The changing face of pathogen discovery and surveillance

Clinical Metagenomic Next-Generation Sequencing for Diagnosis of Central Nervous System Infections: Advances and Challenges

Central nervous system (CNS) infections carry a substantial burden of morbidity and mortality worldwide, and accurate and timely diagnosis is required to optimize management. Metagenomic next-generation sequencing (mNGS) has proven to be a valuable tool in detecting pathogens in patients with suspected CNS infection. By sequencing microbial nucleic acids present in a patient's cerebrospinal fluid, brain tissue, or samples collected outside of the CNS, such as plasma, mNGS can detect a wide range of pathogens, including rare, unexpected, and/or fastidious organisms. Furthermore, its target-agnostic approach allows for the identification of both known and novel pathogens. This is particularly useful in cases where conventional diagnostic methods fail to provide an answer. In addition, mNGS can detect multiple microorganisms simultaneously, which is crucial in cases of mixed infections without a clear predominant pathogen. Overall, clinical mNGS testing can help expedite the diagnostic process for CNS infections, guide appropriate management decisions, and ultimately improve clinical outcomes. However, there are key challenges surrounding its use that need to be considered to fully leverage its clinical impact. For example, only a few specialized laboratories offer clinical mNGS due to the complexity of both the laboratory methods and analysis pipelines. Clinicians interpreting mNGS results must be aware of both false negatives-as mNGS is a direct detection modality and requires a sufficient amount of microbial nucleic acid to be present in the sample tested-and false positives-as mNGS detects environmental microbes and their nucleic acids, despite best practices to minimize contamination. Additionally, current costs and turnaround times limit broader implementation of clinical mNGS. Finally, there is uncertainty regarding the best practices for clinical utilization of mNGS, and further work is needed to define the optimal patient population(s), syndrome(s), and time of testing to implement clinical mNGS.

Metagenomics for Pathogen Detection During a Mass Mortality Event in Songbirds

Mass mortality events in wildlife can be indications of an emerging infectious disease. During the spring and summer of 2021, hundreds of dead passerines were reported across the eastern US. Birds exhibited a range of clinical signs including swollen conjunctiva, ocular discharge, ataxia, and nystagmus. As part of the diagnostic investigation, high-throughput metagenomic next-generation sequencing was performed across three molecular laboratories on samples from affected birds. Many potentially pathogenic microbes were detected, with bacteria forming the largest proportion; however, no singular agent was consistently identified, with many of the detected microbes also found in unaffected (control) birds and thus considered to be subclinical infections. Congruent results across laboratories have helped drive further investigation into alternative causes, including environmental contaminants and nutritional deficiencies. This work highlights the utility of metagenomic approaches in investigations of emerging diseases and provides a framework for future wildlife mortality events.

Genomic-wide analysis approach revealed genomic similarity for environmental Mexican S. Oranienburg genomes

As the human population grows, an increase in food trade is needed. This elevates the risk of epidemiological outbreaks. One of the prevalent pathogens associated with food production in Mexico has been Salmonella Oranienburg. Effective surveillance systems require microbial genetic knowledge. The objective of this work is to describe the genetic composition of Mexican S. Oranienburg genomes. For that, 53 strains from different environmental sources were isolated and sequenced. Additionally, 109 S. Oranienburg genomes were downloaded. Bioinformatic analyses were used to explore the clonal complex and genomic relatedness. A major clonal group formed by ST23 was identified comprising four STs. 202 SNPs were found the maximum difference among isolates. Virulence genes for host invasion and colonization as rpoS, fimbria type 1, and, T3SS were found common for all isolates. This study suggests that Mexican S. Oranienburg strains are potential pathogens circulating continuously in the region between host and non-host environments.

Cutaneous granulomas associated with rubella virus: A clinical review

Since the initial identification of vaccine-derived rubella virus (RuV) in the cutaneous granulomas of pediatric patients with inborn errors of immunity in 2014, more than 80 cases of RuV granulomas have been reported implicating both vaccine-derived and wild type RuV. Previously thought to arise exclusively in patients with significant immunocompromise, the identification of RuV granulomas in clinically immunocompetent patients adds nuance to our understanding of the interplay between host environment, immune dysregulation, and RuV granuloma formation. This review summarizes the literature on RuV granulomas including clinical and histopathologic features, proposed pathomechanisms supporting granuloma development, and potential therapeutic options. There is no standardized algorithm to guide the workup and diagnosis of suspected RuV granulomas. We highlight the importance of contributing RuV granuloma cases to ongoing Centers for Disease Control and Prevention surveillance efforts to monitor wild type and vaccine-derived RuV transmission. Studies advancing our understanding of RuV granulomas may provide insights into the role of viral infectious agents in granulomatous disease pathogenesis and guide the development of improved therapeutic options.

Label-free multidimensional bacterial characterization with an ultrawide detectable concentration range by microfluidic impedance cytometry

Rapid and accurate identification of bacteria is of great importance to public health in various fields, including medical diagnostics, food safety, and environmental monitoring. However, most existing bacterial detection methods have very narrow detectable concentration ranges and limited detection information, which easily leads to wrong diagnosis and treatment. This work presents a novel high-throughput microfluidic electrical impedance-based multidimensional single-bacterium profiling system for ultrawide concentration range detection and accurate differentiation of viability and Gram types of bacteria. The electrical impedance-based microfluidic cytometry is capable of multi-frequency impedance quantification, which allows profiling of the bacteria size, concentration, and membrane impedance as an indicator of bacterial viability and Gram properties in a single flow-through interrogation. It has been demonstrated that this novel impedance cytometry has an ultrawide bacterial counting range (102-108 cells per mL), and exhibits a rapid and accurate discrimination of viability and Gram types of bacteria in a label-free manner. Escherichia coli (E. coli) has been used as an analog species for the accuracy assessment of the electrical impedance-based bacterial detection system in an authentic complex beverage matrix within 24 hours. The impedance-based quantifications of viable bacteria are consistent with those obtained by the classical bacterial colony counting method (R2 = 0.996). This work could pave the way for providing a novel microfluidic cytometry system for rapid and multidimensional bacterial detection in diverse areas.

Relevance of national, regional and global virome projects on pandemics prediction, prevention, and control: a social network analysis of GVP-citing articles

BACKGROUND

The Global Virome Project (GVP) was proposed in 2018 as an evolution of the USAID PREDICT project and was presented as a "collaborative scientific initiative to discover zoonotic viral threats and stop future pandemics". The immediate response was mixed, with public health and scientific communities representatives showing skepticism, if not direct opposition.

OBJECTIVES

The economic, social, and health consequences of the coronavirus disease 2019 (COVID-19) pandemic demonstrated how unprepared the world was in the face of new pandemics. This paper analyses the impact of the GVP on the scientific and public health communities.

METHODS

Published scientific articles that cited the two 2018 seminal publications proposing the project were analysed using social network analysis methods.

FINDINGS

Encompassing the periods before and after the onset of the Covid-19 pandemic, the results indicate that (i) the concepts of the GVP have received more support than opposition in the scientific literature; (ii) its foundations should be updated to address the specific criticisms.

MAIN CONCLUSIONS

Shifting focus to national virome projects can provide tangible, regional benefits that can positively contribute towards a consensus on achieving a high level of preparedness for the ever-present possibility of the following global viral pandemic.

Characterization of the Human Blood Virome in Iranian Multiple Transfused Patients

Blood transfusion safety is an essential element of public health. Current blood screening strategies rely on targeted techniques that could miss unknown or unexpected pathogens. Recent studies have demonstrated the presence of a viral community (virobiota/virome) in the blood of healthy individuals. Here, we characterized the blood virome in patients frequently exposed to blood transfusion by using Illumina metagenomic sequencing. The virome of these patients was compared to viruses present in healthy blood donors. A total number of 155 beta-thalassemia, 149 hemodialysis, and 100 healthy blood donors were pooled with five samples per pool. Members of the Anelloviridae and Flaviviridae family were most frequently observed. Interestingly, samples of healthy blood donors harbored traces of potentially pathogenic viruses, including adeno-, rota-, and Merkel cell polyomavirus. Viruses of the Anelloviridae family were most abundant in the blood of hemodialysis patients and displayed a higher anellovirus richness. Pegiviruses (Flaviviridae) were only observed in patient populations. An overall trend of higher eukaryotic read abundance in both patient groups was observed. This might be associated with increased exposure through blood transfusion. Overall, the findings in this study demonstrated the presence of various viruses in the blood of Iranian multiple-transfused patients and healthy blood donors.

Metagenomic Detection of Divergent Insect- and Bat-Associated Viruses in Plasma from Two African Individuals Enrolled in Blood-Borne Surveillance

Metagenomic next-generation sequencing (mNGS) has enabled the high-throughput multiplexed identification of sequences from microbes of potential medical relevance. This approach has become indispensable for viral pathogen discovery and broad-based surveillance of emerging or re-emerging pathogens. From 2015 to 2019, plasma was collected from 9586 individuals in Cameroon and the Democratic Republic of the Congo enrolled in a combined hepatitis virus and retrovirus surveillance program. A subset (n = 726) of the patient specimens was analyzed by mNGS to identify viral co-infections. While co-infections from known blood-borne viruses were detected, divergent sequences from nine poorly characterized or previously uncharacterized viruses were also identified in two individuals. These were assigned to the following groups by genomic and phylogenetic analyses: densovirus, nodavirus, jingmenvirus, bastrovirus, dicistrovirus, picornavirus, and cyclovirus. Although of unclear pathogenicity, these viruses were found circulating at high enough concentrations in plasma for genomes to be assembled and were most closely related to those previously associated with bird or bat excrement. Phylogenetic analyses and in silico host predictions suggested that these are invertebrate viruses likely transmitted through feces containing consumed insects or through contaminated shellfish. This study highlights the power of metagenomics and in silico host prediction in characterizing novel viral infections in susceptible individuals, including those who are immunocompromised from hepatitis viruses and retroviruses, or potentially exposed to zoonotic viruses from animal reservoir species.

Causal Link of Human Papillomavirus in Barrett Esophagus and Adenocarcinoma: Are We There Yet?

Esophageal cancer is a relatively common malignancy worldwide with a high mortality (5-year survival of <15%). Despite screening, surveillance, improved imaging and treatment, the exponential rise in OAC continues. The strongest risk factors for OAC are chronic heartburn and metaplastic transformation of the lower third of the esophagus (Barrett's esophagus). The risk profile includes Caucasian race, male gender older age, obesity and smoking. Although the tumor risk in BO has been progressively revised downwards, the exponential rise in OAC remains unchecked. This paradox points to an unidentified missing link. Relatively recently, we provided the world's initial data for a strong association of biologically relevant hr-HPV with BD and OAC. Since then, systematic reviews and meta-analysis have documented HPV DNA prevalence rates in OAC of between 13 to 35%. In this review, we provide some evidence for a probable causal relationship between hr-HPV and OAC. This is challenging given the multifactorial etiology and long latency. Increasingly, high-risk HPV (hr-HPV) is regarded as a risk factor for OAC. This discovery will aid identification of a sub-group of high-risk progressors to esophageal cancer by surveillance and the development of effective preventive strategies including vaccination.

Deep tech innovation for parasite diagnosis: New dimensions and opportunities

By converging advanced science, engineering, and design, deep techs are bringing a great wave of future innovations by mastering challenges and problem complexity across sectors and the field of parasitology is no exception. Remarkable research and advancements can be seen in the field of parasite detection and diagnosis through smartphone applications. Supervised and unsupervised data deep learnings are heavily exploited for the development of automated neural network models for the prediction of parasites, eggs, etc., From microscopic smears and/or sample images with more than 99% accuracy. It is expected that several models will emerge in the future wherein greater attention is being paid to improving the model's accuracy. Invariably, it will increase the chances of adoption across the commercial sectors dealing in health and related applications. However, parasitic life cycle complexity, host range, morphological forms, etc., need to be considered further while developing such models to make the deep tech innovations perfect for bedside and field applications. In this review, the recent development of deep tech innovations focusing on human parasites has been discussed focusing on the present and future dimensions, opportunities, and applications.

Building a global immune system

The COVID-19 pandemic exposed global vulnerabilities to emerging infectious diseases, heralded by earlier outbreaks, that did not result in appropriate investments in surveillance, international collaboration, and response. We propose specific steps that should be taken to reduce future risks to public health, economic and political stability, and food security.

[130th anniversary of virology]

130 years ago, in 1892, our great compatriot Dmitry Iosifovich Ivanovsky (18641920) discovered a new type of pathogen viruses. Viruses have existed since the birth of life on Earth and for more than three billion years, as the biosphere evolved, they are included in interpopulation interactions with representatives of all kingdoms of life: archaea, bacteria, protozoa, algae, fungi, plants, invertebrates, and vertebrates, including the Homo sapiens (Hominidae, Homininae). Discovery of D.I. Ivanovsky laid the foundation for a new science virology. The rapid development of virology in the 20th century was associated with the fight against emerging and reemerging infections, epidemics (epizootics) and pandemics (panzootics) of which posed a threat to national and global biosecurity (tick-borne and other encephalitis, hemorrhagic fevers, influenza, smallpox, poliomyelitis, HIV, parenteral hepatitis, coronaviral and other infections). Fundamental research on viruses created the basis for the development of effective methods of diagnostics, vaccine prophylaxis, and antiviral drugs. Russian virologists continue to occupy leading positions in some priority areas of modern virology in vaccinology, environmental studies oz zoonotic viruses, studies of viral evolution in various ecosystems, and several other areas. A meaningful combination of theoretical approaches to studying the evolution of viruses with innovative methods for studying their molecular genetic properties and the creation of new generations of vaccines and antiviral drugs on this basis will significantly reduce the consequences of future pandemics or panzootics. The review presents the main stages in the formation and development of virology as a science in Russia with an emphasis on the most significant achievements of soviet and Russian virologists in the fight against viral infectious diseases.

The association between early-life gut microbiota and childhood respiratory diseases: a systematic review

Data from animal models suggest a role of early-life gut microbiota in lung immune development, and in establishing susceptibility to respiratory infections and asthma in humans. This systematic review summarises the association between infant (ages 0-12 months) gut microbiota composition measured by genomic sequencing, and childhood (ages 0-18 years) respiratory diseases (ie, respiratory infections, wheezing, or asthma). Overall, there was evidence that low α-diversity and relative abundance of particular gut-commensal bacteria genera (Bifidobacterium, Faecalibacterium, Ruminococcus, and Roseburia) are associated with childhood respiratory diseases. However, results were inconsistent and studies had important limitations, including insufficient characterisation of bacterial taxa to species level, heterogeneous outcome definitions, residual confounding, and small sample sizes. Large longitudinal studies with stool sampling during the first month of life and shotgun metagenomic approaches to improve bacterial and fungal taxa resolution are needed. Standardising follow-up times and respiratory disease definitions and optimising causal statistical approaches might identify targets for primary prevention of childhood respiratory diseases.

Passive epidemiological surveillance in wildlife in Costa Rica identifies pathogens of zoonotic and conservation importance

Epidemiological surveillance systems for pathogens in wild species have been proposed as a preventive measure for epidemic events. These systems can minimize the detrimental effects of an outbreak, but most importantly, passive surveillance systems are the best adapted to countries with limited resources. Therefore, this research aimed to evaluate the technical and infrastructural feasibility of establishing this type of scheme in Costa Rica by implementing a pilot program targeting the detection of pathogens of zoonotic and conservation importance in wildlife. Between 2018 and 2020, 85 carcasses of free-ranging vertebrates were admitted for post-mortem and microbiology analysis. However, we encountered obstacles mainly related to the initial identification of cases and limited local logistics capacity. Nevertheless, this epidemiological surveillance scheme allowed us to estimate the general state of health of the country’s wildlife by establishing the causes of death according to pathological findings. For instance, 60% (51/85) of the deaths were not directly associated with an infectious agent. Though in 37.6% (32/85) of these cases an infectious agent associated or not with disease was detected. In 27.1% (23/85) of the cases, death was directly related to infectious agents. Furthermore, 12.9% (11/85), the cause of death was not determined. Likewise, this wildlife health monitoring program allowed the detection of relevant pathogens such as Canine Distemper Virus, Klebsiella pneumoniae, Angiostrongylus spp., Baylisascaris spp., among others. Our research demonstrated that this passive surveillance scheme is cost-effective and feasible in countries with limited resources. This passive surveillance can be adapted to the infrastructure dedicated to monitoring diseases in productive animals according to the scope and objectives of monitoring wildlife specific to each region. The information generated from the experience of the initial establishment of a WHMP is critical to meeting the challenges involved in developing this type of scheme in regions with limited resources and established as hotspots for emerging infectious diseases.

Climate Change Effects on Pathogen Emergence: Artificial Intelligence to Translate Big Data for Mitigation

Plant pathology has developed a wide range of concepts and tools for improving plant disease management, including models for understanding and responding to new risks from climate change. Most of these tools can be improved using new advances in artificial intelligence (AI), such as machine learning to integrate massive data sets in predictive models. There is the potential to develop automated analyses of risk that alert decision-makers, from farm managers to national plant protection organizations, to the likely need for action and provide decision support for targeting responses. We review machine-learning applications in plant pathology and synthesize ideas for the next steps to make the most of these tools in digital agriculture. Global projects, such as the proposed global surveillance system for plant disease, will be strengthened by the integration of the wide range of new data, including data from tools like remote sensors, that are used to evaluate the risk ofplant disease. There is exciting potential for the use of AI to strengthen global capacity building as well, from image analysis for disease diagnostics and associated management recommendations on farmers' phones to future training methodologies for plant pathologists that are customized in real-time for management needs in response to the current risks. International cooperation in integrating data and models will help develop the most effective responses to new challenges from climate change.

The successful use of -omic technologies to achieve the 'One Health' concept in meat producing animals

Human health and wellbeing are closely linked to healthy domestic animals, a vital wildlife, and an intact ecosystem. This holistic concept is referred to as 'One Health'. In this review, we provide an overview of the potential and the challenges for the use of modern -omics technologies, especially transcriptomics and proteomics, to implement the 'One Health' idea for food-producing animals. These high-throughput studies offer opportunities to find new potential molecular biomarkers to monitor animal health, detect pharmacological interventions and evaluate the wellbeing of farm animals in modern intensive livestock systems.

Host-pathogen protein-nucleic acid interactions: A comprehensive review

Recognition of pathogen-derived nucleic acids by host cells is an effective host strategy to detect pathogenic invasion and trigger immune responses. In the context of pathogen-specific pharmacology, there is a growing interest in mapping the interactions between pathogen-derived nucleic acids and host proteins. Insight into the principles of the structural and immunological mechanisms underlying such interactions and their roles in host defense is necessary to guide therapeutic intervention. Here, we discuss the newest advances in studies of molecular interactions involving pathogen nucleic acids and host factors, including their drug design, molecular structure and specific patterns. We observed that two groups of nucleic acid recognizing molecules, Toll-like receptors (TLRs) and the cytoplasmic retinoic acid-inducible gene (RIG)-I-like receptors (RLRs) form the backbone of host responses to pathogen nucleic acids, with additional support provided by absent in melanoma 2 (AIM2) and DNA-dependent activator of Interferons (IFNs)-regulatory factors (DAI) like cytosolic activity. We review the structural, immunological, and other biological aspects of these representative groups of molecules, especially in terms of their target specificity and affinity and challenges in leveraging host-pathogen protein-nucleic acid interactions (HP-PNI) in drug discovery.

Parasite identification in mullet fish (Mugil curema) from Chautengo Lagoon, Guerrero, Mexico, based on morphology and molecular analysis

Parasite identification is crucial in areas where no sanitary inspection is conducted on fish, especially considering that parasitic zoonoses like anisakiasis and gnathostomiasis can pose a risk for human health. In this study, parasites in mullet fish (Mugil curema) from the Chautengo Lagoon, Guerrero, Mexico, were identified by morphological and molecular methods. A total of 122 specimens weighing 317 ± 51.25 g and 19.3 ± 1.14 cm in length were assessed. Their helminthofauna was classified by measuring internal structures, total length, and maximum width; a morphometric index was also calculated for larval stages. The prevalence of parasitosis in these mullets was 91.8%, with a mean infection intensity of 4.1. The acanthocephalan Floridosentis mugilis was identified by its external and internal structures. The nematodes found were of the Anisakidae family in stage 3 (L3), with a morphology consistent with Contracaecum sp. To determine the species, the ITS ribosomal gene and the mitochondrial genes COX2 and rrnS were molecularly characterized by PCR; then, they were aligned by CLUSTAL W, and a phylogenetic tree was obtained. In this analysis, the sequences were compared with those reported in GenBank. A total of 460 parasites were studied, 283 of which were nematodes (61.5%) and 177 were acanthocephalans (38.5%). The sequences of seven nematodes showed 99% homology with each other, and thus they formed an independent branch within the Contracaecum sp. group. This is the first report identifying Contracaecum multipapillatum in mullet fish in the Chautengo Lagoon, Guerrero.

A Hierarchical Framework for Assessing Transmission Causality of Respiratory Viruses

Systematic reviews of 591 primary studies of the modes of transmission for SARS-CoV-2 show significant methodological shortcomings and heterogeneity in the design, conduct, testing, and reporting of SARS-CoV-2 transmission. While this is partly understandable at the outset of a pandemic, evidence rules of proof for assessing the transmission of this virus are needed for present and future pandemics of viral respiratory pathogens. We review the history of causality assessment related to microbial etiologies with a focus on respiratory viruses and suggest a hierarchy of evidence to integrate clinical, epidemiologic, molecular, and laboratory perspectives on transmission. The hierarchy, if applied to future studies, should narrow the uncertainty over the twin concepts of causality and transmission of human respiratory viruses. We attempt to address the translational gap between the current research evidence and the assessment of causality in the transmission of respiratory viruses with a focus on SARS-CoV-2. Experimentation, consistency, and independent replication of research alongside our proposed framework provide a chain of evidence that can reduce the uncertainty over the transmission of respiratory viruses and increase the level of confidence in specific modes of transmission, informing the measures that should be undertaken to prevent transmission.

Trends and Developments in the Detection of Pathogens in Central Nervous System Infections: A Bibliometric Study

Introduction

Rapid, sensitive, and specific laboratory assays are critical for the diagnosis and management of central nervous system (CNS) infections. The purpose of this study is to explore the intellectual landscape of research investigating methods for the detection of pathogens in patients with CNS infections and to identify the development trends and research frontier in this field.

Methods

A bibliometric study is conducted by analyzing literature retrieved from the Web of Science (WoS) Core Collection Database for the years 2000 to 2021. CiteSpace software is used for bibliometric analysis and network visualization, including co-citation analysis of references, co-occurrence analysis of keywords, and cooperation network analysis of authors, institutions, and countries/regions.

Results

A total of 2,282 publications are eventually screened, with an upward trend in the number of publications per year. The majority of papers are attributed to the disciplines of MICROBIOLOGY, INFECTIOUS DISEASES, IMMUNOLOGY, NEUROSCIENCES & NEUROLOGY, and VIROLOGY. The co-citation analysis of references shows that recent research has focused on the largest cluster “metagenomic next-generation sequencing”; the results of the analysis of the highest-cited publications and the citation burst of publications reveal that there is a strong interest stimulated in metagenomic next-generation sequencing. The co-occurrence analysis of keywords indicates that “infection”, “pathogen”, “diagnosis”, “gene”, “virus”, “polymerase chain reaction”, “cerebrospinal fluid”, “epidemiology”, and “metagenomic next-generation sequencing” are the main research priorities in the field of pathogen detection for CNS infections, and the keyword with the highest strength of burst is “metagenomic next-generation sequencing”. Collaborative network analysis reveals that the USA, the Centers for Disease Control and Prevention of USA, and XIN WANG and JENNIFER DIEN BARD are the most influential country, institution, and researchers, respectively.

Conclusions

Exploring more advanced laboratory assays to improve the diagnostic accuracy of pathogens is essential for CNS infection research. Metagenomic next-generation sequencing is emerging as a novel useful unbiased approach for diagnosing infectious diseases of the CNS.

Climate adaptation impacting parasitic infection

The steady and ongoing change in climatic patterns across the globe is triggering a cascade of climate-adaptive phenomena, both genetic and behavioral in parasites, and influencing the host–pathogen–transmission triangle. Parasite and vector traits are now heavily influenced due to increasing temperature that almost dissolved geospatial boundaries and impacted the basic reproductive number of parasites. As consequence, continents unknown to some parasites are experiencing altered distribution and abundance of new and emerging parasites that are developing into a newer epidemiological model. These are posing a burden to healthcare and higher disease prevalence. This calls for multidisciplinary actions focusing on One Health to improve and innovate in areas of detection, reporting, and medical countermeasures to combat the growing threat of parasite emergence owing to climate adaptations for better public health outcomes.

A novel Betaretrovirus discovered in cattle with neurological disease and encephalitis

Background

The majority of emerging infectious diseases in humans are of animal origin, and many of them are caused by neuropathogenic viruses. Many cases of neurological disease and encephalitis in livestock remain etiologically unresolved, posing a constant threat to animal and human health. Thus, continuous extension of our knowledge of the repertoire of viruses prone to infect the central nervous system (CNS) is vital for pathogen monitoring and the early detection of emerging viruses. Using high-throughput sequencing (HTS) and bioinformatics, we discovered a new retrovirus, bovine retrovirus CH15 (BoRV CH15), in the CNS of a cow with non-suppurative encephalitis. Phylogenetic analysis revealed the affiliation of BoRV CH15 to the genus Betaretrovirus.

Results

BoRV CH15 genomes were identified prospectively and retrospectively by PCR, RT-PCR, and HTS, with targeting of viral RNA and proviral DNA, in six additional diseased cows investigated over a period of > 20 years and of different geographical origins. The virus was not found in brain samples from healthy slaughtered control animals (n = 130). We determined the full-length proviral genomes from six of the seven investigated animals and, using in situ hybridization, identified viral RNA in the cytoplasm of cells morphologically compatible with neurons in diseased brains.

Conclusions

Further screening of brain samples, virus isolation, and infection studies are needed to estimate the significance of these findings and the causative association of BoRV CH15 with neurological disease and encephalitis in cattle. However, with the full-length proviral sequences of BoRV CH15 genomes, we provide the basis for a molecular clone and further in vitro investigation.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12977-021-00585-x.

Demography, education, and research trends in the interdisciplinary field of disease ecology

Micro- and macroparasites are a leading cause of mortality for humans, animals, and plants, and there is great need to understand their origins, transmission dynamics, and impacts. Disease ecology formed as an interdisciplinary field in the 1970s to fill this need and has recently rapidly grown in size and influence. Because interdisciplinary fields integrate diverse scientific expertise and training experiences, understanding their composition and research priorities is often difficult. Here, for the first time, we quantify the composition and educational experiences of a subset of disease ecology practitioners and identify topical trends in published research. We combined a large survey of self-declared disease ecologists with a literature synthesis involving machine-learning topic detection of over 18,500 disease ecology research articles. The number of graduate degrees earned by disease ecology practitioners has grown dramatically since the early 2000s. Similar to other science fields, we show that practitioners in disease ecology have diversified in the last decade in terms of gender identity and institution, with weaker diversification in race and ethnicity. Topic detection analysis revealed how the frequency of publications on certain topics has declined (e.g., HIV, serology), increased (e.g., the dilution effect, infectious disease in bats), remained relatively common (e.g., malaria ecology, influenza, vaccine research and development), or have consistently remained relatively infrequent (e.g., theoretical models, field experiments). Other topics, such as climate change, superspreading, emerging infectious diseases, and network analyses, have recently come to prominence. This study helps identify the major themes of disease ecology and demonstrates how publication frequency corresponds to emergent health and environmental threats. More broadly, our approach provides a framework to examine the composition and publication trends of other major research fields that cross traditional disciplinary boundaries.

Towards a more healthy conservation paradigm: integrating disease and molecular ecology to aid biological conservation†

Parasites, and the diseases they cause, are important from an ecological and evolutionary perspective because they can negatively affect host fitness and can regulate host populations. Consequently, conservation biology has long recognized the vital role that parasites can play in the process of species endangerment and recovery. However, we are only beginning to understand how deeply parasites are embedded in ecological systems, and there is a growing recognition of the important ways in which parasites affect ecosystem structure and function. Thus, there is an urgent need to revisit how parasites are viewed from a conservation perspective and broaden the role that disease ecology plays in conservation-related research and outcomes. This review broadly focusses on the role that disease ecology can play in biological conservation. Our review specifically emphasizes on how the integration of tools and analytical approaches associated with both disease and molecular ecology can be leveraged to aid conservation biology. Our review first concentrates on disease-mediated extinctions and wildlife epidemics. We then focus on elucidating how host–parasite interactions has improved our understanding of the eco-evolutionary dynamics affecting hosts at the individual, population, community and ecosystem scales. We believe that the role of parasites as drivers and indicators of ecosystem health is especially an exciting area of research that has the potential to fundamentally alter our view of parasites and their role in biological conservation. The review concludes with a broad overview of the current and potential applications of modern genomic tools in disease ecology to aid biological conservation.

DsRNA Sequencing for RNA Virus Surveillance Using Human Clinical Samples

Although viruses infect various organs and are associated with diseases, there may be many unidentified pathogenic viruses. The recent development of next-generation sequencing technologies has facilitated the establishment of an environmental viral metagenomic approach targeting the intracellular viral genome. However, an efficient method for the detection of a viral genome derived from an RNA virus in animal or human samples has not been established. Here, we established a method for the efficient detection of RNA viruses in human clinical samples. We then tested the efficiency of the method compared to other conventional methods by using tissue samples collected from 57 recipients of living donor liver transplantations performed between June 2017 and February 2019 at Kyushu University Hospital. The viral read ratio in human clinical samples was higher by the new method than by the other conventional methods. In addition, the new method correctly identified viral RNA from liver tissues infected with hepatitis C virus. This new technique will be an effective tool for intracellular RNA virus surveillance in human clinical samples and may be useful for the detection of new RNA viruses associated with diseases.

Tailoring metal-organic frameworks-based nanozymes for bacterial theranostics

Nanozymes are next-generation artificial enzymes having distinguished features such as cost-effective, enhanced surface area, and high stability. However, limited selectivity and moderate activity of nanozymes in the biochemical environment hindered their usage and encouraged researchers to seek alternative catalytic materials. Recently, metal-organic frameworks (MOFs) characterized by distinct crystalline porous structures with large surface area, tunable pores, and uniformly dispersed active sites emerged, that filled the gap between natural enzymes and nanozymes. Moreover, by selecting suitable metal ions and organic linkers, MOFs can be designed for effective bacterial theranostics. In this review, we briefly presented the design and fabrication of MOFs. Then, we demonstrated the applications of MOFs in bacterial theranostics and their safety considerations. Finally, we proposed the major obstacles and opportunities for further development in research on the interface of nanozymes and MOFs. We expect that MOFs based nanozymes with unique physicochemical and intrinsic enzyme-mimicking properties will gain broad interest in both fundamental research and biomedical applications.

Blood virosphere in febrile Tanzanian children

Viral infections are the leading cause of childhood acute febrile illnesses motivating consultation in sub-Saharan Africa. The majority of causal viruses are never identified in low-resource clinical settings as such testing is either not part of routine screening or available diagnostic tools have limited ability to detect new/unexpected viral variants. An in-depth exploration of the blood virome is therefore necessary to clarify the potential viral origin of fever in children. Metagenomic next-generation sequencing is a powerful tool for such broad investigations, allowing the detection of RNA and DNA viral genomes. Here, we describe the blood virome of 816 febrile children (<5 years) presenting at outpatient departments in Dar es Salaam over one-year. We show that half of the patients (394/816) had at least one detected virus recognized as causes of human infection/disease (13.8% enteroviruses (enterovirus A, B, C, and rhinovirus A and C), 12% rotaviruses, 11% human herpesvirus type 6). Additionally, we report the detection of a large number of viruses (related to arthropod, vertebrate or mammalian viral species) not yet known to cause human infection/disease, highlighting those who should be on the radar, deserve specific attention in the febrile paediatric population and, more broadly, for surveillance of emerging pathogens.Trial registration: ClinicalTrials.gov identifier: NCT02225769.

Spatiotemporal Analysis of COVID-19 Incidence Data

(1) Background: A better understanding of COVID-19 dynamics in terms of interactions among individuals would be of paramount importance to increase the effectiveness of containment measures. Despite this, the research lacks spatiotemporal statistical and mathematical analysis based on large datasets. We describe a novel methodology to extract useful spatiotemporal information from COVID-19 pandemic data. (2) Methods: We perform specific analyses based on mathematical and statistical tools, like mathematical morphology, hierarchical clustering, parametric data modeling and non-parametric statistics. These analyses are here applied to the large dataset consisting of about 19,000 COVID-19 patients in the Veneto region (Italy) during the entire Italian national lockdown. (3) Results: We estimate the COVID-19 cumulative incidence spatial distribution, significantly reducing image noise. We identify four clusters of connected provinces based on the temporal evolution of the incidence. Surprisingly, while one cluster consists of three neighboring provinces, another one contains two provinces more than 210 km apart by highway. The survival function of the local spatial incidence values is modeled here by a tapered Pareto model, also used in other applied fields like seismology and economy in connection to networks. Model's parameters could be relevant to describe quantitatively the epidemic. (4) Conclusion: The proposed methodology can be applied to a general situation, potentially helping to adopt strategic decisions such as the restriction of mobility and gatherings.

In the landscape of SARS-CoV-2 and fresh fruits and vegetables: The fake and hidden transmission risks

From the first notification reporting to the WHO a cluster of coronavirus in Wuhan City (China), over 114 million cases of SARS‐CoV‐2 have been confirmed, with more than 2,530,000 deaths, and over 400,000 new cases and 10,000 deaths daily. Numerous viruses are susceptible to contaminate crops during growth, harvesting, handling, marketing and minimally processing, and these steps share one common factor which is human. Different studies showed that viruses might persist on different crops for periods of 2 to 14 days under different conditions such as refrigeration, household and freezing. Little is known on SARS‐CoV‐2, but preliminary studies showed that this virus might survive 24 hr on cardboard and 72 hr on plastic, materials used in fruits and vegetables packaging. Based on preliminary data, there is no evidence of food or food packaging being associated with transmission of SARS‐CoV‐2. Certainly, to date there is no scientific evidence that SARS‐CoV‐2 might be transmitted by a contact with, or the ingestion of contaminated fresh or minimally processed fruits and vegetables. However, this risk even though being considered improbable, it cannot be “completely and definitely” discarded or ignored, particularly where the virus is spreading in the word. Some agencies indicated that in case some commodities and handlers are contaminated among the multiple people involved from the farm to the table, a cross‐contamination may occur, and the risk of the contamination of food, food contact materials, and packaging from infected but asymptomatic workers should not be discarded even though considered “Very Low = meaning very rare but cannot be excluded.”

Bioinspired Artificial "Clickase" for the Catalytic Click Immunoassay of Foodborne Pathogens

The copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) click reaction has drawn increasing attention in the field of analytical science. However, the poor stability of Cu(I) usually hinders not only the simplicity of the click reaction but also its applications in precise analyses. Therefore, the development of a nanocatalyst containing stable Cu(I) is of great significance for broadening the application of CuAAC-based assays. Herein, inspired by the active center structure of natural multicopper oxidases (MCOs), we successfully prepared a novel nanocatalyst containing abundant stable Cu(I) as an artificial "clickase" (namely, CCN) by using glutathione to stabilize Cu(I). The stability and enzyme-like catalytic activity in the CuAAC reaction of the prepared CCN clickase were studied, and the catalytic mechanism of the CCN clickase-mediated CuAAC reaction between 3-azide-7-hydroxycoumarin (Azide 1) and propargyl alcohol (Alkyne 2) was also revealed. Compared with the existing solid CuO nanocatalysts used in CuAAC-based assays, CCN clickases exhibited plenty of superior properties (including high stability, excellent catalytic activity, no requirements of dissolution and reducing agents/radical initiator during the detection, well-defined porosities benefiting the substrate diffusion, and good biocompatibility), which can greatly increase the reaction efficiency and shorten the detection time. Encouraged by these remarkable performances, CCN clickases were used as labels to establish a new catalytic click fluorescence immunoassay for foodborne pathogens. Notably, the proposed CCN clickase-based immunoassay exhibited high analytical performances for the quantification of Salmonella enteritidis in the linear range of 10²-10⁶ CFU/mL with a limit of detection as low as 11 CFU/mL. The developed method has also been used in the determination of S. enteritidis in food samples, showing its great potential in the detection of foodborne pathogens.

Next-generation Sequencing of Cerebrospinal Fluid for the Diagnosis of Unexplained Central Nervous System Infections

BACKGROUND

Central nervous system infections cause substantial morbidity and mortality in pediatric patients. However, in approximately half of the clinical cases, the etiology is unidentified. As an unbiased molecular diagnostic technology, next-generation sequencing is gradually being applied to investigate central nervous system infections. This review summarizes and critiques the literature on this new technology for etiologic identification of unexplained central nervous system infections in pediatric patients and discusses the future prospects for development of this technology in pediatrics.

METHODS

A comprehensive PubMed search was conducted of articles published from January 1, 2008, to June 26, 2020 in order to retrieve all available studies on this topic. Other relevant articles were identified from recent reviews and the bibliographies of the retrieved full-text articles.

RESULTS

Among the 441 studies retrieved, 26 pediatric studies, comprising 15 case reports and 11 case series, used next-generation sequencing as a diagnostic tool. In these 26 studies, next-generation sequencing was performed on cerebrospinal fluid samples from 529 pediatric patients, and potential causal pathogens were identified in 22.1% of the cases.

CONCLUSION

There is increasing evidence that next-generation sequencing can play a role in identifying the causes of unexplained encephalitis, meningoencephalitis, and meningitis in pediatric patients, although the diagnostic value of next-generation sequencing is difficult to quantify. There is an increasing need for close collaboration between laboratory scientists and clinicians. We believe that further clinical studies should be performed to evaluate the performance of next-generation sequencing for individual targets and in high-risk populations.

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.

STROBE-metagenomics: a STROBE extension statement to guide the reporting of metagenomics studies

The term metagenomics refers to the use of sequencing methods to simultaneously identify genomic material from all organisms present in a sample, with the advantage of greater taxonomic resolution than culture or other methods. Applications include pathogen detection and discovery, species characterisation, antimicrobial resistance detection, virulence profiling, and study of the microbiome and microecological factors affecting health. However, metagenomics involves complex and multistep processes and there are important technical and methodological challenges that require careful consideration to support valid inference. We co-ordinated a multidisciplinary, international expert group to establish reporting guidelines that address specimen processing, nucleic acid extraction, sequencing platforms, bioinformatics considerations, quality assurance, limits of detection, power and sample size, confirmatory testing, causality criteria, cost, and ethical issues. The guidance recognises that metagenomics research requires pragmatism and caution in interpretation, and that this field is rapidly evolving.

Distinct Roles for Bacterial and Fungal Communities During the Curing of Vanilla

Vanilla produces aroma after curing. There were a few reports about the possible involvement of microorganisms during the curing process. Bacterial and fungal community was analyzed to explore the distinct roles. Alpha diversity analysis indicated that the abundance and diversity of microorganisms did not increase regularly as the curing progressed. Weighted and unweighted principal coordinates analysis (PCoA) showed that the fungal community of blanching beans was significantly different from those of the vanilla beans of other stages, respectively. Bacillus and Aspergillus were the dominant genus during the curing process. Correlation analysis indicated that the bacterial and fungal structure was positively related to the vanillin formation, respectively. The study was conducive to reveal the formation of flavor components and the biosynthesis of vanillin. Furthermore, it proposed the possible curing methods of regulating the bacterial and fungal community to increase vanillin formation.

The Prediction of Infectious Diseases: A Bibliometric Analysis

OBJECTIVE

The outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars are increasingly concerned with the prediction of infectious diseases. However, a knowledge mapping analysis of literature regarding the prediction of infectious diseases using rigorous bibliometric tools, which are supposed to offer further knowledge structure and distribution, has been conducted infrequently. Therefore, we implement a bibliometric analysis about the prediction of infectious diseases to objectively analyze the current status and research hotspots, in order to provide a reference for related researchers.

METHODS

We viewed "infectious disease*" and "prediction" or "forecasting" as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis.

RESULTS

1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases.

CONCLUSION

Our study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses.

Bovine Polyomavirus 2 is a Probable Cause of Non-Suppurative Encephalitis in Cattle

Tissues from two cows with neurological signs that were admitted to the Vetsuisse Faculty under suspicion of rabies and bovine spongiform encephalopathy (BSE), respectively, were further analyzed for this case report. After histopathological examination and exclusion of BSE and rabies, the animals were diagnosed with etiologically unresolved disseminated non-suppurative encephalitis. Using next-generation sequencing, we detected the full genome of bovine polyomavirus 2 (BoPyV2) in brain samples from both animals. This virus has been identified in beef samples in three independent studies conducted in the United States and Germany, but has not been linked to any disease. Analysis of the two new BoPyV2 genome sequences revealed close phylogenetic relationships to one another and to BoPyV2 isolates detected in beef samples. In situ hybridization demonstrated the presence of viral nucleic acid in all investigated brain areas and in areas with signs of inflammation in both animals. Thus, we provide the first evidence that BoPyV2 is a probable cause of non-suppurative encephalitis in cattle, and encourage further molecular and serological testing to elucidate the disease's epidemiology, as well as experimental transmission studies to prove causality between the infection and disease.

First Prototype of the Infectious Diseases Seeker (IDS) Software for Prompt Identification of Infectious Diseases

The rapid detection of ongoing outbreak – and the identification of causative pathogen – is pivotal for the early recognition of public health threats. The emergence and re-emergence of infectious diseases are linked to several determinants, both human factors – such as population density, travel, and trade – and ecological factors – like climate change and agricultural practices. Several technologies are available for the rapid molecular identification of pathogens [e.g. real-time polymerase chain reaction (PCR)], and together with on line monitoring tools of infectious disease activity and behaviour, they contribute to the surveillance system for infectious diseases. Web-based surveillance tools, infectious diseases modelling and epidemic intelligence methods represent crucial components for timely outbreak detection and rapid risk assessment. The study aims to integrate the current prevention and control system with a prediction tool for infectious diseases, based on regression analysis, to support decision makers, health care workers, and first responders to quickly and properly recognise an outbreak. This study has the intention to develop an infectious disease regressive prediction tool working with an off-line database built with specific epidemiological parameters of a set of infectious diseases of high consequences. The tool has been developed as a first prototype of a software solution called Infectious Diseases Seeker (IDS) and it had been established in two main steps, the database building stage and the software implementation stage (MATLAB^® environment). The IDS has been tested with the epidemiological data of three outbreaks occurred recently: severe acute respiratory syndrome epidemic in China (2002–2003), plague outbreak in Madagascar (2017) and the Ebola virus disease outbreak in the Democratic Republic of Congo (2018). The outcomes are promising and they reveal that the software has been able to recognize and characterize these outbreaks. The future perspective about this software regards the developing of that tool as a useful and user-friendly predictive tool appropriate for first responders, health care workers, and public health decision makers to help them in predicting, assessing and contrasting outbreaks.

Implementation of geographical information systems for the study of diseases caused by vector-borne arboviruses in Southeast Asia: A review based on the publication record

The spread of mosquito-borne diseases in Southeast Asia has dramatically increased in the latest decades. These infections include dengue, chikungunya and Japanese Encephalitis (JE), high-burden viruses sharing overlapping disease manifestation and vector distribution. The use of Geographical Information Systems (GIS) to monitor the dynamics of disease and vector distribution can assist in disease epidemic prediction and public health interventions, particularly in Southeast Asia where sustained high temperatures drive the epidemic spread of these mosquito-borne viruses. Due to lack of accurate data, the spatial and temporal dynamics of these mosquito-borne viral disease transmission countries are poorly understood, which has limited disease control effort. By following studies carried out on these three viruses across the region in a specific time period revealing general patterns of research activities and characteristics, this review finds the need to improve decision-support by disease mapping and management. The results presented, based on a publication search with respect to diseases due to arboviruses, specifically dengue, chikungunya and Japanese encephalitis, should improve opportunities for future studies on the implementation of GIS in the control of mosquito-borne viral diseases in Southeast Asia.

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures

The spread of coronavirus disease 2019 (COVID-19) in Italy prompted drastic measures for transmission containment. We examine the effects of these interventions, based on modeling of the unfolding epidemic. We test modeling options of the spatially explicit type, suggested by the wave of infections spreading from the initial foci to the rest of Italy. We estimate parameters of a metacommunity Susceptible-Exposed-Infected-Recovered (SEIR)-like transmission model that includes a network of 107 provinces connected by mobility at high resolution, and the critical contribution of presymptomatic and asymptomatic transmission. We estimate a generalized reproduction number ([Formula: see text] = 3.60 [3.49 to 3.84]), the spectral radius of a suitable next-generation matrix that measures the potential spread in the absence of containment interventions. The model includes the implementation of progressive restrictions after the first case confirmed in Italy (February 21, 2020) and runs until March 25, 2020. We account for uncertainty in epidemiological reporting, and time dependence of human mobility matrices and awareness-dependent exposure probabilities. We draw scenarios of different containment measures and their impact. Results suggest that the sequence of restrictions posed to mobility and human-to-human interactions have reduced transmission by 45% (42 to 49%). Averted hospitalizations are measured by running scenarios obtained by selectively relaxing the imposed restrictions and total about 200,000 individuals (as of March 25, 2020). Although a number of assumptions need to be reexamined, like age structure in social mixing patterns and in the distribution of mobility, hospitalization, and fatality, we conclude that verifiable evidence exists to support the planning of emergency measures.

Parainfluenza Virus 5 Infection in Neurological Disease and Encephalitis of Cattle

The etiology of viral encephalitis in cattle often remains unresolved, posing a potential risk for animal and human health. In metagenomics studies of cattle with bovine non-suppurative encephalitis, parainfluenza virus 5 (PIV5) was identified in three brain samples. Interestingly, in two of these animals, bovine herpesvirus 6 and bovine astrovirus CH13 were additionally found. We investigated the role of PIV5 in bovine non-suppurative encephalitis and further characterized the three cases. With traditional sequencing methods, we completed the three PIV5 genomes, which were compared to one another. However, in comparison to already described PIV5 strains, unique features were revealed, like an 81 nucleotide longer open reading frame encoding the small hydrophobic (SH) protein. With in situ techniques, we demonstrated PIV5 antigen and RNA in one animal and found a broad cell tropism of PIV5 in the brain. Comparative quantitative analyses revealed a high viral load of PIV5 in the in situ positive animal and therefore, we propose that PIV5 was probably the cause of the disease. With this study, we clearly show that PIV5 is capable of naturally infecting different brain cell types in cattle in vivo and therefore it is a probable cause of encephalitis and neurological disease in cattle.

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.

Detection of dicistroviruses RNA in blood of febrile Tanzanian children

Fever is the leading cause of paediatric outpatient consultations in Sub-Saharan Africa. Although most are suspected to be of viral origin, a putative causative pathogen is not identified in over a quarter of these febrile episodes. Using a de novo assembly sequencing approach, we report the detection (15.4%) of dicistroviruses (DicV) RNA in sera collected from 692 febrile Tanzanian children. In contrast, DicV RNA was only detected in 1/77 (1.3%) plasma samples from febrile Tanzanian adults, suggesting that children could represent the primary susceptible population. Estimated viral load by specific quantitative real-time RT–PCR assay ranged from < 1.32E3 to 1.44E7 viral RNA copies/mL serum. Three DicV full-length genomes were obtained, and a phylogenetic analyse on the capsid region showed the presence of two clusters representing tentative novel genus. Although DicV-positive cases were detected throughout the year, a significantly higher positivity rate was observed during the rainy season.

This study reveals that novel DicV RNA is frequently detected in the blood of Tanzanian children, paving the way for further investigations to determine if DicV possibly represent a new agent in humans.

Development and analytical validation of a group-specific RT-qPCR assay for the detection of the Simbu serogroup orthobunyaviruses

The Simbu serogroup within the genus Orthobunyavirus belongs to the family Peribunyaviridae and comprises 32 recognised three-segmented negative-sense single-stranded RNA viruses, with a cosmopolitan distribution. This group of arthropod-borne viruses includes important pathogens of humans and domestic animals e.g. Oropouche orthobunyavirus and Schmallenberg virus. Sensitive and specific diagnostic tools are required for recognition and control of outbreaks. A novel TaqMan® RT-qPCR assay was developed, optimised and analytically validated for the broad detection of the Simbu serogroup orthobunyaviruses. A region in the S segment, which encodes the nucleocapsid protein, was used to design a group primer set and a pair of differently labelled TaqMan® minor groove binder probes to distinguish phylogenetic clade A and B of the serogroup. Efficiencies determined for seven members of the group were 99% for Akabane orthobunyavirus (AKAV), 96% for Simbu orthobunyavirus (SIMV), 96% for Shuni orthobunyavirus (SHUV), 97% for Sathuperi orthobunyavirus (SATV), 84% for Shamonda orthobunyavirus (SHAV), 93% for Ingwavuma virus (INGV, now classified as Manzanilla orthobunyavirus) and 110% for Sabo virus (SABOV, now classified as AKAV). The 95% limit of detection (TCID50/reaction) was 10-3.61 for AKAV, 10-2.38 for SIMV, 10-3.42 for SHUV, 10-3.32 for SATV, 10-1.67 for SHAV, 100.39 for INGV and 10-2.70 for SABOV.

High-throughput sequencing for the aetiologic identification of viral encephalitis, meningoencephalitis, and meningitis. A narrative review and clinical appraisal

Background

Viral aetiologies are the most common cause of central nervous system (CNS) infections. Approximately one-half of CNS infections remain of undetermined origin. High-throughput sequencing (HTS) brought new perspectives to CNS infection investigations, allowing investigation of viral aetiologies with an unbiased approach. HTS use is still limited to specific clinical situations.

Objectives

The aim of this review was to evaluate the contribution and pitfalls of HTS for the aetiologic identification of viral encephalitis, meningoencephalitis, and meningitis in CNS patient samples.

Sources

PubMed was searched from 1 January 2008 to 2 August 2018 to retrieve available studies on the topic. Additional publications were included from a review of full-text sources.

Content

Among 366 studies retrieved, 29 used HTS as a diagnostic technique. HTS was performed in cerebrospinal fluid and brain biopsy samples of 307 patients, including immunocompromised, immunocompetent paediatric, and adult cases. HTS was performed retrospectively in 18 studies and prospectively in 11. HTS led to the identification of a potential causal virus in 41 patients, with 11 viruses known and ten not expected to cause CNS infections. Various HTS protocols were used.

Implications

The additional value of HTS is difficult to quantify because of various biases. Nevertheless, HTS led to the identification of a viral cause in 13% of encephalitis, meningoencephalitis, and meningitis cases in which various assays failed to identify the cause. HTS should be considered early in clinical management as a complement to routine assays. Standardized strategies and systematic studies are needed for the integration of HTS in clinical management.

Colorimetric-Fluorescent-Magnetic Nanosphere-Based Multimodal Assay Platform for Salmonella Detection

Rapid and sensitive foodborne pathogen detection assay, which can be applied in multiple fields, is essential to timely diagnosis. Herein, we proposed a multisignal readout lateral flow immunoassay for Salmonella typhimurium ( S. typhi) detection. The assay employs colorimetric-fluorescent-magnetic nanospheres (CFMNs) as labels, which possess multifunctional target separation and enrichment, multisignal readout, and two formats of quantitation. The assay for S. typhi detection involves magnetic separation and chromatography. First, the S. typhi were separated and enriched from matrix by antibody labeled CFMNs, and then the S. typhi-containing suspension is added onto the sample pad to flow up the test strip. The introduction of magnetic separation enhances anti-interference ability and 10-fold sensitivity, making the assay possible for practical application. The assay has realized naked eye detection of 1.88 × 10⁴ CFU/mL S. typhi, and 3.75 × 10³ CFU/mL S. typhi can be detected with a magnetic assay reader, which is 2-4 orders of magnitude lower than other label-based LFIAs, with a quantitation range of 1.88 × 10⁴ to 1.88 × 10⁷ CFU/mL by measuring the fluorescence intensity and magnetic signal. Moreover, the successful detection of S. typhi in complex matrix (tap water, milk, fetal bovine serum, and whole blood) indicated its potential application in real samples.

Current progress and future opportunities in applications of bioinformatics for biodefense and pathogen detection: report from the Winter Mid-Atlantic Microbiome Meet-up, College Park, MD, January 10, 2018

The Mid-Atlantic Microbiome Meet-up (M3) organization brings together academic, government, and industry groups to share ideas and develop best practices for microbiome research. In January of 2018, M3 held its fourth meeting, which focused on recent advances in biodefense, specifically those relating to infectious disease, and the use of metagenomic methods for pathogen detection. Presentations highlighted the utility of next-generation sequencing technologies for identifying and tracking microbial community members across space and time. However, they also stressed the current limitations of genomic approaches for biodefense, including insufficient sensitivity to detect low-abundance pathogens and the inability to quantify viable organisms. Participants discussed ways in which the community can improve software usability and shared new computational tools for metagenomic processing, assembly, annotation, and visualization. Looking to the future, they identified the need for better bioinformatics toolkits for longitudinal analyses, improved sample processing approaches for characterizing viruses and fungi, and more consistent maintenance of database resources. Finally, they addressed the necessity of improving data standards to incentivize data sharing. Here, we summarize the presentations and discussions from the meeting, identifying the areas where microbiome analyses have improved our ability to detect and manage biological threats and infectious disease, as well as gaps of knowledge in the field that require future funding and focus.