The coevolutionary mosaic of bat betacoronavirus emergence risk.

Pathogen evolution is one of the least predictable components of disease emergence, particularly in nature. Here, building on principles established by the geographic mosaic theory of coevolution, we develop a quantitative, spatially explicit framework for mapping the evolutionary risk of viral emergence. Driven by interest in diseases like Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and Coronavirus disease 2019 (COVID-19), we examine the global biogeography of bat-origin betacoronaviruses, and find that coevolutionary principles suggest geographies of risk that are distinct from the hotspots and coldspots of host richness. Further, our framework helps explain patterns like a unique pool of merbecoviruses in the Neotropics, a recently discovered lineage of divergent nobecoviruses in Madagascar, and-most importantly-hotspots of diversification in southeast Asia, sub-Saharan Africa, and the Middle East that correspond to the site of previous zoonotic emergence events. Our framework may help identify hotspots of future risk that have also been previously overlooked, like West Africa and the Indian subcontinent, and may more broadly help researchers understand how host ecology shapes the evolution and diversity of pandemic threats.

Viral genomic features predict orthopoxvirus reservoir hosts.

Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs. We demonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range.

Network embedding unveils the hidden interactions in the mammalian virome.

Predicting host-virus interactions is fundamentally a network science problem. We develop a method for bipartite network prediction that combines a recommender system (linear filtering) with an imputation algorithm based on low-rank graph embedding. We test this method by applying it to a global database of mammal-virus interactions and thus show that it makes biologically plausible predictions that are robust to data biases. We find that the mammalian virome is under-characterized anywhere in the world. We suggest that future virus discovery efforts could prioritize the Amazon Basin (for its unique coevolutionary assemblages) and sub-Saharan Africa (for its poorly characterized zoonotic reservoirs). Graph embedding of the imputed network improves predictions of human infection from viral genome features, providing a shortlist of priorities for laboratory studies and surveillance. Overall, our study indicates that the global structure of the mammal-virus network contains a large amount of information that is recoverable, and this provides new insights into fundamental biology and disease emergence.

A framework for understanding and predicting orthohantavirus functional traits.

Orthohantaviruses present a global public health threat; there are 58 distinct viruses currently recognized and case fatality of pathogenic orthohantaviruses ranges from <0.1% to 50%. An Old World versus New World dichotomy is frequently applied to distinguish human diseases caused by orthohantaviruses. However, this geographic grouping masks the importance of phylogeny and virus-host ecology in shaping orthohantavirus traits, especially since related arvicoline rodents and their orthohantaviruses are found in both regions. We argue that orthohantaviruses can be separated into three phylogenetically based rodent host groups with differences in key functional traits, including human disease, transmission route, and virus-host fidelity. This framework can help understand and predict traits of under-studied and newly discovered orthohantaviruses and guide public health and biosafety policy.

Acute effects of moderate vs. vigorous endurance exercise on urinary metabolites in healthy, young, physically active men-A multi-platform metabolomics approach.

Introduction: Endurance exercise alters whole-body as well as skeletal muscle metabolism and physiology, leading to improvements in performance and health. However, biological mechanisms underlying the body's adaptations to different endurance exercise protocols are not entirely understood. Methods: We applied a multi-platform metabolomics approach to identify urinary metabolites and associated metabolic pathways that distinguish the acute metabolic response to two endurance exercise interventions at distinct intensities. In our randomized crossover study, 16 healthy, young, and physically active men performed 30 min of continuous moderate exercise (CME) and continuous vigorous exercise (CVE). Urine was collected during three post-exercise sampling phases (U01/U02/U03: until 45/105/195 min post-exercise), providing detailed temporal information on the response of the urinary metabolome to CME and CVE. Also, fasting spot urine samples were collected pre-exercise (U00) and on the following day (U04). While untargeted two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) led to the detection of 608 spectral features, 44 metabolites were identified and quantified by targeted nuclear magnetic resonance (NMR) spectroscopy or liquid chromatography-mass spectrometry (LC-MS). Results: 104 urinary metabolites showed at least one significant difference for selected comparisons of sampling time points within or between exercise trials as well as a relevant median fold change >1.5 or <0. 6 ¯ (NMR, LC-MS) or >2.0 or <0.5 (GC×GC-MS), being classified as either exercise-responsive or intensity-dependent. Our findings indicate that CVE induced more profound alterations in the urinary metabolome than CME, especially at U01, returning to baseline within 24 h after U00. Most differences between exercise trials are likely to reflect higher energy requirements during CVE, as demonstrated by greater shifts in metabolites related to glycolysis (e.g., lactate, pyruvate), tricarboxylic acid cycle (e.g., cis-aconitate, malate), purine nucleotide breakdown (e.g., hypoxanthine), and amino acid mobilization (e.g., alanine) or degradation (e.g., 4-hydroxyphenylacetate). Discussion: To conclude, this study provided first evidence of specific urinary metabolites as potential metabolic markers of endurance exercise intensity. Future studies are needed to validate our results and to examine whether acute metabolite changes in urine might also be partly reflective of mechanisms underlying the health- or performance-enhancing effects of endurance exercise, particularly if performed at high intensities.

Human movement and transmission dynamics early in Ebola outbreaks.

Human movement drives the transmission and spread of communicable pathogens. It is especially influential for emerging pathogens when population immunity is low and spillover events are rare. We digitized serial printed maps to measure transportation networks (roads and rivers) in Central and West Africa as proxies for population mobility to assess relationships between movement and Ebola transmission. We find that the lengths of roads and rivers in close proximity to spillover sites at or near the time of spillover events are significantly correlated with the number of EVD cases, particularly in the first 100 days of each outbreak. Early management and containment efforts along transportation networks may be beneficial in mitigation during the early days of transmission and spatial spread for Ebola outbreaks.

Severe acute respiratory disease in American mink experimentally infected with SARS-CoV-2.

An animal model that fully recapitulates severe COVID-19 presentation in humans has been a top priority since the discovery of SARS-CoV-2 in 2019. Although multiple animal models are available for mild to moderate clinical disease, models that develop severe disease are still needed. Mink experimentally infected with SARS-CoV-2 developed severe acute respiratory disease, as evident by clinical respiratory disease, radiological, and histological changes. Virus was detected in nasal, oral, rectal, and fur swabs. Deep sequencing of SARS-CoV-2 from oral swabs and lung tissue samples showed repeated enrichment for a mutation in the gene encoding nonstructural protein 6 in open reading frame 1ab. Together, these data indicate that American mink develop clinical features characteristic of severe COVID-19 and, as such, are uniquely suited to test viral countermeasures.

An ACE2-dependent Sarbecovirus in Russian bats is resistant to SARS-CoV-2 vaccines.

Spillover of sarbecoviruses from animals to humans has resulted in outbreaks of severe acute respiratory syndrome SARS-CoVs and the ongoing COVID-19 pandemic. Efforts to identify the origins of SARS-CoV-1 and -2 has resulted in the discovery of numerous animal sarbecoviruses-the majority of which are only distantly related to known human pathogens and do not infect human cells. The receptor binding domain (RBD) on sarbecoviruses engages receptor molecules on the host cell and mediates cell invasion. Here, we tested the receptor tropism and serological cross reactivity for RBDs from two sarbecoviruses found in Russian horseshoe bats. While these two viruses are in a viral lineage distinct from SARS-CoV-1 and -2, the RBD from one virus, Khosta 2, was capable of using human ACE2 to facilitate cell entry. Viral pseudotypes with a recombinant, SARS-CoV-2 spike encoding for the Khosta 2 RBD were resistant to both SARS-CoV-2 monoclonal antibodies and serum from individuals vaccinated for SARS-CoV-2. Our findings further demonstrate that sarbecoviruses circulating in wildlife outside of Asia also pose a threat to global health and ongoing vaccine campaigns against SARS-CoV-2.

Zaire ebolavirus surveillance near the Bikoro region of the Democratic Republic of the Congo during the 2018 outbreak reveals presence of seropositive bats.

On the 8th of May, 2018, an outbreak of Ebola virus disease (EVD) was declared, originating in the Bikoro region of the Democratic Republic of the Congo (DRC) near the border with neighboring Republic of the Congo (ROC). Frequent trade and migration occur between DRC and ROC-based communities residing along the Congo River. In June 2018, a field team was deployed to determine whether Zaire ebolavirus (Ebola virus (EBOV)) was contemporaneously circulating in local bats at the human-animal interface in ROC near the Bikoro EVD outbreak. Samples were collected from bats in the Cuvette and Likouala departments, ROC, bordering the Équateur Province in DRC where the Bikoro EVD outbreak was first detected. EBOV genomic material was not detected in bat-derived samples by targeted quantitative reverse transcription-polymerase chain reaction or by family-level consensus polymerase chain reaction; however, serological data suggests recent exposure to EBOV in bats in the region. We collected serum from 144 bats in the Cuvette department with 6.9% seropositivity against the EBOV glycoprotein and 14.3% seropositivity for serum collected from 27 fruit bats and one Molossinae in the Likouala department. We conclude that proactive investment in longitudinal sampling for filoviruses at the human-animal interface, coupled with ecological investigations are needed to identify EBOV wildlife reservoirs.

Imported SARS-COV-2 Variants of Concern Drove Spread of Infections Across Kenya During the Second Year of the Pandemic.

Background: Using classical and genomic epidemiology, we tracked the COVID-19 pandemic in Kenya over 23 months to determine the impact of SARS-CoV-2 variants on its progression. Methods: SARS-CoV-2 surveillance and testing data were obtained from the Kenya Ministry of Health, collected daily from 306 health facilities. COVID-19-associated fatality data were also obtained from these health facilities and communities. Whole SARS-CoV-2 genome sequencing were carried out on 1241 specimens. Results: Over the pandemic duration (March 2020 - January 2022) Kenya experienced five waves characterized by attack rates (AR) of between 65.4 and 137.6 per 100,000 persons, and intra-wave case fatality ratios (CFR) averaging 3.5%, two-fold higher than the national average COVID-19 associated CFR. The first two waves that occurred before emergence of global variants of concerns (VoC) had lower AR (65.4 and 118.2 per 100,000). Waves 3, 4, and 5 that occurred during the second year were each dominated by multiple introductions each, of Alpha (74.9% genomes), Delta (98.7%), and Omicron (87.8%) VoCs, respectively. During this phase, government-imposed restrictions failed to alleviate pandemic progression, resulting in higher attack rates spread across the country. Conclusions: The emergence of Alpha, Delta, and Omicron variants was a turning point that resulted in widespread and higher SARS-CoV-2 infections across the country.

The Global Virome in One Network (VIRION): an Atlas of Vertebrate-Virus Associations.

Data that catalogue viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open sharing, posing challenges for research on macroecology, evolution, and public health. Here, we solve this problem by establishing a dynamically maintained database of vertebrate-virus associations, called The Global Virome in One Network (VIRION). The VIRION database has been assembled through both reconciliation of static data sets and integration of dynamically updated databases. These data sources are all harmonized against one taxonomic backbone, including metadata on host and virus taxonomic validity and higher classification; additional metadata on sampling methodology and evidence strength are also available in a harmonized format. In total, the VIRION database is the largest open-source, open-access database of its kind, with roughly half a million unique records that include 9,521 resolved virus "species" (of which 1,661 are ICTV ratified), 3,692 resolved vertebrate host species, and 23,147 unique interactions between taxonomically valid organisms. Together, these data cover roughly a quarter of mammal diversity, a 10th of bird diversity, and ∼6% of the estimated total diversity of vertebrates, and a much larger proportion of their virome than any previous database. We show how these data can be used to test hypotheses about microbiology, ecology, and evolution and make suggestions for best practices that address the unique mix of evidence that coexists in these data. IMPORTANCE Animals and their viruses are connected by a sprawling, tangled network of species interactions. Data on the host-virus network are available from several sources, which use different naming conventions and often report metadata in different levels of detail. VIRION is a new database that combines several of these existing data sources, reconciles taxonomy to a single consistent backbone, and reports metadata in a format designed by and for virologists. Researchers can use VIRION to easily answer questions like "Can any fish viruses infect humans?" or "Which bats host coronaviruses?" or to build more advanced predictive models, making it an unprecedented step toward a full inventory of the global virome.

Three-Week Old Pigs Are Not Susceptible to Productive Infection with SARS-COV-2.

As the COVID-19 pandemic moves into its third year, there remains a need for additional animal models better recapitulating severe COVID to study SARS-CoV-2 pathogenesis and develop countermeasures, especially treatment options. Pigs are known intermediate hosts for many viruses with zoonotic potential and are susceptible to infection with alpha, beta and delta genera of coronaviruses. Herein, we infected young (3 weeks of age) pigs with SARS-CoV-2 using a combination of respiratory and parenteral inoculation routes. Pigs did not develop clinical disease, nor macroscopic or microscopic pathologic lesions upon SARS-CoV-2 infection. Despite occasional low levels of SARS-CoV-2 genomic RNA in the respiratory tract, subgenomic RNA and infectious virus were never found, and SARS-CoV-2-specific adaptive immune responses were not detectable over the 13-day study period. We concluded that pigs are not susceptible to productive SARS-CoV-2 infection and do not serve as a SARS-CoV-2 reservoir for zoonotic transmission.

Mammal virus diversity estimates are unstable due to accelerating discovery effort.

Host-virus association data underpin research into the distribution and eco-evolutionary correlates of viral diversity and zoonotic risk across host species. However, current knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are either constant or accelerating, with little evidence of declines towards viral richness asymptotes, even in highly sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species' ranked viral richness. Our results illustrate that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since it is feasible that an analysis conducted today could draw quite different conclusions than one conducted only a decade ago.

The science of the host-virus network.

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.

Surface‒Aerosol Stability and Pathogenicity of Diverse Middle East Respiratory Syndrome Coronavirus Strains, 2012‒2018.

Middle East respiratory syndrome coronavirus (MERS-CoV) infects humans and dromedary camels and is responsible for an ongoing outbreak of severe respiratory illness in humans in the Middle East. Although some mutations found in camel-derived MERS-CoV strains have been characterized, most natural variation found across MERS-CoV isolates remains unstudied. We report on the environmental stability, replication kinetics, and pathogenicity of several diverse isolates of MERS-CoV, as well as isolates of severe acute respiratory syndrome coronavirus 2, to serve as a basis of comparison with other stability studies. Although most MERS-CoV isolates had similar stability and pathogenicity in our experiments, the camel-derived isolate C/KSA/13 had reduced surface stability, and another camel isolate, C/BF/15, had reduced pathogenicity in a small animal model. These results suggest that although betacoronaviruses might have similar environmental stability profiles, individual variation can influence this phenotype, underscoring the need for continual global viral surveillance.

The future of zoonotic risk prediction.

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

A randomized, multicenter phase II study comparing efficacy, safety and tolerability of two dosing regimens of cisplatin and pemetrexed in patients with advanced or metastatic non-small-cell lung cancer.

BACKGROUND: Pemetrexed and cisplatin is a first-line standard in non-squamous non-small-cell lung cancer without targetable mutations. It became the backbone of checkpoint-inhibitor-chemotherapy combinations. Single high doses of cisplatin pose toxicity risks and require hyperhydration, potentially prolonging outpatient application. The aim of this study was to compare efficacy, safety and tolerability of split-dose cisplatin with the standard schedule. METHODS: Patients with metastatic non-squamous non-small-cell lung cancer were randomly assigned to up to six 21-day cycles of pemetrexed 500 mg/m2 and cisplatin 75 mg/m2 on day 1 (arm A), or pemetrexed 500 mg/m2 (day 1) and cisplatin 40 mg/m2 (day 1 + 8, arm B), followed by pemetrexed maintenance. Primary endpoint was objective response rate. Secondary objectives were overall survival, progression-free survival, time to progression, treatment compliance, toxicity profile, and quality of life. RESULTS: We enrolled 130 patients (129 evaluable). Median cycle numbers in A and B were six (1-6) and five (1-6). Dose intensities were comparable between arms. More patients in A received pemetrexed maintenance (24.2% versus 11.1%). With 16 (24.2%) in A and 19 (30.2%) patients in B achieving objective responses [odds ratio 0.74 (0.34-1.62), p = 0.55] the primary endpoint was met. Overall survival was not different between arms (median 14.4 versus 14.9 months); [HR = 1.07; (0.68-1.68), p = 0.78]. Median progression-free survival was 7.0 months in A and 6.2 months in B [HR = 1.63; (1.17-2.38); p = 0.01]. Adverse events of CTCAE grade ⩾3, particularly hematological, were more frequent in B. No difference in grade 4 and 5 infections between arms was noted. Treatment-related asthenia and nausea/vomiting of any grade were more frequent in A. Global health status, fatigue and constipation measured on day 1 of cycle 4 demonstrated superior scores in B. CONCLUSION: Pemetrexed and split-dose cisplatin is safe and effective. Advantages of split-dose cisplatin with regard to specific toxicities allow personalization of this important chemotherapy backbone. TRIAL REGISTRATION: European Clinical Trials Database (EudraCT) number 2011-001963-37.

Development and validation of portable, field-deployable Ebola virus point-of-encounter diagnostic assay for wildlife surveillance.

Early detection of Ebola virus spillover into wildlife is crucial for rapid response. We developed and validated a portable, cold-chain independent Ebola virus RT-qPCR assay. METHODS: The field syringe-based RNA extraction method was compared with a conventional laboratory-based spin-column RNA extraction method. Next, the qPCR efficiency and limit of detection of the assay was compared to standard laboratory-based reagents and equipment. The specificity of the assay was confirmed by testing against multiple Zaire Ebolavirus (EBOV) variants and other ebolavirus species. Lastly, swabs from an EBOV-infected non-human primate carcass, stored at environmental conditions mimicking central and west Africa, were analyzed to mimic in field conditions. RESULTS: The syringe-based RNA extraction method performed comparably to a standard laboratory spin-column-based method. The developed assay was comparable in sensitivity and specificity to standard laboratory-based diagnostic assays. The assay specifically detected EBOV and not any of the other tested ebolavirus species, including Reston ebolavirus, Sudan ebolavirus, Bundibugyo ebolavirus, and Tai Forrest ebolavirus. Notably, the assays limit of detection for EBOV isolates were all below 4 genome copies/µL. The assay was able to detect EBOV in oral, nasal, thoracic cavity, and conjunctiva swabs obtained from an infected non-human primate. CONCLUSION: We developed a field-based Ebolavirus assay which is comparable in sensitivity and specificity to laboratory-based assays. Currently, the assay is being incorporated into wildlife carcass surveillance in the Republic of the Congo and is being adapted for other infectious disease agents.

Unveiling the Correlation between Inadequate Energy/Macronutrient Intake and Clinical Alterations in Volunteers at Risk of Metabolic Syndrome by a Predictive Model.

Although lifestyle-based interventions are the most effective to prevent metabolic syndrome (MetS), there is no definitive agreement on which nutritional approach is the best. The aim of the present retrospective analysis was to identify a multivariate model linking energy and macronutrient intake to the clinical features of MetS. Volunteers at risk of MetS (F = 77, M = 80) were recruited in four European centres and finally eligible for analysis. For each subject, the daily energy and nutrient intake was estimated using the EPIC questionnaire and a 24-h dietary recall, and it was compared with the dietary reference values. Then we built a predictive model for a set of clinical outcomes computing shifts from recommended intake thresholds. The use of the ridge regression, which optimises prediction performances while retaining information about the role of all the nutritional variables, allowed us to assess if a clinical outcome was manly dependent on a single nutritional variable, or if its prediction was characterised by more complex interactions between the variables. The model appeared suitable for shedding light on the complexity of nutritional variables, which effects could be not evident with univariate analysis and must be considered in the framework of the reciprocal influence of the other variables.