Towards reliable whole genome sequencing for outbreak preparedness and response

Ongoing mpox outbreak in Kamituga, South Kivu province, associated with monkeypox virus of a novel Clade I sub-lineage, Democratic Republic of the Congo, 2024

Since the beginning of 2023, the number of people with suspected monkeypox virus (MPXV) infection have sharply increased in the Democratic Republic of the Congo (DRC). We report near-to-complete MPXV genome sequences derived from six cases from the South Kivu province. Phylogenetic analyses reveal that the MPXV affecting the cases belongs to a novel Clade I sub-lineage. The outbreak strain genome lacks the target sequence of the probe and primers of a commonly used Clade I-specific real-time PCR.

Circulation, viral diversity and genomic rearrangement in mpox virus in the Netherlands during the 2022 outbreak and beyond

Mpox is an emerging zoonotic disease which has now spread to over 113 countries as of August 2023, with over 89,500 confirmed human cases. The Netherlands had one of the highest incidence rates in Europe during the peak of the outbreak. In this study, we generated 158 near-complete mpox virus (MPXV) genomes (12.4% of nationwide cases) that were collected throughout the Netherlands from the start of the outbreak in May 2022 to August 2023 to track viral evolution and investigate outbreak dynamics. We detected 14 different viral lineages, suggesting multiple introductions followed by rapid initial spread within the country. The estimated evolutionary rate was relatively high compared to previously described in orthopoxvirus literature, with an estimated 11.58 mutations per year. Genomic rearrangement events occurred at a rate of 0.63% and featured a large deletion event. In addition, based on phylogenetics, we identified multiple potential transmission clusters which could be supported by direct source- and contact tracing data. This led to the identification of at least two main transmission locations at the beginning of the outbreak. We conclude that whole genome sequencing of MPXV is essential to enhance our understanding of outbreak dynamics and evolution of a relatively understudied and emerging zoonotic pathogen.

First Detection of West Nile Virus Lineage 2 in Mosquitoes in Switzerland, 2022

West Nile virus (WNV) is one of the most widespread flaviviruses in the world, and in recent years, it has been frequently present in many Mediterranean and Eastern European countries. A combination of different conditions, such as a favourable climate and higher seasonal average temperatures, probably allowed its introduction and spread to new territories. In Switzerland, autochthonous cases of WNV have never been reported, and the virus was not detected in mosquito vectors until 2022, despite an entomological surveillance in place in Canton Ticino, southern Switzerland, since 2010. In 2022, 12 sites were monitored from July to October, using BOX gravid mosquito traps coupled with honey-baited FTA cards. For the first time, we could detect the presence of WNV in FTA cards and mosquitoes in 8 out of the 12 sampling sites monitored, indicating an unexpectedly widespread circulation of the virus throughout the territory. Positive findings were recorded from the beginning of August until mid-October 2022, and whole genome sequencing analysis identified a lineage 2 virus closely related to strains circulating in Northern Italy. The entomological surveillance has proved useful in identifying viral circulation in advance of possible cases of WNV infection in humans or horses.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

Viral and Bacterial Profiles in Endemic Influenza A Virus Infected Swine Herds Using Nanopore Metagenomic Sequencing on Tracheobronchial Swabs

Swine influenza A virus (swIAV) plays an important role in porcine respiratory infections. In addition to its ability to cause severe disease by itself, it is important in the multietiological porcine respiratory disease complex. Still, to date, no comprehensive diagnostics with which to study polymicrobial infections in detail have been offered. Hence, veterinary practitioners rely on monospecific and costly diagnostics, such as Reverse Transcription quantitative PCR (RT-qPCR), antigen detection, and serology. This prevents the proper understanding of the entire disease context, thereby hampering effective preventive and therapeutic actions. A new, nanopore-based, metagenomic diagnostic platform was applied to study viral and bacterial profiles across 4 age groups on 25 endemic swIAV-infected German farms with respiratory distress in the nursery. Farms were screened for swIAV using RT-qPCR on nasal and tracheobronchial swabs (TBS). TBS samples were pooled per age, prior to metagenomic characterization. The resulting data showed a correlation between the swIAV loads and the normalized reads, supporting a (semi-)quantitative interpretation of the metagenomic data. Interestingly, an in-depth characterization using beta diversity and PERMANOVA analyses allowed for the observation of an age-dependent interplay of known microbial agents. Also, lesser-known microbes, such as porcine polyoma, parainfluenza, and hemagglutinating encephalomyelitis viruses, were observed. Analyses of swIAV incidence and clinical signs showed differing microbial communities, highlighting age-specific observations of various microbes in porcine respiratory disease. In conclusion, nanopore metagenomics were shown to enable a panoramic view on viral and bacterial profiles as well as putative pathogen dynamics in endemic swIAV-infected herds. The results also highlighted the need for better insights into lesser studied agents that are potentially associated with porcine respiratory disease. IMPORTANCE To date, no comprehensive diagnostics for the study of polymicrobial infections that are associated with porcine respiratory disease have been offered. This precludes the proper understanding of the entire disease landscape, thereby hampering effective preventive and therapeutic actions. Compared to the often-costly diagnostic procedures that are applied for the diagnostics of porcine respiratory disease nowadays, a third-generation nanopore sequencing diagnostics workflow presents a cost-efficient and informative tool. This approach offers a panoramic view of microbial agents and contributes to the in-depth observation and characterization of viral and bacterial profiles within the respiratory disease context. While these data allow for the study of age-associated, swIAV-associated, and clinical symptom-associated observations, it also suggests that more effort should be put toward the investigation of coinfections and lesser-known pathogens (e.g., PHEV and PPIV), along with their potential roles in porcine respiratory disease. Overall, this approach will allow veterinary practitioners to tailor treatment and/or management changes on farms in a quicker, more complete, and cost-efficient way.