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The 2022 multicountry mpox outbreak concurrent with the ongoing Coronavirus Disease 2019 (COVID-19) pandemic further highlighted the need for genomic surveillance and rapid pathogen whole-genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical specimens that tested presumptively positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (Ct) (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR Ct below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon-based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole-genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.

Background: Information on vaccine effectiveness in a context of novel variants of concern (VOC) emergence is of key importance to inform public health policies. This study aimed to estimate a measure of comparative vaccine effectiveness between Omicron (BA.1) and Delta (B.1.617.2 and sub-lineages) VOC according to vaccination exposure (primary or booster). Methods: We developed a case–case study using data on RT-PCR SARS-CoV2-positive cases notified in Portugal during Weeks 49–51, 2021. To obtain measure of comparative vaccine effectiveness, we compared the odds of vaccination in Omicron cases versus Delta using logistic regression adjusted for age group, sex, region, week of diagnosis, and laboratory of origin. Results: Higher odds of vaccination were observed in cases infected by Omicron VOC compared with Delta VOC cases for both complete primary vaccination (odds ratio [OR] = 2.1; 95% confidence interval [CI]: 1.8 to 2.4) and booster dose (OR = 5.2; 95% CI: 3.1 to 8.8), equivalent to reduction of vaccine effectiveness from 44.7% and 92.8%, observed against infection with Delta, to 6.0% (95% CI: 29.2% to 12.7%) and 62.7% (95% CI: 35.7% to 77.9%), observed against infection with Omicron, for complete primary vaccination and booster dose, respectively. Conclusion: Consistent reduction in vaccine-induced protection against infection with Omicron was observed. Complete primary vaccination may not be protective against SARS-CoV-2 infection in regions where Omicron variant is dominant. Grant no. 2021/PHF/23776; POCI-01-0145-FEDER-022184; Project ALG-D2-2021-06 info:eu-repo/semantics/publishedVersion

We developed a case–case study to compare mRNA vaccine effectiveness against Delta versus Alpha coronavirus variants. We used data on 2,097 case-patients with PCR-positive severe acute respiratory syndrome coronavirus 2 infections reported in Portugal during May–July 2021. We estimated the odds of vaccine breakthrough infection in Delta-infected versus Alpha-infected patients by using conditional logistic regression adjusted for age group and sex and matched by the week of diagnosis. We compared reverse-transcription PCR cycle threshold values by vaccination status and variant as an indirect measure of viral load. We found significantly higher odds of vaccine breakthrough infection in Delta-infected patients than in Alpha-infected patients (odds ratio 1.96 [95% CI 1.22–3.14]), suggesting lower effectiveness of the mRNA vaccines in preventing infection with the Delta variant. We estimated lower mean cycle threshold values for the Delta cases (mean difference −2.10 [95% CI −2.74 to −1.47]), suggesting higher infectiousness than the Alpha variant.

Foodborne pathogens pose an important and serious threat to human and animal health. Therefore, genomics-based surveillance systems able to track the circulation of these pathogens and monitor their clinical and epidemiological relevant features have been implemented at the reference laboratories of multiple countries and sectors. However, there is a lack of harmonization between them that challenges the integration and comparison of data at international and intersectoral levels, and, ultimately, the establishment of fully integrative and efficient One Health genomic surveillance frameworks. In the BeONE project, we aimed to perform a massive comparison between different bioinformatics pipelines used for genomic surveillance of foodborne bacterial pathogens, as a way to assess the congruence and comparability of their clustering results. Specifically, BeONE WP1-T3 had as main objectives the: Evaluation of the behavior of different surveillance-oriented genomics pipelines in the definition of genetic clusters, through the identification of threshold ranges with high resolution for outbreak detection or stable threshold ranges for nomenclature design (useful for longitudinal surveillance); Determination of the congruence with traditional typing nomenclatures, such as Sequence Type (ST) or serovar; Identification of congruent resolution levels between pipelines, as a way to facilitate international data sharing and cooperation; Assessment of the similarities and discrepancies between pipelines in the identification of outbreak-related isolates In this repository, we provide the Deliverable of BeONE WP1-T3 with a brief overview of its activities and the preliminary results obtained until the end of the BeONE project. We anticipate that this study will provide important information regarding the behavior of each pipeline and facilitate the direct comparability of their results.

ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data Genomics-informed pathogen surveillance strengthens public health decision-making, playing an important role in infectious diseases’ prevention and control. A pivotal outcome of genomics surveillance is the identification of pathogen genetic clusters and their characterization in terms of geotemporal spread or linkage to clinical and demographic data. This task often consists of the visual exploration of (large) phylogenetic trees and associated metadata, being time consuming and difficult to reproduce.We developed ReporTree, a exible bioinformatics pipeline that allows diving into the complexity of pathogen diversity to rapidly identify genetic clusters at any (or all) distance thresholds (e.g., high resolution thresholds used for outbreak detection or stable threshold ranges for nomenclature design) and to generate surveillance-oriented reports based on the available metadata, such as timespan, geography or vaccination/clinical status. By handling several input formats (SNP/allele matrices, trees/dendrograms, multiple sequence alignments, VCF files or distance matrices) and clustering methods, ReporTree is applicable to multiple pathogens, thus constituting a flexible resource that can be smoothly deployed in routine surveillance bioinformatics workflows with negligible computational and time costs. This is demonstrated through a benchmarking using core genome- (cg) or whole genome- (wg) Multiple Locus Sequence Type (MLST) (cg/wgMLST) datasets of four foodborne bacterial pathogens (each comprising more than a thousand isolates), in which genetic clusters at possible outbreak level were identied and reported in a matter of seconds. To further validate this tool, we reproduced a previous large-scale study on Neisseria gonorrhoeae, demonstrating how ReporTree is able to rapidly identify the main species genogroups and characterize them with key surveillance metadata (e.g., antibiotic resistance data). By providing examples for SARS-CoV-2 and the foodborne bacterial pathogen Listeria monocytogenes, we show how this tool is currently a useful asset in genomics- informed routine surveillance and outbreak detection of a wide variety of species.In summary, ReporTree is a pan-pathogen tool for automated and reproducible identication and characterization of genetic clusters that contributes to a sustainable and ecient public health genomics- informed pathogen surveillance. ReporTree is implemented in python 3.8 and is freely available at https://github.com/insapathogenomics/ReporTree or as a Docker image at insapathogenomics/reportree.

We propose a novel, non-discriminatory classification of monkeypox virus. Together with the World Health Organization, we named three clades (I, IIa and IIb) in order of detection. Within IIb, the cause the current global outbreak, we identified multiple lineages (A.1, A.2, A.1.1 and B.1) to support real-time genomics surveillance.