage fluid (2.8%, 2/71), blood (1.4%, 1/71) and pus (2.8%, 2/71). The specimens were predominantly isolated from the intensive care unit (36.6%, 26/71) and emergency (32.4%, 23/71) departments, with fewer specimens from the neurosurgery department (9.9%, 7/71). Most patients had various underlying conditions, such as pulmonary infection, hypertension, and diabetes. A total of 61 patients (85.9%) were hospitalized for more than two weeks. In addition, most patients underwent invasive treatment, including mechanical ventilation (71.8%, 51/71), nasogastric tube placement (63.4%, 45/71) and catheter insertion (59.2%, 42/71). All patients had a history of antibiotic exposure, and 94.4% of patients (67/71) had used broad-spectrum antibiotics for more than one week. The in-hospital mortality rate was 29.6% (21/71).

Table 1 Characteristics of 71 patients with Elizabethkingia infectionsAntimicrobial susceptibility

Table 2 displays the antimicrobial susceptibility of Elizabethkingia isolates and the corresponding MICs for the tested antibiotics. All strains exhibited resistance to 13 ~ 16 antimicrobial agents, including aminoglycosides, macrolides, cephalosporins and carbapenems (imipenem and meropenem). Additionally, they exhibited higher rates of resistance to trimethoprim-sulfamethoxazole. The rate of resistance to piperacillin was 100%, but when piperacillin was combined with β-lactamase inhibitors (cefoperazone/sulbactam and piperacillin/tazobactam), increased sensitivity rates of 90.1% (64/71) and 66.2% (47/71), respectively, were observed. Importantly, all the isolates were found to be susceptible to minocycline and colistin.

Table 2 Antimicrobial susceptibilities of 71 Elizabethkingia strainsGeneral features of Elizabethkingia strains

The next-generation sequencing and assembly data for the 7 genomes are presented in Table 3. The genome size ranged from 4.04 Mb to 4.31 Mb, with an average size of 4.10 Mb, which is consistent with the genome size of the 83 Elizabethkingia strains selected from the NCBI database (Supplementary Materials Table S1). The sizes of these 83 genomes ranged from 3.59 Mb to 4.58 Mb, with an average size of 4.26 Mb. The number of contigs per genome ranged from 1 to 378, with a mean of 32.75. The read depth ranged from 23.26 to 80.63, with a mean of 38.79. The average GC content and tRNA content in 83 Elizabethkingia strains were 35.84% and 45.42%, respectively.

Table 3 General features of seven Elizabethkingia strainsResistance-associated genes of the various Elizabethkingia strains

We analyzed the resistance genes of the 83 strains from NCBI and 7 strains from our study and found that different genes were involved in resistance to 6 antibiotics. Antimicrobial resistance genes in the 83 Elizabethkingia strains are presented in Supplementary Materials Table S2. These resistance genes included the extended-spectrum β-lactamase genes blaCME,blaOXA−347 and blaTEM−116; the carbapenem resistance genes blaBlaB and blaGOB and their various subtypes; the aminoglycoside resistance genes aadS and aph(3’)-IIa; the tetracycline resistance genes tetX and tet36; and the sulfonamide resistance gene sul2. Molecular analysis did not reveal any genes in the mobile colistin resistance (mcr) gene family. There was no difference in the distribution of drug resistance genes among the five species. The 7 strains carried all three previously described β-lactamase genes unique to Elizabethkingia, including the extended-spectrum β-lactamase blaCME and metallo-β-lactams blaBlaB and blaGOB. The specific genes included macrolide, lincosamide and streptogramin (MLS) resistance genes ermF, ereD, mefC and mphG. In addition, certain aminoglycoside resistance genes, such as aac(3)-IVb and aac(3)-IIIc, were only found in our 7 strains (Table S3).

Virulence-associated genes of the various Elizabethkingia strains

The potential virulence factors and the associated genes of the 83 strains and 7 Elizabethkingia strains in our study are shown in Table S2 and Table S4, respectively. We found that some virulence genes, such as catalase/(hydro)peroxidase (katA) and translation elongation factor (tufA), were widely distributed in our seven strains. We identified a total of 753 virulence genes in all strains, and 23 kinds of virulence factors could be classified into three types: stress adaptation, adherence and immune modulation. The virulence genes catalase/(hydro)peroxidase (katA) and translation elongation factor (tufA) were widely distributed in all 90 strains. In addition, the capsular polysaccharide biosynthesis protein (cps4J) gene was detected only in E. miricola. In addition, 60 K heat shock protein (htpB), urease accessory protein (ureE), urease beta subunit (ureB), Vi polysaccharide biosynthesis (tviB) and chaperonin (groEL) were identified in these strains. The immune modulation gene rfbA and stress survival gene fcl were identified only in the 83 strains from the NCBI.

Core and pangenome analysis and phylogenetic relationships between Elizabethkingia species

To clarify the characteristics and differences in the pangenome between the seven Elizabethkingia strains in this study and those from the database, we performed a pangenome analysis on these 90 strains. Core genome analysis revealed that the number of shared genes decreased with the addition of the input genomes. Overall, E. meningoseptica exhibited an open pangenome feature, with new genes appearing when more sequenced genomes were added to the analysis. Pangenome analysis can be used to determine the diversity of genomes and explore core, accessory, and unique genes. In the 90 strains, 2079 core genes were identified. In each strain, the number of accessory genes ranged from 1097 to 1925, and the number of unique genes ranged from 0 to 364. With the addition of new genome sequences, the number of genes in the pangenome increased from 3265 to 11,813, and the number of core genes decreased from 2546 to 1959 (Fig. 1). The distributions of different gene families and the numbers of new genes are illustrated in Fig. 2A and B, respectively. Whole-genome comparisons allow for the distinction between different strains and species with high resolution. Genome sequences were analyzed using a pairwise method, calculating and comparing the ANI for the 90 Elizabethkingia strains (Fig. 2C). The pairwise comparisons revealed a minimum ANI of ∼80.72% for the most distant strains, whereas the E. anophelis subspecies showed an ANI of > 98.0%. Additionally, we observed that the ANIs of E. meningoseptica and four other species were notably lower than those of the other species. According to the dendrogram, E. ursingii and E. occulta appeared to be relatively close to E. miricola. The delineation of the five species within the Elizabethkingia genus was clearly evident in the heatmap generated from the similarity matrix. The phylogenetic analysis of all the isolates was based on whole-genome sequences (Figure S1). Similar to the dendrogram generated from the ANI analysis, E. ursingii and E. occulta were located close to E. miricola and were distant from E. anophelis and E. meningoseptica. E. anophelis was divided into two major sublineages.

Fig. 1

Pan, core and singleton genome evolution according to the number of selected Elizabethkingia strains

Fig. 2

Pangenome analysis of 90 Elizabethkingia strains. (A) The distribution of the various gene families in the 90 Elizabethkingia strains. (B) The distribution of new genes in the 90 Elizabethkingia strains. (C) Dendrogram and heatmap generated using the ANIs of 90 different Elizabethkingia strains

Functional analysis of COGs

COG analysis (Fig. 3A and C) revealed 1,497 conserved genes. There were 1888 accessory genes and 557 unique genes. The functional analysis of the COGs in all the Elizabethkingia genomes revealed core, accessory and unique genes related to the regulation of metabolism, cellular processes and signaling, as well as various poorly characterized functions. Core genes were significantly enriched in pathways related to metabolism and biogenesis, including general function, amino acid transport and metabolism, translation, ribosomal structure and biogenesis, and cell wall/membrane/envelope biogenesis. Unique and accessory genes were significantly enriched in transcription; defense mechanisms; and replication, recombination and repair pathways.

Fig. 3

Clusters of orthologous groups (COGs) in the core, accessory, and unique genomes and the associated Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of 90 Elizabethkingia strains. (A) Distribution of functional COGs in each core, accessory, and unique genome. (B) The detailed distribution of KEGG pathways with their functions. (C) The majority of core, accessory, and unique genes were associated with metabolism. (D) Functional annotations showing that the gene families associated with carbohydrate metabolism, amino acid metabolism, cofactor and vitamin metabolism, and energy metabolism accounted for the largest proportion of these 90 Elizabethkingia strains

The functions of COGs involved in information storage and processing are associated with intracellular survival. In addition, according to the functional prediction of genomes, general function prediction accounted for the largest proportion of COGs, followed by transcription and replication, recombination and repair. Regarding the constituents of each functional gene family, the core genes accounted for the largest proportion of genes related to transcription (11.7%); replication, recombination and repair (10.4%); cell wall, membrane, envelope and biogenesis (7.1%); and defense mechanisms (10.5%).

KEGG analysis

According to the KEGG analysis (Fig. 3B and D), the largest proportion of genes were enriched in metabolic functions. The other KEGG categories included cellular processes, environmental information processing, genetic information processing, human diseases and organismal systems. The core and accessory genes were most strongly associated with carbohydrate metabolism, followed by amino acid metabolism. Among the genes associated with carbohydrate metabolism, 15.3% were core genes, 12.7% were accessory genes, and 18.5% were unique genes. In addition, the majority of these core genes were also involved in carbohydrate metabolism, and the regulation of amino acid metabolism and lipid metabolism was the focus of the greatest number of genes, followed by signal transduction, replication and repair. In addition to metabolic functions, these genes were also associated with membrane transport, translation, and modulation of cellular growth and death. These functions collectively provide bacteria with the ability to withstand and adapt to the external environment. However, the unique genes in our 7 strains were mostly enriched in KEGG pathways related to microRNAs in cancer, drug resistance (β-lactam and vancomycin), ABC transporters, biological metabolism and biosynthesis, and nucleotide excision repair.