Combining Functional Genomics and Whole-Genome Sequencing to Detect Antibiotic Resistance Genes in Bacterial Strains Co-Occurring Simultaneously in a Brazilian Hospital

Abstract

(1) Background: The rise of multi-antibiotic resistant bacteria represents an emergent threat to human health. Here, we investigate antibiotic resistance mechanisms in bacteria of several species isolated from an intensive care unit in Brazil. (2) Methods: We used whole-genome analysis to identify antibiotic resistance genes (ARGs) and plasmids in 34 strains of Gram-negative and Gram-positive bacteria, providing the first genomic description of Morganella morganii and Ralstonia mannitolilytica clinical isolates from South America. (3) Results: We identified a high abundance of beta-lactamase genes in resistant organisms, including seven extended-spectrum beta-lactamases (OXA-1, OXA-10, CTX-M-1, KPC, TEM, HYDRO, BLP) shared between organisms from different species. Additionally, we identified several ARG-carrying plasmids indicating the potential for a fast transmission of resistance mechanism between bacterial strains. Furthermore, we uncovered two pairs of (near) identical plasmids exhibiting multi-drug resistance. Finally, since many highly resistant strains carry several different ARGs, we used functional genomics to investigate which of them were indeed functional. In this sense, for three bacterial strains (Escherichia coli, Klebsiella pneumoniae, and M. morganii), we identified six beta-lactamase genes out of 15 predicted in silico as those mainly responsible for the resistance mechanisms observed, corroborating the existence of redundant resistance mechanisms in these organisms. (4) Conclusions: Systematic studies similar to the one presented here should help to prevent outbreaks of novel multidrug-resistant bacteria in healthcare facilities.

Keywords: antibiotic resistance genes; functional genomics; mobilome; resistome; whole-genome analysis.

Figure 1

Overall strategy used for the whole-genome analysis of clinical strains. (A) In total, 34 bacterial strains were isolated from several samples, such as cerebrospinal fluid (I, 2 strains), bronchoalveolar lavage (II, 3 strains), ascitic fluid (III, 5 strains), and blood (IV, 25 strains). The four most common bacterial groups (Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus spp.) are colored. (B) Schematic representation of the main bioinformatic pipeline used for genome sequencing, assembly, annotation, and identification of antibiotic resistance genes (ARGs) and virulence factor and genomic analysis.

Figure 2

Identification of ARGs in sequenced genomes. (A) Heatmap showing the presence of ARGs identified by ARG-ANNOT indicating the number of each resistance gene per genome. Data were clustered using hierarchical mapping with Euclidian distance. The blue to red scale indicates the number of ARGs for each strain in each category, as indicated in the legend. The nucleotide sequences in ARG-ANNOT from different antibiotics classes are abbreviated as follows—AGly: Aminoglycoside resistance genes; Bla: Beta-lactamases; Fcyn: Fosfomycin; Flq: Fluoroquinolones; Gly: Glycopeptides; MLS: Macrolide–lincosamide–streptogramin; Phe: phenicols; Rif: rifampin; Sul: sulfonamides; Tet: tetracyclines; and Tmt: trimethoprim. (B) Distribution of different ARGs per genome of E. coli, colored by antibiotic category. The maximum likelihood phylogeny for the strains was based on the core genome. (C) Distribution of different ARGs per genome of K. pneumoniae, following the scheme in (B).

Figure 3

Shared beta-lactamases with 100% identity at the protein level. Seven beta-lactamase coding genes were found as shared among gram-negative strains analyzed. Connected circles indicate that the genes are presented in those strains. On the right, the antibiotic resistance profile of the analyzed strains is shown. Genes for bla_OXA-1 and bla_KPC are highlighted (red triangles) since these genes were identified in the functional screening carried out in this study. On the right, antibiotic resistance levels are indicated, with numbers indicating the resistance levels in mg/mL. Red indicates resistance to the antibiotic, while blue denotes sensitivity. In the final column it is indicated if the strain is extended-spectrum ß-lactamase (ESBL)-positive or -negative. AMP: ampicillin; APS: ampicillin/sulbactam; PIT: piperacillin/tazobactam; CFX: cefuroxime, CFX-A: cefuroxime axetil; CTX: cefotaxime; CAZ: ceftazidime; CPM: cefepime; CFO: cefoxitin; ERT: ertapenem; IMP: imipenem; MER: meropenem; CIP: ciprofloxacin; GEN: gentamicin.

Figure 4

Schematic representation of genes of three K. pneumoniae plasmids. (A) Plasmid pKP98M3N42 (43 kb) from K. pneumoniae 98M3. This plasmid carries two ARGs (bla_KPC-2 and sat-2A), elements of a type IV secretion system, two resolvases, and a Tn3 transposase. This plasmid is very similar to pKP125M3N44 from K. pneumoniae 125M3 (Figure S4A). Whole-plasmid visualization was performed using a python module for prokaryotic genome analyses (DnaFeaturesView) and a matplotlib module combined, as well as ARG-ANNOT and Prokka’s results [49]. (B) Plasmid pKP508BN15 (136.8 kb) from K. pneumoniae 508B transports sul2 and an rRNA adenine n-6-methyltransferase (ermC) resistance marker. A transposase, a xerC recombinase, and a type IV secretion system virB8 protein are also found in this plasmid. (C) Plasmid pKP508BN34 (63 kb) is also from K. pneumoniae 508B and carries several transposases and two resistance determinants, qnr-S1 and bla_LAP-2. Legends represent the colors code for the identified genes.

Figure 5

Experimental design for functional genomics analysis. (A) Strains and backbone used to construct the library and features of the obtained libraries. (B) Functional screening for beta-lactam resistant clones, phenotypic confirmation, and sequence identification. CFU: Colony forming unit; RFLP: Restriction fragment length polymorphism; KmR: Kanamycin resistance marker; pBBR1: A broad host range oriV; lacZα: lacZα gene with multiple cloning site; Plac: Plac promoter; pFGRnnnn: Plasmid naming schema.

Figure 6

Features found in identified clones conferring resistance to antibiotics. (A) ampC-2 gene identified from E. coli 126M3. (B) bla_KPC-2 gene identified from E. coli 126M3. (C) bla_LAP-2 gene identified from pKP508BN34 plasmid from K. pneumoniae 508B. (D) blaCTX-M-15 gene identified from K. pneumoniae 508B. (E) bla_OXA-1 gene identified from K. pneumoniae 508B. (F) bla_MOR-2 gene identified from M. morganii 538A. ORFs are colored according to their function: red—ORFs directly related to antibiotic resistance; orange—ORFs related to virulence; yellow—ORFs related to horizontal transfer of the ARG; blue—ORFs with no identified relation to pathogenesis. The cloned region represents contig regions that were identified in our screenings. Overlapping cloned regions are darker, while dim regions have fewer overlapping identified clones.

Figure 7

Distance relationship analysis for two plasmids from K. pneumoniae. (A) Distance relationship of the seven closest plasmids’ nucleotide sequences to pKP98M3N42, showing an E-value of less than 0.0 and a minimal sequence cover of 70% in BLAST analysis. The tree was produced using pairwise alignments by means of the fast-minimum evolution method. The year denotes the collection data, and the asterisk indicates the data reported in the public database. (B) Distance relationship of the 18 closest plasmids’ nucleotide sequences to pKP508BN34, showing an E-value of less than 0.0 and a minimal sequence cover of 50% in BLAST analysis. The tree was produced using pairwise alignments by means of the fast-minimum evolution method. The year indicates the collection data and the asterisk indicates the data reported in the public database, provided when the collection data were not available. iTOL (https://itol.embl.de accessed on 1 December 2020) was used for tree visualization.

Figure 8

Structural comparison of plasmids from K. pneumoniae strains. Identified plasmids were analyzed using blast, and the best hits were used for comparison using BLAST Ring Image Generator (BRIG) [66]. For simplification, only divergent regions between the plasmids are shown. (A) pKP98M3N42 (black) and pKP1253N44 (magenta). (B) pKP508BN34 (black). (C) pKP508BN15 (black).