Antimicrobial Resistance Genes Research Articles

Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistant Acinetobacter baumannii from whole genome sequencing and gene expression.

Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the challenge still exists to predict fully minimum inhibitory concentrations (MICs) and antimicrobial susceptibility phenotypes based on WGS data. This study aimed to establish an artificial intelligence-based computational approach in predicting antimicrobial susceptibilities of multidrug-resistant Acinetobacter baumannii from WGS and gene expression data. Antimicrobial susceptibility testing (AST) was performed using the broth microdilution method for 10 antimicrobial agents. In silico multilocus sequence typing (MLST), antimicrobial resistance genes, and phylogeny based on cgSNP and cgMLST strategies were analyzed. High-throughput qPCR was performed to measure the expression level of antimicrobial resistance (AMR) genes. Most isolates exhibited a high level of resistance to most of the tested antimicrobial agents, with the majority belonging to the IC2/CC92 lineage. Phylogenetic analysis revealed undetected transmission events or local outbreaks. The percentage agreements between AMR phenotype and genotype ranged from 70.08% to 89.96%, with the coefficient of agreement (κ) extending from 0.025 and 0.881. The prediction of AST employed by deep neural network models achieved an accuracy of up to 98.64% on the testing data set. Additionally, several linear regression models demonstrated high prediction accuracy, reaching up to 86.15% within an error range of one gradient, indicating a linear relationship between certain gene expressions and the corresponding antimicrobial MICs. In conclusion, neural network-based predictions could be used as a tool for the surveillance of antimicrobial resistance in multidrug-resistant A. baumannii.

Genomic characteristics of Salmonella enterica serovar Blockley.

Non-typhoidal Salmonella (NTS) is a significant cause of foodborne illness worldwide, with increasing antimicrobial resistance posing a public health concern. Salmonella enterica serovar Blockley (S. Blockley) is relatively uncommon, and its antimicrobial resistance profile and population structure have been understudied. This study presents a comprehensive genomic analysis of 264 S. Blockley isolates from diverse geographical regions to elucidate antimicrobial resistance patterns and population structure. Bayesian analysis classified these genomes into 10 distinct groups (BAPS A to BAPS J), further categorized into two lineages, R and S. Lineage R comprised six BAPS clusters (BAPSs A-F), predominantly found in Asia and Africa, all of which harbored the azithromycin resistance gene mph(A) and other resistance determinants. In contrast, lineage S, lacking mph(A), comprised the remaining four BAPS clusters, which were primarily found in Europe and the Americas. Several types of mutations in gyrA were found in lineage R, which were specific to BAPS clusters. These BAPS clusters exhibited distinct geographic distributions, with BAPS B, BAPS D, and BAPS E unique to China, Taiwan, and Japan, respectively, while BAPS H and BAPS I were predominantly found in the United States. Temporal phylogenetic analysis suggested that lineage R diverged in the 1980s, with notable microevolutionary changes. The presence of a genomic island with mph(A), aph(3')-Ia, aph(3")-Ib, aph(6)-Id, and tet(A) in lineage R underscores the public health threat, highlighting a need for continuous surveillance.IMPORTANCEAntimicrobial resistance in Salmonella is a global public health concern. In this study, we focused on serovar Blockley, and a whole-genome analysis revealed its global population structure. The results revealed the existence of azithromycin-resistant strains, which were characterized both phylogenetically and geographically. The resistance genes were transmitted via genomic islands, and their micro-scale evolution was also revealed. Our findings are the first to reveal the dissemination of antimicrobial resistance genes, including azithromycin, in serovar Blockley, and provide valuable insights into understanding the spread of antimicrobial resistance.

Salmonella Typhi Haplotype 58 biofilm formation and genetic variation in isolates from typhoid fever patients with gallstones in an endemic setting in Kenya

Although typhoid fever has largely been eliminated in high-income countries, it remains a major global public health concern especially among low- and middle-income countries. The causative agent, Salmonella enterica serovar Typhi (S. Typhi), is a human restricted pathogen with a limited capacity to replicate outside the human host. Human carriers, 90% of whom have gallstones in their gallbladder, continue to shed the pathogen for an ill-defined period of time after treatment. The genetic mechanisms involved in establishing the carrier state are poorly understood, but S. Typhi is thought to undergo specific genetic changes within the gallbladder as an adaptive mechanism. In the current study, we aimed to identify the genetic differences in longitudinal clinical S. Typhi isolates from asymptomatic carriers with gallstones in a typhoid endemic setting in Nairobi, Kenya. Whole-genome sequences were analyzed from 22 S. Typhi isolates, 20 from stool samples, and 2 from blood samples, all genotype 4.3.1 (H58). Out of this, 19 strains were from four patients also diagnosed with gallstones, of whom three had typhoid symptoms and continued to shed S. Typhi after treatment. All isolates had point mutations in the quinolone resistance-determining region (QRDR), and only sub-lineage 4.3.1.2.EA3 encoded multidrug resistance genes. There was no variation in antimicrobial resistance patterns among strains from the same patient/household. Non-multidrug resistant (MDR) isolates formed significantly stronger biofilms in vitro than the MDR isolates, p<0.001. A point mutation within the treB gene (treB A383T) was observed in strains isolated after clinical resolution from patients living in 75% of the households. For missense mutations in Vi capsular polysaccharide genes, tviE P263S was also observed in 18% of the isolates. This study provides insights into the role of typhoid carriage, biofilm formation, AMR genes, and genetic variations in S. Typhi during asymptomatic carriage.

A nosocomial outbreak of colistin and carbapenem-resistant hypervirulent Klebsiella pneumoniae in a large teaching hospital.

Recently, colistin and carbapenem-resistant hypervirulent Klebsiella pneumoniae (CCR-hvKP) has been observed sporadically. The aim of this study was to report a nosocomial outbreak due to CCR-hvKP, so as to control the transmission of CCR-hvKP and prevent future outbreaks. The clinical characteristics of five involved cases were analyzed and infection prevention and control measures were documented. Five CCR-hvKP isolates were discovered from the five involved cases. Molecular features of the isolates including sequence type, capsule locus, antimicrobial resistance genes, virulence factors and phylogenetic relationship were analyzed by whole-genome sequencing. Validation of the role of the deleterious amino acid mutations to colistin resistance was examined by complementation assays. PCR was performed to identify insertion sequences within the mgrB gene. Mouse intraperitoneal infection models were used to assess virulence phenotype. Five cases infected with CCR-hvKP were identified with a high attributable mortality rate of 60% in the patients. The five outbreak isolates belonged to the high-risk ST11-KL64 clone and were closely clustered. They were highly resistant to commonly used antibiotics and showed hypervirulent in vivo. WGS revealed multiple antimicrobial resistance genes such as blaKPC-2 and blaCTX-M-65 and important virulence factors. Concerning colistin resistance, amino acid mutations G53S in pmrA gene, and T157P, T246A and R256G in pmrB gene were indentified. Among them, the deleterious mutation T157P in pmrB gene was validated to be responsible for the resistance phenotype of isolate KP01, KP03 and KP05. In addition, disruption of mgrB gene by insertion sequences of ISKpn26 and IS903B was indentified in isolate KP02 and KP04, respectively. This is the first report of an outbreak caused by CCR-hvKP. The study highlights infection prevention and control measures are key to successfully fight against CCR-hvKP dissemination and nosocomial infections. Continuous surveillance should be performed to limit the spread of these isolates.

Limited Evidence of Spillover of Antimicrobial-Resistant Klebsiella pneumoniae from Animal/Environmental Reservoirs to Humans in Vellore, India.

Klebsiella pneumoniae is a common opportunistic pathogen in humans, often associated with both virulence and antimicrobial resistance (AMR) phenotypes. K. pneumoniae have a highly plastic genome and can act as a vehicle for disseminating genetic information. Aiming to assess the impact of the human-animal-environment interface on AMR dissemination in K. pneumoniae we sampled and genome sequenced organisms from a range of environments and compared their genetic composition. Representative K. pneumoniae isolated from clinical specimens (n = 59), livestock samples (n = 71), and hospital sewage samples (n = 16) during a two-year surveillance study were subjected to whole genome sequencing. We compared the taxonomic and genomic distribution of K. pneumoniae, AMR gene abundance, virulence gene composition, and mobile genetic elements between the three sources. The K. pneumoniae isolates originating from livestock were clonally distinct from those derived from clinical/hospital effluent samples. Notably, the clinical and hospital sewage isolates typically possessed a greater number of resistance/virulence genes than those from animals. Overall, we observed a limited overlap of K. pneumoniae clones, AMR genes, virulence determinants, and plasmids between the different settings. In this setting, the spread of XDR and hypervirulent clones of K. pneumoniae appears to be restricted to humans with no obvious association with non-clinical sources. Emergent clones of K. pneumoniae carrying both resistance and virulence determinants are likely to have emerged in hospital settings rather than in animal or natural environments. These data challenge the current view of AMR transmission in K. pneumoniae in a One-Health context.

Antimicrobial resistance, virulence factors and phylogenetic profiles of Vibrio parahaemolyticus in the eastern coast of Shenzhen

Vibrio parahaemolyticus (V. parahaemolyticus) is a major food-borne pathogen which causes human gastroenteritis. Since the characteristics of V. parahaemolyticus remain unknown, 220 isolates selected from clinical and environmental samples in Dapeng of Shenzhen were tested for the presence of two hemolysin-expressing genes tdh and trh. Among 27 clinical isolates, 26 carrired the tdh gene, and the other one carried both tdh and trh genes, however neither genes were detected in environmental isolates. Meanwhile, antimicrobial susceptibility profiles revealed the isolates with high frequency of resistance to ampicillin (77.73%) and colistin (71.82%) and medium to streptomycin (57.27%). Genetically, by whole genome sequencing (WGS), comparative genomics studies was performed on isolates from various districts and GenBank. Data analysis showed that antimicrobial resistance genes (ARGs) blaCARB, tet(34) and tet(35) were harbored in all genomes and other ARGs was absent in the genomes of 27 clinical isolates. Besides, little regional difference was observed. As for virulence factors, MAM7, T3SS1, T3SS1 secret effector, T3SS2, T3SS2 secret effector, and VpadF were carried by most isolates. Two isolates from other districts were tdh gene positive which clustered with clinical isolates from Dapeng in the same clade, indicating close genetic distance. This study revealed the widely distribution of V. parahaemolyticus in Shenzhen and the diverse ARGs and virulence genes it carried. Furthermore, pathways that pathogen disseminated through were discussed.

Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling

AbstractBackgroundMicrobial infections, particularly in children, require rapid and accurate diagnostics. It is difficult to differentiate pathogens from commensal organisms, and it is impossible to identify antibiotic resistance genes that belong to pathogens with current methods. Third‐generation sequencing provides rapid library preparation and real‐time data acquisition. Nanopore normal sampling (NNS) enables unbiased sequencing of clinical samples without amplification, aiding pathogen identification and antimicrobial resistance gene prediction. However, clinical samples often contain a considerable amount of human DNA, potentially masking pathogen data. Nanopore adaptive sampling (NAS) aims to selectively enrich pathogens, promising improved diagnostics for acute infections and better treatment decisions in clinical practice. This study aimed to determine the utility of NAS in enhancing the real‐time detection of pathogens and predicting AMR in infectious disease outbreaks.MethodsThis study used NAS technology to rapidly and directly detect Mycoplasma pneumoniae infection in bronchoalveolar lavage fluid samples from 28 pediatric patients at Shenzhen Children's Hospital. We assessed the efficacy of NAS compared with that of NNS by evaluating the number of microbial reads and the amount of microbial DNA data. We then compared the accuracy of detecting pathogens between NNS and NAS and between NAS and real‐time polymerase chain reaction assays. Furthermore, we predicted antimicrobial resistance (AMR) and examined AMR genes associated with pathogens.ResultsNAS showed up to a 14.67‐fold increase in the amount of microbial DNA data from patients' samples compared with NNS within the initial 2.5 h of sequencing. Additionally, NAS reduced the amount of host DNA data by up to 6.67‐fold compared with NNS. Unlike TaqMan real‐time polymerase chain reaction assays, NAS technology identified dominant pathogens and provided detailed insight into the abundance of the microbial community. Furthermore, NAS was able to predict AMR profiles of microbial communities and attribute specific AMR traits to individual microbes within the samples.ConclusionThis study shows that NAS advances the clinical diagnosis because it can rapidly detect pathogens directly from patients' samples and provides antimicrobial resistance information for clinical guidance. These abilities further facilitate the application of NAS in personalized treatment, reduce the misuse of broad‐spectrum antibiotics, and promote patients' recovery.

Characterization of two lytic bacteriophages infecting carbapenem-resistant clinical Klebsiella pneumoniae in Dhaka, Bangladesh

Bacteriophages or bacteria infecting viruses are genetically diverse. Due to the emergence of antimicrobial-resistant bacteria, lytic bacteriophages are gaining enormous attention for treating superbug infections. Klebsiella pneumoniae is one of the eight most significant nosocomial pathogens and is addressed as a critical priority pathogen by WHO, requiring alternative treatment options. We reported two highly lytic bacteriophages, Klebsiella phage Kpn BM7 and the novel Klebsiella phage Kpn BU9, isolated from hospital wastewater and exhibiting lytic activity against different clinical isolates. Whole-genome analysis revealed that phages BM7 and BU9 belong to class Caudoviricetes. Phage BM7, with a genome length of 170,558 bp, is a member of the genus Marfavirus and the species Marfavirus F48. While phage BU9, with a genome length of 60,450 bp, remains unclassified. Neither phage harbors any lysogenic, toxin, or antimicrobial resistance genes. Both phages can steadily survive up to 40 °C and at pH 5–7. The optimal MOI was 0.1 for BM7 and 1 for BU9, with short latent periods of 10 and 25 min and burst sizes of 85 PFU/cell and 12 PFU/cell, respectively. This is the first carbapenem-resistant K. pneumoniae targeting lytic phages to be reported from Bangladesh. This study suggests that BM7 and BU9 are potential candidates for targeting carbapenem-resistant K. pneumoniae.

Microbial Contamination and Antibiotic Resistance in Fresh Produce and Agro-Ecosystems in South Asia—A Systematic Review

Fresh produce prone to microbial contamination is a potential reservoir for antimicrobial-resistant bacteria (ARB) and antimicrobial resistance genes (ARGs), posing challenges to food safety and public health. This systematic review aims to comprehensively assess the prevalence of bacterial pathogens and the incidence of ARB/ARGs in fresh produce and agro-ecosystems across South Asia. Twenty-two relevant studies published between 2012 and 2022 from three major scientific databases and the grey literature were identified. The results revealed a wide occurrence of microbial contamination in various types of fresh produce across South Asia, with a predominance of E. coli (16/22), Salmonella spp. (13/22), Staphylococcus spp. (5/22), and Klebsiella spp. (4/22). The agro-ecosystem serves as a complex interface for microbial interactions; studies have reported the prevalence of E. coli (1/4), Salmonella spp. (1/4) and Listeria monocytogenes (1/4) in farm environment samples. A concerning prevalence of ARB has been reported, with resistance to multiple classes of antibiotics. The presence of ARGs in fresh produce underscores the potential for gene transfer and the emergence of resistant pathogens. To conclude, our review provides insights into the requirements of enhanced surveillance, collaborative efforts, implementation of good agricultural practices, and public awareness for food safety and safeguarding public health in the region.

Recovery of clinically relevant multidrug-resistant Klebsiella pneumoniae lineages from wastewater in Kumasi Metropolis, Ghana.

Antimicrobial resistance (AMR) is under-monitored in Africa, with few reports characterizing resistant bacteria from the environment. This study examined physicochemical parameters, chemical contaminants and antibiotic-resistant bacteria in waste stabilization pond effluents, hospital wastewater and domestic wastewater from four sewerage sites in Kumasi. The bacteria isolates were sequenced. Three sites exceeded national guidelines for total suspended solids, biochemical oxygen demand, chemical oxygen demand and electrical conductivity. Although sulfamethoxazole levels were low, the antibiotic was detected at all sites. Multi-drug-resistant Klebsiella pneumoniae and Pseudomonas aeruginosa were isolated with multi-locus sequence typing identifying K. pneumoniae strains as ST18 and ST147, and P. aeruginosa as ST235, all of clinical relevance. A comparison of ST147 genomes with isolates from human infections in Africa showed remarkable similarity and shared AMR profiles. Thirteen of the twenty-one plasmids from ST147 harbored at least one AMR gene, including blaCTX-M-15 linked to copper-resistance genes. Our study demonstrated high bacterial counts and organic matter in the analysed wastewater. The recovery of clinically significant isolates with multiple antibiotic and heavy metal resistance genes from the wastewater samples raises public health concerns.

Expanding the diversity of origin of transfer-containing sequences in mobilizable plasmids.

Conjugative plasmids are important drivers of bacterial evolution. Most plasmids lack genes for conjugation and characterized origins of transfer (oriT), which has hampered our understanding of plasmid mobility. Here we used bioinformatic analyses to characterize occurrences of known oriT families across 38,057 plasmids, confirming that most conjugative and mobilizable plasmids lack identifiable oriTs. Recognizable oriT sequences tend to be intergenic, upstream of relaxase genes and specifically associated with relaxase types. We used these criteria to develop a computational method to search for and identify 21 additional families of oriT-containing sequences in plasmids from the pathogens Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii. Sequence analyses found 3,072 occurrences of these oriT-containing sequences across 2,976 plasmids, many of which encoded antimicrobial resistance genes. Six candidate oriT-containing sequences were validated experimentally and were shown to facilitate conjugation in E. coli. These findings expand our understanding of plasmid mobility.

Profiling the bacterial microbiome diversity and assessing the potential to detect antimicrobial resistance bacteria in wastewater in Kimberley, South Africa

Wastewater treatment plants (WWTPs) are hotspots for pathogens, and can facilitate horizontal gene transfer, potentially releasing harmful genetic material and antimicrobial resistance genes into the environment. Little information exists on the composition and behavior of microbes in WWTPs, especially in developing countries. This study used environmental DNA (eDNA) techniques to examine the microbiome load of wastewater from WWTPs. The DNA was isolated from wastewater samples collected from the treatment trains of three WWTPs in Kimberley, South Africa, and the microbial diversity and composition was compared through 16 S rRNA gene sequencing. The microbes detected were of the Kingdom Bacteria, and of these, 48.27% were successfully identified to genus level. The majority of reads from the combined bacterial data fall within the class Gammaproteobacteria, which is known to adversely impact ecological and human health. Arcobacteraceae constituted 19% of the bacterial reads, which is expected as this family is widespread in aquatic environments. Interestingly, the most abundant bacterial group was Bacteroides, which contain a variety of antibiotic-resistant members. Overall, various antibiotic-resistant taxa were detected in the wastewater, indicating a concerning level of antibiotic resistance within the bacterial community. Therefore, eDNA analysis can be a valuable tool in monitoring and assessing the bacterial microbiome in wastewater, thus providing important information for the optimization and improvement of wastewater treatment systems and mitigate public health risks.

Emergence of Salmonella enterica Serovar Heidelberg Producing OXA 48 Carbapenemase in Eastern Algeria.

Salmonella infections have become increasingly resistant to antibiotics, including fluoroquinolones, third-generation cephalosporins (C3G), and even carbapenems. This report describes the emergence of a strain of Salmonella enterica serovar Heidelberg that produces the carbapenemase OXA 48. The strain was isolated from a stool sample taken from a newborn. Antimicrobial susceptibility testing was carried out following the recommendations of the Clinical and Laboratory Standard Institute. Whole genome sequencing was performed on MiSeq Illumina™. The strain was resistant to ertapenem (minimal inhibitory concentration [MIC] = 12 µg/mL), intermediate to imipenem (MIC = 1.5 µg/mL), resistant to nalidixic acid, and intermediate to fluoroquinolones but was susceptible to C3G, cotrimoxazole, chloramphenicol, and colistin (MIC = 0.064 µg/mL). The strain was identified as ST-15. The strain of Salmonella Heidelberg ST-15 was found to have antimicrobial resistance genes, specifically blaOXA-48, aac(6')-Iaa and fosA7, which mediate resistance to carbapenems, aminoglycosides and fosfomycin, respectively. Additionally, mutations were detected in the gyrA, parC. Three plasmid replicon type IncL, IncX1, and Col156 have been identified. The strain has the potential to cause an epidemic. The genomic analysis of the strain allowed us to understand the mechanisms of resistance. Preventing the spread of Salmonella carbapenemase-producing strains is crucial, particularly in hospital settings. Epidemiological measures are necessary to achieve this goal.

Data-Driven Approaches in Antimicrobial Resistance: Machine Learning Solutions

Background/Objectives: The emergence of antimicrobial resistance (AMR) due to the misuse and overuse of antibiotics has become a critical threat to global public health. There is a dire need to forecast AMR to understand the underlying mechanisms of resistance for the development of effective interventions. This paper explores the capability of machine learning (ML) methods, particularly unsupervised learning methods, to enhance the understanding and prediction of AMR. It aims to determine the patterns from AMR gene data that are clinically relevant and, in public health, capable of informing strategies. Methods: We analyzed AMR gene data in the PanRes dataset by applying unsupervised learning techniques, namely K-means clustering and Principal Component Analysis (PCA). These techniques were applied to identify clusters based on gene length and distribution according to resistance class, offering insights into the resistance genes’ structural and functional properties. Data preprocessing, such as filtering and normalization, was conducted prior to applying machine learning methods to ensure consistency and accuracy. Our methodology included the preprocessing of data and reduction of dimensionality to ensure that our models were both accurate and interpretable. Results: The unsupervised learning models highlighted distinct clusters of AMR genes, with significant patterns in gene length, including their associated resistance classes. Further dimensionality reduction by PCA allows for clearer visualizations of relationships among gene groupings. These patterns provide novel insights into the potential mechanisms of resistance, particularly the role of gene length in different resistance pathways. Conclusions: This study demonstrates the potential of ML, specifically unsupervised approaches, to enhance the understanding of AMR. The identified patterns in resistance genes could support clinical decision-making and inform public health interventions. However, challenges remain, particularly in integrating genomic data and ensuring model interpretability. Further research is needed to advance ML applications in AMR prediction and management.

Highly resistant Salmonella Heidelberg circulating in broiler farms in southern Brazil.

Salmonella Heidelberg, a serotype commonly found in Southern Brazil, is characterized by its high resistance and persistence in the poultry production. This study aimed to characterize the antimicrobial resistance of S. Heidelberg strains. In total, 100 strains isolated from poultry between 2020 and 2022 were evaluated. Phenotypic analyses were performed to determine the susceptibility of 16 antimicrobial agents and detect extended-spectrum beta-lactamase (ESBL)-producing strains. Molecular analyses were performed to detect 11 antimicrobial resistance genes (using polymerase chain reaction [PCR]) and integron class 1 genes (using real-time PCR). A total of 98% of isolates was classified as multidrug-resistant. All isolates were resistant to penicillin and lincomycin. High resistance rates (> 85%) were observed for tetracycline, doxycycline, cephalexin, amoxicillin, and ceftiofur. A significant increase (p < 0.05) in antimicrobial resistance is observed for amoxicillin, cephalexin, and ceftiofur between 2020 and 2022. No significant differences (p > 0.05) were observed in antimicrobial resistance with respect to the region of isolation, season, or company. In total, 25% of isolates were ESBL producers. Integron class 1 gene was detected in only one strain, whereas sul2 was detected in 99%, tet(A) in 66%, blaTEM in 37%, strB in 17%, cmlA in 15%, and tet(B) in 11% of the strains. Other genes were not detected or were detected in < 2% of the strains. The results showed a high overall resistance, which increased over the evaluated period. The high proportions of ESBL-producing and antimicrobial resistant strains represent a risk for highly-resistant S. Heidelberg dissemination across broiler flocks.

Emergence of the mobile RND-type efflux pump gene cluster tmexCD1-toprJ1 in Klebsiella pneumoniae clinical isolates in Japan.

Tigecycline is an antimicrobial agent with a broad spectrum of activity against both Gram-positive and Gram-negative bacteria. However, mobile tigecycline resistance gene clusters, such as tnfxB-tmexCD-toprJ, have spread globally. The prevalence of tigecycline-resistant Enterobacterales in clinical settings in Japan is unknown. To investigate the tnfxB-tmexCD-toprJ gene cluster in the genome sequences of Enterobacterales clinical isolates in Japan. We investigated the tnfxB-tmexCD-toprJ cluster from the genome sequences of 5143 Enterobacterales isolates collected from 175 hospitals around Japan between 2019 and 2020 as part of a national genomic surveillance program for antimicrobial-resistant bacteria. The tnfxB1-tmexCD1-toprJ1 cluster was detected in two Klebsiella pneumoniae isolates in 2019. One isolate possessed a 299.4 kb IncFIB(K) plasmid, pJBBGAAF19431, and the other possessed a 224.9 kb IncHI1B/IncFIB(K) hybrid plasmid, pJBEAACG19501, co-carrying multiple antimicrobial resistance genes, including extended-spectrum β-lactamase genes, blaOXA-1 and blaCTX-M-27, respectively, along with tnfxB1-tmexCD1-toprJ1. The genetic context of the tnfxB1-tmexCD1-toprJ1-surrounding structure on pJBBGAAF19431 was similar to that of a K. pneumoniae plasmid pHNAH8I-1 from a chicken in China in 2017, and the cluster was embedded in an apparently intact mobile DNA element: strand-biased circularizing integrative element. The tnfxB1-tmexCD1-toprJ1 on pJBEAACG19501 was embedded in a Tn3 family transposon related to TnAs1. The plasmid pJBEAACG19501 was highly similar to that of K. pneumoniae, isolated from humans in China in 2021. tmexCD-toprJ was present in Japan as of 2019. Even in Japan, where the clinical use of tigecycline is significantly rare, tmexCD-toprJ-harbouring multidrug-resistant Enterobacterales is a public health threat and requires continuous monitoring.

Factors impacting target-enriched long-read sequencing of resistomes and mobilomes.

We investigated the efficiency of target-enriched long-read sequencing (TELSeq) for detecting antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) within complex matrices. We aimed to overcome limitations associated with traditional antimicrobial resistance (AMR) detection methods, including short-read shotgun metagenomics, which can lack sensitivity, specificity, and the ability to provide detailed genomic context. By combining biotinylated probe-based enrichment with long-read sequencing, we facilitated the amplification and sequencing of ARGs, eliminating the need for bioinformatic reconstruction. Our experimental design included replicates of human fecal microbiota transplant material, bovine feces, pristine prairie soil, and a mock human gut microbial community, allowing us to examine variables including genomic DNA input and probe set composition. Our findings demonstrated that TELSeq markedly improves the detection rates of ARGs and MGEs compared to traditional sequencing methods, underlining its potential for accurate AMR monitoring. A key insight from our research is the importance of incorporating mobilome profiles to better predict the transferability of ARGs within microbial communities, prompting a recommendation for the use of combined ARG-MGE probe sets for future studies. We also reveal limitations for ARG detection from low-input workflows, and describe the next steps for ongoing protocol refinement to minimize technical variability and expand utility in clinical and public health settings. This effort is part of our broader commitment to advancing methodologies that address the global challenge of AMR.

Single Laboratory Evaluation of the Q20+ Nanopore Sequencing Kit for Bacterial Outbreak Investigations

Leafy greens are a significant source of produce-related Shiga toxin-producing Escherichia coli (STEC) outbreaks in the United States, with agricultural water often implicated as a potential source. Current FDA outbreak detection protocols are time-consuming and rely on sequencing methods performed in costly equipment. This study evaluated the potential of Oxford Nanopore Technologies (ONT) with Q20+ chemistry as a cost-effective, rapid, and accurate method for identifying and clustering foodborne pathogens. The study focuses on assessing whether ONT Q20+ technology could facilitate near real-time pathogen identification, including SNP differences, serotypes, and antimicrobial resistance genes. This pilot study evaluated different combinations of two DNA extraction methods (Maxwell RSC Cultured Cell DNA kit and Monarch high molecular weight extraction kits) and two ONT library preparation protocols (ligation and the rapid barcoding sequencing kit) using five well-characterized strains representing diverse foodborne pathogens. High-quality, closed bacterial genomes were obtained from all combinations of extraction and sequencing kits. However, variations in assembly length and genome completeness were observed, indicating the need for further optimization. In silico analyses demonstrated that Q20+ nanopore sequencing chemistry accurately identified species, genotype, and virulence factors, with comparable results to Illumina sequencing. Phylogenomic clustering showed that ONT assemblies clustered with reference genomes, though some indels and SNP differences were observed, likely due to sequencing and analysis methodologies rather than inherent genetic variation. Additionally, the study evaluated the impact of a change in the sampling rates from 4 kHz (260 bases pair second) to 5 kHz (400 bases pair second), finding no significant difference in sequencing accuracy. This evaluation workflow offers a framework for evaluating novel technologies for use in surveillance and foodborne outbreak investigations. Overall, the evaluation demonstrated the potential of ONT Q20+ nanopore sequencing chemistry to assist in identifying the correct strain during outbreak investigations. However, further research, validation studies, and optimization efforts are needed to address the observed limitations and fully realize the technology’s potential for improving public health outcomes and enabling more efficient responses to foodborne disease threats.

Development of a Recombinase Polymerase Amplification-Coupled CRISPR/Cas12a Platform for Rapid Detection of Antimicrobial-Resistant Genes in Carbapenem-Resistant Enterobacterales

The worldwide spread of carbapenemase-producing Enterobacterales (CPE) represents a significant threat owing to the high mortality and morbidity rates. Traditional diagnostic methods are often too slow and complex for rapid point-of-care testing. Therefore, we developed a recombinase polymerase amplification (RPA)-coupled CRISPR/Cas12a system (RCCS), a rapid, accurate, and simple diagnostic platform for detecting antimicrobial-resistant genes. The RCCS detected carbapenemase genes (blaKPC and blaNDM) within 50 min, including 10 min for DNA extraction and 30–40 min for RCCS reaction (a 20 min RPA reaction with a 10–20-min CRISPR/Cas12a assay). Fluorescence signals obtained from the RCCS platform were visualized using lateral-flow test strips (LFSs) and real-time and endpoint fluorescence. The LFS clearly displayed test lines while detecting carbapenemase genes. Furthermore, the RCCS platform demonstrated high sensitivity by successfully detecting blaKPC and blaNDM at the attomolar and picomolar levels, respectively. The accuracy of the RCCS platform was validated with clinical isolates of Klebsiella pneumoniae and Escherichia coli; a 100% detection accuracy was achieved, which has not been reported when using conventional PCR. Overall, these findings indicate that the RCCS platform is a powerful tool for rapid and reliable detection of carbapenemase-encoding genes, with significant potential for implementation in point-of-care settings and resource-limited environments.

Limit of detection of Salmonella ser. Enteritidis using culture-based versus culture-independent diagnostic approaches.

The appeal of culture-independent diagnostic tests (CIDTs) is increased speed with lowered cost, as well as the potential to detect multiple pathogen species in a single analysis and to monitor other areas of concern such as antimicrobial resistance genes or virulence factors. This study provides quantitative data on the sensitivity of CIDTs relative to current approaches, which is essential for determining the feasibility of implementing these methods in pathogen surveillance programs.