Transmissibility of emerging viral zoonoses

SARS-CoV-2 infection in animals: Patterns, transmission routes, and drivers

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is more widespread in animals than previously thought, and it may be able to infect a wider range of domestic and wild species. To effectively control the spread of the virus and protect animal health, it is crucial to understand the cross-species transmission mechanisms and risk factors of SARS-CoV-2. This article collects published literature on SARS-CoV-2 in animals and examines the distribution, transmission routes, biophysical, and anthropogenic drivers of infected animals. The reported cases of infection in animals are mainly concentrated in South America, North America, and Europe, and species affected include lions, white-tailed deer, pangolins, minks, and cats. Biophysical factors influencing infection of animals with SARS-CoV-2 include environmental determinants, high-risk landscapes, air quality, and susceptibility of different animal species, while anthropogenic factors comprise human behavior, intensive livestock farming, animal markets, and land management. Due to current research gaps and surveillance capacity shortcomings, future mitigation strategies need to be designed from a One Health perspective, with research focused on key regions with significant data gaps in Asia and Africa to understand the drivers, pathways, and spatiotemporal dynamics of interspecies transmission.

Investigating and combatting the key drivers of viral zoonoses in Africa: an analysis of eight epidemics

Investigating the interplay of factors that result in a viral zoonotic outbreak is difficult, though it is increasingly important. As anthropogenic influences shift the delicate balance of ecosystems, new zoonoses emerge in humans. Sub-Saharan Africa is a notable hotspot for zoonotic disease due to abundant competent mammalian reservoir hosts. Furthermore, poverty, corruption, and an overreliance on natural resources play considerable roles in depleting biological resources, exacerbating the population's susceptibility. Unsurprisingly, viral zoonoses have emerged in Africa, including HIV/AIDS, Ebola, Avian influenza, Lassa fever, Zika, and Monkeypox. These diseases are among the principal causes of death in endemic areas. Though typically distinct in their manifestations, viral zoonoses are connected by underlying, definitive factors. This review summarises vital findings on viral zoonoses in Africa using nine notable case studies as a benchmark for future studies. We discuss the importance of ecological recuperation and protection as a central strategy to control zoonotic diseases. Emphasis was made on moderating key drivers of zoonotic diseases to forestall future pandemics. This is in conjunction with attempts to redirect efforts from reactive to pre-emptive through a multidisciplinary "one health" approach.

Predicting zoonotic potential of viruses: where are we?

The prospect of identifying high-risk viruses and designing interventions to pre-empt their emergence into human populations is enticing, but controversial, particularly when used to justify large-scale virus discovery initiatives. We review the current state of these efforts, identifying three broad classes of predictive models that have differences in data inputs that define their potential utility for triaging newly discovered viruses for further investigation. Prospects for model predictions of public health risk to guide preparedness depend not only on computational improvements to algorithms, but also on more efficient data generation in laboratory, field and clinical settings. Beyond public health applications, efforts to predict zoonoses provide unique research value by creating generalisable understanding of the ecological and evolutionary factors that promote viral emergence.

Climate change increases cross-species viral transmission risk

At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals^1,2. However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife^3,4. In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence. Here we simulate potential hotspots of future viral sharing, using a phylogeographical model of the mammal-virus network, and projections of geographical range shifts for 3,139 mammal species under climate-change and land-use scenarios for the year 2070. We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times. Owing to their unique dispersal ability, bats account for the majority of novel viral sharing and are likely to share viruses along evolutionary pathways that will facilitate future emergence in humans. Notably, we find that this ecological transition may already be underway, and holding warming under 2 °C within the twenty-first century will not reduce future viral sharing. Our findings highlight an urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking the range shifts of species, especially in tropical regions that contain the most zoonoses and are experiencing rapid warming.

Climate change increases cross-species viral transmission risk

At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals^1,2. However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife^3,4. In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence. Here we simulate potential hotspots of future viral sharing, using a phylogeographical model of the mammal-virus network, and projections of geographical range shifts for 3,139 mammal species under climate-change and land-use scenarios for the year 2070. We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times. Owing to their unique dispersal ability, bats account for the majority of novel viral sharing and are likely to share viruses along evolutionary pathways that will facilitate future emergence in humans. Notably, we find that this ecological transition may already be underway, and holding warming under 2 °C within the twenty-first century will not reduce future viral sharing. Our findings highlight an urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking the range shifts of species, especially in tropical regions that contain the most zoonoses and are experiencing rapid warming.

Bats host the most virulent-but not the most dangerous-zoonotic viruses

SignificanceThe clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective "burden" on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human-animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.

Bats host the most virulent-but not the most dangerous-zoonotic viruses

SignificanceThe clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective "burden" on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human-animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.

Excess mortality after hip fracture during COVID-19 pandemic: More about disruption, less about virulence—Lesson from a trauma center

To date, literature has depicted an increase in mortality among patients with hip fractures, directly related to acute coronavirus disease 2019 (COVID-19) infection and not due to underlying comorbidities. Usual orthogeriatric pathway in our Department was disrupted during the pandemic. This study aimed to evaluate early mortality within 30 days, in 2019 and 2020 in our Level 1 trauma-center. We compared two groups of patients aged >60 years, with osteoporotic upper hip fractures, in February/March/April 2020 and February/March/April 2019, in our level 1 trauma center. A total of 102 and 79 patients met the eligibility criteria in 2019 and 2020, respectively. Mortality was evaluated, merging our database with the French open database for death from the INSEE, which is prospectively updated each month. Causes of death were recorded. Charlson Comorbidity Index was evaluated for comorbidities, Instrumental Activity of Daily Living (IADL), and Activity of Daily Living (ADL) scores were assessed for autonomy. There were no differences in age, sex, fracture type, Charlson Comorbidity Index, IADL, and ADL. 19 patients developed COVID-19 infection. The 30-day survival was 97% (95% CI, 94%–100%) in 2019 and 86% (95% CI, 79%–94%) in 2020 (HR = 5, 95%CI, 1.4–18.2, p = 0.013). In multivariable Cox’PH model, the period (2019/2020) was significantly associated to the 30-day mortality (HR = 6.4, 95%CI, 1.7–23, p = 0.005) and 6-month mortality (HR = 3.4, 95%CI, 1.2–9.2, p = 0.01). COVID infection did not modify significantly the 30-day and 6-month mortality. This series brought new important information, early mortality significantly increased because of underlying disease decompensation. Minimal comprehensive care should be maintained in all circumstances in order to avoid excess of mortality among elderly population with hip fractures.

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.

Lateral flow assays (LFA) as an alternative medical diagnosis method for detection of virus species: The intertwine of nanotechnology with sensing strategies

Viruses are responsible for multiple infections in humans that impose huge health burdens on individuals and populations worldwide. Therefore, numerous diagnostic methods and strategies have been developed for prevention, management, and decreasing the burden of viral diseases, each having its advantages and limitations. Viral infections are commonly detected using serological and nucleic acid-based methods. However, these conventional and clinical approaches have some limitations that can be resolved by implementing other detector devices. Therefore, the search for sensitive, selective, portable, and costless approaches as efficient alternative clinical methods for point of care testing (POCT) analysis has gained much attention in recent years. POCT is one of the ultimate goals in virus detection, and thus, the tests need to be rapid, specific, sensitive, accessible, and user-friendly. In this review, after a brief overview of viruses and their characteristics, the conventional viral detection methods, the clinical approaches, and their advantages and shortcomings are firstly explained. Then, LFA systems working principles, benefits, classification are discussed. Furthermore, the studies regarding designing and employing LFAs in diagnosing different types of viruses, especially SARS-CoV-2 as a main concern worldwide and innovations in the LFAs' approaches and designs, are comprehensively discussed here. Furthermore, several strategies addressed in some studies for overcoming LFA limitations like low sensitivity are reviewed. Numerous techniques are adopted to increase sensitivity and perform quantitative detection. Employing several visualization methods, using different labeling reporters, integrating LFAs with other detection methods to benefit from both LFA and the integrated detection device advantages, and designing unique membranes to increase reagent reactivity, are some of the approaches that are highlighted.

Predictors of zoonotic potential in helminths

Helminths are parasites that cause disease at considerable cost to public health and present a risk for emergence as novel human infections. Although recent research has elucidated characteristics conferring a propensity to emergence in other parasite groups (e.g. viruses), the understanding of factors associated with zoonotic potential in helminths remains poor. We applied an investigator-directed learning algorithm to a global dataset of mammal helminth traits to identify factors contributing to spillover of helminths from wild animal hosts into humans. We characterized parasite traits that distinguish between zoonotic and non-zoonotic species with 91% accuracy. Results suggest that helminth traits relating to transmission (e.g. definitive and intermediate hosts) and geography (e.g. distribution) are more important to discriminating zoonotic from non-zoonotic species than morphological or epidemiological traits. Whether or not a helminth causes infection in companion animals (cats and dogs) is the most important predictor of propensity to cause human infection. Finally, we identified helminth species with high modelled propensity to cause zoonosis (over 70%) that have not previously been considered to be of risk. This work highlights the importance of prioritizing studies on the transmission of helminths that infect pets and points to the risks incurred by close associations with these animals. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

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'.

Inherent virus characteristics and host range drive the zoonotic and emerging potential of viruses

Understanding the zoonotic and emerging potential of viruses is critical to prevent and control spread that can cause disease epidemics or pandemics. We developed a database using the most up-to-date information from the International Committee on Taxonomy of Viruses (4958 virus species) and identified 1479 vertebrate virus species and their host ranges. Viral traits and host ranges were then used as predictors in generalized linear mixed models for three host-associated outcomes - confirmed zoonotic, potential zoonotic and disease emergence. We identified significant interactions between host range and viral characteristics, not previously reported, that influence the zoonotic and emergence potential of viruses. Bat- and livestock-adapted viruses posed high risk, and the risk increased substantially if these viruses were also present in other vertebrates or were not reported from invertebrates. Our model predicted 39 viruses of interest that have never been reported to have zoonotic potential (27) or to potentially become emerging human viruses (12). We conclude that nucleic acid type is important in identifying the zoonotic and emerging potential of viruses. We recommend enhanced surveillance and monitoring of these virus species identified with a zoonotic and emerging potential to mitigate disease outbreaks and future epidemics.

Zoonotic spillover: Understanding basic aspects for better prevention

The transmission of pathogens from wild animals to humans is called “zoonotic spillover”. Most human infectious diseases (60-75%) are derived from pathogens that originally circulated in non-human animal species. This demonstrates that spillover has a fundamental role in the emergence of new human infectious diseases. Understanding the factors that facilitate the transmission of pathogens from wild animals to humans is essential to establish strategies focused on the reduction of the frequency of spillover events. In this context, this article describes the basic aspects of zoonotic spillover and the main factors involved in spillover events, considering the role of the inter-species interactions, phylogenetic distance between host species, environmental drivers, and specific characteristics of the pathogens, animals, and humans. As an example, the factors involved in the emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic are discussed, indicating what can be learned from this public health emergency, and what can be applied to the Brazilian scenario. Finally, this article discusses actions to prevent or reduce the frequency of zoonotic spillover events.

A scientometric analysis on coronaviruses research (1900-2020): Time for a continuous, cooperative and global approach

Infectious diseases remain a complex, recurring, and challenging public health hazard. Coronaviruses have led to multidimensional consequences on health, mobility, and socio-economic conditions. Despite the significance and magnitude of impact from epidemics to the pandemic, literature is sparse on comprehensive coronaviruses related research performance over time. This study aimed at a scientometric evaluation of coronaviruses related literature including COVID-19. Data related to Coronavirus research was extracted from the Web of Science (WoS). All types of publications (28,846) were included and retrieved. To measure the quantity and quality of the publications, "R-Bibliometrix" package was used for detailed analysis exploring a wide range of indicators. Generally, an increasing trend was observed over time led by the USA and China followed by the United Kingdom, Europe, and few other developed countries. The last two decades contributed around 39.5% of documents while only 06 months of 2020 additionally contributed around 46.5% of total documents. Earlier shorter spikes of increased post epidemic publications followed by decreased productivity were detected in the last 2 decades and showed a lack of continuity-'a research epidemic following a disease epidemic'. Articles (53.4%) were the most common publication type. Journal of Virology, British Medical Journal (BMJ), and Virology were leading sources while BMJ, and Lancet showed increased contributions recently. Overall, similar trends of top authors were observed in terms of productivity, impact, collaborations, funding sources, and affiliations with few exceptions mainly from affected regions. Top 20 countries contributed >89% of documents suggesting a lack of global efforts. Networking was found to be mainly among developed nations with limited contributions from resource-limited countries perhaps requiring more cooperation. Recent post-COVID publications rise is highest, unprecedented, and rapidly growing. Authors strongly recommend recent COVID-19 pandemic as a call for continuous, more cooperative, and collective global research.

Preparing for Emerging Zoonotic Viruses

The risk of emergence and spread of novel human pathogens originating from an animal reservoir has increased in the past decades. However, the unpredictable nature of disease emergence makes surveillance and preparedness challenging. Knowledge of general risk factors for emergence and spread, combined with local level data is needed to develop a risk-based methodology for early detection. This involves the implementation of the One Health approach, integrating human, animal and environmental health sectors, as well as social sciences, bioinformatics and more. Recent technical advances, such as metagenomic sequencing, will aid the rapid detection of novel pathogens on the human-animal interface.

Global discovery of human-infective RNA viruses: A modelling analysis

RNA viruses are a leading cause of human infectious diseases and the prediction of where new RNA viruses are likely to be discovered is a significant public health concern. Here, we geocoded the first peer-reviewed reports of 223 human RNA viruses. Using a boosted regression tree model, we matched these virus data with 33 explanatory factors related to natural virus distribution and research effort to predict the probability of virus discovery across the globe in 2010–2019. Stratified analyses by virus transmissibility and transmission mode were also performed. The historical discovery of human RNA viruses has been concentrated in eastern North America, Europe, central Africa, eastern Australia, and north-eastern South America. The virus discovery can be predicted by a combination of socio-economic, land use, climate, and biodiversity variables. Remarkably, vector-borne viruses and strictly zoonotic viruses are more associated with climate and biodiversity whereas non-vector-borne viruses and human transmissible viruses are more associated with GDP and urbanization. The areas with the highest predicted probability for 2010–2019 include three new regions including East and Southeast Asia, India, and Central America, which likely reflect both increasing surveillance and diversity of their virome. Our findings can inform priority regions for investment in surveillance systems for new human RNA viruses.

There is a lack of evidence on the factors driving the discovery of RNA viruses in general globally. Here, we recorded the initial discovery sites of all 223 human RNA viruses and revealed its global distribution pattern. By using a machine learning method, we found that the virus discovery was driven by a combination of variables describing socio-economic level, land use, climate and biodiversity, with GDP and GDP growth found to be the two leading predictors. We also predicted the probability of virus discovery in 2010–2019 across the globe, and identified three new areas (East and Southeast Asia, India, and Central America) in addition to the historical high-risk areas. The further stratified analyses (distinguishing viruses transmissible in humans or strictly zoonotic, and vector-borne or non-vector-borne) helped pinpoint the explanatory factors for the discovery of specific categories of viruses and confirm the plausibility of the model. The results of our study further understanding of the spatial distribution of human RNA virus discovery, and map the likelihood of further discoveries across the world. By identifying where new viruses are most likely to be discovered in the near future the study helps identify priority areas for surveillance.

Combating SARS-CoV-2: leveraging microbicidal experiences with other emerging/re-emerging viruses

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan City, China, late in December 2019 is an example of an emerging zoonotic virus that threatens public health and international travel and commerce. When such a virus emerges, there is often insufficient specific information available on mechanisms of virus dissemination from animal-to-human or from person-to-person, on the level or route of infection transmissibility or of viral release in body secretions/excretions, and on the survival of virus in aerosols or on surfaces. The effectiveness of available virucidal agents and hygiene practices as interventions for disrupting the spread of infection and the associated diseases may not be clear for the emerging virus. In the present review, we suggest that approaches for infection prevention and control (IPAC) for SARS-CoV-2 and future emerging/re-emerging viruses can be invoked based on pre-existing data on microbicidal and hygiene effectiveness for related and unrelated enveloped viruses.

Integrating data mining and transmission theory in the ecology of infectious diseases

Our understanding of ecological processes is built on patterns inferred from data. Applying modern analytical tools such as machine learning to increasingly high dimensional data offers the potential to expand our perspectives on these processes, shedding new light on complex ecological phenomena such as pathogen transmission in wild populations. Here, we propose a novel approach that combines data mining with theoretical models of disease dynamics. Using rodents as an example, we incorporate statistical differences in the life history features of zoonotic reservoir hosts into pathogen transmission models, enabling us to bound the range of dynamical phenomena associated with hosts, based on their traits. We then test for associations between equilibrium prevalence, a key epidemiological metric and data on human outbreaks of rodent-borne zoonoses, identifying matches between empirical evidence and theoretical predictions of transmission dynamics. We show how this framework can be generalized to other systems through a rubric of disease models and parameters that can be derived from empirical data. By linking life history components directly to their effects on disease dynamics, our mining-modelling approach integrates machine learning and theoretical models to explore mechanisms in the macroecology of pathogen transmission and their consequences for spillover infection to humans.

The problem of scale in the prediction and management of pathogen spillover

Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

Host phylogenetic distance drives trends in virus virulence and transmissibility across the animal-human interface

Historically, efforts to assess 'zoonotic risk' have focused mainly on quantifying the potential for cross-species emergence of viruses from animal hosts. However, viruses clearly differ in relative burden, both in terms of morbidity and mortality (virulence) incurred and the capacity for sustained human-to-human transmission. Extending previously published databases, we delineated host and viral traits predictive of human mortality associated with viral spillover, viral capacity to transmit between humans following spillover and the probability of a given virus being zoonotic. We demonstrate that increasing host phylogenetic distance from humans positively correlates with human mortality but negatively correlates with human transmissibility, suggesting that the virulence induced by viruses emerging from hosts at high phylogenetic distance may limit capacity for human transmission. Our key result is that hosts most closely related to humans harbour zoonoses of lower impact in terms of morbidity and mortality, while the most distantly related hosts-in particular, order Chiroptera (bats)-harbour highly virulent zoonoses with a lower capacity for endemic establishment in human hosts. As a whole, our results emphasize the importance of understanding how zoonoses manifest in the human population and also highlight potential risks associated with multi-host transmission chains in spillover. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

Diverse picornaviruses are prevalent among free-living and laboratory rats (Rattus norvegicus) in Hungary and can cause disseminated infections

In this study, the full length genomes of three phylogenetically distant picornaviruses (family Picornaviridae) belonging to the genus Rosavirus (rat08/rRoB/HUN, MN116648), Kobuvirus (rat08/rAiA/HUN, MN116647), and Cardiovirus (rat08/rCaB/HUN, MN116646) were obtained from a single faecal sample of a free-living Norway rat (Rattus norvegicus) in Hungary using viral metagenomics and RT-PCR/Sanger sequencing. The acquired complete genomes were in silico analyzed in detail revealing the presence of a second minor open reading frame encoding an alternative Leader peptide (L*) in rat08/rCaB/HUN and a ca. 222 nt-long sequence repeat with compact secondary RNA structure in the 3' UTR of rat08/rRoB/HUN. The studied rat picornaviruses were frequently detectable by RT-PCR with relatively high viral loads ranged between 8.99E+02 and 1.29E+06 copies/ml in rat faecal samples collected from five geographically distant locations throughout Hungary. The VP1 sequence-based phylogenetic analyses show the presence of multiple, mostly location-specific lineages for all three picornaviruses. Rat rosavirus and rat cardiovirus were identified in spleen while rat cardiovirus was also detected in liver, muscle and kidney samples with variable copy numbers (6.42E+01-1.90E+05 copies/μg total RNA) suggesting extra-intestinal dissemination. Both viruses were also prevalent (70.0% and 18.2%) among two populations of laboratory rats ("Wistar-type" and "hooded-type") held in different, isolated laboratory animal units.

Designer Probiotics: The Next-Gen High Efficiency Biotherapeutics

The probiotic engineering is a cutting edge technology for improving disease diagnosis, treating gastrointestinal disorders and infectious diseases, and improving nutrition and ecological health. Use of bioengineered microorganisms in animals has different targets and prospects owing to differences in their anatomy, physiology, and feeding habits. In ruminants, the bioengineered microorganism is primarily aimed to enhance nutrient utilization, detoxify toxic plant metabolites, and lessen the enteric methanogenesis, while in non-ruminants, the bioengineered microorganisms are aimed to enhance nutrient utilizations, confer protection against pathogens, and inhibit infectious agents.

Highlights

The microorganisms can be engineered to enhance their metabolic efficiency

The bioengineered microorganisms could solve the burgeoning problem of drug-resistant pathogens

The recombinant probiotics are promising therapeutic agents against infectious diseases.