Various species of Ebolavirus have caused, and are still causing, zoonotic outbreaks and public health crises in Africa. Bats have long been hypothesized to be important reservoir populations for a series of viruses such as Hendra or Marburg viruses, the severe acute respiratory syndrome coronavirus (SARS-CoV, SARS-CoV-2) as well as Ebolaviruses [2, 3]. However the ecology of disease dynamics, disease transmission, and coevolution with their natural hosts of these viruses is still poorly understood, despite their importance for predicting novel outbreaks in human or livestock populations. The evidence that bats function as sylvatic reservoirs for Ebola viruses is yet only partial. Indeed, only few serological studies demonstrated the presence of Ebolavirus antibodies in young bats [4], albeit without providing positive controls of viral detection or identifying the viral species (via PCR). There is thus an unexplained discrepancy between serological data and viral detection [2, 4]. 

In this article, Pleydell et al. [1] use a modeling approach as well as published serological and age-structure (of the bat population) data to calibrate the model simulations. The study starts with the development of an age-structured epidemiological model which includes seasonal birth pulses and waning immunity, both generating pulses of Ebolavirus transmission within a colony of African straw-coloured fruit bats (Eidolon helvum). The epidemiological dynamics of such system of ordinary differential equations can generate annual outbreaks, skipped years or multi-annual cycles up to chaotic dynamics. Therefore, the calibration of the parameters, and the definition of biologically relevant priors, are key. To this aim, the serological data are obtained from a previous study in Cameroon [5], and the age structured of the bat population (birth and mortality) from a population study in Ghana [6]. These data are integrated into the Bayesian analysis and statistical framework to fit the model and generate predictions. In a nutshell, the authors show an overlap between the data and credibility intervals generated by the calibrated model, which thus explains well the seasonality of age-structure, namely changes in pup presence, number of lactating females, or proportion of juveniles in May. The authors can estimate that 76% of adults and 39% of young bats do survive each year, and infections are expected to last one and a half weeks. The epidemiological model predicts that annual birth pulses likely generate annual disease outbreaks, so that weeks 30 to 31 of each year, are predicted to be the best period to isolate the circulating Ebolavirus in this bat population. From the model predictions, the authors estimate the probability to have missed an infectious bat among all the samples tested by PCR being approximately of one per two thousands. The disease dynamics pattern observed in the serology data, and replicated by the model, is likely driven by seasonal pulses of young susceptible bats entering the population. This seasonal birth event increases the viral transmission, resulting in the observed peak of viral prevalence. With the inclusion of immunity waning and antibody persistence, the model results illuminate therefore why previous studies have detected only few positive cases by PCR tests, in contrast to the evidence from serological data. 

 This study provides a first proof of principle that epidemiological modeling, despite its many simplifying assumptions, can be applied to wild species reservoirs of zoonotic diseases in order to optimize the design of field studies to detect viruses. Furthermore, such models can contribute to assess the probability and timing of zoonotic outbreaks in human or livestock populations. This article illustrates one of the manifold applications of mathematical theory of disease epidemiology to optimize sampling of pathogens/parasites or vaccine development and release [7, 8]. The further coupling of such models with population genetics theory and statistical inference methods (using parasite genome data) increasingly provide insights into the adaptation and evolution of parasites to human, crops and livestock populations [9, 10].

References

[1] Pleydell D.R.J., Ndong Bass I., Mba Djondzo F.A., Djomsi D.M., Kouanfack C., Peeters M., and J. Cappelle. 2023. A Bayesian analysis of birth pulse effects on the probability of detecting Ebola virus in fruit bats. bioRxiv, ver. 3 peer reviewed and recommended by Peer Community In Infections. https://doi.org/10.1101/2023.08.10.552777

[2] Caron A., Bourgarel M., Cappelle J., Liégeois F., De Nys H.M., and F. Roger. 2018. Ebola virus maintenance: if not (only) bats, what else? Viruses 10, 549. https://doi.org/10.3390/v10100549

[3] Letko M., Seifert S.N., Olival K.J., Plowright R.K., and V.J. Munster. 2020. Bat-borne virus diversity, spillover and emergence. Nature Reviews Microbiology 18, 461–471. https://doi.org/10.1038/s41579-020-0394-z

[4] Leroy E.M., Kumulungui B., Pourrut X., Rouquet P., Hassanin A., Yaba P., Délicat A., Paweska J.T., Gonzalez J.P., and R. Swanepoel. 2005. Fruit bats as reservoirs of Ebola virus. Nature 438, 575–576. https://doi.org/10.1038/438575a

[5] Djomsi D.M. et al. 2022. Dynamics of antibodies to Ebolaviruses in an Eidolon helvum bat colony in Cameroon. Viruses 14, 560. https://doi.org/10.3390/v14030560

[6] Peel A.J. et al. 2016. Bat trait, genetic and pathogen data from large-scale investigations of African fruit bats Eidolon helvum. Scientific data 3, 1–11. https://doi.org/10.1038/sdata.2016.49

[7] Nyandjo Bamen H.L., Ntaganda J.M., Tellier A. and O. Menoukeu Pamen. 2023. Impact of imperfect vaccine, vaccine trade-off and population turnover on infectious disease dynamics. Mathematics, 11(5), p.1240. https://doi.org/10.3390/math11051240

[8] Saadi N., Chi Y.L., Ghosh S., Eggo R.M., McCarthy C.V., Quaife M., Dawa J., Jit M. and A. Vassall. 2021. Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review. BMC medicine, 19, pp.1-11. https://doi.org/10.1186/s12916-021-02190-3

[9] Maerkle, H., John S., Metzger, L., STOP-HCV Consortium, Ansari, M.A., Pedergnana, V. and Tellier, A., 2023. Inference of host-pathogen interaction matrices from genome-wide polymorphism data. bioRxiv, https://doi.org/10.1101/2023.07.06.547816.

[10] Gandon S., Day T., Metcalf C.J.E. and B.T. Grenfell. 2016. Forecasting epidemiological and evolutionary dynamics of infectious diseases. Trends in ecology & evolution, 31(10), pp.776-788. https://doi.org/10.1016/j.tree.2016.07.010

Mycobacterium bovis, also called M. tuberculosis var. bovis, is a bacterium belonging to the M. tuberculosis complex (i.e., MTBC) and which can cause through zoonotic transmission another form of human tuberculosis (Tb). It is above all the agent of bovine tuberculosis (i.e., bTb) which affects not only cattle (wild or farmed) but also a large diversity of other wild mammals worldwide. An increasing number of infected animal cases are being discovered in many regions of the world, thus raising the problem of tuberculosis transmission, including to humans, more complex than previously thought. Efforts have been made in terms of vaccination or culling of populations of host carrier species, such as the badger for example, however leading to consequences of greater dispersion of the infectious agent. M. bovis shows a more or less significant capacity to persist outside its hosts, particularly in the environment under certain abiotic and biotic conditions. This bacillus can be transmitted and spread in many ways, including through aerosol, mucus and sputum, urine and feces, by direct contact with infected animals, their dead bodies or rather via their excreta or by inhalation of aerosols, depending on the host species concerned.

In this paper, Calenge and his collaborators (Callenge et al. 2024) benefited from a national surveillance program on M. bovis cases in wild species, set up in 2011 in France, i.e., Sylvatub, for detecting and monitoring M. bovis infection in European badger (Meles meles) populations. Sylvatub is a participatory program involving both national and local stakeholder systems in order to determine changes in bTb infection levels in domestic and wild animal species. This original work had two aims: to describe spatial disease dynamics in the three clusters under scrutiny using a complex Bayesian model; and to develop indicators for the monitoring of the M. bovis infection by stakeholders and decision-makers of the program. This paper is timely and very comprehensive.

In this cogent study, the authors illustrate this point by using epidemiological surveillance to obtain large amounts of data (which is generally lacking in human epidemiology, but more dramatically lacking in animal epidemiology) and a highly sophisticated biostatistical analysis (Callenge et al. 2024). It is in itself a demonstration of the current capabilities of population dynamics applied to infectious disease situations, in this case animal, in the rapidly developing discipline of disease ecology and evolution. One of the aims of the study is to propose statistical models that can be used by the different stakeholders in charge, for instance, of wildlife conservation or the regional or State veterinary services to assess disease risk in the most affected regions.

References

Assel AKHMETOVA​, Jimena GUERRERO​, Paul McADAM, Liliana CM SALVADOR​, Joseph CRISPELL​, John LAVERY​, Eleanor PRESHO​, Rowland R KAO​, Roman BIEK​, Fraser MENZIES​, Nigel TRIMBLE​, Roland HARWOOD​, P Theo PEPLER, Katarina ORAVCOVA​, Jordon GRAHAM​, Robin SKUCE​, Louis DU PLESSIS​, Suzan THOMPSON​, Lorraine WRIGHT​, Andrew W BYRNE​, Adrian R ALLEN. 2023. Genomic epidemiology of Mycobacterium bovis infection in sympatric badger and cattle populations in Northern Ireland. Microbial Genomics 9: mgen001023. https://doi.org/10.1099/mgen.0.001023

Roman BIEK, Anthony O’HARE, David WRIGHT, Tom MALLON, Carl McCORMICK, Richard J ORTON, Stanley McDOWELL, Hannah TREWBY, Robin A SKUCE, Rowland R KAO. 2012. Whole genome sequencing reveals local transmission patterns of Mycobacterium bovis in sympatric cattle and badger populations. PLoS Pathogens 8: e1003008. https://doi.org/10.1371/journal.ppat.1003008

Clément CALENGE, Ariane PAYNE, Edouard REVEILLAUD, Céline RICHOMME, Sébastien GIRARD, Stephanie DESVAUX. 2024. Assessing the dynamics of Mycobacterium bovis infection in three French badger populations. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community In Infections. https://doi.org/10.1101/2023.05.31.543041

Marc CHOISY, Pejman ROHANI. 2006. Harvesting can increase severity of wildlife disease epidemics. Proceedings of the Royal Society, London, Ser. B 273: 2025-2034. https://doi.org/10.1098/rspb.2006.3554

Shannon C DUFFY, Sreenidhi SRINIVASAN, Megan A SCHILLING, Tod STUBER, Sarah N DANCHUK, Joy S MICHAEL, Manigandan VENKATESAN, Nitish BANSAL, Sushila MAAN, Naresh JINDAL, Deepika CHAUDHARY, Premanshu DANDAPAT, Robab KATANI, Shubhada CHOTHE, Maroudam VEERASAMI, Suelee ROBBE-AUSTERMAN, Nicholas JULEFF, Vivek KAPUR, Marcel A BEHR. 2020. Reconsidering Mycobacterium bovis as a proxy for zoonotic tuberculosis: a molecular epidemiological surveillance study. Lancet Microbe 1: e66-e73. https://doi.org/10.1016/S2666-5247(20)30038-0

Jean-François GUEGAN. 2019. The nature of ecology of infectious disease. The Lancet Infectious Diseases 19. https://doi.org/10.1016/s1473-3099(19)30529-8

Brandon H HAYES, Timothée VERGNE, Mathieu ANDRAUD, Nicolas ROSE. 2023. Mathematical modeling at the livestock-wildlife interface: scoping review of drivers of disease transmission between species. Frontiers in Veterinary Science 10: 1225446. https://doi.org/10.3389/fvets.2023.1225446

David KING, Tim ROPER, Douglas YOUNG, Mark EJ WOOLHOUSE, Dan COLLINS, Paul WOOD. 2007. Bovine tuberculosis in cattle and badgers. Report to Secretary of State about tuberculosis in cattle and badgers. London, UK. https://www.bovinetb.info/docs/RBCT_david_%20king_report.pdf  

Robert MM SMITH , Francis DROBNIEWSKI, Andrea GIBSON, John DE MONTAGUE, Margaret N LOGAN, David HUNT, Glyn HEWINSON, Roland L SALMON, Brian O’NEILL. 2004. Mycobacterium bovis Infection, United Kingdom. Emerging Infectious Diseases 10: 539-541. https://doi.org/10.3201/eid1003.020819 

Structural variations (SVs) play a key role in viral evolution, and therefore they are also important for infection dynamics. However, the contribution of structural variations to the evolution of double-stranded viruses is limited. This knowledge can help to understand the population dynamics and might be crucial for the future development of viral attenuated vaccines.

In this study, Fuandila et al (1) use the Cyprinid herpesvirus 3 (CyHV-3), commonly known as koi herpesvirus (KHV), to investigate the variability and contribution of structural variations (SV) for viral evolution after 99 passages in vitro. This virus, with the largest genome among herperviruses, causes a lethal infection in common carp and koi associated with mortalities up to 95% (2). Interestingly, KHV infections are caused by haplotype mixtures, which possibly are a source of genome diversification, but make genomic comparisons more difficult.

The authors have used ultra-deep long-read sequencing of two passages, P78 and P99, which were previously described to have differences in virulence. They have found a surprisingly high and wide distribution of SVs along the genome, which were enriched in inversion and deletion events and that often led to defective viral genomes. Although it is known that these defective viral genomes negatively impact viral replication, their implications for virus persistence are still unclear.

Subsequently, the authors concentrated on the virulence-relevant region ORF150, which was found to be different in P78 (deletion in 100% of the reads) and P99 (reference-like haplotype). To understand this loss and gain of full ORF150, they searched for SV turn-over in 10 intermediate passages. This analysis revealed that by passage 10 deleted and inverted (attenuated) haplotypes had already appeared, steadily increased frequency until P78, and then completely disappeared between P78 and P99. This is a striking result that raises new questions as to how this clearance occurs, which is really important as these reversions may result in undesirable increases in virulence of live-attenuated vaccines.

We recommend this preprint because its use of ultra-deep long-read sequencing has permitted to better understand the role of SV diversity and dynamics in viral evolution. This study shows an unexpectedly high number of structural variations, revealing a novel source of virus diversification and confirming the different mixtures of haplotypes in different passages, including the gain of function. This research provides basic knowledge for the future design of live-attenuated vaccines, to prevent the reversion to virulent viruses. 

References

(1)  Fuandila NN, Gosselin-Grenet A-S, Tilak M-K, Bergmann SM, Escoubas J-M, Klafack S, Lusiastuti AM, Yuhana M, Fiston-Lavier A-S, Avarre J-C, Cherif E (2022) Structural variation turnovers and defective genomes: key drivers for the in vitro evolution of the large double-stranded DNA koi herpesvirus (KHV). bioRxiv, 2022.03.10.483410, ver. 4 peer-reviewed and recommended by Peer Community in Infections. https://doi.org/10.1101/2022.03.10.483410

(2)  Sunarto A, McColl KA, Crane MStJ, Sumiati T, Hyatt AD, Barnes AC, Walker PJ. Isolation and characterization of koi herpesvirus (KHV) from Indonesia: identification of a new genetic lineage. Journal of Fish Diseases, 34, 87-101. https://doi.org/10.1111/j.1365-2761.2010.01216.x 

The impact of virus infection of a plant on an aphid’s behaviour has been observed in many studies [1]. Indeed, virus infection can alter plant biochemistry through the emission of volatile organic compounds and plant tissue content modification. These alterations can further impact the interactions between plants and aphids. However, although it is a well-known phenomenon, very few studies have explored the consequences of plant virus infection on the gene expression of aphids to understand better the aphid’s manipulation by the plant virus. In this context, the recommended study [2] reports a comprehensive transcriptomic analysis of the genes expressed by one aphid species, Myzus persicae, a vector of several plant viruses, when feeding on plants. Michelle Heck underlined how significant this study is for comprehending the molecular bases of aphid-vector manipulation by plant viruses (see below).

Interestingly, the study design has integrated several factors that might influence the gene expression of M. persicae when feeding on the plant. Indeed, the authors investigated the effect of two plant species (Arabidopsis thaliana and Camelia sativa) and two virus species [turnip yellows virus (TuYV) and cauliflower mosaic virus (CaMV)]. Noteworthy, the transmission mode of TuYV is circulative and persistent, while CaMV is transmitted by a semi-persistent non-circulative mode. As Juan José Lopez Moya mentioned, multiple comparisons allowed the identification of the different responses of aphids in front of different host plants infected or not by different viruses (see below). This publication is complementary to a previous publication from the same team focusing on plant transcriptome analysis [3].

Thanks to their experimental design, the authors identified genes commonly deregulated by both viruses and/or both plant species and deregulated genes by a single virus or a single plant. Figure 4 nicely summarizes the number of deregulated genes. A thorough discussion on the putative role of deregulated genes in different conditions gave a comprehensive follow-up of the results and their impact on the current knowledge of plant-virus-vector interactions.

This study has now opened the gate to promising research focusing on the functional validation of the identified genes while also narrowing the study from the body to the tissue level.

References:

1. Carr JP, Tungadi T, Donnelly R, Bravo-Cazar A, Rhee S-J, Watt LG, Mutuku JM, Wamonje FO, Murphy AM, Arinaitwe W, Pate AE, Cunniffe NJ, Gilligan CA (2020) Modelling and manipulation of aphid-mediated spread of non-persistently transmitted viruses. Virus Research, 277, 197845. https://doi.org/10.1016/j.virusres.2019.197845

2. Chesnais Q, Golyaev V, Velt A, Rustenholz C, Verdier M, Brault V, Pooggin MM, Drucker M (2022) Transcriptome responses of the aphid vector Myzus persicae are shaped by identities of the host plant and the virus. bioRxiv , 2022.07.18.500449, ver. 5 peer-reviewed and recommended by Peer Community in Infections. https://doi.org/10.1101/2022.07.18.500449

3. Chesnais Q, Golyaev V, Velt A, Rustenholz C, Brault V, Pooggin MM, Drucker M (2022) Comparative Plant Transcriptome Profiling of Arabidopsis thaliana Col-0 and Camelina sativa var. Celine Infested with Myzus persicae Aphids Acquiring Circulative and Noncirculative Viruses Reveals Virus- and Plant-Specific Alterations Relevant to Aphid Feeding Behavior and Transmission. Microbiology Spectrum, 10, e00136-22. https://doi.org/10.1128/spectrum.00136-22

Understanding the ecological and evolutionary factors underlying the spread of new fungal pathogen populations can inform the development of more effective management strategies. In plant pathology, pathogenicity is generally presented as having two components: ‘virulence’ (qualitative pathogenicity) and aggressiveness (quantitative pathogenicity). Changes in virulence in response to the deployment of new resistant varieties are a major driver of the spread of new populations (called pathotypes, or races) in modern agrosystems, and the genomic (i.e. proximal) and eco-evolutionary (i.e. ultimate) factors underlying these changes are well-documented [1,2,3]. By contrast, the role of changes in aggressiveness in the spread of pathotypes remains little known [4].

The study by Cécilia Fontyn and collaborators [5] set out to characterize changes in aggressiveness for isolates of two pathotypes of the wheat leaf rust (Puccinia triticina) that have been dominant in France during the 2005-2016 period. Isolates were genetically characterized using multilocus microsatellite typing and phenotypically characterized for three components of aggressiveness on wheat varieties: infection efficiency, latency period, and sporulation capacity. Using experiments that represent quite a remarkable amount of work and effort, Fontyn et al. showed that each dominant pathotype consisted of several genotypes, including common genotypes whose frequency changed over time. For each pathotype, the genotypes that were more common initially were replaced by a more aggressive genotype. Together, these results show that changes in the genetic composition of populations of fungal plant pathogens can be associated with, and may be caused by, changes in the quantitative components of pathogenicity. This study also illustrates how extensive, decade-long monitoring of fungal pathogen populations, such as the one conducted for wheat leaf rust in France, represents a very valuable resource for research.

REFERENCES

[1] Brown, J. K. (1994). Chance and selection in the evolution of barley mildew. Trends in Microbiology, 2(12), 470-475. https://doi.org/10.1016/0966-842x(94)90650-5

[2] Daverdin, G., Rouxel, T., Gout, L., Aubertot, J. N., Fudal, I., Meyer, M., Parlange, F., Carpezat, J., & Balesdent, M. H. (2012). Genome structure and reproductive behaviour influence the evolutionary potential of a fungal phytopathogen. PLoS Pathogens, 8(11), e1003020. https://doi.org/10.1371/journal.ppat.1003020

[3] Gladieux, P., Feurtey, A., Hood, M. E., Snirc, A., Clavel, J., Dutech, C., Roy, M., & Giraud, T. (2015). The population biology of fungal invasions.Molecular Ecology, 24(9), 1969-86. https://doi.org/10.1111/mec.13028

[4] Fontyn, C., Zippert, A. C., Delestre, G., Marcel, T. C., Suffert, F., & Goyeau, H. (2022). Is virulence phenotype evolution driven exclusively by Lr gene deployment in French Puccinia triticina populations?. Plant Pathology, 71(7), 1511-1524. https://doi.org/10.1111/ppa.13599

[5] Fontyn, C., Meyer, K. J., Boixel, A. L., Delestre, G., Piaget, E., Picard, C., Suffer, F., Marcel, T.C., & Goyeau, H. (2022). Evolution within a given virulence phenotype (pathotype) is driven by changes in aggressiveness: a case study of French wheat leaf rust populations. bioRxiv, 2022.08.29.505401, ver. 3 peer-reviewed and recommended by Peer Community in Infections.  https://doi.org/10.1101/2022.08.29.505401