Using host traits to predict reservoir host species of rabies virus

Predicting hosts and cross-species transmission of Streptococcus agalactiae by interpretable machine learning

BACKGROUND

Streptococcus agalactiae, commonly known as Group B Streptococcus (GBS), exhibits a broad host range, manifesting as both a beneficial commensal and an opportunistic pathogen across various species. In humans, it poses significant risks, causing neonatal sepsis and meningitis, along with severe infections in adults. Additionally, it impacts livestock by inducing mastitis in bovines and contributing to epidemic mortality in fish populations. Despite its wide host spectrum, the mechanisms enabling GBS to adapt to specific hosts remain inadequately elucidated. Therefore, the development of a rapid and accurate method differentiates GBS strains associated with particular animal hosts based on genome-wide information holds immense potential. Such a tool would not only bolster the identification and containment efforts during GBS outbreaks but also deepen our comprehension of the bacteria's host adaptations spanning humans, livestock, and other natural animal reservoirs.

METHODS AND RESULTS

Here, we developed three machine learning models-random forest (RF), logistic regression (LR), and support vector machine (SVM) based on genome-wide mutation data. These models enabled precise prediction of the host origin of GBS, accurately distinguishing between human, bovine, fish, and pig hosts. Moreover, we conducted an interpretable machine learning using SHapley Additive exPlanations (SHAP) and variant annotation to uncover the most influential genomic features and associated genes for each host. Additionally, by meticulously examining misclassified samples, we gained valuable insights into the dynamics of host transmission and the potential for zoonotic infections.

CONCLUSIONS

Our study underscores the effectiveness of random forest (RF) and logistic regression (LR) models based on mutation data for accurately predicting GBS host origins. Additionally, we identify the key features associated with each GBS host, thereby enhancing our understanding of the bacteria's host-specific adaptations.

Tracking lethal threat: in-depth review of rabies

An infectious disease known as rabies (family Rhabdoviridae, genus Lyssavirus) causes severe damage to mammals' central nervous systems (CNS). This illness has been around for a very long time. The majority of human cases of rabies take place in underdeveloped regions of Africa and Asia. Following viral transmission, the Rhabdovirus enters the peripheral nervous system and proceeds to the CNS, where it targets the encephalon and produces encephalomyelitis. Postbite prophylaxis requires laboratory confirmation of rabies in both people and animals. All warm-blooded animals can transmit the Lyssavirus infection, while the virus can also develop in the cells of cold-blooded animals. In the 21st century, more than 3 billion people are in danger of contracting the rabies virus in more than 100 different nations, resulting in an annual death toll of 50,000-59,000. There are three important elements in handling rabies disease in post exposure prophylaxis (PEP), namely wound care, administration of anti-rabies serum, and anti-rabies vaccine. Social costs include death, lost productivity as a result of early death, illness as a result of vaccination side effects, and the psychological toll that exposure to these deadly diseases has on people. Humans are most frequently exposed to canine rabies, especially youngsters and the poor, and there are few resources available to treat or prevent exposure, making prevention of human rabies challenging.

Functional traits explain waterbirds' host status, subtype richness, and community-level infection risk for avian influenza

Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community-level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community-weighted means of these traits were also correlated with community-level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait-based ecology into the framework of diversity-disease relationship, and provide new insights for HPAI prediction and prevention.

The spectral underpinnings of pathogen spread on animal networks

Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.

A review of the diet of the common vampire bat (Desmodus rotundus) in the context of anthropogenic change

The common vampire bat (Desmodus rotundus) maintains a diverse, sanguivorous diet, utilizing a broad range of prey taxa. As anthropogenic change alters the distribution of this species, shifts in predator-prey interactions are expected. Understanding prey richness and patterns of prey selection is, thus, increasingly informative from ecological, epidemiological, and economic perspectives. We reviewed D. rotundus diet and assessed the geographical, taxonomical, and behavioral features to find 63 vertebrate species within 21 orders and 45 families constitute prey, including suitable host species in regions of invasion outside D. rotundus' range. Rodentia contained the largest number of species utilized by D. rotundus, though cattle were the most commonly reported prey source, likely linked to the high availability of livestock and visibility of bite wounds compared to wildlife. Additionally, there was tendency to predate upon species with diurnal activity and social behavior, potentially facilitating convenient and nocturnal predation. Our review highlights the dietary heterogeneity of D. rotundus across its distribution. We define D. rotundus as a generalist predator, or parasite, depending on the ecological definition of its symbiont roles in an ecosystem (i.e., lethal vs. non-lethal blood consumption). In view of the eminent role of D. rotundus in rabies virus transmission and its range expansion, an understanding of its ecology would benefit public health, wildlife management, and agriculture.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42991-023-00358-3.

Rabies virus in white-nosed coatis (Nasua narica) in Mexico: what do we know so far?

Rabies is a neglected disease that affects all mammals. To determine the appropriate sanitary measures, the schedule of preventive medicine campaigns requires the proper identification of the variants of the virus circulating in the outbreaks, the species involved, and the interspecific and intraspecific virus movements. Urban rabies has been eradicated in developed countries and is being eradicated in some developing countries. In Europe and North America, oral vaccination programs for wildlife have been successful, whereas in Latin America, Asia, and Africa, rabies remains a public health problem due to the habitation of a wide variety of wild animal species that can act as rabies virus reservoirs in their environment. After obtaining recognition from the WHO/PAHO as the first country to eliminate human rabies transmitted by dogs, Mexico faces a new challenge: the control of rabies transmitted by wildlife to humans and domestic animals. In recent years, rabies outbreaks in the white-nosed coati (Nasua narica) have been detected, and it is suspected that the species plays a significant role in maintaining the wild cycle of rabies in the southeast of Mexico. In this study, we discussed cases of rabies in white-nosed coatis that were diagnosed at InDRE (in English: Institute of Epidemiological Diagnosis and Reference; in Spanish: Instituto de Diagnostico y Referencia Epidemiologicos) from 1993 to 2022. This study aimed to determine whether white-nosed coatis might be an emergent rabies reservoir in the country. A total of 13 samples were registered in the database from the Rabies laboratories of Estado de Mexico (n = 1), Jalisco (n = 1), Quintana Roo (n = 5), Sonora (n = 1), and Yucatan (n = 5). Samples from 1993 to 2002 from Estado de Mexico, Jalisco, and Sonora were not characterized because we no longer had any samples available. Nine samples were antigenically and genetically characterized. To date, coatis have not been considered important vectors of the rabies virus. The results from our research indicate that the surveillance of the rabies virus in coatis should be relevant to prevent human cases transmitted by this species.

A species-level trait dataset of bats in Europe and beyond

Knowledge of species' functional traits is essential for understanding biodiversity patterns, predicting the impacts of global environmental changes, and assessing the efficiency of conservation measures. Bats are major components of mammalian diversity and occupy a variety of ecological niches and geographic distributions. However, an extensive compilation of their functional traits and ecological attributes is still missing. Here we present EuroBaTrait 1.0, the most comprehensive and up-to-date trait dataset covering 47 European bat species. The dataset includes data on 118 traits including genetic composition, physiology, morphology, acoustic signature, climatic associations, foraging habitat, roost type, diet, spatial behaviour, life history, pathogens, phenology, and distribution. We compiled the bat trait data obtained from three main sources: (i) a systematic literature and dataset search, (ii) unpublished data from European bat experts, and (iii) observations from large-scale monitoring programs. EuroBaTrait is designed to provide an important data source for comparative and trait-based analyses at the species or community level. The dataset also exposes knowledge gaps in species, geographic and trait coverage, highlighting priorities for future data collection.

Phylogenetic and biogeographical traits predict unrecognized hosts of zoonotic leishmaniasis

The spatio-temporal distribution of leishmaniasis, a parasitic vector-borne zoonotic disease, is significantly impacted by land-use change and climate warming in the Americas. However, predicting and containing outbreaks is challenging as the zoonotic Leishmania system is highly complex: leishmaniasis (visceral, cutaneous and muco-cutaneous) in humans is caused by up to 14 different Leishmania species, and the parasite is transmitted by dozens of sandfly species and is known to infect almost twice as many wildlife species. Despite the already broad known host range, new hosts are discovered almost annually and Leishmania transmission to humans occurs in absence of a known host. As such, the full range of Leishmania hosts is undetermined, inhibiting the use of ecological interventions to limit pathogen spread and the ability to accurately predict the impact of global change on disease risk. Here, we employed a machine learning approach to generate trait profiles of known zoonotic Leishmania wildlife hosts (mammals that are naturally exposed and susceptible to infection) and used trait-profiles of known hosts to identify potentially unrecognized hosts. We found that biogeography, phylogenetic distance, and study effort best predicted Leishmania host status. Traits associated with global change, such as agricultural land-cover, urban land-cover, and climate, were among the top predictors of host status. Most notably, our analysis suggested that zoonotic Leishmania hosts are significantly undersampled, as our model predicted just as many unrecognized hosts as unknown hosts. Overall, our analysis facilitates targeted surveillance strategies and improved understanding of the impact of environmental change on local transmission cycles.

In silico method for predicting infectious strains of influenza A virus from its genome and protein sequences

Influenza A is a contagious viral disease responsible for four pandemics in the past and a major public health concern. Being zoonotic in nature, the virus can cross the species barrier and transmit from wild aquatic bird reservoirs to humans via intermediate hosts. In this study, we have developed a computational method for the prediction of human-associated and non-human-associated influenza A virus sequences. The models were trained and validated on proteins and genome sequences of influenza A virus. Firstly, we have developed prediction models for 15 types of influenza A proteins using composition-based and one-hot-encoding features. We have achieved a highest AUC of 0.98 for HA protein on a validation dataset using dipeptide composition-based features. Of note, we obtained a maximum AUC of 0.99 using one-hot-encoding features for protein-based models on a validation dataset. Secondly, we built models using whole genome sequences which achieved an AUC of 0.98 on a validation dataset. In addition, we showed that our method outperforms a similarity-based approach (i.e., blast) on the same validation dataset. Finally, we integrated our best models into a user-friendly web server 'FluSPred' (https://webs.iiitd.edu.in/raghava/fluspred/index.html) and a standalone version (https://github.com/raghavagps/FluSPred) for the prediction of human-associated/non-human-associated influenza A virus strains.

High prevalence does not necessarily equal maintenance species: Avoiding biased claims of disease reservoirs when using surveillance data

1. Many pathogens of public health and conservation concern persist in host communities. Identifying candidate maintenance and reservoir species is therefore a central component of disease management. The term maintenance species implies that if all species but the putative maintenance species were removed, then the pathogen would still persist. In the absence of field manipulations, this statement inherently requires a causal or mechanistic model to assess. 2. However, we lack a systematic understanding of i) how often conclusions are made about maintenance and reservoir species without reference to mechanistic models ii) what types of biases may be associated with these conclusions and iii) how explicitly invoking causal or mechanistic modeling can help ameliorate these biases. Filling these knowledge gaps is critical for robust inference on pathogen persistence and spillover in multihost parasite systems, with clear implications for human and wildlife health. 3. To address these gaps, we performed a literature review on the evidence previous studies have used to make claims regarding maintenance or reservoir species. We then developed a multihost-parasite model to explore and demonstrate common biases that could arise when inferring maintenance potential from observational prevalence data. Finally, we developed new theory to show how model-driven inference of maintenance species can minimize and eliminate emergent biases. 4. In our review, we found that 83% of studies used some form of observational prevalence data to draw conclusions on maintenance potential and only 6% of these studies combined observational data with mechanistic modeling. Using our model, we demonstrate how the community, spatial, and temporal context of observational data can lead to substantial biases in inferences of maintenance potential. Importantly, our theory identifies that model-driven inference of maintenance species elucidates other streams of observational data that can be leveraged to correct these biases. 5. Model-driven inference is an essential, yet underused, component of multidisciplinary studies that make inference on host reservoir and maintenance species. Better integration of wildlife disease surveillance and mechanistic models is necessary to improve the robustness and reproducibility of our conclusions regarding maintenance and reservoir species.

Virus isolation data improve host predictions for New World rodent orthohantaviruses

Identifying reservoir host species is crucial for understanding the ecology of multi-host pathogens and predicting risks of pathogen spillover from wildlife to people. Predictive models are increasingly used for identifying ecological traits and prioritizing surveillance of likely zoonotic reservoirs, but these often employ different types of evidence for establishing host associations. Comparisons between models with different infection evidence are necessary to guide inferences about the trait profiles of likely hosts and identify which hosts and geographical regions are likely sources of spillover. Here, we use New World rodent-orthohantavirus associations to explore differences in the performance and predictions of models trained on two types of evidence for infection and onward transmission: RT-PCR and live virus isolation data, representing active infections versus host competence, respectively. Orthohantaviruses are primarily carried by muroid rodents and cause the diseases haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) in humans. We show that although boosted regression tree (BRT) models trained on RT-PCR and live virus isolation data both performed well and capture generally similar trait profiles, rodent phylogeny influenced previously collected RT-PCR data, and BRTs using virus isolation data displayed a narrower list of predicted reservoirs than those using RT-PCR data. BRT models trained on RT-PCR data identified 138 undiscovered hosts and virus isolation models identified 92 undiscovered hosts, with 27 undiscovered hosts identified by both models. Distributions of predicted hosts were concentrated in several different regions for each model, with large discrepancies between evidence types. As a form of validation, virus isolation models independently predicted several orthohantavirus-rodent host associations that had been previously identified through empirical research using RT-PCR. Our model predictions provide a priority list of species and locations for future orthohantavirus sampling. More broadly, these results demonstrate the value of multiple data types for predicting zoonotic pathogen hosts. These methods can be applied across a range of systems to improve our understanding of pathogen maintenance and increase efficiency of pathogen surveillance.

Making genomic surveillance deliver: A lineage classification and nomenclature system to inform rabies elimination

The availability of pathogen sequence data and use of genomic surveillance is rapidly increasing. Genomic tools and classification systems need updating to reflect this. Here, rabies virus is used as an example to showcase the potential value of updated genomic tools to enhance surveillance to better understand epidemiological dynamics and improve disease control. Previous studies have described the evolutionary history of rabies virus, however the resulting taxonomy lacks the definition necessary to identify incursions, lineage turnover and transmission routes at high resolution. Here we propose a lineage classification system based on the dynamic nomenclature used for SARS-CoV-2, defining a lineage by phylogenetic methods for tracking virus spread and comparing sequences across geographic areas. We demonstrate this system through application to the globally distributed Cosmopolitan clade of rabies virus, defining 96 total lineages within the clade, beyond the 22 previously reported. We further show how integration of this tool with a new rabies virus sequence data resource (RABV-GLUE) enables rapid application, for example, highlighting lineage dynamics relevant to control and elimination programmes, such as identifying importations and their sources, as well as areas of persistence and routes of virus movement, including transboundary incursions. This system and the tools developed should be useful for coordinating and targeting control programmes and monitoring progress as countries work towards eliminating dog-mediated rabies, as well as having potential for broader application to the surveillance of other viruses.

Rabies Virus Variants Detected from Cougar (Puma concolor) in Mexico 2000–2021

In 2019, the World Health Organization (WHO) and the Pan-American Health Organization (PAHO) recognized Mexico as a country free of human rabies transmitted by dogs. Nevertheless, the sylvatic cycle remains as a public health concern in the country. Although cougars (Puma concolor) are not reservoirs of any rabies virus variant (RVV), these felines could act as vectors at the top of the food chain, and their relationships with other organisms must be considered important for the regulatory effect on their prey’s populations. In this study, genetic and antigenic characterization was performed on all cougar rabies cases diagnosed at the Rabies Laboratory Network of the Ministry of Health (RLNMH) in Mexico from 2000 to 2021. Samples from other species, a skunk, a horse (Equus caballus) (attacked by a cougar), and a gray fox (Urocyon cineroargenteus), were included as reference. Rabies cases in cougars were restricted to two Northern states of Mexico (Sonora and Chihuahua). Five out of six samples of cougars were RVV7 (Arizona gray fox RVV) and one from Sonora was RVV1. Interestingly, there is no evidence of RVV1 in dogs in the Northern states since the 1990s but skunk species now harbor this RVV1 in this region of the country.

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.

The Causes and Long-Term Consequences of Viral Encephalitis

Reports regarding brain inflammation, known as encephalitis, have shown an increasing frequency during the past years. Encephalitis is a relevant concern to public health due to its high morbidity and mortality. Infectious or autoimmune diseases are the most common cause of encephalitis. The clinical symptoms of this pathology can vary depending on the brain zone affected, with mild ones such as fever, headache, confusion, and stiff neck, or severe ones, such as seizures, weakness, hallucinations, and coma, among others. Encephalitis can affect individuals of all ages, but it is frequently observed in pediatric and elderly populations, and the most common causes are viral infections. Several viral agents have been described to induce encephalitis, such as arboviruses, rhabdoviruses, enteroviruses, herpesviruses, retroviruses, orthomyxoviruses, orthopneumovirus, and coronaviruses, among others. Once a neurotropic virus reaches the brain parenchyma, the resident cells such as neurons, astrocytes, and microglia, can be infected, promoting the secretion of pro-inflammatory molecules and the subsequent immune cell infiltration that leads to brain damage. After resolving the viral infection, the local immune response can remain active, contributing to long-term neuropsychiatric disorders, neurocognitive impairment, and degenerative diseases. In this article, we will discuss how viruses can reach the brain, the impact of viral encephalitis on brain function, and we will focus especially on the neurocognitive sequelae reported even after viral clearance.

Endemic persistence of a highly contagious pathogen: Foot-and-mouth disease in its wildlife host

Extremely contagious pathogens are a global biosecurity threat because of their high burden of morbidity and mortality, as well as their capacity for fast-moving epidemics that are difficult to quell. Understanding the mechanisms enabling persistence of highly transmissible pathogens in host populations is thus a central problem in disease ecology. Through a combination of experimental and theoretical approaches, we investigated how highly contagious foot-and-mouth disease viruses persist in the African buffalo, which serves as their wildlife reservoir. We found that viral persistence through transmission among acutely infected hosts alone is unlikely. However, the inclusion of occasional transmission from persistently infected carriers reliably rescues the most infectious viral strain from fade-out. Additional mechanisms such as antigenic shift, loss of immunity, or spillover among host populations may be required for persistence of less transmissible strains.

The ecology of zoonotic parasites in the Carnivora

The order Carnivora includes over 300 species that vary many orders of magnitude in size and inhabit all major biomes, from tropical rainforests to polar seas. The high diversity of carnivore parasites represents a source of potential emerging diseases of humans. Zoonotic risk from this group may be driven in part by exceptionally high functional diversity of host species in behavioral, physiological, and ecological traits. We review global macroecological patterns of zoonotic parasites within carnivores, and explore the traits of species that serve as hosts of zoonotic parasites. We synthesize theoretical and empirical research and suggest future work on the roles of carnivores as biotic multipliers, regulators, and sentinels of zoonotic disease as timely research frontiers.

Rabies in Costa Rica - Next Steps Towards Controlling Bat-Borne Rabies After its Elimination in Dogs

Rabies is an acute, progressive encephalitis caused by a lyssavirus, with the highest case fatality of any conventional infectious disease. More than 17 different lyssaviruses have been described, but rabies virus is the most widely distributed and important member of the genus. Globally, tens of thousands of human fatalities still occur each year. Although all mammals are susceptible, most human fatalities are caused by the bites of rabid dogs, within lesser developed countries. A global plan envisions the elimination of human rabies cases caused via dogs by the year 2030. The combination of prophylaxis of exposed humans and mass vaccination of dogs is an essential strategy for such success. Regionally, the Americas are well on the way to meet this goal. As one example of achievement, Costa Rica, a small country within Central America, reported the last autochthonous case of human rabies transmitted by a dog at the end of the 1970s. Today, rabies virus transmitted by the common vampire bat, Desmodus rotundus, as well as other wildlife, remains a major concern for humans, livestock, and other animals throughout the region. This review summarizes the historical occurrence of dog rabies and its elimination in Costa Rica, describes the current occurrence of the disease with a particular focus upon affected livestock, discusses the ecology of the vampire bat as the primary reservoir relevant to management, details the clinical characteristics of recent human rabies cases, and provides suggestions for resolution of global challenges posed by this zoonosis within a One Health context.