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The proliferation of digital communication has profoundly transformed the landscape of persuasive discourse. Online platforms have amplified the reach and impact of persuasive techniques. However, they have also enabled the rapid spread of manipulative content, targeted propaganda, and divisive rhetoric. Consequently, a wide range of computational approaches has emerged to address the multifaceted nature of digital persuasion, to detect and mitigate its harmful practices. In light of this, the paper surveys computational methods for detecting persuasive means in digital communication, focusing on how they integrate humanistic knowledge to operationalize this construct. Additionally, special emphasis is placed on models' explainability, a pivotal aspect considering these models are used by institutions to influence societal interactions. For the analysis, two primary perspectives in persuasion are defined: linguistic and argumentative. The linguistic approach analyzes specific textual features, allowing for highly accountable algorithms based on explicit rules. The argumentative approach focuses on broader persuasive mechanisms, offering greater scalability but often resulting in less explainable models due to their complexity. This tension between model sophistication and explainability presents a key challenge in developing effective and transparent persuasion detection systems. The results highlight the spectrum of methodologies for studying persuasion, ranging from analyzing stylistic elements to detecting explicitly propagandist messages. Our findings highlight two key challenges in using these algorithms to tackle societal issues of persuasion misuse: the opacity of deep learning models and the absence of a theoretically grounded distinction between vicious and virtuous persuasion. To address these challenges, we propose integrating social sciences and humanities theories to enhance the effectiveness and ethical robustness of persuasion detection systems. This interdisciplinary approach enables a more nuanced characterization of text, facilitating the differentiation between vicious and virtuous persuasion through analysis of rhetorical, argumentative, and emotional aspects. We emphasize the potential of hybrid approaches that combine rule-based methods with deep learning techniques, as these offer a promising avenue for implementing this interdisciplinary framework. The paper concludes by outlining future challenges, including the importance of multimodal and multilingual analysis, ethical considerations in handling user-generated data and the growing challenge of distinguishing between human and AI-generated persuasive content.

Introduction: The World Health Organization (WHO)'s Research and Development (R&D) Blueprint for Action to Prevent Epidemics, a plan of action, highlighted several infectious diseases as crucial targets for prevention. These infections were selected based on a thorough assessment of factors such as transmissibility, infectivity, severity, and evolutionary potential. In line with this blueprint, the VACCELERATE Site Network approached infectious disease experts to rank the diseases listed in the WHO R&D Blueprint according to their perceived risk of triggering a pandemic. VACCELERATE is an EU-funded collaborative European network of clinical trial sites, established to respond to emerging pandemics and enhance vaccine development capabilities. Methods: Between February and June 2023, a survey was conducted using an online form to collect data from members of the VACCELERATE Site Network and infectious disease experts worldwide. Participants were asked to rank various pathogens based on their perceived risk of causing a pandemic, including those listed in the WHO R&D Blueprint and additional pathogens. Results: A total of 187 responses were obtained from infectious disease experts representing 57 countries, with Germany, Spain, and Italy providing the highest number of replies. Influenza viruses received the highest rankings among the pathogens, with 79 % of participants including them in their top rankings. Disease X, SARS-CoV-2, SARS-CoV, and Ebola virus were also ranked highly. Hantavirus, Lassa virus, Nipah virus, and henipavirus were among the bottom-ranked pathogens in terms of pandemic potential. Conclusion: Influenza, SARS-CoV, SARS-CoV-2, and Ebola virus were found to be the most concerning pathogens with pandemic potential, characterised by transmissibility through respiratory droplets and a reported history of epidemic or pandemic outbreaks.

ABSTRACTIn agricultural production, intercropping is a widely used system with many benefits. Lupin (Lupinus angustifolius L.) is a legume that contains a large variety of plant secondary metabolites, which have multiple functions in the plant, e.g. signalling, nodulation and stress response. An untargeted metabolomics approach was applied to investigate how the metabolome of lupin was affected by intercropped barley (Hordeum vulgare L.). The only primary metabolite of lupin affected by intercropping was tryptophan. Several secondary metabolites were affected by intercropping in lupin, and five flavonoids were annotated hereof. The flavonoid levels were increased, and tryptophan levels decreased in lupin when intercropped. Two flavonoids are prenylated, and prenylated flavonoids are believed to play a role in the plant’s stress response. Furthermore, flavonoids are involved in plant defence and the nodulation process. Thus the present flavonoids may affect regulation of lupin N2-fixation activity.Highlights Intercropping caused a change in the secondary metabolites of Lupinus angustifolius L.Prenylated flavonoids were generated in Lupinus angustifolius L. as a response to intercroppingTryptophan was the only identified primary metabolite affected by intercropping

An in-depth analysis of antibody epitopes following vaccination with different regimens provides important insight for developing future vaccine strategies. B-cell epitopes conserved across virus variants may be ideal targets for vaccine-induced antibodies and therapeutic drugs. However, challenges lie in identifying these key antigenic regions, and directing the immune system to target them. We previously evaluated the immunogenicity of two candidate DNA vaccines encoding the unmodified spike protein of either the SARS-CoV-2 Index strain or the Beta variant of concern (VOC). As a follow-on study, we characterized here the antibody binding profiles of three groups of mice immunized with either the DNA vaccine encoding the SARS-CoV-2 Index strain spike protein only, the Beta VOC spike protein only, or a combination of both as an antigen-heterologous prime-boost regimen. The latter induced an antibody response targeting overlapping regions that were observed for the individual vaccines but with additional high levels of antibody directed against epitopes in the SD2 region and the HR2 region. These heterologous-vaccinated animals displayed improved neutralization breadth. We believe that a broad-focused vaccine regimen increases neutralization breadth, and that the in-depth analysis of B-cell epitope targeting used in this study can be applied in future vaccine research.

ABSTRACT Multiple mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) increase transmission, disease severity, and immune evasion and facilitate zoonotic or anthropozoonotic infections. Four such mutations, ΔH69/V70, L452R, E484K, and N501Y, occurred in the SARS-CoV-2 spike glycoprotein in combinations that allow the simultaneous detection of VOCs. Here, we present two flexible reverse transcription-quantitative PCR (RT-qPCR) platforms for small- and large-scale screening (also known as variant PCR) to detect these mutations and schemes for adapting the platforms to future mutations. The large-scale RT-qPCR platform was validated by pairwise matching of RT-qPCR results with whole-genome sequencing (WGS) consensus genomes, showing high specificity and sensitivity. Both platforms are valuable examples of complementing WGS to support the rapid detection of VOCs. Our mutational signature approach served as an important intervention measure for the Danish public health system to detect and delay the emergence of new VOCs. IMPORTANCE Denmark weathered the SARS-CoV-2 crisis with relatively low rates of infection and death. Intensive testing strategies with the aim of detecting SARS-CoV-2 in symptomatic and nonsymptomatic individuals were available by establishing a national test system called TestCenter Denmark. This testing regime included the detection of SARS-CoV-2 signature mutations, with referral to the national health system, thereby delaying outbreaks of variants of concern. Our study describes the design of the large-scale RT-qPCR platform established at TestCenter Denmark in conjunction with whole-genome sequencing to report mutations of concern to the national health system. Validation of the large-scale RT-qPCR platform using paired WGS consensus genomes showed high sensitivity and specificity. For smaller laboratories with limited infrastructure, we developed a flexible small-scale RT-qPCR platform to detect three signature mutations in a single run. The RT-qPCR platforms are important tools to support the control of the SARS-CoV-2 endemic in Denmark.

In this study, the authors compare the transmission dynamics of the Delta and Omicron SARS-CoV-2 variants using household data from Denmark. They find that Omicron has a higher secondary attack rate, and that the odds of infection with Omicron was higher than with Delta, particularly for vaccinated individuals.

In this study, the authors use household data from Denmark to investigate the transmissibility of the BA.1 and BA.2 Omicron SARS-CoV-2 subvariants. They find that the secondary attack rate was higher for BA.2, but that it had higher infectiousness only when cases were not vaccinated.

Neuraminidase (NA) accounts for approximately 10-20% of the total glycoproteins on the surface of influenza viruses. It cleaves sialic acids on glycoproteins, which facilitates virus entry into the airways by cleaving heavily glycosylated mucins in mucus and the release of progeny virus from the surface of infected cells. These functions make NA an attractive vaccine target. To inform rational vaccine design, we define the functionality of influenza DNA vaccine-induced NA-specific antibodies relative to antigenic sites in pigs and ferrets challenged with a vaccine-homologous A/California/7/2009(H1N1)pdm09 strain. Sera collected pre-vaccination, post-vaccination and post-challenge were analyzed for antibody-mediated inhibition of NA activity using a recombinant H7N1CA09 virus. Antigenic sites were further identified with linear and conformational peptide microarrays spanning the full NA of A/California/04/2009(H1N1)pdm09. Vaccine-induced NA-specific antibodies inhibited the enzymatic function of NA in both animal models. The antibodies target critical sites of NA such as the enzymatic site, second sialic binding site and framework residues, shown here by high-resolution epitope mapping. New possible antigenic sites were identified that potentially block the catalytic activity of NA, including an epitope recognized solely in pigs and ferrets with neuraminidase inhibition, which could be a key antigenic site affecting NA function. These findings show that our influenza DNA vaccine candidate induces NA-specific antibodies that target known critical sites, and new potential antigenic sites of NA, inhibiting the catalytic activity of NA.

Early detection of pathogens at the point of care helps reduce the threats to human and animal health from emerging pathogens. Initially, the disease-causing agent will be unknown and needs to be identified; this often requires specific laboratory facilities. Here we describe the development of an unbiased detection assay for RNA and DNA viruses using metagenomic Nanopore sequencing and simple methods that can be transferred into a field setting. Human clinical samples containing the RNA virus SARS-CoV-2 or the DNA viruses human papillomavirus (HPV) and molluscum contagiosum virus (MCV) were used as a test of concept. Firstly, the virus detection potential was optimized by investigating different pretreatments for reducing non-viral nucleic acid components. DNase I pretreatment followed by filtration increased the proportion of SARS-CoV-2 sequenced reads > 500-fold compared with no pretreatments. This was sufficient to achieve virus detection with high confidence and allowed variant identification. Next, we tested individual SARS-CoV-2 samples with various viral loads (measured as CT-values determined by RT-qPCR). Lastly, we tested the assay on clinical samples containing the DNA virus HPV and co-infection with MCV to show the assay's detection potential for DNA viruses.This protocol is fast (same day results). We hope to apply this method in other settings for point of care detection of virus pathogens, thus eliminating the need for transport of infectious samples, cold storage and a specialized laboratory.

Abstract Background People experiencing homelessness (PEH) and associated shelter workers may be at higher risk of infection with “Severe acute respiratory syndrome coronavirus 2” (SARS-CoV-2). The aim of this study was to determine the prevalence of SARS-CoV-2 among PEH and shelter workers in Denmark. Design and methods In November 2020, we conducted a nationwide cross-sectional seroprevalence study among PEH and shelter workers at 21 recruitment sites in Denmark. The assessment included a point-of-care test for antibodies against SARS-CoV-2, followed by a questionnaire. The seroprevalence was compared to that of geographically matched blood donors considered as a proxy for the background population, tested using a total Ig ELISA assay. Results We included 827 participants in the study, of whom 819 provided their SARS-CoV-2 antibody results. Of those, 628 were PEH (median age 50.8 (IQR 40.9–59.1) years, 35.5% female) and 191 were shelter workers (median age 46.6 (IQR 36.1–55.0) years and 74.5% female). The overall seroprevalence was 6.7% and was similar among PEH and shelter workers (6.8% vs 6.3%, p = 0.87); and 12.2% among all participants who engaged in sex work. The overall participant seroprevalence was significantly higher than that of the background population (2.9%, p

Abstract Background In early 2021, the SARS-CoV-2 lineage B.1.1.7 (Alpha variant) became dominant across large parts of the world. In Denmark, comprehensive and real-time test, contact-tracing, and sequencing efforts were applied to sustain epidemic control. Here, we use these data to investigate the transmissibility, introduction, and onward transmission of B.1.1.7 in Denmark. Methods We analyzed a comprehensive set of 60,178 SARS-CoV-2 genomes generated from high-throughput sequencing by the Danish COVID-19 Genome Consortium, representing 34% of all positive cases in the period 14 November 2020 to 7 February 2021. We calculated the transmissibility of B.1.1.7 relative to other lineages using Poisson regression. Including all 1976 high-quality B.1.1.7 genomes collected in the study period, we constructed a time-scaled phylogeny, which was coupled with detailed travel history and register data to outline the introduction and onward transmission of B.1.1.7 in Denmark. Results In a period with unchanged restrictions, we estimated an increased B.1.1.7 transmissibility of 58% (95% CI: [56%, 60%]) relative to other lineages. Epidemiological and phylogenetic analyses revealed that 37% of B.1.1.7 cases were related to the initial introduction in November 2020. The relative number of cases directly linked to introductions varied between 10 and 50% throughout the study period. Conclusions Our findings corroborate early estimates of increased transmissibility of B.1.1.7. Both substantial early expansion when B.1.1.7 was still unmonitored and continuous foreign introductions contributed considerably to case numbers. Finally, our study highlights the benefit of balanced travel restrictions and self-isolation procedures coupled with comprehensive surveillance efforts, to sustain epidemic control in the face of emerging variants.

ABSTRACT The aim of this study was to provide information about immunity against COVID-19 along with risk factors and behavior among employees in day care facilities and preschools (DCS) in Denmark. In collaboration with the Danish Union of Pedagogues, during February and March 2021, 47,810 members were offered a point-of-care rapid SARS-CoV-2 antibody test (POCT) at work and were invited to fill in an electronic questionnaire covering COVID-19 exposure. Seroprevalence data from Danish blood donors (total Ig enzyme-linked immunosorbent assay [ELISA]) were used as a proxy for the Danish population. A total of 21,018 (45%) DCS employees completed the questionnaire and reported their POCT result {median age, 44.3 years (interquartile range [IQR], [32.7 to 53.6]); females, 84.1%}, of which 20,267 (96.4%) were unvaccinated and included in analysis. A total of 1,857 (9.2%) participants tested seropositive, significantly higher than a seroprevalence at 7.6% (risk ratio [RR], 1.2; 95% confidence interval [CI], 1.14 to 1.27) among 40,541 healthy blood donors (median age, 42 years [IQR, 28 to 53]; males, 51.3%). Exposure at work (RR, 2.9; 95% CI, 2.3 to 3.6) was less of a risk factor than exposure within the household (RR, 12.7; 95% CI, 10.2 to 15.8). Less than 25% of participants reported wearing face protection at work. Most of the participants expressed some degree of fear of contracting COVID-19 both at work and outside work. SARS-CoV-2 seroprevalence was slightly higher in DCS staff than in blood donors, but possible exposure at home was associated with a higher risk than at work. DCS staff expressed fear of contracting COVID-19, though there was limited use of face protection at work. IMPORTANCE Identifying at-risk groups and evaluating preventive interventions in at-risk groups is imperative for the ongoing pandemic as well as for the control of future epidemics. Although DCS staff have a much higher risk of being infected within their own household than at their workplace, most are fearful of being infected with COVID-19 or bringing COVID-19 to work. This represents an interesting dilemma and an important issue which should be addressed by public health authorities for risk communication and pandemic planning. This study design can be used in a strategy for ongoing surveillance of COVID-19 immunity or other infections in the population. The findings of this study can be used to assess the need for future preventive interventions in DCS, such as the use of personal protective equipment.

Abstract Prostate cancer (PC) is a common cancer among men, and preventive strategies are warranted. Benzoxazinoids (BXs) in rye have shown potential against PC in vitro but human studies are lacking. The aim was to establish a quantitative method for analysis of BXs and investigate their plasma levels after a whole grain/bran rye vs refined wheat intervention, as well as exploring their association with PSA, in men with PC. A quantitative method for analysis of 22 BXs, including novel metabolites identified by mass spectrometry and NMR, was established, and applied to plasma samples from a randomized crossover study where patients with indolent PC (n = 17) consumed 485 g whole grain rye/rye bran or fiber supplemented refined wheat daily for 6 wk. Most BXs were significantly higher in plasma after rye (0.3–19.4 nmol/L in plasma) vs. refined wheat (0.05–2.9 nmol/L) intake. HBOA-glc, 2-HHPAA, HBOA-glcA, 2-HPAA-glcA were inversely correlated to PSA in plasma (p

Abstract Background COVID-19 is thought to be more prevalent among ethnic minorities and individuals with low socioeconomic status. We aimed to investigate the prevalence of SARS-CoV-2 antibodies during the COVID-19 pandemic among citizens 15 years or older in Denmark living in social housing (SH) areas. Methods We conducted a study between January 8th and January 31st, 2021 with recruitment in 13 selected SH areas. Participants were offered a point-of-care rapid SARS-CoV-2 IgM and IgG antibody test and a questionnaire concerning risk factors associated with COVID-19. As a proxy for the general Danish population we accessed data on seroprevalence from Danish blood donors (total Ig ELISA assay) in same time period. Results Of the 13,279 included participants, 2296 (17.3%) were seropositive (mean age 46.6 (SD 16.4) years, 54.2% female), which was 3 times higher than in the general Danish population (mean age 41.7 (SD 14.1) years, 48.5% female) in the same period (5.8%, risk ratios (RR) 2.96, 95% CI 2.78–3.16, p > 0.001). Seropositivity was higher among males (RR 1.1, 95% CI 1.05–1.22%, p = 0.001) and increased with age, with an OR seropositivity of 1.03 for each 10-year increase in age (95% CI 1.00–1.06, p = 0.031). Close contact with COVID-19-infected individuals was associated with a higher risk of infection, especially among household members (OR 5.0, 95% CI 4.1–6.2 p

The proliferation of digital communication has profoundly transformed the landscape of persuasive discourse. Online platforms have amplified the reach and impact of persuasive techniques. However, they have also enabled the rapid spread of manipulative content, targeted propaganda, and divisive rhetoric. Consequently, a wide range of computational approaches has emerged to address the multifaceted nature of digital persuasion, to detect and mitigate its harmful practices. In light of this, the paper surveys computational methods for detecting persuasive means in digital communication, focusing on how they integrate humanistic knowledge to operationalize this construct. Additionally, special emphasis is placed onmodels' explainability, a pivotal aspect considering these models are used by institutions to influence societal interactions. For the analysis, two primary perspectives in persuasion are defined: linguistic and argumentative. The linguistic approach analyzes specific textual features, allowing for highly accountable algorithms based on explicit rules. The argumentative approach focuses on broader persuasive mechanisms, offering greater scalability but often resulting in less explainable models due to their complexity. This tension between model sophistication and explainability presents a key challenge in developing effective and transparent persuasion detection systems. The results highlight the spectrum of methodologies for studying persuasion, ranging from analyzing stylistic elements to detecting explicitly propagandist messages. Our findings highlight two key challenges in using these algorithms to tackle societal issues of persuasionmisuse: the opacity of deep learning models and the absence of a theoretically grounded distinction between vicious and virtuous persuasion. To address these challenges, we propose integrating social sciences and humanities theories to enhance the effectiveness and ethical robustness of persuasion detection systems. This interdisciplinary approach enables a more nuanced characterization of text, facilitating the differentiation between vicious and virtuous persuasion through analysis of rhetorical, argumentative, and emotional aspects. We emphasize the potential of hybrid approaches that combine rule-based methods with deep learning techniques, as these offer a promising avenue for implementing this interdisciplinary framework. The paper concludes by outlining future challenges, including the importance of multimodal and multilingual analysis, ethical considerations in handling user-generated data and the growing challenge of distinguishing between human and AI-generated persuasive content. [ABSTRACT FROM AUTHOR]

The ideal vaccine against viral infections should elicit antibody responses that protect against divergent strains. Designing broadly protective vaccines against SARS-CoV-2 and other divergent viruses requires insight into the specific targets of cross-protective antibodies on the viral surface protein(s). However, unlike therapeutic monoclonal antibodies, the B-cell epitopes of vaccine-induced polyclonal antibody responses remain poorly defined. Here we show that, through the combination of neutralizing antibody functional responses with B-cell epitope mapping, it is possible to identify unique antibody targets associated with neutralization breadth. The polyclonal antibody profiles of SARS-CoV-2 index-strain-vaccinated rabbits that demonstrated a low, intermediate, or high neutralization efficiency of different SARS-CoV-2 variants of concern (VOCs) were distinctly different. Animals with an intermediate and high cross-neutralization of VOCs targeted fewer antigenic sites on the spike protein and targeted one particular epitope, subdomain 1 (SD1), situated outside the receptor binding domain (RBD). Our results indicate that a targeted functional antibody response and an additional focus on non-RBD epitopes could be effective for broad protection against different SARS-CoV-2 variants. We anticipate that the approach taken in this study can be applied to other viral vaccines for identifying future epitopes that confer cross-neutralizing antibody responses, and that our findings will inform a rational vaccine design for SARS-CoV-2.

Abstract New generation plasmid DNA vaccines may be a safe, fast and simple emergency vaccine platform for preparedness against emerging viral pathogens. Applying platform optimization strategies, we tested the pre-clinical immunogenicity and protective effect of a candidate DNA plasmid vaccine specific for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The DNA vaccine induced spike-specific binding IgG and neutralizing antibodies in mice, rabbits, and rhesus macaques together with robust Th1 dominant cellular responses in small animals. Intradermal and intramuscular needle-free administration of the DNA vaccine yielded comparable immune responses. In a vaccination-challenge study of rhesus macaques, the vaccine demonstrated protection from viral replication in the lungs following intranasal and intratracheal inoculation with SARS-CoV-2. In conclusion, the candidate plasmid DNA vaccine encoding the SARS-CoV-2 spike protein is immunogenic in different models and confers protection against lung infection in nonhuman primates. Further evaluation of this DNA vaccine candidate in clinical trials is warranted.

Abstract Rapid nucleic-acid based tests that can be performed by non-professionals outside laboratory settings could help the containment of the pandemic SARS-CoV-2 virus and may potentially prevent further widespread lockdowns. Here, we present a novel compact portable detection instrument (the Egoo Health System) for extraction-free detection of SARS-CoV-2 using isothermal reverse transcription strand invasion based amplification (RT-SIBA). The SARS-CoV-2 RT-SIBA assay can be performed directly on crude oropharyngeal swabs without nucleic acid extraction with a reaction time of 30 min. The Egoo Health system uses a capsule system, which is automatically sealed tight in the Egoo instrument after applying the sample, resulting in a closed system optimal for molecular isothermal amplification. The performance of the Egoo Health System is comparable to the PCR instrument with an analytical sensitivity of 25 viral RNA copies per SARS-CoV-2 RT-SIBA reaction and a clinical sensitivity and specificity between 87.0–98.4% and 96.6–98.2% respectively.

ABSTRACT While the plant host metabolome drives distinct enrichment of detrimental and beneficial members of the microbiome, the mechanistic interomics relationships remain poorly understood. Here, we studied microbiome and metabolome profiles of two Arabidopsis thaliana accessions after Fusarium oxysporum f.sp. mathioli (FOM) inoculation, Landsberg erecta (Ler-0) being susceptible and Col-0 being resistant against FOM. By using bacterial and fungal amplicon sequencing and targeted metabolite analysis, we observed highly dynamic microbiome and metabolome profiles across FOM host progression, while being markedly different between FOM-inoculated and noninoculated Col-0 and Ler-0. Co-occurrence network analysis revealed more robust microbial networks in the resistant Col-0 compared to Ler-0 during FOM infection. Correlation analysis revealed distinct metabolite-OTU correlations in Ler-0 compared with Col-0 which could possibly be explained by missense variants of the Rfo3 and Rlp2 genes in Ler-0. Remarkably, we observed positive correlations in Ler-0 between most of the analyzed metabolites and the bacterial phyla Proteobacteria, Bacteroidetes, Planctomycetes, Acidobacteria, and Verrucomicrobia, and negative correlations with Actinobacteria, Firmicutes, and Chloroflexi. The glucosinolates 4-methyoxyglucobrassicin, glucoerucin and indole-3 carbinol, but also phenolic compounds were strongly correlating with the relative abundances of indicator and hub OTUs and thus could be active in structuring the A. thaliana root-associated microbiome. Our results highlight interactive effects of host plant defense and root-associated microbiota on Fusarium infection and progression. Our findings provide significant insights into plant interomic dynamics during pathogen invasion and could possibly facilitate future exploitation of microbiomes for plant disease control. IMPORTANCE Plant health and fitness are determined by plant-microbe interactions which are guided by host-synthesized metabolites. To understand the orchestration of this interaction, we analyzed the distinct interomic dynamics in resistant and susceptible Arabidopsis ecotypes across different time points after infection with Fusarium oxysporum (FOM). Our results revealed distinct microbial profiles and network resilience during FOM infection in the resistant Col-0 compared with the susceptible Ler-0 and further pinpointed specific microbe-metabolite associations in the Arabidopsis microbiome. These findings provide significant insights into plant interomics dynamics that are likely affecting fungal pathogen invasion and could possibly facilitate future exploitation of microbiomes for plant disease control.

Metagenomic next-generation sequencing (mNGS) is receiving increased attention for the detection of new viruses and infections occurring at the human–animal interface. The ability to actively transport and relocate this technology enables in situ virus identification, which could reduce response time and enhance disease management. In a previous study, we developed a straightforward mNGS procedure that greatly enhances the detection of RNA and DNA viruses in human clinical samples. In this study, we improved the mNGS protocol with transportable battery-driven equipment for the portable, non-targeted detection of RNA and DNA viruses in animals from a large zoological facility, to simulate a field setting for point-of-incidence virus detection. From the resulting metagenomic data, we detected 13 vertebrate viruses from four major virus groups: (+)ssRNA, (+)ssRNA-RT, dsDNA and (+)ssDNA, including avian leukosis virus in domestic chickens (Gallus gallus), enzootic nasal tumour virus in goats (Capra hircus) and several small, circular, Rep-encoding, ssDNA (CRESS DNA) viruses in several mammal species. More significantly, we demonstrate that the mNGS method is able to detect potentially lethal animal viruses, such as elephant endotheliotropic herpesvirus in Asian elephants (Elephas maximus) and the newly described human-associated gemykibivirus 2, a human-to-animal cross-species virus, in a Linnaeus two-toed sloth (Choloepus didactylus) and its enclosure, for the first time.

Severe acute respiratory syndrome coronavirus 2 has caused a pandemic in humans. Farmed mink (Neovison vison) are also susceptible. In Denmark, this virus has spread rapidly among farmed mink, resulting in some respiratory disease. Full-length virus genome sequencing revealed novel virus variants in mink. These variants subsequently appeared within the local human community.