Transmission from vaccinated individuals in a large SARS-CoV-2 Delta variant outbreak.

An outbreak of over 1,000 COVID-19 cases in Provincetown, Massachusetts (MA), in July 2021-the first large outbreak mostly in vaccinated individuals in the US-prompted a comprehensive public health response, motivating changes to national masking recommendations and raising questions about infection and transmission among vaccinated individuals. To address these questions, we combined viral genomic and epidemiological data from 467 individuals, including 40% of outbreak-associated cases. The Delta variant accounted for 99% of cases in this dataset; it was introduced from at least 40 sources, but 83% of cases derived from a single source, likely through transmission across multiple settings over a short time rather than a single event. Genomic and epidemiological data supported multiple transmissions of Delta from and between fully vaccinated individuals. However, despite its magnitude, the outbreak had limited onward impact in MA and the US overall, likely due to high vaccination rates and a robust public health response.

The human genetic epidemiology of COVID-19.

Human genetics can inform the biology and epidemiology of coronavirus disease 2019 (COVID-19) by pinpointing causal mechanisms that explain why some individuals become more severely affected by the disease upon infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Large-scale genetic association studies, encompassing both rare and common genetic variants, have used different study designs and multiple disease phenotype definitions to identify several genomic regions associated with COVID-19. Along with a multitude of follow-up studies, these findings have increased our understanding of disease aetiology and provided routes for management of COVID-19. Important emergent opportunities include the clinical translatability of genetic risk prediction, the repurposing of existing drugs, exploration of variable host effects of different viral strains, study of inter-individual variability in vaccination response and understanding the long-term consequences of SARS-CoV-2 infection. Beyond the current pandemic, these transferrable opportunities are likely to affect the study of many infectious diseases.

The emergence, genomic diversity and global spread of SARS-CoV-2.

Since the first cases of COVID-19 were documented in Wuhan, China in 2019, the world has witnessed a devastating global pandemic, with more than 238 million cases, nearly 5 million fatalities and the daily number of people infected increasing rapidly. Here we describe the currently available data on the emergence of the SARS-CoV-2 virus, the causative agent of COVID-19, outline the early viral spread in Wuhan and its transmission patterns in China and across the rest of the world, and highlight how genomic surveillance, together with other data such as those on human mobility, has helped to trace the spread and genetic variation of the virus and has also comprised a key element for the control of the pandemic. We pay particular attention to characterizing and describing the international spread of the major variants of concern of SARS-CoV-2 that were first identified in late 2020 and demonstrate that virus evolution has entered a new phase. More broadly, we highlight our currently limited understanding of coronavirus diversity in nature, the rapid spread of the virus and its variants in such an increasingly connected world, the reduced protection of vaccines, and the urgent need for coordinated global surveillance using genomic techniques. In summary, we provide important information for the prevention and control of both the ongoing COVID-19 pandemic and any new diseases that will inevitably emerge in the human population in future generations.

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.

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.

Genetic epidemiology of blood type, disease and trait variants, and genome-wide genetic diversity in over 11,000 domestic cats.

In the largest DNA-based study of domestic cats to date, 11,036 individuals (10,419 pedigreed cats and 617 non-pedigreed cats) were genotyped via commercial panel testing elucidating the distribution and frequency of known disease, blood type, and physical trait associated genetic variants across cat breeds. This study provides allele frequencies for many disease-associated variants for the first time and provides updates on previously reported information with evidence suggesting that DNA testing has been effectively used to reduce disease associated variants within certain pedigreed cat populations over time. We identified 13 disease-associated variants in 47 breeds or breed types in which the variant had not previously been documented, highlighting the relevance of comprehensive genetic screening across breeds. Three disease-associated variants were discovered in non-pedigreed cats only. To investigate the causality of nine disease-associated variants in cats of different breed backgrounds our veterinarians conducted owner interviews, reviewed clinical records, and invited cats to have follow-up clinical examinations. Additionally, genetic variants determining blood types A, B and AB, which are relevant clinically and in cat breeding, were genotyped. Appearance-associated genetic variation in all cats is also discussed. Lastly, genome-wide SNP heterozygosity levels were calculated to obtain a comparable measure of the genetic diversity in different cat breeds. This study represents the first comprehensive exploration of informative Mendelian variants in felines by screening over 10,000 pedigreed cats. The results qualitatively contribute to the understanding of feline variant heritage and genetic diversity and demonstrate the clinical utility and importance of such information in supporting breeding programs and the research community. The work also highlights the crucial commitment of pedigreed cat breeders and registries in supporting the establishment of large genomic databases, that when combined with phenotype information can advance scientific understanding and provide insights that can be applied to improve the health and welfare of cats.

A Brief History behind the journal Genetic Epidemiology and the International Genetic Epidemiology Society.

This commentary briefly describes the process and steps that underlie the launching of the journal Genetic Epidemiology in 1984 and the International Genetic Epidemiology Society (IGES, to be pronounced as "I guess") in 1992.

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.

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.

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 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.

Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2.

Genomic epidemiology is important to study the COVID-19 pandemic, and more than two million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a node-picking rendering strategy. In total, 1,002,739 high-quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, highly efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and ongoing positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB was written in Java and JavaScript. It not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2.

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.