Expansion and transmission dynamics of high risk carbapenem-resistant Klebsiella pneumoniae subclones in China: An epidemiological, spatial, genomic analysis.

AIMS: Carbapenem-resistant Klebsiella pneumonia (CRKP) is a global threat that varies by region. The global distribution, evolution, and clinical implications of the ST11 CRKP clone remain obscure. METHODS: We conducted a multicenter molecular epidemiological survey using isolates obtained from 28 provinces and municipalities across China between 2011 and 2021. We integrated sequences from public databases and performed genetic epidemiology analysis of ST11 CRKP. RESULTS: Among ST11 CRKP, KL64 serotypes exhibited considerable expansion, increasing from 1.54% to 46.08% between 2011 and 2021. Combining our data with public databases, the phylogenetic and phylogeography analyses indicated that ST11 CRKP appeared in the Americas in 1996 and spread worldwide, with key clones progressing from China's southeastern coast to the inland by 2010. Global phylogenetic analysis showed that ST11 KL64 CRKP has evolved to a virulent, resistant clade with notable regional spread. Single-nucleotide polymorphism (SNP) analysis identified BMPPS (bmr3, mltC, pyrB, ppsC, and sdaC) as a key marker for this clade. The BMPPS SNP clade is associated with high mortality and has strong anti-phagocytic and competitive traits in vitro. CONCLUSIONS: The high-risk ST11 KL64 CRKP subclone showed strong expansion potential and survival advantages, probably owing to genetic factors.

Genomic Epidemiology of Large Blastomycosis Outbreak, Ontario, Canada, 2021.

Using phylogenomic analysis, we provide genomic epidemiology analysis of a large blastomycosis outbreak in Ontario, Canada, caused by Blastomyces gilchristii. The outbreak occurred in a locale where blastomycosis is rarely diagnosed, signaling a possible shift in geographically associated incidence patterns. Results elucidated fungal population genetic structure, enhancing understanding of the outbreak.

Molecular Epidemiology of Mayaro Virus among Febrile Patients, Roraima State, Brazil, 2018-2021.

We detected Mayaro virus (MAYV) in 3.4% (28/822) of febrile patients tested during 2018-2021 from Roraima State, Brazil. We also isolated MAYV strains and confirmed that these cases were caused by genotype D. Improved surveillance is needed to better determine the burden of MAYV in the Amazon Region.

Molecular Epidemiology of Western Equine Encephalitis Virus, South America, 2023-2024.

Western equine encephalitis virus (WEEV) is a mosquitoborne virus that reemerged in December 2023 in Argentina and Uruguay, causing a major outbreak. We investigated the outbreak using epidemiologic, entomological, and genomic analyses, focusing on WEEV circulation near the Argentina‒Uruguay border in Rio Grande do Sul state, Brazil. During November 2023‒April 2024, the outbreak in Argentina and Uruguay resulted in 217 human cases, 12 of which were fatal, and 2,548 equine cases. We determined cases on the basis of laboratory and clinical epidemiologic criteria. We characterized 3 fatal equine cases caused by a novel WEEV lineage identified through a nearly complete coding sequence analysis, which we propose as lineage C. Our findings highlight the importance of continued surveillance and equine vaccination to control future WEEV outbreaks in South America.

Molecular Epidemiology of Underreported Emerging Zoonotic Pathogen Streptococcus suis in Europe.

Streptococcus suis, a zoonotic bacterial pathogen circulated through swine, can cause severe infections in humans. Because human S. suis infections are not notifiable in most countries, incidence is underestimated. We aimed to increase insight into the molecular epidemiology of human S. suis infections in Europe. To procure data, we surveyed 7 reference laboratories and performed a systematic review of the scientific literature. We identified 236 cases of human S. suis infection from those sources and an additional 87 by scanning gray literature. We performed whole-genome sequencing to type 46 zoonotic S. suis isolates and combined them with 28 publicly available genomes in a core-genome phylogeny. Clonal complex (CC) 1 isolates accounted for 87% of typed human infections; CC20, CC25, CC87, and CC94 also caused infections. Emergence of diverse zoonotic clades and notable severity of illness in humans support classifying S. suis infection as a notifiable condition.

Regional spread of an atypical ESBL-producing Escherichia coli ST131H89 clone among different human and environmental reservoirs in Western Switzerland.

We describe the inter-regional spread of a novel ESBL-producing Escherichia coli subclone (ST131H89) in long-term care facility residents, general population, and environmental water sources in Western Switzerland between 2017 and 2020. The study highlights the importance of molecular surveillance for tracking emerging antibiotic-resistant pathogens in healthcare and community settings.

Whole-genome analysis of human group A rotaviruses in 1980s Japan and evolutionary assessment of global Wa-like strains across half a century.

Historically, the Wa-like strains of human group A rotavirus (RVA) have been major causes of gastroenteritis. However, since the 2010s, the circulation of non-Wa-like strains has been increasingly reported, indicating a shift in the molecular epidemiology of RVA. Although understanding RVA evolution requires the analysis of both current and historical strains, comprehensive pre-1980's sequencing data are scarce globally. We determined the whole-genome sequences of representative strains from six RVA gastroenteritis outbreaks observed at an infant home in Sapporo, Japan, between 1981 and 1989. These outbreaks were mainly caused by G1 or G3 Wa-like strains, resembling strains from the United States in the 1970s-1980s and from Malawi in the 1990s. Phylogenetic analysis of these infant home strains, together with Wa-like strains collected worldwide from the 1970s to 2020, revealed a notable trend: pre-2010 strains diverged into multiple lineages in many genomic segments, whereas post-2010 strains tended to converge into a single lineage. However, Bayesian skyline plot indicated near-constant effective population sizes from the 1970s to 2020, and selection pressure analysis identified positive selection only at amino acid 75 of NSP2. These results suggest that evidence supporting the influence of rotavirus vaccines, introduced globally since 2006, on Wa-like RVA molecular evolution is lacking at present, and phylogenetic analysis may simply reflect natural fluctuations in RVA molecular evolution. Evaluating the long-term impact of RV vaccines on the molecular evolution of RVA requires sustained surveillance.

Single-tube protocol for culture-independent spoligotyping of Mycobacterium tuberculosis based on MeltArray.

IMPORTANCE: Spacer oligonucleotide typing (spoligotyping), the first-line genotyping assay for Mycobacterium tuberculosis (MTB), plays a fundamental role in the investigation of its epidemiology and evolution. In this study, we established a single-tube spoligotyping assay using MeltArray, a highly multiplex polymerase chain reaction (PCR) approach that runs on a real-time PCR thermocycler. The MeltArray protocol included an internal positive control, gyrB, to indicate the abundance of MTB via the quantification cycle and 43 spacers to identify the spoligotype via melting curve analysis. The entire protocol was completed in a single step within 2.5 hours. The lowest detectable copy number for the tested strains was 20 copies/reaction and thus sufficient for analyzing both culture and sputum samples. We conclude that MeltArray-based spoligotyping could be used immediately in low- and middle-income countries with a high tuberculosis burden, given its easy access, improved throughput, and potential applicability to clinical samples.

Genomic evolution of ST228 SCCmec-I MRSA 10 years after a major nosocomial outbreak.

In this study, we investigated the genomic changes in a major methicillin-resistant Staphylococcus aureus (MRSA) clone following a significant outbreak at a hospital. Whole-genome sequencing of MRSA isolates was utilized to explore the genomic evolution of post-outbreak MRSA strains. The epidemicity of the clone declined over time, coinciding with the introduction of multimodal infection control measures. A genome-wide association study (GWAS) identified multiple genes significantly associated with either high or low epidemic success, indicating alterations in mobilome, virulence, and defense mechanisms. Random Forest models pinpointed a gene related to fibrinogen binding as the most influential predictor of epidemicity. The decline of the MRSA clone may be attributed to various factors, including the implementation of new infection control measures, single nucleotide polymorphisms accumulation, and the genetic drift of a given clone. This research underscores the complex dynamics of MRSA clones, emphasizing the multifactorial nature of their evolution. The decline in epidemicity seems linked to alterations in the clone's genetic profile, with a probable shift towards decreased virulence and adaptation to long-term carriage. Understanding the genomic basis for the decline of epidemic clones is crucial to develop effective strategies for their surveillance and management, as well as to gain insights into the evolutionary dynamics of pathogen genomes.

Development and implementation of a core genome multilocus sequence typing scheme for Yersinia enterocolitica: a tool for surveillance and outbreak detection.

Yersinia enterocolitica (Y. enterocolitica) is the most frequent etiological agent of yersiniosis and has been responsible for several national outbreaks in Norway and elsewhere. A standardized high-resolution method, such as core genome Multilocus Sequence Typing (cgMLST), is needed for pathogen traceability at the national and international levels. In this study, we developed and implemented a cgMLST scheme for Y. enterocolitica. We designed a cgMLST scheme in SeqSphere + using high-quality genomes from different Y. enterocolitica biotype sublineages. The scheme was validated if more than 95% of targets were found across all tested Y. enterocolitica: 563 Norwegian genomes collected between 2012 and 2022 and 327 genomes from public data sets. We applied the scheme to known outbreaks to establish a threshold for identifying major complex types (CTs) based on the number of allelic differences. The final cgMLST scheme included 2,582 genes with a median of 97.9% (interquartile range 97.6%-98.8%) targets found across all tested genomes. Analysis of outbreaks identified all outbreak strains using single linkage clustering at four allelic differences. This threshold identified 311 unique CTs in Norway, of which CT18, CT12, and CT5 were identified as the most frequently associated with outbreaks. The cgMLST scheme showed a very good performance in typing Y. enterocolitica using diverse data sources and was able to identify outbreak clusters. We recommend the implementation of this scheme nationally and internationally to facilitate Y. enterocolitica surveillance and improve outbreak response in national and cross-border outbreaks.

Genomic diversity and antimicrobial resistance in clinical Klebsiella pneumoniae isolates from tertiary hospitals in Southern Ghana.

OBJECTIVES: Comprehensive data on the genomic epidemiology of hospital-associated Klebsiella pneumoniae in Ghana are scarce. This study investigated the genomic diversity, antimicrobial resistance patterns, and clonal relationships of 103 clinical K. pneumoniae isolates from five tertiary hospitals in Southern Ghana-predominantly from paediatric patients aged under 5 years (67/103; 65%), with the majority collected from urine (32/103; 31%) and blood (25/103; 24%) cultures. METHODS: We generated hybrid Nanopore-Illumina assemblies and employed Pathogenwatch for genotyping via Kaptive [capsular (K) locus and lipopolysaccharide (O) antigens] and Kleborate (antimicrobial resistance and hypervirulence) and determined clonal relationships using core-genome MLST (cgMLST). RESULTS: Of 44 distinct STs detected, ST133 was the most common, comprising 23% of isolates (n = 23/103). KL116 (28/103; 27%) and O1 (66/103; 64%) were the most prevalent K-locus and O-antigen types. Single-linkage clustering highlighted the global spread of MDR clones such as ST15, ST307, ST17, ST11, ST101 and ST48, with minimal allele differences (1-5) from publicly available genomes worldwide. Conversely, 17 isolates constituted novel clonal groups and lacked close relatives among publicly available genomes, displaying unique genetic diversity within our study population. A significant proportion of isolates (88/103; 85%) carried resistance genes for ≥3 antibiotic classes, with the blaCTX-M-15 gene present in 78% (n = 80/103). Carbapenem resistance, predominantly due to blaOXA-181 and blaNDM-1 genes, was found in 10% (n = 10/103) of the isolates. CONCLUSIONS: Our findings reveal a complex genomic landscape of K. pneumoniae in Southern Ghana, underscoring the critical need for ongoing genomic surveillance to manage the substantial burden of antimicrobial resistance.

Recent dynamics in Neisseria gonorrhoeae genomic epidemiology in Brazil: antimicrobial resistance and genomic lineages in 2017-20 compared to 2015-16.

OBJECTIVES: Regular quality-assured WGS with antimicrobial resistance (AMR) and epidemiological data of patients is imperative to elucidate the shifting gonorrhoea epidemiology, nationally and internationally. We describe the dynamics of the gonococcal population in 11 cities in Brazil between 2017 and 2020 and elucidate emerging and disappearing gonococcal lineages associated with AMR, compare to Brazilian WGS and AMR data from 2015 to 2016, and explain recent changes in gonococcal AMR and gonorrhoea epidemiology. METHODS: WGS was performed using Illumina NextSeq 550 and genomes of 623 gonococcal isolates were used for downstream analysis. Molecular typing and AMR determinants were obtained and links between genomic lineages and AMR (determined by agar dilution/Etest) examined. RESULTS: Azithromycin resistance (15.6%, 97/623) had substantially increased and was mainly explained by clonal expansions of strains with 23S rRNA C2611T (mostly NG-STAR CC124) and mtr mosaics (mostly NG-STAR CC63, MLST ST9363). Resistance to ceftriaxone and cefixime remained at the same levels as in 2015-16, i.e. at 0% and 0.2% (1/623), respectively. Regarding novel gonorrhoea treatments, no known zoliflodacin-resistance gyrB mutations or gepotidacin-resistance gyrA mutations were found. Genomic lineages and sublineages showed a phylogenomic shift from sublineage A5 to sublineages A1-A4, while isolates within lineage B remained diverse in Brazil. CONCLUSIONS: Azithromycin resistance, mainly caused by 23S rRNA C2611T and mtrD mosaics/semi-mosaics, had substantially increased in Brazil. This mostly low-level azithromycin resistance may threaten the recommended ceftriaxone-azithromycin therapy, but the lack of ceftriaxone resistance is encouraging. Enhanced gonococcal AMR surveillance, including WGS, is imperative in Brazil and other Latin American and Caribbean countries.

Clinical characteristics and genome epidemiology of Stenotrophomonas maltophilia in Japan.

BACKGROUND: Stenotrophomonas maltophilia is a carbapenem-resistant Gram-negative pathogen increasingly responsible for difficult-to-treat nosocomial infections. OBJECTIVES: To describe the contemporary clinical characteristics and genome epidemiology of patients colonized or infected by S. maltophilia in a multicentre, prospective cohort. METHODS: All patients with a clinical culture growing S. maltophilia were enrolled at six tertiary hospitals across Japan between April 2019 and March 2022. The clinical characteristics, outcomes, antimicrobial susceptibility and genomic epidemiology of cases with S. maltophilia were investigated. RESULTS: In total, 78 patients were included representing 34 infection and 44 colonization cases. The median age was 72.5 years (IQR, 61-78), and males accounted for 53 cases (68%). The most common comorbidity was localized solid malignancy (39%). Nearly half of the patients (44%) were immunosuppressed, with antineoplastic chemotherapy accounting for 31%. The respiratory tract was the most common site of colonization (86%), whereas bacteraemia accounted for most infection cases (56%). The 30 day all-cause mortality rate was 21%, which was significantly higher in infection cases than colonization cases (35% versus 9%; adjusted HR, 3.81; 95% CI, 1.22-11.96). Susceptibility rates to ceftazidime, levofloxacin, minocycline and sulfamethoxazole/trimethoprim were 14%, 65%, 87% and 100%, respectively. The percentage of infection ranged from 13% in the unclassified group to 86% in genomic group 6A. The percentage of non-susceptibility to ceftazidime ranged from 33% in genomic group C to 100% in genomic groups 6 and 7 and genomic group geniculate. CONCLUSIONS: In this contemporary multicentre cohort, S. maltophilia primarily colonized the respiratory tract, whereas patients with bacteraemia had the highest the mortality from this pathogen. Sulfamethoxazole/trimethoprim remained consistently active, but susceptibility to levofloxacin was relatively low. The proportions of cases representing infection and susceptibility to ceftazidime differed significantly based on genomic groups.

Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges.

Multi-omics approaches have been successfully applied to investigate pregnancy and health outcomes at a molecular and genetic level in several studies. As omics technologies advance, research areas are open to study further. Here we discuss overall trends and examples of successfully using omics technologies and techniques (e.g., genomics, proteomics, metabolomics, and metagenomics) to investigate the molecular epidemiology of pregnancy. In addition, we outline omics applications and study characteristics of pregnancy for understanding fundamental biology, causal health, and physiological relationships, risk and prediction modeling, diagnostics, and correlations.

Developing a next level integrated genomic surveillance: Advances in the molecular epidemiology of HIV in Germany.

Advances in the molecular epidemiological studies of the Human Immunodeficiency Virus (HIV) at the Robert Koch Institute (RKI) by laboratory and bioinformatic automation should allow the processing of larger numbers of samples and more comprehensive and faster data analysis in order to provide a higher resolution of the current HIV infection situation in near real-time and a better understanding of the dynamic of the German HIV epidemic. The early detection of the emergence and transmission of new HIV variants is important for the adaption of diagnostics and treatment guidelines. Likewise, the molecular epidemiological detection and characterization of spatially limited HIV outbreaks or rapidly growing sub-epidemics is of great importance in order to interrupt the transmission pathways by regionally adapting prevention strategies. These aims are becoming even more important in the context of the SARS-CoV2 pandemic and the Ukrainian refugee movement, which both have effects on the German HIV epidemic that should be monitored to identify starting points for targeted public health measures in a timely manner. To this end, a next level integrated genomic surveillance of HIV is to be established.

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.

Molecular epidemiology of Mycoplasma pneumoniae pneumonia in children, Wuhan, 2020-2022.

BACKGROUND: Mycoplasma pneumoniae (M. pneumoniae) is an important pathogen of community-acquired pneumonia in children. The factors contributing to the severity of illness caused by M. pneumoniae infection are still under investigation. We aimed to evaluate the sensitivity of common M. pneumoniae detection methods, as well as to analyze the clinical manifestations, genotypes, macrolide resistance, respiratory microenvironment, and their relationship with the severity of illness in children with M. pneumoniae pneumonia in Wuhan. RESULTS: Among 1,259 clinical samples, 461 samples were positive for M. pneumoniae via quantitative polymerase chain reaction (qPCR). Furthermore, we found that while serological testing is not highly sensitive in detecting M. pneumoniae infection, but it may serve as an indicator for predicting severe cases. We successfully identified the adhesin P1 (P1) genotypes of 127 samples based on metagenomic and Sanger sequencing, with P1-type 1 (113/127, 88.98%) being the dominant genotype. No significant difference in pathogenicity was observed among different genotypes. The macrolide resistance rate of M. pneumoniae isolates was 96% (48/50) and all mutations were A2063G in domain V of 23S rRNA gene. There was no significant difference between the upper respiratory microbiome of patients with mild and severe symptoms. CONCLUSIONS: During the period of this study, the main circulating M. pneumoniae was P1-type 1, with a resistance rate of 96%. Key findings include the efficacy of qPCR in detecting M. pneumoniae, the potential of IgM titers exceeding 1:160 as indicators for illness severity, and the lack of a direct correlation between disease severity and genotypic characteristics or respiratory microenvironment. This study is the first to characterize the epidemic and genomic features of M. pneumoniae in Wuhan after the COVID-19 outbreak in 2020, which provides a scientific data basis for monitoring and infection prevention and control of M. pneumoniae in the post-pandemic era.

Molecular characterization and epidemiological investigation of colistin resistance in carbapenem-resistant Klebsiella pneumoniae in a tertiary care hospital in Tehran, Iran.

BACKGROUND: Carbapenemase-producing Klebsiella pneumoniae (CRKP) presents a significant challenge to antimicrobial therapy, especially when compounded by resistance to colistin. The objective of this study was to explore molecular epidemiological insights into strains of clinical K. pneumoniae that produce carbapenemases and exhibit resistance to colistin. Eighty clinical isolates of CRKP were obtained from Milad Hospital in Tehran, Iran. Antimicrobial susceptibility and colistin broth disk elution were determined. PCR assays were conducted to examine the prevalence of resistance-associated genes, including blaKPC, blaIMP, blaVIM, blaOXA-48, blaNDM and mcr-1 to -10. Molecular typing (PFGE) was used to assess their spread. RESULTS: Colistin resistance was observed in 27 isolates (33.7%) using the Broth Disk Elution method. Among positive isolates for carbapenemase genes, the most frequent gene was blaOXA-48, identified in 36 strains (45%). The mcr-1 gene was detected in 3.7% of the obtained isolates, with none of the other of the other mcr genes detected in the studied isolates. CONCLUSION: To stop the spread of resistant K. pneumoniae and prevent the evolution of mcr genes, it is imperative to enhance surveillance, adhere rigorously to infection prevention protocols, and implement antibiotic stewardship practices.

The origin and spread of HIV-1 CRF59_01B epidemic in China: A molecular network and phylogeographic analysis.

Human immunodeficiency virus type 1 CRF59_01B, identified in China in 2013, has been detected nationwide, exhibiting notably high prevalence in Guangzhou and its vicinity. This study aimed to unravel its origin and migration. A data set was established, incorporating all available CRF59_01B pol gene sequences and their metadata from Guangzhou and the public database. Bayesian phylogeographic analysis demonstrated that CRF59_01B originated in Shenzhen, the neighboring city of Guangzhou, around 1998 with posterior probability of 0.937. Molecular network analysis detected 1131 transmission links and showed a remarkably high clustering rate (78.9%). Substantial inter-city transmissions (26.5%, 300/1131) were observed between Shenzhen and Guangzhou while inter-region transmissions linked Guangzhou with South (46) and Southwest (64) China. The centre of Guangzhou was the hub of CRF59_01B transmission, including the inflow from Shenzhen (3.57 events/year) and outflow to the outskirts of Guangzhou (>2 events/year). The large-scale analysis revealed significant migration from Shenzhen to Guangzhou (5.08 events/year) and North China (0.59 events/year), and spread from Guangzhou to Central (0.47 events/year), East (0.42 events/year), South (0.76 events/year), Southwest China (0.76 events/year) and Shenzhen (1.89 events/year). Shenzhen and Guangzhou served as the origin and the hub of CRF59_01B circulation, emphasizing inter-city cooperation and data sharing to confine its nationwide diffusion.

Molecular epidemiology of human herpesvirus 8 in patients with HHV-8-related diseases in Ireland.

Human Herpesvirus 8 (HHV-8) has been classified by sequence analysis of open reading frame (ORF) K1, ORF K15, and variable sequence loci within the central constant region. The purpose of this study was to examine the molecular epidemiology of HHV-8 in an Irish population. This retrospective study included 30 patients who had HHV-8 DNA detected in plasma. Nested end-point PCR was used to characterise four regions of the HHV-8 genome, K1, T0.7 (K12), ORF 75, and K15. Sequencing data were obtained for 23 specimens from 19 patients. Phylogenetic analysis of ORF K1 demonstrated that subtypes A, B, C and F were present in 37%, 11%, 47% and 5%, respectively. For T0.7 and ORF 75, sequencing data were obtained for 12 patients. For T0.7, subtypes A/C, J, B, R and Q were present in 58%, 17%, 8%, 8%, and 8%, respectively. For ORF 75, subtypes A, B, C and D were present in 58%, 8%, 25%, and 8%, respectively. K15 sequences were determined for 13 patients. 69% had the P allele and 31% had the M allele. The data generated by this study demonstrate that a broad variety of HHV-8 subtypes are represented in patients exhibiting HHV-8-related disease in Ireland, a low prevalence country. The predominance of C and A K1 subtypes was as expected for a Western European population. The 31% prevalence for K15 subtype M was higher than expected for a Western European population. This may represent the changing and evolving epidemiology in Ireland due to altered migration patterns.