Application of a new designed high resolution melting analysis for mycobacterial species identification.

The Non-tuberculous mycobacterial (NTM) isolates should be distinguished from tuberculosis and identified at the species level for choosing an appropriate treatment plan. In this study, two molecular methods were used to differentiate NTM species, including a new designed High Resolution Melting (HRM) and Multilocus Sequence Analysis (MLSA). Seventy-five mycobacterial isolates were evaluated by sequencing four genes ( MLSA) and a HRM assay specifically targeting atpE was designed to rapidly and accurately identify and differentiate mycobacterium species. Out of 70 NTM isolates, 66 (94.3%), 65 (92.9%), 65 (92.9%) and 64 (91.4%) isolates were identified to the species level by PCR of atpE, tuf, rpoB and dnaK genes. We could identify 100% of the isolates to the species level (14 different species) by MLSA. By using HRM assay, all NTM isolates were identified and classified into eight groups, in addition, Mycobacterium tuberculosis and Nocardia were also detected simultaneously. The MLSA technique was able to differentiate all 14 species of NTM isolates. According to the results, the HRM assay is a rapid and beneficial method for identifying NTM, M. tuberculosis (MTB), and Nocardia isolates without sequencing.

In Silico Typing and Identification Confirmation of Isolates.

Streptococcus suis is an important zoonotic pathogen causing severe infections in pigs and humans. Serotyping of S. suis strains is crucial for epidemiological surveillance, outbreak investigations, and understanding the pathogenesis of this bacterium. Here, we describe a step-by-step approach that enhances a previously developed pipeline by utilizing a computational script for efficient and accurate typing of S. suis strains. The pipeline is implemented in Perl programming language and leverages the Short Read Sequence Typing for Bacterial Pathogens (SRST2) tool. It integrates various bioinformatics techniques and utilizes multiple databases, including a serotype database, cpsH confirmation database, multi-locus sequence typing (MLST) database, recN species-specific gene database, and virulence gene database. These databases contain comprehensive information on S. suis serotypes, genetic markers, and virulence factors. The script can utilize paired-end or single-end fastq files as input and first confirms the species by sequence read data aligning to the recN gene, ensuring the accurate identification of S. suis strains. The pipeline next performs MLST typing and virulence factor identification using SRST2 while in a parallel processes it performs in silico serotyping of the strains. The pipeline offers a streamlined and semiautomated approach to serotyping S. suis strains, facilitating large-scale studies and reducing the manual effort required for data analysis.

Mini-Multilocus Sequence Typing Scheme for the Global Population of Neisseria gonorrhoeae.

The increasing problem of antimicrobial resistance in N. gonorrhoeae necessitates the development of molecular typing schemes that are suitable for rapid and mass screening. The objective of this study was to design and validate a mini-MLST scheme for N. gonorrhoeae based on global pathogen population data. Using sequences of seven housekeeping genes of 21,402 isolates with known MLSTs from the PubMLST database, we identified eighteen informative polymorphisms and obtained mini-MLST nucleotide profiles to predict MLSTs of isolates. We proposed a new MLST grouping system for N. gonorrhoeae based on mini-MLST profiles. Phylogenetic analysis revealed that MLST genogroups are a stable characteristic of the N. gonorrhoeae global population. The proposed grouping system has been shown to bring together isolates with similar antimicrobial susceptibility, as demonstrated by the characteristics of major genogroups. Established MLST prediction algorithms based on nucleotide profiles are now publicly available. The mini-MLST scheme was evaluated using a MLST detection/prediction method based on the original hydrogel DNA microarray. The results confirmed a high predictive ability up to the MLST genogroup. The proposed holistic approach to gonococcal population analysis can be used for the continuous surveillance of known and emerging resistant N. gonorrhoeae isolates.

Whole Genome-Sequencing and Phylogenetic Analysis of Bacillus anthracis from 2019-2023 in Ningxia Hui Autonomous Region, China.

BACKGROUND: Since 2019, the incidence of anthrax in the Ningxia Hui Autonomous Region has increased significantly compared with previous years, so in this situation the anthrax in the Ningxia region not only had a detrimental impact on public health, but also inflicted significant economic repercussions. Therefore, we conducted a molecular epidemiological study of 20 strains from 2019-2023 isolates. This study investigated the origin of Bacillus anthracis and its genetic diversity. METHODS: We conducted canonical single-nucleotide polymorphisms (CanSNPs) typing and whole genome sequencing based on the extracted nucleic acid of Bacillus anthracis. Based on the whole genome drafts, we studied the genomic characteristics of 20 isolates. Meanwhile, we performed phylogenetic studies based on genome-wide core single-nucleotide polymorphisms (SNPs) using MEGA's Maximum Likelihood (ML) method and core-genome-based multilocus sequence typing (cgMLST) of the core genomes of these strains using BioNumerics' minimum spanning tree (MST) model. RESULTS: The 20 isolates were categorized into sub-lineages A.Br.001/002, and comparative genomic analyses of these strains with other isolates from other parts of the world showed that the strains from Ningxia were correlated with isolates from Europe, Indonesia, Georgia (USA), and Beijing (China). For the 20 isolates in Ningxia, the genetic relationship of the isolates isolated from the same year or region was relatively close. CONCLUSION: The A.Br.001/002 subgroup was the dominant endemic strain in Ningxia. The genetic relationship and phylogenesis between isolates from Ningxia and strains from Europe and Indonesia suggest that anthrax spread around the globe through ancient trade routes.

Diversity of Wolbachia infections in Sri Lankan mosquitoes with a new record of Wolbachia Supergroup B infecting Aedes aegypti vector populations.

Wolbachia bacteria are common endosymbionts of insects and have recently been applied for controlling arboviral vectors, especially Aedes aegypti mosquito populations. However, several medically important mosquito species in Sri Lanka were present with limited information for the Wolbachia infection status. Therefore, the screening of Wolbachia in indigenous mosquitoes is required prior to a successful application of Wolbachia-based vector control strategy. In this study, screening of 78 mosquito species collected from various parts of the country revealed that 13 species were positive for Wolbachia infection, giving ~ 17% infection frequency of Wolbachia among the Sri Lankan mosquitoes. Twelve Wolbachia-positive mosquito species were selected for downstream Wolbachia strain genotyping using Multi Locus Sequencing Type (MLST), wsp gene, and 16S rRNA gene-based approaches. Results showed that these Wolbachia strains clustered together with the present Wolbachia phylogeny of world mosquito populations with some variations. Almost 90% of the mosquito populations were infected with supergroup B while the remaining were infected with supergroup A. A new record of Wolbachia supergroup B infection in Ae. aegypti, the main vectors of dengue, was highlighted. This finding was further confirmed by real-time qPCR, revealing Wolbachia density variations between Ae. aegypti and Ae. albopictus (p = 0.001), and between males and females (p < 0.05). The evidence of natural Wolbachia infections in Ae. aegypti populations in Sri Lanka is an extremely rare incident that has the potential to be used for arboviral vector control.

Core genome multilocus sequence typing (cgMLST) applicable to the monophyletic Klebsiella oxytoca species complex.

The environmental bacterium Klebsiella oxytoca displays an alarming increase of antibiotic-resistant strains that frequently cause outbreaks in intensive care units. Due to its prevalence in the environment and opportunistic presence in humans, molecular surveillance (including resistance marker screening) and high-resolution cluster analysis are of high relevance. Furthermore, K. oxytoca previously described in studies is rather a species complex (KoSC) than a single species comprising at least six closely related species that are not easily differentiated by standard typing methods. To reach a discriminatory power high enough to identify and resolve clusters within these species, whole genome sequencing is necessary. The resolution is achievable with core genome multilocus sequence typing (cgMLST) extending typing of a few housekeeping genes to thousands of core genome genes. CgMLST is highly standardized and provides a nomenclature enabling cross laboratory reproducibility and data exchange for routine diagnostics. Here, we established a cgMLST scheme not only capable of resolving the KoSC species but also producing reliable and consistent results for published outbreaks. Our cgMLST scheme consists of 2,536 core genome and 2,693 accessory genome targets, with a percentage of good cgMLST targets of 98.31% in 880 KoSC genomes downloaded from the National Center for Biotechnology Information (NCBI). We also validated resistance markers against known resistance gene patterns and successfully linked genetic results to phenotypically confirmed toxic strains carrying the til gene cluster. In conclusion, our novel cgMLST enables highly reproducible typing of four different clinically relevant species of the KoSC and thus facilitates molecular surveillance and cluster investigations.

Different sampling strategies for optimal detection of the overall genetic diversity of methicillin-resistant Staphylococcus aureus.

Surveillance schemes for methicillin-resistant Staphylococcus aureus (MRSA) are widely established at the national and international levels. Due to the simple standardization of the protocol, mainly isolates from bloodstream infections are used. However, the limitations of this simple surveillance system are well described. We conducted a comprehensive analysis of MRSA isolates in a large Slovenian region over 5 years to identify the optimal sample group for assessing the overall MRSA diversity. At the same time, this study provides to date non-available molecular characterization of Slovenian MRSA isolates. A total of 306 MRSA isolates from various sources were sequenced and phenotypically tested for resistance. The isolates exhibited significant molecular diversity, encompassing 30 multi locus sequence type (MLST) sequence types (STs), 39 ST-SCCmec genetic lineages, 49 spa types, and 29 antibiotic resistance profiles. Furthermore, the isolate pool comprised 57 resistance genes, representing 22 resistance mechanisms, and 96 virulence genes. While bloodstream isolates, commonly used in surveillance, provided insights into frequently detected clones, they overlooked majority of clones and important virulence and resistance genes. Blood culture isolates detected 21.3% spa types, 24.1% resistance phenotypes, and 28.2% MLST-SCCmec profiles. In contrast, strains from soft tissues demonstrated superior genomic diversity capture, with 65.3% spa types, 58.6% resistance phenotypes, and 71.8% MLST-SCCmec profiles. These strains also encompassed 100.0% of virulence and 82.5% of resistance genes, making them better candidates for inclusion in surveillance programs. This study highlights the limitations of relying solely on bloodstream isolates in MRSA surveillance and suggests incorporating strains from soft tissues to obtain a more comprehensive understanding of the epidemiology of MRSA.IMPORTANCEIn this study, we investigated the diversity of methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that can cause infections that are difficult to treat due to its resistance to antimicrobial agents. Currently, surveillance programs for MRSA mainly rely on isolates from bloodstream infections, employing a standardized protocol. However, this study highlights the limitations of this approach and introduces a more comprehensive method. The main goal was to determine which group of samples is best suited to understand the overall diversity of MRSA and to provide, for the first time, molecular characterization of Slovenian MRSA isolates. Our results suggest that including MRSA strains from soft tissue infections rather than just blood infections provides a more accurate and comprehensive view of bacterial diversity and characteristics. This insight is valuable for improving the effectiveness of surveillance programs and for developing strategies to better manage MRSA infections.

A novel cgMLST for genomic surveillance of Yersinia enterocolitica infections in France allowed the detection and investigation of outbreaks in 2017-2021.

Enteric yersiniosis, the third most common food-borne zoonosis in Europe, is mainly caused by the pathogen Yersinia enterocolitica. In France, the yersiniosis microbiological surveillance is conducted at the Yersinia National Reference Laboratory (YNRL). Since 2017, isolates have been characterized by whole genome sequencing (WGS) followed by a 500-gene Yersinia-cgMLST. We report here the data of the WGS-based surveillance on Y. enterocolitica isolates for the 2017-2021 period. The YNRL characterized 7,642 Y. enterocolitica strains distributed in 2,497 non-pathogenic isolates from lineages 1Aa and 1Ab, and 5,145 specimens belonging to 8 pathogenic lineages. Among pathogenic isolates, lineage 4 was the most common (87.2%) followed by lineages 2/3-9b (10.6%), 2/3-5a (1.2%), 2/3-9a (0.6%), 3-3b, 3-3c, 1B, and 3-3d (0.1% per each). Importantly, we developed a routine surveillance system based on a new typing method consisting of a 1,727-genes core genome Multilocus Sequence Typing (cgMLST) specific to the species Y. enterocolitica followed by isolate clustering. Thresholds of allelic distances (AD) were determined and fixed for the clustering of isolates: AD ≤ 5 for lineages 4, 2/3-5a, and 2/3-9a, and AD ≤ 3 for lineage 2/3-9b. Clustering programs were implemented in 2019 in routine surveillance to detect genomic clusters of pathogenic isolates. In total, 419 clusters with at least 2 isolates were identified, representing 2,504 of the 3,503 isolates characterized between 2019 and 2021. Most clusters (n = 325) comprised 2 to 5 isolates. The new typing method proved to be useful for the molecular investigation of unusual grouping of cases as well as for the detection of genomic clusters in routine surveillance. IMPORTANCE: We describe here the new typing method used for molecular surveillance of Yersinia enterocolitica infections in France based on a novel core genome Multilocus Sequence Typing (cgMLST) specific to Y. enterocolitica species. This method can reliably identify the pathogenic Y. enterocolitica subspecies and compare the isolates with a high discriminatory power. Between 2017 and 2021, 5,145 pathogenic isolates belonging to 8 lineages were characterized and lineage 4 was by far the most common followed by lineage 2/3-9b. A clustering program was implemented, and detection thresholds were cross-validated by the molecular and epidemiological investigation of three unusual groups of Y. enterocolitica infections. The routine molecular surveillance system has been able to detect genomic clusters, leading to epidemiological investigations.

High prevalence of ST5-SCCmec II-t311 clone of methicillin-resistant Staphylococcus aureus isolated from bloodstream infections in East China.

OBJECTIVES: Methicillin-resistant Staphylococcus aureus (MRSA) is a challenging global health threat, resulting in significant morbidity and mortality worldwide. This study aims to determine the molecular characteristics and antimicrobial susceptibility of 263 MRSA isolates in Zhejiang Province, east China. METHODS: From 2014 to 2019, a total of 263 MRSA isolates from bloodstream infections (BSIs) were collected from 6 hospitals in 4 cities in Zhejiang province, east China. Antimicrobial susceptibility tests were conducted according to the guidelines set forth by the Clinical and Laboratory Standards Institute (CLSI). To characterize and analyze these isolates, multilocus sequence typing (MLST), staphylococcal cassette chromosome mec (SCCmec) typing, staphylococcal protein A (spa) typing and virulence genes gene profiles were performed. RESULTS: The most predominant clone was ST5-SCCmec II-t311, which accounted for 41.8% (110/263), followed by ST59 (44/263, 16.7%). Compared with non-ST5-II-t311 isolates, ST5-II-t311 isolates were more resistant to erythromycin, tetracycline, levofloxacin, moxifloxacin, and ciprofloxacin, but more susceptible to clindamycin. Moreover, the rates of multidrug resistance were higher in ST5-II-t311 isolates compared to the non-ST5-II-t311 isolates. In comparison to the non-ST5-II-t311 isolates, ST5-II-t311 isolates showed no significant difference in virulence genes detected. CONCLUSIONS: MRSA ST5-II-t311 clone has become the most predominant clone in Zhejiang Province, east China and has higher rates of multidrug resistance than other isolates, that should be kept in mind when treating BSI. Moreover, MRSA ST59 clone shows an upward trend and has begun to spread into hospitals. Our findings highlight the importance of epidemiological studies of S. aureus carriage in the eastern region.

Genetic diversity and phylogenetic relationships of Streptococcus thermophilus isolates from traditional Turkish yogurt: multilocus sequence typing (MLST).

Yogurt, a globally consumed fermented dairy product, is recognized for its taste and potential health benefits attributed to probiotic bacteria, particularly Streptococcus thermophilus. In this study, we employed Multilocus Sequence Typing (MLST) to investigate the genetic diversity and phylogenetic relationships of 13 S. thermophilus isolates from traditional Turkish yogurt samples. We also assessed potential correlations between genetic traits and geographic origins. The isolates were identified as S. thermophilus using VITEK® MALDI-TOF MS, ribotyping, and 16S rRNA analysis methods. MLST analysis revealed 13 different sequence types (STs), with seven new STs for Turkey. The most prevalent STs were ST/83 (n = 3), ST/135 (n = 2), and ST/134 (n = 2). eBURST analysis showed that these isolates mainly were singletons (n = 7) defined as sequence types (STs) that cannot be assigned to any group and differ at two or more alleles from every other ST in the sample. This information suggests that the isolates under study were genetically distinct from the other isolates in the dataset, highlighting their unique genetic profiles within the population. Genetic diversity analysis of ten housekeeping genes revealed polymorphism, with some genes showing higher allelic variation than others. Tajima's D values suggested that selection pressures differed among these genes, with some being more conserved, likely due to their vital functions. Phylogenetic analysis revealed distinct genetic diversity between Turkish isolates and European and Asian counterparts. These findings demonstrate the genetic diversity of S. thermophilus isolates in Turkish yogurt and highlight their unique evolutionary patterns. This research contributes to our understanding of local microbial diversity associated with yogurt production in Turkey and holds the potential for identifyic strains with enhanced functional attributes.

High performance Legionella pneumophila source attribution using genomics-based machine learning classification.

Fundamental to effective Legionnaires' disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionized pathogen surveillance, but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here, we present a powerful machine learning approach that assigns the geographical source of Legionnaires' disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires' disease outbreaks through detailed case investigations. Our classification models were developed in a cross-validation framework using only environmental L. pneumophila genomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534-genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance-agreement with epidemiological information. Our multivariate statistical learning approach maximizes the use of genomic variation data and is thus well-suited for supporting Legionnaires' disease outbreak investigations.IMPORTANCEIdentifying the sources of Legionnaires' disease outbreaks is crucial for effective control. Current genomic methods, while useful, often fall short due to the complex ecology and population structure of Legionella pneumophila, the causative agent. Our study introduces a high-performing machine learning approach for more accurate geographical source attribution of Legionnaires' disease outbreaks. Developed using cross-validation on environmental L. pneumophila genomes, our models demonstrate excellent predictive sensitivity and specificity. Importantly, this new approach outperforms traditional methods like phylogenomic trees and core genome multi-locus sequence typing, proving more efficient at leveraging genomic variation data to infer outbreak sources. Our machine learning algorithms, harnessing both core and accessory genomic variation, offer significant promise in public health settings. By enabling rapid and precise source identification in Legionnaires' disease outbreaks, such approaches have the potential to expedite intervention efforts and curtail disease transmission.

Multilocus sequence typing schemes for the emerging swine pathogen Mycoplasma hyosynoviae.

Mycoplasma (M.) hyosynoviae is a commensal of the upper respiratory tract in swine, which has the potential to spread systemically, usually resulting in arthritis in fattening pigs and gilts. To date, very little is known about the epidemiology of M. hyosynoviae, mainly due to a lack of suitable typing methods. Therefore, this study aimed to develop both a conventional multi locus sequence typing (MLST) and a core genome (cg) MLST scheme. The development of the cgMLST was based on whole genome sequences of 64 strains isolated from pigs and wild boars during routine diagnostics as well as nine publicly available genomes. A cgMLST scheme containing 390 target genes was established using the Ridom© SeqSphere+ software. Using this scheme as a foundation, seven housekeeping genes were selected for conventional MLST based on their capability to reflect genome wide relatedness and subsequently, all 73 strains were typed by applying both methods. Core genome MLST results revealed a high diversity of the studied strain population and less than 100 allele differences between epidemiologically unrelated strains were only detected for four isolates from the US. On the other hand, seven clonal clusters (≤ 12 allele differences) comprising 20 isolates were identified. Comparison of the two typing methods resulted in highly congruent phylogenetic trees and an Adjusted Rand Coefficient of 0.893, while cgMLST showed marginally higher resolution when comparing closely related isolates, indicated by a slightly higher Simpson's ID (0.992) than conventional MLST (Simpson's ID = 0.990). Overall, both methods seem well suited for epidemiological analyses for scientific as well as diagnostic purposes. While MLST is faster and cheaper, cgMLST can be used to further differentiate closely related isolates.

Antimicrobial susceptibilities and genomic characteristics of methicillin-resistant Staphylococcus aureus resistant to mupirocin in Stockholm, Sweden.

The aim of this study was to investigate antimicrobial susceptibilities and genomic characteristics of mupirocin-resistant MRSA isolates in Stockholm, Sweden. In total, 44 non-duplicate mupirocin-resistant MRSA isolates detected in Stockholm during 2010-2022 were investigated. Antimicrobial susceptibility testing was performed using broth microdilution method and further tested for high-level mupirocin-resistance (MuH) and rifampicin by Etest®. All isolates were subjected to whole genome sequencing. 41 isolates presented MuH with MICs ≥1024 mg/L whilst three isolates displayed low-level mupirocin resistance (MuL). mupA-gene was detected in all MuH isolates. Point mutations in ileS gene leading to N213D and V588F were identified in the three MuL isolates. Mutation in rpoB (H481N) was detected in a rifampicin-resistant isolate. Among the isolates, 15 multi-locus sequence types (MLST) were identified, with the four most common sequence types (ST22, ST72, ST8, and ST125) accounting for 66% of the isolates. Mupirocin-resistant MRSA in Stockholm was uncommon, with a percentage of <0.5% among MRSA cases during 2010-2022. In the present study, most mupirocin-resistant isolates were MuH and mupA-positive, predominantly linked to ST22 or ST72 isolates. MuL-resistance was associated with a point mutation in the IleS protein. A multidrug-resistant ST1-MRSA-IV strain was resistant to both mupirocin and rifampicin.

Performance evaluation of core genome multilocus sequence typing for genotyping of Mycobacterium tuberculosis strains in China: based on multicenter, population-based collection.

PURPOSE: To evaluate the performance of core genome multilocus sequence typing (cgMLST) for genotyping Mycobacterium tuberculosis (M.tuberculosis) Strains in regions where the lineage 2 strains predominate. METHODS: We compared clustering by whole-genome SNP typing with cgMLST clustering in the analysis of WGS data of 6240 strains from five regions of China. Using both the receiver operating characteristic (ROC) curve and epidemiological investigation to determine the optimal threshold for defining genomic clustering by cgMLST. The performance of cgMLST was evaluated by quantifying the sensitivity, specificity and concordance of clustering between two methods. Logistic regression was used to gauge the impact of strain genetic diversity and lineage on cgMLST clustering. RESULTS: The optimal threshold for cgMLST to define genomic clustering was determined to be ≤ 10 allelic differences between strains. The overall sensitivity and specificity of cgMLST averaged 99.6% and 96.3%, respectively; the concordance of clustering between two methods averaged 97.1%. Concordance was significantly correlated with strain genetic diversity and was 3.99 times (95% CI, 2.94-5.42) higher in regions with high genetic diversity (π > 1.55 × 10-4) compared to regions with low genetic diversity. The difference missed statistical significance, while concordance for lineage 2 strains (96.8%) was less than that for lineage 4 strains (98.3%). CONCLUSION : cgMLST showed a discriminatory power comparable to whole-genome SNP typing and could be used to genotype clinical M.tuberculosis strains in different regions of China. The discriminative power of cgMLST was significantly correlated with strain genetic diversity and was slightly lower with strains from regions with low genetic diversity.

Characterization of blaOXA-48-carrying plasmids and small non-AMR-coding plasmids collected from Ukrainian patients.

PURPOSE: Carbapenemase-producing Enterobacterales (CPE) pose a serious threat for healthcare facilities worldwide, yet the mode of transmission is often unclear. Recently, we recorded an increase of blaOXA-48-harboring isolates at our hospital associated with patients with previous medical treatment in the Ukraine. We used long-read whole genome sequencing (lrWGS) to characterize these isolates including their plasmids. METHODS: Samples were collected as part of clinical routine diagnostic or screening of multi-drug resistance bacteria (MDRB). Antimicrobial susceptibility testing was performed and all MDRB (n = 10) were sequenced by lrWGS for genotyping, identification of antimicrobial resistance (AMR) genes, and characterization of plasmids. RESULTS: While routine analysis of core genome multilocus sequence typing (cgMLST) did not show any genetic similarities between isolates, we found an unexpected high similarity in the plasmid diversity of different Enterobacterales in patients with previous medical treatment in the Ukraine. This included an IncL/M plasmid carrying blaOXA-48 and additional small non-AMR-coding plasmids. CONCLUSION: Our results show that lrWGS can be used in the routine setting to uncover similarities in plasmids and may give further information about potential epidemiologic associations. In the future, analysis of both AMR and non-AMR plasmids may provide an additional layer of information for molecular surveillance of CPE.

Prolonged carriage of OXA-244-carbapenemase-producing Escherichia coli complicates epidemiological investigations.

The rapid increase of OXA-244-producing Escherichia coli, predominantly driven by genetically clustered isolates of sequence type (ST)38, has been observed in at least nine European countries, including Germany. However, the reasons for the spread of OXA-244-producing E. coli remain unclear. Here, we aim to evaluate the possibility of prolonged carriage. We identified a total of six different patients with repeated detection of OXA-244-producing E. coli isolates, which were subjected to both short and long-read whole-genome sequencing (WGS). Besides allelic differences using core genome multilocus sequence typing (cgMLST) analyses, we obtained numbers of single-nucleotide polymorphisms (SNPs) to calculate individual base-pair substitution (BPS) rates. To assess possible re-exposure and risk factors for prolonged carriage, case interviews were conducted. The time between detections ranged from eleven months to more than three years. Initial isolates originated in three+ out of six cases from clinical samples, whereas remaining samples were from screening, mostly in the inpatient setting. As expected, cgMLST analyses showed low numbers of allelic differences between isolates of each case ranging from 1 to 4, whereas numbers of SNPs were between 2 and 99 (mean = 36), thus clearly highlighting the discrepancy between these different bacterial typing approaches. For five out of six cases, observed BPS rates suggest that patients can be colonized with OXA-244-producing E. coli, including ST38 cluster isolates, for extensively long times. Thus, we may have previously missed the epidemiological link between cases because exposure to OXA-244-producing E. coli could have occurred in a time frame, which has not been evaluated in previous investigations. Our results may help to guide future epidemiological investigations as well as to support the interpretation of genetic diversity of OXA-244-producing E. coli, particularly among ST38 cluster isolates.

Phylogeographic characterization of Burkholderia pseudomallei isolated from Bangladesh.

BACKGROUND: Burkholderia pseudomallei possesses a diverse set of genes which encode a vast array of biological functions reflecting its clinical, ecological and phenotypic diversity. Strain variation is linked to geographic location as well as pattern of land uses. This soil-dwelling Gram-negative pathogen causes melioidosis, a tropical disease endemic in northern Australia and Southeast Asian regions including Bangladesh. Phylogeographic analyses of B. pseudomallei isolates by molecular typing techniques could be used to examine the diversity of this organism as well as to track melioidosis epidemics. METHODS: In this study, 22 B. pseudomallei isolates, of which 20 clinical and two soil isolates were analyzed, utilizing Real-time PCR assay and multilocus sequence typing (MLST). The sequences were then submitted to PubMLST database for analysis and construction of phylogenetic tree. FINDINGS: A total of 12 different sequence types (STs) that includes four novel STs were identified for the first time. Strains having STs 1005, 1007 and 56 were the most widespread STs frequently isolated in Bangladesh. ST 1005, ST 56, ST 1007 and ST 211 have been detected not only in Bangladesh but are also present in many Southeast Asian countries. SIGNIFICANCE: ST 1005 was detected in both soil and clinical samples of Gazipur. Most prevalent, ST 56 has been previously reported from Myanmar, Thailand, Cambodia and Vietnam, confirming the persistence of the genotype over the entire continent. Further large-scale study is necessary to find out the magnitude of the infection and its different reservoirs in the environment along with phylogeographic association.

Molecular epidemiology and antimicrobial resistance patterns of carbapenem-resistant Acinetobacter baumannii isolates from patients admitted at ICUs of a teaching hospital in Zunyi, China.

Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a predominant strain of healthcare-associated infections worldwide, particularly in intensive care units (ICUs). Therefore, it is imperative to study the molecular epidemiology of CRAB in the ICUs using multiple molecular typing methods to lay the foundation for the development of infection prevention and control strategies. This study aimed to determine the antimicrobial susceptibility profile, the molecular epidemiology and conduct homology analysis on CRAB strains isolated from ICUs. Methods: The sensitivity to various antimicrobials was determined using the minimum inhibitory concentration (MIC) method, Kirby-Bauer disk diffusion (KBDD), and E-test assays. Resistance genes were identified by polymerase chain reaction (PCR). Molecular typing was performed using multilocus sequence typing (MLST) and multiple-locus variable-number tandem repeat analysis (MLVA). Results: Among the 79 isolates collected, they exhibited high resistance to various antimicrobials but showed low resistance to levofloxacin, trimethoprim-sulfamethoxazole, and tetracyclines. Notably, all isolates of A. baumannii were identified as multidrug-resistant A. baumannii (MDR-AB). The bla OXA-51-like, adeJ, and adeG genes were all detected, while the detection rates of bla OXA-23-like (97.5%), adeB (93.67%), bla ADC (93.67%), qacEΔ1-sul1 (84.81%) were higher; most of the Ambler class A and class B genes were not detected. MLST analysis on the 79 isolates identified five sequence types (STs), which belonged to group 3 clonal complexes 369. ST1145Ox was the most frequently observed ST with a count of 56 out of 79 isolates (70.89%). MLST analysis for non-sensitive tigecycline isolates, which were revealed ST1145Ox and ST1417Ox as well. By using the MLVA assay, the 79 isolates could be grouped into a total of 64 distinct MTs with eleven clusters identified in them. Minimum spanning tree analysis defined seven different MLVA complexes (MCs) labeled MC1 to MC6 along with twenty singletons. The locus MLVA-AB_2396 demonstrated the highest Simpson's diversity index value at 0.829 among all loci tested in this study while also having one of the highest variety of tandem repeat species. Conclusion: The molecular diversity and clonal affinities within the genomes of the CRAB strains were clearly evident, with the identification of ST1144Ox, ST1658Ox, and ST1646Oxqaq representing novel findings.

Introduction and benchmarking of pyMLST: open-source software for assessing bacterial clonality using core genome MLST.

Core genome multilocus sequence typing (cgMLST) has gained in popularity for bacterial typing since whole-genome sequencing (WGS) has become affordable. We introduce here pyMLST, a new complete, stand-alone, free and open source pipeline for cgMLST analysis. pyMLST can create or import a core genome database. For each gene, the first allele is aligned against the bacterial genome of interest using BLAT. Incomplete genes are aligned using MAFT. All data are stored in a SQLite database. pyMLST accepts assembly genomes or raw data (with the option pyMLST-KMA) as input. To evaluate our new tool, we selected three genome collections of major bacterial pathogens (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) and compared them with pyMLST, pyMLST-KMA, ChewBBACA, SeqSphere and the variant calling approach. We compared the sensitivity, precision and false-positive rate for each method with those of the variant calling approach. Minimal spanning trees were generated with each type of software to evaluate their interest in the context of a bacterial outbreak. We found that pyMLST-KMA is a convenient screening method to avoid assembling large bacterial collections. Our data showed that pyMLST (free, open source, available in Galaxy and pipeline ready) performed similarly to the commercial SeqSphere and performed better than ChewBBACA and pyMLST-KMA.

The emergence of Klebsiella pneumoniae sequence type 395 non-susceptible to carbapenems and colistin from Turkey.

PURPOSE: OXA-48 producing Klebsiella pneumoniae is an emerging threat and outbreaks due to specific sequence types have been commonly reported. Here, we report an outbreak due to multidrug-resistant ST395 K. pneumoniae ST395. To the best of our knowledge, this is the first outbreak of K. pneumoniae ST395 harbouring blaOXA-48 genes in our country. METHODS: The strains were characterized by antimicrobial susceptibility, extended-spectrum ß-lactamase (ESBL) and carbapenemase production, plasmid-mediated colistin, high-level aminoglycoside, and quinolone resistance. Also multidrug efflux pumps and porin coding genes were investigated. Pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), wzi typing and plasmid analysis were used for the epidemiological relationships. RESULTS: All strains were positive for blaOXA-48 with at least one of the ß-lactamase genes (blaCTX-M, blaTEM, blaSHV) and harboured IncL plasmids. 16 of 20 (80%) isolates carried qnrA. All isolates were positive for aac(6')-1b, acrAB-tolC, ompK35, and ompK36 genes but none of them harboured 16s rRNA methyltransferase, mcr-1-5, qepA, oqxAB, and mdtK genes. All strains had the same PFGE pattern, that is, wzi type K2 and found to be ST395 with MLST. CONCLUSION: The association of ST395 with OXA-48-producers could be an emerging threat for Turkey and continuous monitoring is crucial to prevent the spread of these powerful strains.