Genomic and functional characterization of fecal sample strains of Proteus cibarius carrying two floR antibiotic resistance genes and a multiresistance plasmid-encoded cfr gene

Whole Genome Sequencing: Applications in Clinical Bacteriology

The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.

Risk Factors for Non-Healing Wounds-A Single-Centre Study

Background: Chronic wounds present a significant clinical, social, and economic challenge. This study aimed to objectify the risk factors of healing outcomes and the duration of chronic wounds from various etiologies. Methods: Patients treated for non-healing wounds at the surgical outpatient clinic of the Olomouc Military Hospital were involved. Data from patients treated between 8/2021 and 9/2023 were selected. Patients were mostly treated as outpatients, with microbiological follow-up indicated in cases of advanced signs of inflammation. Results: There were 149 patients who met our selection criteria (the mean age was 64.4 years). Predominant causes of wounds involved diabetes (30.9%), post-trauma (25.5%), pressure ulcers (14.8%), surgical site infections (14.8%), and vascular ulcers (14.1%). Patient outcomes included wound resolution in 77.2% of patients (with a mean healing time of 110.9 days), amputation in 14.1%, and wound-related death in 8.7% of patients. Non-healing cases (amputation/death) were predicted by several local factors including an initial depth greater than 1 cm, wound secretion, inflammatory base, and a maximum wound size. Systemic factors included most strongly clinically manifested atherosclerosis and its risk factors. Of the 110 swabs performed, 103 identified at least 1 bacterial genus. The dominant risk factor for a prolonged healing duration was bacterial infection. Wounds contaminated by Proteus or Pseudomonas had prolonged healing times of 87 days (p = 0.02) and 72 days (p = 0.045), respectively. Conclusions: The early identification of local and systemic risk factors contributes to the successful resolution of chronic wounds and a reduced duration of healing.

Detection of linezolid and vancomycin resistant Enterococcus isolates collected from healthy chicken caecum

AIM

The poultry industry represents an important economic sector in Tunisia. This study aims to determine the antimicrobial resistance phenotypes and genotypes and virulence factors of enterococci collected from chicken caecum in Tunisia.

METHODS AND RESULTS

Forty-nine composite chicken caecum samples were recovered in 49 different Tunisian farms (December 2019-March 2020). Each composite sample corresponds to six individual caecum from each farm. Composite samples were plated on Slanetz-Bartley agar both supplemented (SB-Van) and not supplemented (SB) with vancomycin and isolates were identified by matrix-assisted laser desorption/ionization time-of-flight. Antibiotic resistance and virulence genes were tested by Polymerase Chain Reaction (PCR) and sequencing and multilocus-sequence-typing of selected enterococci was performed. One hundred sixty seven enterococci of six different species were recovered. Acquired linezolid resistance was detected in 6 enterococci of 4/49 samples (8.1%): (A) four optrA-carrying Enterococcus faecalis isolates assigned to ST792, ST478, and ST968 lineages; (B) two poxtA-carrying Enterococcus faecium assigned to ST2315 and new ST2330. Plasmid typing highlighted the presence of the rep10, rep14, rep7, rep8, and pLG1 in these strains. One vancomycin-resistant E. faecium isolate (typed as ST1091) with vanA gene (included in Tn1546) was detected in SB-Van plates. The gelE, agg, esp, and hyl virulence genes were found in linezolid- and vancomycin-resistant enterococci. High resistance rates were identified in the enterococci recovered in SB plates: tetracycline [74.8%, tet(M) and tet(L) genes], erythromycin [65.9%, erm(B)], and gentamicin [37.1%, aac(6')-Ie-aph(2″)-Ia].

CONCLUSION

The detection of emerging mechanisms of resistance related to linezolid and vancomycin in the fecal enterococci of poultry farms has public health implications, and further surveillance should be carried out to control their dissemination by the food chain.

Systems Biology: New Insight into Antibiotic Resistance

Over the past few decades, antimicrobial resistance (AMR) has emerged as an important threat to public health, resulting from the global propagation of multidrug-resistant strains of various bacterial species. Knowledge of the intrinsic factors leading to this resistance is necessary to overcome these new strains. This has contributed to the increased use of omics technologies and their extrapolation to the system level. Understanding the mechanisms involved in antimicrobial resistance acquired by microorganisms at the system level is essential to obtain answers and explore options to combat this resistance. Therefore, the use of robust whole-genome sequencing approaches and other omics techniques such as transcriptomics, proteomics, and metabolomics provide fundamental insights into the physiology of antimicrobial resistance. To improve the efficiency of data obtained through omics approaches, and thus gain a predictive understanding of bacterial responses to antibiotics, the integration of mathematical models with genome-scale metabolic models (GEMs) is essential. In this context, here we outline recent efforts that have demonstrated that the use of omics technology and systems biology, as quantitative and robust hypothesis-generating frameworks, can improve the understanding of antibiotic resistance, and it is hoped that this emerging field can provide support for these new efforts.

Oxazolidinones: mechanisms of resistance and mobile genetic elements involved

The oxazolidinones (linezolid and tedizolid) are last-resort antimicrobial agents used for the treatment of severe infections in humans caused by MDR Gram-positive bacteria. They bind to the peptidyl transferase centre of the bacterial ribosome inhibiting protein synthesis. Even if the majority of Gram-positive bacteria remain susceptible to oxazolidinones, resistant isolates have been reported worldwide. Apart from mutations, affecting mostly the 23S rDNA genes and selected ribosomal proteins, acquisition of resistance genes (cfr and cfr-like, optrA and poxtA), often associated with mobile genetic elements [such as non-conjugative and conjugative plasmids, transposons, integrative and conjugative elements (ICEs), prophages and translocatable units], plays a critical role in oxazolidinone resistance. In this review, we briefly summarize the current knowledge on oxazolidinone resistance mechanisms and provide an overview on the diversity of the mobile genetic elements carrying oxazolidinone resistance genes in Gram-positive and Gram-negative bacteria.

Molecular characterization of florfenicol and oxazolidinone resistance in Enterococcus isolates from animals in China

Florfenicol is widely used for the treatment of bacterial infections in domestic animals. The aim of this study was to analyze the molecular mechanisms of florfenicol and oxazolidinone resistance in Enterococcus isolates from anal feces of domestic animals. The minimum inhibitory concentration (MIC) levels were determined by the agar dilution method. Polymerase chain reaction (PCR) was performed to analyze the distribution of the resistance genes. Whole-genome sequencing and comparative plasmid analysis was conducted to analyze the resistance gene environment. A total of 351 non-duplicated enteric strains were obtained. Among these isolates, 22 Enterococcus isolates, including 19 Enterococcus. faecium and 3 Enterococcus. faecalis, were further studied. 31 florfenicol resistance genes (13 fexA, 3 fexB, 12 optrA, and 3 poxtA genes) were identified in 15 of the 19 E. faecium isolates, and no florfenicol or oxazolidinone resistance genes were identified in 3 E. faecalis isolates. Whole-genome sequencing of E. faecium P47, which had all four florfenicol and oxazolidinone resistance genes and high MIC levels for both florfenicol (256 mg/L) and linezolid (8 mg/L), revealed that it contained a chromosome and 3 plasmids (pP47-27, pP47-61, and pP47-180). The four florfenicol and oxazolidinone resistance genes were all related to the insertion sequences IS1216 and located on two smaller plasmids. The genes fexB and poxtA encoded in pP47-27, while fexA and optrA encoded in the conjugative plasmid pP47-61. Comparative analysis of homologous plasmids revealed that the sequences with high identities were plasmid sequences from various Enterococcus species except for the Tn6349 sequence from a Staphylococcus aureus chromosome (MH746818.1). The current study revealed that florfenicol and oxazolidinone resistance genes (fexA, fexB, poxtA, and optrA) were widely distributed in Enterococcus isolates from animal in China. The mobile genetic elements, including the insertion sequences and conjugative plasmid, played an important role in the horizontal transfer of florfenicol and oxazolidinone resistance.

Detection of tet(X6) variant-producing Proteus terrae subsp. cibarius from animal cecum in Zhejiang, China

OBJECTIVES

The prevalence of tet(X) genes threatens the clinical use of last-line tigecycline. tet(X6) gene has been reported in Proteus strains, but its genetic context is rarely reported. This study aimed to investigate the prevalence and genetic contexts of tet(X6) gene in Proteus spp.

METHODS

A tet(X6) variant-bearing P. terrae subsp. cibarius strain was subjected to susceptibility testing, determination of growth curves, scanning electron microscopy, transmission electron microscopy and whole-genome sequencing (WGS). The genomic contexts of the tet(X6)-positive strain were analyzed by sequence comparison and annotation.

RESULTS

ZJ19PC, a P. terrae subsp. cibarius strain harboring the tet(X6) variant, was isolated from 20 cecum samples collected in Zhejiang, China. The chromosome size of ZJ19PC was 3,952,084 bp and that the GC content was 38.2%, and hugA, sul2, tet(H), floR, dfra1, aadA1, aac(3)-IV, and aph(4)-la were found in addition to the tet(X6) variant. Proteus spp. could be classified into three groups based on the tet(X6) gene contexts. Strain ZJ19PC belongs to Group 1 (sra-sul2-ISCR2-floR-ISCR2-floR-ISCR2- tet(X6)_variant-tnpA-ISEc59-aph(4)-la-aac(3)-Iva-IS26), and this region of Group 1 was inserted between modA and guaA. The common antimicrobial resistance (AMR) genes of the three types of AMR gene islands were sul2, floR, tet(X6) and aac(3). The tet(X6) gene contexts and SNP tree showed that ZJ19PC was homologous to HNCF44W and HNCF43W, which indicated that these strains may be clonally transmitted.

CONCLUSION

This study analyzed the genetic contexts of the tet(X6) gene in Proteus spp., and highlighted the significance of monitoring tigecycline-resistant P. terrae subsp. cibarius.

Mobile Oxazolidinone Resistance Genes in Gram-Positive and Gram-Negative Bacteria

Seven mobile oxazolidinone resistance genes, including cfr, cfr(B), cfr(C), cfr(D), cfr(E), optrA, and poxtA, have been identified to date. The cfr genes code for 23S rRNA methylases, which confer a multiresistance phenotype that includes resistance to phenicols, lincosamides, oxazolidinones, pleuromutilins, and streptogramin A compounds. The optrA and poxtA genes code for ABC-F proteins that protect the bacterial ribosomes from the inhibitory effects of oxazolidinones. The optrA gene confers resistance to oxazolidinones and phenicols, while the poxtA gene confers elevated MICs or resistance to oxazolidinones, phenicols, and tetracycline. These oxazolidinone resistance genes are most frequently found on plasmids, but they are also located on transposons, integrative and conjugative elements (ICEs), genomic islands, and prophages. In these mobile genetic elements (MGEs), insertion sequences (IS) most often flanked the cfr, optrA, and poxtA genes and were able to generate translocatable units (TUs) that comprise the oxazolidinone resistance genes and occasionally also other genes. MGEs and TUs play an important role in the dissemination of oxazolidinone resistance genes across strain, species, and genus boundaries. Most frequently, these MGEs also harbor genes that mediate resistance not only to antimicrobial agents of other classes, but also to metals and biocides. Direct selection pressure by the use of antimicrobial agents to which the oxazolidinone resistance genes confer resistance, but also indirect selection pressure by the use of antimicrobial agents, metals, or biocides (the respective resistance genes against which are colocated on cfr-, optrA-, or poxtA-carrying MGEs) may play a role in the coselection and persistence of oxazolidinone resistance genes.

Characterization of florfenicol resistance genes in the coagulase-negative Staphylococcus (CoNS) isolates and genomic features of a multidrug-resistant Staphylococcus lentus strain H29

Background

With the wide use of florfenicol to prevent and treat the bacterial infection of domestic animals, the emergence of the florfenicol resistance bacteria is increasingly serious. It is very important to elucidate the molecular mechanism of the bacteria’s resistance to florfenicol.

Methods

The minimum inhibitory concentration (MIC) levels were determined by the agar dilution method, and polymerase chain reaction was conducted to analyze the distribution of florfenicol resistance genes in 39 CoNS strains isolated from poultry and livestock animals and seafood. The whole genome sequence of one multidrug resistant strain, Staphylococcus lentus H29, was characterized, and comparative genomics analysis of the resistance gene-related sequences was also performed.

Results

As a result, the isolates from the animals showed a higher resistance rate (23/28, 82.1%) and much higher MIC levels to florfenicol than those from seafood. Twenty-seven animal isolates carried 37 florfenicol resistance genes (including 26 fexA, 6 cfr and 5 fexB genes) with one carrying a cfr gene, 16 each harboring a fexA gene, 5 with both a fexA gene and a fexB gene and the other 5 with both a fexA gene and a cfr gene. On the other hand, all 11 isolates from seafood were sensitive to florfenicol, and only 3 carried a fexA gene each. The whole genome sequence of S. lentus H29 was composed of a chromosome and two plasmids (pH29-46, pH29-26) and harbored 11 resistance genes, including 6 genes [cfr, fexA, ant(6)-Ia, aacA-aphD, mecA and mph(C)] encoded on the chromosome, 4 genes [cfr, fexA, aacA-aphD and tcaA] on pH29-46 and 1 gene (fosD) on pH29-26. We found that the S. lentus H29 genome carried two identical copies of the gene arrays of radC-tnpABC-hp-fexA (5671 bp) and IS256-cfr (2690 bp), of which one copy of the two gene arrays was encoded on plasmid pH29-46, while the other was encoded on the chromosome.

Conclusions

The current study revealed the wide distribution of florfenicol resistance genes (cfr, fexA and fexB) in animal bacteria, and to the best of our knowledge, this is the first report that one S. lentus strain carried two identical copies of florfenicol resistance-related gene arrays.