After the initial coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China, the outbreaks during the dynamic-zero policy period in the mainland of China have not been systematically documented.

Recent viral hemorrhagic fever (VHF) disease outbreaks caused by Ebola virus (EBOV) and Marburg virus (MARV) in West Africa are unique and alarming. The intents of this editorial are to highlight what is known about these viruses and the disease outbreaks that they cause in the African continent and elsewhere and to raise awareness of a related virus called Lassa virus (LASV) that causes endemic viral hemorrhagic fever infections and frequent outbreaks in West Africa.

Outbreaks of emerging infectious diseases pose a serious threat to public health security, human health and economic development. After an outbreak, an animal model for an emerging infectious disease is urgently needed for studying the etiology, host immune mechanisms and pathology of the disease, evaluating the efficiency of vaccines or drugs against infection, and minimizing the time available for animal model development, which is usually hindered by the nonsusceptibility of common laboratory animals to human pathogens. Thus, we summarize the technologies and methods that induce animal susceptibility to human pathogens, which include viral receptor humanization, pathogen-targeted tissue humanization, immunodeficiency induction and screening for naturally susceptible animal species. Furthermore, the advantages and deficiencies of animal models developed using each method were analyzed, and these will guide the selection of susceptible animals and potentially reduce the time needed to develop animal models during epidemics.

The Pacific oyster (PO), Crassostrea gigas, is an important commercial marine species but periodically experiences large stock losses due to disease events known as summer mortality. Summer mortality has been linked to environmental perturbations and numerous viral and bacterial agents, indicating this disease is multifactorial in nature. In 2013 and 2014, several summer mortality events occurred within the Port Stephens estuary (NSW, Australia). Extensive culture and molecular-based investigations were undertaken and several potentially pathogenic Vibrio species were identified. To improve species identification and genomically characterise isolates obtained from this outbreak, whole-genome sequencing (WGS) and subsequent genomic analyses were performed on 48 bacterial isolates, as well as a further nine isolates from other summer mortality studies using the same batch of juveniles. Average nucleotide identity (ANI) identified most isolates to the species level and included members of the Photobacterium, Pseudoalteromonas, Shewanella and Vibrio genera, with Vibrio species making up more than two-thirds of all species identified. Construction of a phylogenomic tree, ANI analysis, and pan-genome analysis of the 57 isolates represents the most comprehensive culture-based phylogenomic survey of Vibrios during a PO summer mortality event in Australian waters and revealed large genomic diversity in many of the identified species. Our analysis revealed limited and inconsistent associations between isolate species and their geographical origins, or host health status. Together with ANI and pan-genome results, these inconsistencies suggest that to determine the role that microbes may have in Pacific oyster summer mortality events, isolate identification must be at the taxonomic level of strain. Our WGS data (specifically, the accessory genomes) differentiated bacterial strains, and coupled with associated metadata, highlight the possibility of predicting a strain's environmental niche and level of pathogenicity.

The increase of Vancomycin-resistant Enterococcus faecium (VREfm) in recent years has been partially attributed to the rise of specific clonal lineages, which have been identified throughout Germany. To date, there is no gold standard for the interpretation of genomic data for outbreak analyses. New genomic approaches such as split k-mer analysis (SKA) could support cluster attribution for routine outbreak investigation. The aim of this project was to investigate frequent clonal lineages of VREfm identified during suspected outbreaks across different hospitals, and to compare genomic approaches including SKA in routine outbreak investigation. We used routine outbreak laboratory data from seven hospitals and three different hospital networks in Berlin, Germany. Short-read libraries were sequenced on the Illumina MiSeq system. We determined clusters using the published Enterococcus faecium-cgMLST scheme (threshold ≤20 alleles), and assigned sequence and complex types (ST, CT), using the Ridom SeqSphere+ software. For each cluster as determined by cgMLST, we used pairwise core-genome SNP-analysis and SKA at thresholds of ten and seven SNPs, respectively, to further distinguish cgMLST clusters. In order to investigate clinical relevance, we analysed to what extent epidemiological linkage backed the clusters determined with different genomic approaches. Between 2014 and 2021, we sequenced 693 VREfm strains, and 644 (93 %) were associated within cgMLST clusters. More than 74 % (n=475) of the strains belonged to the six largest cgMLST clusters, comprising ST117, ST78 and ST80. All six clusters were detected across several years and hospitals without apparent epidemiological links. Core SNP analysis identified 44 clusters with a median cluster size of three isolates (IQR 2-7, min-max 2-63), as well as 197 singletons (41.4 % of 475 isolates). SKA identified 67 clusters with a median cluster size of two isolates (IQR 2-4, min-max 2-19), and 261 singletons (54.9 % of 475 isolates). Of the isolate pairs attributed to clusters, 7 % (n=3064/45 596) of pairs in clusters determined by standard cgMLST, 15 % (n=1222/8500) of pairs in core SNP-clusters and 51 % (n=942/1880) of pairs in SKA-clusters showed epidemiological linkage. The proportion of epidemiological linkage differed between sequence types. For VREfm, the discriminative ability of the widely used cgMLST based approach at ≤20 alleles difference was insufficient to rule out hospital outbreaks without further analytical methods. Cluster assignment guided by core genome SNP analysis and the reference free SKA was more discriminative and correlated better with obvious epidemiological linkage, at least recently published thresholds (ten and seven SNPs, respectively) and for frequent STs. Besides higher overall discriminative power, the whole-genome approach implemented in SKA is also easier and faster to conduct and requires less computational resources.

Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations as well as research. In order to make use of pathogen genomics data, they must be interpreted using contextual data (metadata). Contextual data include sample metadata, laboratory methods, patient demographics, clinical outcomes and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration and their use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool's web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission. In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.

Salmonella enterica Typhi (S. Typhi) and Paratyphi A (S. Paratyphi A) are the causative agents of enteric fever, a systemic human disease with a burden of 300 000 cases per year in India. The majority of enteric fever cases are associated with S. Typhi, resulting in a paucity of data regarding S. Paratyphi A, specifically with respect to genomic surveillance and antimicrobial resistance (AMR). Here, we exploited whole-genome sequencing (WGS) to identify S. Paratyphi A genotypes and AMR determinants associated with an outbreak of S. Paratyphi A in Vadodara, India, from December 2018 to December 2019. In total 117 S. Paratyphi A were isolated and genome sequenced, most were genotype 2.4.2 (72.6 % of all cases), which is the globally dominant genotype. The remainder were genotype 2.3 (25.6 %), while only two isolates belonged to genotype 2.4.1. A single base-pair mutation in gyrA, associated with reduced susceptibility to fluoroquinolones, was present in all of the outbreak isolates; with 74.35 % of isolates having a S83F substitution and the remainder having an S83Y substitution. Our surveillance study suggests that S. Paratyphi A is an emergent pathogen in South Asia, which may become increasingly relevant with the introduction of Vi conjugate vaccines.

Human adenovirus F41 causes acute gastroenteritis in children, and has recently been associated with an apparent increase in paediatric hepatitis of unknown aetiology in the UK, with further cases reported in multiple countries. Relatively little is known about the genetic diversity of adenovirus F41 in UK children; and it is unclear what, if any, impact the COVID-19 pandemic has had on viral diversity in the UK. Methods that allow F41 to be sequenced from clinical samples without the need for viral culture are required to provide the genomic data to address these questions. Therefore, we evaluated an overlapping-amplicon method of sequencing adenovirus genomes from clinical samples using Oxford Nanopore technology. We applied this method to a small sample of adenovirus-species-F-positive extracts collected as part of standard care in the East of England region in January-May 2022. This method produced genomes with >75 % coverage in 13/22 samples and >50 % coverage in 19/22 samples. We identified two F41 lineages present in paediatric patients in the East of England in 2022. Where F41 genomes from paediatric hepatitis cases were available (n=2), these genomes fell within the diversity of F41 from the UK and continental Europe sequenced before and after the 2020-2021 phase of the COVID-19 pandemic. Our analyses suggest that overlapping amplicon sequencing is an appropriate method for generating F41 genomic data from high-virus-load clinical samples, and currently circulating F41 viral lineages were present in the UK and Europe before the COVID-19 pandemic.

Shiga toxin-producing Escherichia coli (STEC) are a cause of severe human illness and are frequently associated with haemolytic uraemic syndrome (HUS) in children. It remains difficult to identify virulence factors for STEC that absolutely predict the potential to cause human disease. In addition to the Shiga-toxin (stx genes), many additional factors have been reported, such as intimin (eae gene), which is clearly an aggravating factor for developing HUS. Current STEC detection methods classically rely on real-time PCR (qPCR) to detect the presence of the key virulence markers (stx and eae). Although qPCR gives an insight into the presence of these virulence markers, it is not appropriate for confirming their presence in the same strain. Therefore, isolation steps are necessary to confirm STEC viability and characterize STEC genomes. While STEC isolation is laborious and time-consuming, metagenomics has the potential to accelerate the STEC characterization process in an isolation-free manner. Recently, short-read sequencing metagenomics have been applied for this purpose, but assembly quality and contiguity suffer from the high proportion of mobile genetic elements occurring in STEC strains. To circumvent this problem, we used long-read sequencing metagenomics for identifying eae-positive STEC strains using raw cow's milk as a causative matrix for STEC food-borne outbreaks. By comparing enrichment conditions, optimizing library preparation for MinION sequencing and generating an easy-to-use STEC characterization pipeline, the direct identification of an eae-positive STEC strain was successful after enrichment of artificially contaminated raw cow's milk samples at a contamination level as low as 5 c.f.u. ml-1. Our newly developed method combines optimized enrichment conditions of STEC in raw milk in combination with a complete STEC analysis pipeline from long-read sequencing metagenomics data. This study shows the potential of the innovative methodology for characterizing STEC strains from complex matrices. Further developments will nonetheless be necessary for this method to be applied in STEC surveillance.

Yersinia are gram-negative zoonotic bacteria that use a type three secretion system (T3SS) to inject Yersinia outer proteins (Yops) into the host cytosol in order to subvert essential components of innate immune signaling. However, Yersinia virulence can elicit activation of immune complexes known as inflammasomes, which lead to inflammatory cell death and cytokine release aimed at containing infection. Yersinia activation and evasion of inflammasomes have been characterized in macrophages but remain poorly defined in intestinal epithelial cells (IECs), the primary site of gastrointestinal Yersinia infection. In contrast to murine macrophages, we find that in human IECs, Yersinia pseudotuberculosis T3SS effectors fully suppress activation of the caspase-4 inflammasome, which senses cytosolic lipopolysaccharide (LPS). The antiphagocytic Yops YopE and YopH, as well as YopK, were entirely responsible for inhibiting inflammasome activation, in part by inhibiting Yersinia internalization into IECs. Surprisingly, Yops E, H and K also suppressed inflammasome activation in human macrophages, which, like human IECs, failed to undergo cell death in response to wild-type Yersinia . These data suggest species-specific differences underlying inflammasome activation in response to Yersinia , and provide insight into the mechanisms of Yersinia- mediated inflammasome activation and suppression in human cells.

Avian pathogenic Escherichia coli (APEC) is the cause of colibacillosis outbreaks in young poultry chicks, resulting in acute to peracute death. The high morbidity and mortality caused by colibacillosis results in poor animal welfare, reduced sustainability and economical loss worldwide. To advance the understanding of the molecular epidemiology, genomic relatedness and virulence traits of APEC, we performed systematic sampling from 45 confirmed colibacillosis broiler flocks with high first week mortality (FWM) during 2018-2021. From these flocks, 219 APEC isolates were whole genome sequenced (WGS) and bioinformatic analyses were performed. The bioinformatic analyses included sequence typing (ST), serotyping, detection of virulence-associated genes (VAGs) and phylogenetic analysis. Our results showed a high prevalence of ST23, ST429 and ST95 among APEC isolates from Norwegian broiler flocks, and identified ST23, ST429, ST117 and ST371 to cause disease more often alone, compared to ST95, ST69 and ST10. Phylogenetic analyses, together with associated metadata, identified two distinct outbreaks of colibacillosis across farms caused by ST429 and ST23 and gave insight into expected SNP distances within and between flocks identified with the same ST. Further, our results highlighted the need for combining two typing methods, such as serotyping and sequence typing, to better discriminate strains of APEC. Ultimately, systematic sampling of APEC from multiple birds in a flock, together with WGS as a diagnostic tool is important to identify the disease-causing APEC within a flock and to detect outbreaks of colibacillosis across farms.

The COVID-19 pandemic changed the way we work, spend, live, and learn. The impact was felt in the health sector where hospitals cancelled elective surgery, put on hold outpatient services, and implemented new social distancing procedures and telehealth systems, to enable hospitals to increase bed capacity. For medical students, these factors meant significant disruption to their clinical placements, remote delivery of their education, cessation of international and interstate placements, complicated by significant travel restrictions and border closures. There were concerns that final year students might be unable to graduate that year due to this lack of clinical exposure.