Hybrid Assembly Provides Improved Resolution of Plasmids, Antimicrobial Resistance Genes, and Virulence Factors in Escherichia coli and Klebsiella pneumoniae Clinical Isolates

Benchmarking short and long read polishing tools for nanopore assemblies: achieving near-perfect genomes for outbreak isolates

BACKGROUND

Oxford Nanopore provides high throughput sequencing platforms able to reconstruct complete bacterial genomes with 99.95% accuracy. However, even small levels of error can obscure the phylogenetic relationships between closely related isolates. Polishing tools have been developed to correct these errors, but it is uncertain if they obtain the accuracy needed for the high-resolution source tracking of foodborne illness outbreaks.

RESULTS

We tested 132 combinations of assembly and short- and long-read polishing tools to assess their accuracy for reconstructing the genome sequences of 15 highly similar Salmonella enterica serovar Newport isolates from a 2020 onion outbreak. While long-read polishing alone improved accuracy, near perfect accuracy (99.9999% accuracy or ~ 5 nucleotide errors across the 4.8 Mbp genome, excluding low confidence regions) was only obtained by pipelines that combined both long- and short-read polishing tools. Notably, medaka was a more accurate and efficient long-read polisher than Racon. Among short-read polishers, NextPolish showed the highest accuracy, but Pilon, Polypolish, and POLCA performed similarly. Among the 5 best performing pipelines, polishing with medaka followed by NextPolish was the most common combination. Importantly, the order of polishing tools mattered i.e., using less accurate tools after more accurate ones introduced errors. Indels in homopolymers and repetitive regions, where the short reads could not be uniquely mapped, remained the most challenging errors to correct.

CONCLUSIONS

Short reads are still needed to correct errors in nanopore sequenced assemblies to obtain the accuracy required for source tracking investigations. Our granular assessment of the performance of the polishing pipelines allowed us to suggest best practices for tool users and areas for improvement for tool developers.

Pathogenomic analysis and characterization of Pasteurella multocida strains recovered from human infections

Pasteurella multocida is an upper respiratory tract commensal in several mammal and bird species but can also cause severe disease in humans and in production animals such as poultry, cattle, and pigs. In this study, we performed whole-genome sequencing of P. multocida isolates recovered from a range of human infections, from the mouths of cats, and from wounds on dogs. Together with publicly available P. multocida genome sequences, we performed phylogenetic and comparative genomic analyses. While isolates from cats and dogs were spread across the phylogenetic tree, human infections were caused almost exclusively by subsp. septica strains. Most of the human isolates were capsule type A and LPS type L1 and L3; however, some strains lacked a capsule biosynthesis locus, and some strains contained a novel LPS outer-core locus, distinct from the eight LPS loci that can currently be identified using an LPS multiplex PCR. In addition, the P. multocida strains isolated from human infections contained novel mobile genetic elements. We compiled a curated database of known P. multocida virulence factor and antibiotic resistance genes (PastyVRDB) allowing for detailed characterization of isolates. The majority of human P. multocida isolates encoded a reduced range of iron receptors and contained only one filamentous hemagglutinin gene. Finally, gene-trait analysis identified a putative L-fucose uptake and utilization pathway that was over-represented in subsp. septica strains and may represent a novel host predilection mechanism in this subspecies. Together, these analyses have identified pathogenic mechanisms likely important for P. multocida zoonotic infections.IMPORTANCEPasteurella multocida can cause serious infections in humans, including skin and wound infections, pneumonia, peritonitis, meningitis, and bacteraemia. Cats and dogs are known vectors of human pasteurellosis, transmitting P. multocida via bite wounds or contact with animal saliva. The mechanisms that underpin P. multocida human predilection and pathogenesis are poorly understood. With increasing identification of antibiotic-resistant P. multocida strains, understanding these mechanisms is vital for developing novel treatments and control strategies to combat P. multocida human infection. Here, we show that a narrow range of P. multocida strains cause disease in humans, while cats and dogs, common vectors for zoonotic infections, can harbor a wide range of P. multocida strains. We also present a curated P. multocida-specific database, allowing quick and detailed characterization of newly sequenced P. multocida isolates.

Hybrid Illumina-Nanopore assembly improves identification of multilocus sequence types and antimicrobial resistance genes of Staphylococcus aureus isolated from Vermont dairy farms: comparison to Illumina-only and R9.4.1 nanopore-only assemblies

Antimicrobial resistance (AMR) in Staphylococcus aureus is a pressing public health challenge with significant implications for the dairy industry, encompassing bovine mastitis concerns and potential zoonotic threats. To delve deeper into the resistance mechanisms of S. aureus, this study employed a hybrid whole genome assembly approach that synergized the precision of Illumina with the continuity of Oxford Nanopore. A total of 62 isolates, collected from multiple sources from Vermont dairy farms, were sequenced using the GridION Oxford Nanopore R9.4.1 platform and the Illumina platform, and subsequently processed through our long-read first bioinformatics pipeline. Our analyses showcased the hybrid-assembled genome's superior completeness compared to Oxford Nanopore (R9.4.1)-only or Illumina-only assembled genomes. Furthermore, the hybrid assembly accurately determined multilocus sequence typing (MLST) strain types across all isolates. The comprehensive probe for antibiotic resistance genes (ARGs) using databases like CARD, Resfinder, and MEGARES 2.0 characterized AMR in S. aureus isolates from Vermont dairy farms, and revealed the presence of notable resistance genes, including beta-lactam genes blaZ, blaI, and blaR. In conclusion, the hybrid assembly approach emerged as a tool for uncovering the genomic nuances of S. aureus isolates collected from multiple sources on dairy farms. Our findings offer a pathway for detecting AMR gene prevalence and shaping AMR management strategies crucial for safeguarding human and animal health.

Short turnaround time of seven to nine hours from sample collection until informed decision for sepsis treatment using nanopore sequencing

Bloodstream infections (BSIs) and sepsis are major health problems, annually claiming millions of lives. Traditional blood culture techniques, employed to identify sepsis-causing pathogens and assess antibiotic susceptibility, usually take 2-4 days. Early and accurate antibiotic prescription is vital in sepsis to mitigate mortality and antibiotic resistance. This study aimed to reduce the wait time for sepsis diagnosis by employing shorter blood culture incubation times for BD BACTEC™ bottles using standard laboratory incubators, followed by real-time nanopore sequencing and data analysis. The method was tested on nine blood samples spiked with clinical isolates from the six most prevalent sepsis-causing pathogens. The results showed that pathogen identification was possible at as low as 102-104 CFU/mL, achieved after just 2 h of incubation and within 40 min of nanopore sequencing. Moreover, all the antimicrobial resistance genes were identified at 103-107 CFU/mL, achieved after incubation for 5 h and only 10 min to 3 h of sequencing. Therefore, the total turnaround time from sample collection to the information required for an informed decision on the right antibiotic treatment was between 7 and 9 h. These results hold significant promise for better clinical management of sepsis compared with current culture-based methods.

Identification of plasmids in avian-associated Escherichia coli using nanopore and illumina sequencing

BACKGROUND

Avian pathogenic Escherichia coli (APEC) are the causative agents of colibacillosis in chickens, a disease which has significant economic impact on the poultry industry. Large plasmids detected in APEC are known to contribute to strain diversity for pathogenicity and antimicrobial resistance, but there could be other plasmids that are missed in standard analysis. In this study, we determined the impact of sequencing and assembly factors for the detection of plasmids in an E. coli whole genome sequencing project.

RESULTS

Hybrid assembly (Illumina and Nanopore) combined with plasmid DNA extractions allowed for detection of the greatest number of plasmids in E. coli, as detected by MOB-suite software. In total, 79 plasmids were identified in 19 E. coli isolates. Hybrid assemblies were robust and consistent in quality regardless of sequencing kit used or if long reads were filtered or not. In contrast, long read only assemblies were more variable and influenced by sequencing and assembly parameters. Plasmid DNA extractions allowed for the detection of physically smaller plasmids, but when averaged over 19 isolates did not significantly change the overall number of plasmids detected.

CONCLUSIONS

Hybrid assembly can be reliably used to detect plasmids in E. coli, especially if researchers are focused on large plasmids containing antimicrobial resistance genes and virulence factors. If the goal is comprehensive detection of all plasmids, particularly if smaller sized vectors are desired for biotechnology applications, the addition of plasmid DNA extractions to hybrid assemblies is prudent. Long read sequencing is sufficient to detect many plasmids in E. coli, however, it is more prone to errors when expanded to analyze a large number of isolates.

Comparing antimicrobial resistant genes and phenotypes across multiple sequencing platforms and assays for Enterobacterales clinical isolates

INTRODUCTION

Whole genome sequencing (WGS) of bacterial isolates can be used to identify antimicrobial resistance (AMR) genes. Previous studies have shown that genotype-based AMR has variable accuracy for predicting carbapenem resistance in carbapenem-resistant Enterobacterales (CRE); however, the majority of these studies used short-read platforms (e.g. Illumina) to generate sequence data. In this study, our objective was to determine whether Oxford Nanopore Technologies (ONT) long-read WGS would improve detection of carbapenem AMR genes with respect to short-read only WGS for nine clinical CRE samples. We measured the minimum inhibitory breakpoint (MIC) using two phenotype assays (MicroScan and ETEST) for six antibiotics, including two carbapenems (meropenem and ertapenem) and four non-carbapenems (gentamicin, ciprofloxacin, cefepime, and trimethoprim/sulfamethoxazole). We generated short-read data using the Illumina NextSeq and long-read data using the ONT MinION. Four assembly methods were compared: ONT-only assembly; ONT-only assembly plus short-read polish; ONT + short-read hybrid assembly plus short-read polish; short-read only assembly.

RESULTS

Consistent with previous studies, our results suggest that the hybrid assembly produced the highest quality results as measured by gene completeness and contig circularization. However, ONT-only methods had minimal impact on the detection of AMR genes and plasmids compared to short-read methods, although, notably, differences in gene copy number differed between methods. All four assembly methods showed identical presence/absence of the blaKPC-2 carbapenemase gene for all samples. The two phenotype assays showed 100% concordant results for the non-carbapenems, but only 65% concordance for the two carbapenems. The presence/absence of AMR genes was 100% concordant with AMR phenotypes for all four non-carbapenem drugs, although only 22%-50% sensitivity for the carbapenems.

CONCLUSIONS

Overall, these findings suggest that the lack of complete correspondence between CRE AMR genotype and phenotype for carbapenems, while concerning, is independent of sequencing platform/assembly method.

The application of long-read sequencing in clinical settings

Long-read DNA sequencing technologies have been rapidly evolving in recent years, and their ability to assess large and complex regions of the genome makes them ideal for clinical applications in molecular diagnosis and therapy selection, thereby providing a valuable tool for precision medicine. In the third-generation sequencing duopoly, Oxford Nanopore Technologies and Pacific Biosciences work towards increasing the accuracy, throughput, and portability of long-read sequencing methods while trying to keep costs low. These trades have made long-read sequencing an attractive tool for use in research and clinical settings. This article provides an overview of current clinical applications and limitations of long-read sequencing and explores its potential for point-of-care testing and health care in remote settings.

Co-Existence of blaNDM-1, blaOXA-23, blaOXA-64, blaPER-7 and blaADC-57 in a Clinical Isolate of Acinetobacter baumannii from Alexandria, Egypt

The increasing rates of antimicrobial resistance among carbapenem-resistant Acinetobacter baumannii in the Middle East and North Africa are one of the major concerns for healthcare settings. We characterised the first A. baumannii isolate harbouring five β-lactamases identified in Egypt. The isolate Ale25 was obtained from an ICU patient of a hospital from Alexandria. The isolate was phenotypically and genotypically screened for carbapenemase genes. The isolate was resistant to carbapenems, aminoglycosides, fluoroquinolones and cefiderocol. Whole-Genome Sequencing identified five β-lactamase genes, blaNDM-1, blaOXA-23, blaOXA-64, blaPER-7 and blaADC-57, together with other antibiotic resistance genes, conferring resistance to sulfonamides, macrolides, tetracyclines, rifamycin and chloramphenicol. Virulome analysis showed the presence of genes involved in adhesion and biofilm production, type II and VI secretion systems, exotoxins, etc. Multi-Locus Sequence Typing analysis identified the isolate as Sequence Types 113Pas and 2246Oxf, belonging to International Clone 7. Sequencing experiments revealed the presence of four plasmids of 2.7, 22.3, 70.4 and 240.8 Kb. All the β-lactamase genes were located in the chromosome, except the blaPER-7, gene which was found within the plasmid of 240.8 Kb. This study highlights the threat of the emergence and dissemination of these types of isolates.

The impact of applying various de novo assembly and correction tools on the identification of genome characterization, drug resistance, and virulence factors of clinical isolates using ONT sequencing

Oxford Nanopore sequencing technology (ONT) is currently widely used due to its affordability, simplicity, and reliability. Despite the advantage ONT has over next-generation sequencing in detecting resistance genes in mobile genetic elements, its relatively high error rate (10-15%) is still a deterrent. Several bioinformatic tools are freely available for raw data processing and obtaining complete and more accurate genome assemblies. In this study, we evaluated the impact of using mix-and-matched read assembly (Flye, Canu, Wtdbg2, and NECAT) and read correction (Medaka, NextPolish, and Racon) tools in generating complete and accurate genome assemblies, and downstream genomic analysis of nine clinical Escherichia coli isolates. Flye and Canu assemblers were the most robust in genome assembly, and Medaka and Racon correction tools significantly improved assembly parameters. Flye functioned well in pan-genome analysis, while Medaka increased the number of core genes detected. Flye, Canu, and NECAT assembler functioned well in detecting antimicrobial resistance genes (AMR), while Wtdbg2 required correction tools for better detection. Flye was the best assembler for detecting and locating both virulence and AMR genes (i.e., chromosomal vs. plasmid). This study provides insight into the performance of several read assembly and read correction tools for analyzing ONT sequencing reads for clinical isolates.

Genomic analysis of Enterococcus faecium strain RAOG174 associated with acute chorioamnionitis carried antibiotic resistance gene: is it time for precise microbiological identification for appropriate antibiotic use?

BACKGROUND

Preterm labor syndrome is associated with high perinatal morbidity and mortality, and intra-amniotic infection is a cause of preterm labor. The standard identification of causative microorganisms is based on the use of biochemical phenotypes, together with broth dilution-based antibiotic susceptibility from organisms grown in culture. However, such methods could not provide an accurate epidemiological aspect and a genetic basis of antimicrobial resistance leading to an inappropriate antibiotic administration. Hybrid genome assembly is a combination of short- and long-read sequencing, which provides better genomic resolution and completeness for genotypic identification and characterization. Herein, we performed a hybrid whole genome assembly sequencing of a pathogen associated with acute histologic chorioamnionitis in women presenting with PPROM.

RESULTS

We identified Enterococcus faecium, namely E. faecium strain RAOG174, with several antibiotic resistance genes, including vancomycin and aminoglycoside. Virulence-associated genes and potential bacteriophage were also identified in this genome.

CONCLUSION

We report herein the first study demonstrating the use of hybrid genome assembly and genomic analysis to identify E. faecium ST17 as a pathogen associated with acute histologic chorioamnionitis. The analysis provided several antibiotic resistance-associated genes/mutations and mobile genetic elements. The occurrence of E. faecium ST17 raised the awareness of the colonization of clinically relevant E. faecium and the carrying of antibiotic resistance. This finding has brought the advantages of genomic approach in the identification of the bacterial species and antibiotic resistance gene for E. faecium for appropriate antibiotic use to improve maternal and neonatal care.

Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics-Current State and Whole Genome Sequencing Implementation Perspectives

Antimicrobial resistance (AMR), defined as the ability of microorganisms to withstand antimicrobial treatment, is responsible for millions of deaths annually. The rapid spread of AMR across continents warrants systematic changes in healthcare routines and protocols. One of the fundamental issues with AMR spread is the lack of rapid diagnostic tools for pathogen identification and AMR detection. Resistance profile identification often depends on pathogen culturing and thus may last up to several days. This contributes to the misuse of antibiotics for viral infection, the use of inappropriate antibiotics, the overuse of broad-spectrum antibiotics, or delayed infection treatment. Current DNA sequencing technologies offer the potential to develop rapid infection and AMR diagnostic tools that can provide information in a few hours rather than days. However, these techniques commonly require advanced bioinformatics knowledge and, at present, are not suited for routine lab use. In this review, we give an overview of the AMR burden on healthcare, describe current pathogen identification and AMR screening methods, and provide perspectives on how DNA sequencing may be used for rapid diagnostics. Additionally, we discuss the common steps used for DNA data analysis, currently available pipelines, and tools for analysis. Direct, culture-independent sequencing has the potential to complement current culture-based methods in routine clinical settings. However, there is a need for a minimum set of standards in terms of evaluating the results generated. Additionally, we discuss the use of machine learning algorithms regarding pathogen phenotype detection (resistance/susceptibility to an antibiotic).

Nanopore-only assemblies for genomic surveillance of the global priority drug-resistant pathogen, Klebsiella pneumoniae

Oxford Nanopore Technologies (ONT) sequencing has rich potential for genomic epidemiology and public health investigations of bacterial pathogens, particularly in low-resource settings and at the point of care, due to its portability and affordability. However, low base-call accuracy has limited the reliability of ONT data for critical tasks such as antimicrobial resistance (AMR) and virulence gene detection and typing, serotype prediction, and cluster identification. Thus, Illumina sequencing remains the standard for genomic surveillance despite higher capital and running costs. We tested the accuracy of ONT-only assemblies for common applied bacterial genomics tasks (genotyping and cluster detection, implemented via Kleborate, Kaptive and Pathogenwatch), using data from 54 unique Klebsiella pneumoniae isolates. ONT reads generated via MinION with R9.4.1 flowcells were basecalled using three alternative models [Fast, High-accuracy (HAC) and Super-accuracy (SUP), available within ONT's Guppy software], assembled with Flye and polished using Medaka. Accuracy of typing using ONT-only assemblies was compared with that of Illumina-only and hybrid ONT+Illumina assemblies, constructed from the same isolates as reference standards. The most resource-intensive ONT-assembly approach (SUP basecalling, with or without Medaka polishing) performed best, yielding reliable capsule (K) type calls for all strains (100 % exact or best matching locus), reliable multi-locus sequence type (MLST) assignment (98.3 % exact match or single-locus variants), and good detection of acquired AMR genes and mutations (88-100 % correct identification across the various drug classes). Distance-based trees generated from SUP+Medaka assemblies accurately reflected overall genetic relationships between isolates. The definition of outbreak clusters from ONT-only assemblies was problematic due to inflation of SNP counts by high base-call errors. However, ONT data could be reliably used to 'rule out' isolates of distinct lineages from suspected transmission clusters. HAC basecalling + Medaka polishing performed similarly to SUP basecalling without polishing. Therefore, we recommend investing compute resources into basecalling (SUP model), wherever compute resources and time allow, and note that polishing is also worthwhile for improved performance. Overall, our results show that MLST, K type and AMR determinants can be reliably identified with ONT-only R9.4.1 flowcell data. However, cluster detection remains challenging with this technology.

A culture-, amplification-independent, and rapid method for identification of pathogens and antibiotic resistance profile in bovine mastitis milk

Introduction

Rapid and accurate diagnosis of causative pathogens in mastitis would minimize the imprudent use of antibiotics and, therefore, reduce the spread of antimicrobial resistance. Whole genome sequencing offers a unique opportunity to study the microbial community and antimicrobial resistance (AMR) in mastitis. However, the complexity of milk samples and the presence of a high amount of host DNA in milk from infected udders often make this very challenging.

Methods

Here, we tested 24 bovine milk samples (18 mastitis and six non-mastitis) using four different commercial kits (Qiagens' DNeasy^® PowerFood^® Microbial, Norgens' Milk Bacterial DNA Isolation, and Molzyms' MolYsis™ Plus and Complete5) in combination with filtration, low-speed centrifugation, nuclease, and 10% bile extract of male bovine (Ox bile). Isolated DNA was quantified, checked for the presence/absence of host and pathogen using PCR and sequenced using MinION nanopore sequencing. Bioinformatics analysis was performed for taxonomic classification and antimicrobial resistance gene detection.

Results

The results showed that kits designed explicitly for bacterial DNA isolation from food and dairy matrices could not deplete/minimize host DNA. Following using MolYsis™ Complete 5 + 10% Ox bile + micrococcal nuclease combination, on average, 17% and 66.5% of reads were classified as bovine and Staphylococcus aureus reads, respectively. This combination also effectively enriched other mastitis pathogens, including Escherichia coli and Streptococcus dysgalactiae. Furthermore, using this approach, we identified important AMR genes such as Tet (A), Tet (38), fosB-Saur, and blaZ. We showed that even 40 min of the MinION run was enough for bacterial identification and detecting the first AMR gene.

Conclusion

We implemented an effective method (sensitivity of 100% and specificity of 92.3%) for host DNA removal and bacterial DNA enrichment (both gram-negative and positive) directly from bovine mastitis milk. To the best of our knowledge, this is the first culture- and amplification-independent study using nanopore-based metagenomic sequencing for real-time detection of the pathogen (within 5 hours) and the AMR profile (within 5-9 hours), in mastitis milk samples. These results provide a promising and potential future on-farm adaptable approach for better clinical management of mastitis.

Highly sensitive quantitative phase microscopy and deep learning aided with whole genome sequencing for rapid detection of infection and antimicrobial resistance

Current state-of-the-art infection and antimicrobial resistance (AMR) diagnostics are based on culture-based methods with a detection time of 48-96 h. Therefore, it is essential to develop novel methods that can do real-time diagnoses. Here, we demonstrate that the complimentary use of label-free optical assay with whole-genome sequencing (WGS) can enable rapid diagnosis of infection and AMR. Our assay is based on microscopy methods exploiting label-free, highly sensitive quantitative phase microscopy (QPM) followed by deep convolutional neural networks-based classification. The workflow was benchmarked on 21 clinical isolates from four WHO priority pathogens that were antibiotic susceptibility tested, and their AMR profile was determined by WGS. The proposed optical assay was in good agreement with the WGS characterization. Accurate classification based on the gram staining (100% recall for gram-negative and 83.4% for gram-positive), species (98.6%), and resistant/susceptible type (96.4%), as well as at the individual strain level (100% sensitivity in predicting 19 out of the 21 strains, with an overall accuracy of 95.45%). The results from this initial proof-of-concept study demonstrate the potential of the QPM assay as a rapid and first-stage tool for species, strain-level classification, and the presence or absence of AMR, which WGS can follow up for confirmation. Overall, a combined workflow with QPM and WGS complemented with deep learning data analyses could, in the future, be transformative for detecting and identifying pathogens and characterization of the AMR profile and antibiotic susceptibility.

Molecular characteristics of global β-lactamase-producing Enterobacter cloacae by genomic analysis

OBJECTIVE

To analyze the characteristics of global β-lactamase-producing Enterobacter cloacae including the distribution of β-lactamase, sequence types (STs) as well as plasmid replicons.

METHODS

All the genomes of the E. cloacae were downloaded from GenBank. The distribution of β-lactamase encoding genes were investigated by genome annotation after the genome quality was checked. The STs of these strains were analyzed by multi-locus sequence typing (MLST). The distribution of plasmid replicons was further explored by submitting these genomes to the genome epidemiology center. The isolation information of these strains was extracted by Per program from GenBank.

RESULTS

A total of 272 out of 276 strains were found to carry β-lactamase encoding genes. Among them, 23 varieties of β-lactamase were identified, bla_CMH (n = 130, 47.8%) and bla_ACT (n = 126, 46.3%) were the most predominant ones, 9 genotypes of carbapenem-hydrolyzing β-lactamase (CHβLs) were identified with bla_VIM (n = 29, 10.7%) and bla_KPC (n = 24, 8.9%) being the most dominant ones. In addition, 115 distinct STs for the 272 ß-lactamase-carrying E. cloacae and 48 different STs for 106 CHβLs-producing E. cloacae were detected. ST873 (n = 27, 9.9%) was the most common ST. Furthermore, 25 different plasmid replicons were identified, IncHI2 (n = 65, 23.9%), IncHI2A (n = 64, 23.5%) and IncFII (n = 62, 22.8%) were the most common ones. Notably, the distribution of plasmid replicons IncHI2 and IncHI2A among CHβLs-producing strains were significantly higher than theat among non-CHβLs-producing strains (p < 0.05).

CONCLUSION

Almost all the E. cloacae contained β-lactamase encoding gene. Among the global E. cloacae, bla_CMH and bla_ACT were main bla_AmpC genes. Bla_TEM and bla_CTX-M were the predominant ESBLs. Bla_KPC, bla_VIM and bla_NDM were the major CHβLs. Additionally, diversely distinct STs and different replicons were identified.

Acquisition of resistance to ceftazidime-avibactam during infection treatment in Pseudomonas aeruginosa through D179Y mutation in one of two blaKPC-2 gene copies without losing carbapenem resistance

Ceftazidime/Avibactam (CAZ/AVI) is frequently used to treat KPC-producing Pseudomonas aeruginosa (KPC-PA) and Enterobacterales. CAZ/AVI resistance is driven by several mechanisms. In P. aeruginosa this mainly occurs through alteration of AmpC, porins, and/or efflux pump overexpression, whereas in Enterobacterales it frequently occurs through D179Y substitution in the active site of KPC enzyme. This aminoacid change abolishes AVI binding to the KPC active site, hence inhibition is impaired. However, this substitution also decreases KPC-mediated resistance to carbapenems ("see-saw" effect). The goal of this work was to characterize the in vivo acquisition of CAZ/AVI resistance through D179Y substitution in a KPC-PA isolated from a hospitalized patient after CAZ/AVI treatment. Two KPC-PA isolates were obtained. The first isolate, PA-1, was obtained before CAZ/AVI treatment and was susceptible to CAZ/AVI. The second isolate, PA-2, was obtained after CAZ/AVI treatment and exhibited high-level CAZ/AVI resistance. Characterization of isolates PA-1 and PA-2 was performed through short and long-read whole genome sequencing analysis. The hybrid assembly showed that PA-1 and PA-2A had a single plasmid of 54,030 bp, named pPA-1 and pPA-2 respectively. Each plasmid harbored two copies of the bla KPC-containing Tn4401b transposon. However, while pPA-1 carried two copies of bla KPC-2, pPA-2 had one copy of bla KPC-2 and one copy of bla KPC-33, the allele with the D179Y substitution. Interestingly, isolate PA-2 did not exhibit the "see-saw" effect. The bla KPC-33 allele was detected only through hybrid assembly using a long-read-first approach. The present work describes a KPC-PA isolate harboring a plasmid-borne CAZ/AVI resistance mechanism based on two copies of bla KPC-2-Tn4401b and D179Y mutation in one of them, that is not associated with loss of resistance to carbapenems. These findings highlight the usefulness of a fine-tuned combined analysis of short and long-read data to detect similar emerging resistance mechanisms.

Ultrafast and Cost-Effective Pathogen Identification and Resistance Gene Detection in a Clinical Setting Using Nanopore Flongle Sequencing

Rapid bacterial identification and antimicrobial resistance gene (ARG) detection are crucial for fast optimization of antibiotic treatment, especially for septic patients where each hour of delayed antibiotic prescription might have lethal consequences. This work investigates whether the Oxford Nanopore Technology’s (ONT) Flongle sequencing platform is suitable for real-time sequencing directly from blood cultures to identify bacteria and detect resistance-encoding genes. For the analysis, we used pure bacterial cultures of four clinical isolates of Escherichia coli and Klebsiella pneumoniae and two blood samples spiked with either E. coli or K. pneumoniae that had been cultured overnight. We sequenced both the whole genome and plasmids isolated from these bacteria using two different sequencing kits. Generally, Flongle data allow rapid bacterial ID and resistome detection based on the first 1,000–3,000 generated sequences (10 min to 3 h from the sequencing start), albeit ARG variant identification did not always correspond to ONT MinION and Illumina sequencing-based data. Flongle data are sufficient for 99.9% genome coverage within at most 20,000 (clinical isolates) or 50,000 (positive blood cultures) sequences generated. The SQK-LSK110 Ligation kit resulted in higher genome coverage and more accurate bacterial identification than the SQK-RBK004 Rapid Barcode kit.

Long-Read Sequencing and Hybrid Assembly for Genomic Analysis of Clinical Brucella melitensis Isolates

Brucella melitensis is a key etiological agent of brucellosis and has been increasingly subject to characterization using sequencing methodologies. This study aimed to investigate and compare short-read, long-read, and hybrid assemblies of B. melitensis. Eighteen B. melitensis isolates from Southern Israel were sequenced using Illumina and the Oxford Nanopore (ONP) MinION, and hybrid assemblies were generated with ONP long reads scaffolded on Illumina short reads. Short reads were assembled with INNUca with SPADes, long reads and hybrid with dragonflye. Abricate with the virulence factor database (VFDB) and in silico PCR (for the genes BetB, BPE275, BSPB, manA, mviN, omp19, perA, PrpA, VceC, and ureI) were used for identifying virulence genes, and a total of 61 virulence genes were identified in short-read, long-read, and hybrid assemblies of all 18 isolates. The phylogenetic analysis using long-read assemblies revealed several inconsistencies in cluster assignment as compared to using hybrid and short-read assemblies. Overall, hybrid assembly provided the most comprehensive data, and stand-alone short-read sequencing provided comparable data to stand-alone long-read sequencing regarding virulence genes. For genomic epidemiology studies, stand-alone ONP sequencing may require further refinement in order to be useful in endemic settings.

Whole-Genome Sequencing of Pathogenic Bacteria-New Insights into Antibiotic Resistance Spreading

In recent years, the acquisition of antimicrobial resistance (AMR) by both pathogenic and opportunistic bacteria has become a major problem worldwide, which was already noticed as a global healthcare threat by the World Health Organization [...].