Most infectious diseases of humans are zoonoses, and many of these come from particularly species diverse reservoir taxa, such as bats, birds, and rodents (1). Because of our changing landscape, there is increased exposure of humans to wildlife diseases reservoirs, yet we have little basic information about prevalence, hotspots, and transmission factors of most zoonotic pathogens. Viruses are particularly worrisome as a public health risk due to their fast mutation rates and well-known cross-species transmission abilities. There is a global push to better survey wildlife for viruses (2), but these studies are difficult, and the problem is vast. Astroviruses (AstVs) comprise a diverse family of ssRNA viruses known from mammals and birds. Astroviruses can cause gastroenteritis in humans and are more common in elderly and young children, but the relationship of human to non-human Astroviridae as well as transmission routes are unclear.  AstVs have been detected at high prevalence in bats in multiple studies (3,4), but it is unclear what factors, such as co-infecting viruses and bat reproductive phenology, influence viral shedding and prevalence.
In this recommended study, Vimbiso et al. (5) study the prevalence and diversity of astroviruses in different insectivorous and frugivorous chiropteran species roosting in trees, caves and building basements across Zimbabwe, a region never investigated for astroviruses. Using both pooled population samples and individual samples from 11 different sites, the authors screened for astrovirus prevalence via RT-PCR and identified bat taxa using mitochondrial gene sequencing. An overall prevalence of 10-14% infection was recorded. No clear association of increased astrovirus and coronavirus coinfection was detected, and although astrovirus infection varied over the season, it did not do so in consistent ways across the two primary sampling sites, Magweto and Chirundu. A phylogeny generated by sequencing all of the astrovirus positive samples showed evidence that most of the viral lineages are transmitting within species but across Zibabwae such that most phylogenetic lineages grouped viruses from the same host species together. However, there was ample evidence for interspecies transmission between bats. Finally, a small percentage of the total astrovirus diversity from Zibabwae clustered with sequences from humans. The timing and direction of the transmission between humans and bats need further investigation.
 
This study provides important baseline data about viral diversity and does an excellent job of capturing the spatial, temporal, host species, and sequence level dynamics of the astroviruses. There are clear limitations on how this study can be interpreted due to different sampling regimes and, in particular, the fact that each of the two primary sites was only explored for temporal variation over a single calendar year. That said, the grand diversity of astroviruses demonstrated in insectivorous bats in Zibabwae shows that we are only seeing the very tip of the iceberg with respect to viral diversity with zoonotic potential. As suggested by the reviewers, more studies like this are needed to understand the basic ecology of viruses and to aid in predicting epidemics.

References

1. Mollentze N, Streicker DG. Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts. Proceedings of the National Academy of Sciences. 2020 Apr 28;117(17):9423-30. https://doi.org/10.1073/pnas.1919176117
2. Carroll D, Daszak P, Wolfe ND, Gao GF, Morel CM, Morzaria S, et al. The Global Virome Project. Science. 2018 Feb 23;359(6378):872-4. https://doi.org/10.1126/science.aap7463
3. Lee SY, Son KD, Yong-Sik K, Wang SJ, Kim YK, Jheong WH, et al. Genetic diversity and phylogenetic analysis of newly discovered bat astroviruses in Korea. Arch Virol. 2018;163(11):3065-72. https://doi.org/10.1007/s00705-018-3992-6
4. Seltmann A, Corman VM, Rasche A, Drosten C, Czirják GÁ, Bernard H, et al. Seasonal Fluctuations of Astrovirus, But Not Coronavirus Shedding in Bats Inhabiting Human-Modified Tropical Forests. EcoHealth. 2017 Jun 1;14(2):272-84. https://doi.org/10.1007/s10393-017-1245-x
5. Vimbiso C, Hélène DN, Malika A, Getrude M, Valérie P, Ngoni C, et al. Longitudinal Survey of Astrovirus infection in different bat species in Zimbabwe: Evidence of high genetic Astrovirus diversity. bioRxiv, 2023.04.14.536987, ver. 6 peer-reviewed and recommended by Peer Community In Infections. https://doi.org/10.1101/2023.04.14.536987

High-throughput sequencing (HTS) has revealed an incredible diversity of microorganisms in ecosystems and is also changing the monitoring of macroorganism biodiversity (Deiner et al. 2017; Piper et al. 2019).  

The diagnostic of plant pathogens and the identification of pests is gradually integrating the use of these techniques, but there are still obstacles. Most of them are related to the reliability of these analyses, which have long been considered insufficient because of their dependence on a succession of sophisticated operations involving parameters that are sometimes difficult to adapt to complex matrices or certain diagnostic contexts. The need to validate HTS approaches is gradually being highlighted in recent work but remains poorly documented (Bester et al. 2022).

In this paper, a large community of experts presents and discusses the key steps for optimal control of HTS performance and reliability in a diagnostic context (Massart et al. 2022). It also addresses the issue of costs. The article provides recommendations that closely combine the quality control requirements commonly used in conventional diagnostics with newer or HTS-specific control elements and concepts that are not yet widely used. It discusses the value of these for the use of the various techniques currently covered by the terms "High Throughput Sequencing" in diagnostic activities. The elements presented are intended to limit false positive or false negative results but will also optimise the interpretation of contentious results close to the limits of analytical sensitivity or unexpected results, both of which appear to be frequent when using HTS.

Furthermore, the need for risk analysis, verification and validation of methods is well illustrated with numerous examples for each of the steps considered crucial to ensure reliable use of HTS. The clear contextualisation of the proposals made by the authors complements and clarifies the need for user expertise according to the experimental objectives. Some unanswered questions that will require further development and validation are also presented.

This article should benefit a large audience including researchers with some level of expertise in HTS but unfamiliar with the recent concepts of controls common in the diagnostic world as well as scientists with strong diagnostic expertise but less at ease with the numerous and complex procedures associated with HTS.

References

Bester R, Steyn C, Breytenbach JHJ, de Bruyn R, Cook G, Maree HJ (2022) Reproducibility and Sensitivity of High-Throughput Sequencing (HTS)-Based Detection of Citrus Tristeza Virus and Three Citrus Viroids. Plants, 11, 1939. https://doi.org/10.3390/plants11151939

Deiner K, Bik HM, Mächler E, Seymour M, Lacoursière-Roussel A, Altermatt F, Creer S, Bista I, Lodge DM, de Vere N, Pfrender ME, Bernatchez L (2017) Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Molecular Ecology, 26, 5872–5895. https://doi.org/10.1111/mec.14350

Massart, S et al. (2022) Guidelines for the reliable use of high throughput sequencing technologies to detect plant pathogens and pests. Zenodo, 6637519, ver. 3  peer-reviewed and recommended by Peer Community in Infections. https://doi.org/10.5281/zenodo.6637519

Piper AM, Batovska J, Cogan NOI, Weiss J, Cunningham JP, Rodoni BC, Blacket MJ (2019) Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance. GigaScience, 8, giz092. https://doi.org/10.1093/gigascience/giz092

As recently reported by the world organisation for animal health, 60% of infectious diseases are zoonotic with a significant part associated to ticks. Ticks can transmit various pathogens such as bacteria, viruses and parasites. Among pathogens known to be transmitted by ticks, Ehrlichia ruminantium is an obligate intracellular Gram-negative bacterium responsible for the fatal heartwater disease of domestic and wild ruminants (Allsopp, 2010). E. ruminantium is transmitted by ticks of the genus Amblyomma in the tropical and sub-Saharan areas, as well as in the Caribbean islands. It constitutes a major threat for the American livestock industries since a suitable tick vector is already present in the American mainland and potential introduction of infected A. variegatum through migratory birds or uncontrolled movement of animals from Caribbean could occur (i.e. Deem, 1998 ; Kasari et al 2010). The disease is also a major obstacle to the introduction of animals from heartwater-free to heartwater-infected areas into sub-Saharan Africa and thus restrains breeding programs aiming at upgrading local stocks (Allsopp, 2010).

In this context, it is essential to develop control strategies against heartwater, as developing effective vaccines, for instance. Such an objective requires a better understanding of the early interaction of E. ruminantium and its host cells and of the mechanisms associated with bacterial adhesion to the host-cell. In this study, the authors. studied the role of E. ruminantium membrane protein ERGA_CDS_01230 in the adhesion process to host bovine aortic endothelial cells (BAEC).

After successfully producing the recombinant version of the protein, Pinarello et al (2022) followed the in vitro culture of E. ruminantium in BAEC and observed that the expression of the protein peaked at the extracellular infectious elementary body stages. This result would suggest the likely involvement of the protein in the early interaction of E. ruminantium with its host cells. The authors then showed using flow cytometry, and scanning electron microscopy, that beads coated with the recombinant protein adhered to BAEC. In addition, they also observed that the adhesion protein of E. ruminantium interacted with proteins of the cell's lysate, membrane and organelle fractions. Additionally, enzymatic treatment, degrading dermatan and chondroitin sulfates on the surface of BAEC, was associated with a 50% reduction in the number of bacteria in the host cell after a development cycle, indicating that glycosaminoglycans might play a role in the adhesion of E. ruminantium to the host-cell. Finally, the authors observed that the adhesion protein of E. ruminantium induced a humoral response in vaccinated animals, making this protein a possible vaccine candidate.

As rightly pointed out by both reviewers, the results of this study represent a significant advance (i) in the understanding of the role of the E. ruminantium membrane protein ERGA_CDS_01230 in the adhesion process to the host-cell and (ii) in the development of new control strategies against heartwater as this protein might potentially be used as an immunogen for the development of future vaccines.

References

Allsopp, B.A. (2010). Natural history of Ehrlichia ruminantium. Vet Parasitol 167, 123-135. https://doi.org/10.1016/j.vetpar.2009.09.014

Deem, S.L. (1998). A review of heartwater and the threat of introduction of Cowdria ruminantium and Amblyomma spp. ticks to the American mainland. J Zoo Wildl Med 29, 109-113.

Kasari, T.R. et al (2010). Recognition of the threat of Ehrlichia ruminantium infection in domestic and wild ruminants in the continental United States. J Am Vet Med Assoc. 237:520-30. https://doi.org/10.2460/javma.237.5.520

Pinarello V, Bencurova E, Marcelino I, Gros O, Puech C, Bhide M, Vachiery N, Meyer DF (2022) Ehrlichia ruminantium uses its transmembrane protein Ape to adhere to host bovine aortic endothelial cells. bioRxiv, 2021.06.15.447525, ver. 3 peer-reviewed and recommended by Peer Community in Infections. https://doi.org/10.1101/2021.06.15.447525

Mosquitoes are first vector of pathogen worldwide and transmit several arbovirus, most of them leading to major outbreaks (1). Chikungunya virus (CHIKV) is a perfect example of the “explosive type” of arbovirus, as observed in La Réunion Island in 2005-2006 (2-6) and also in the outbreak of 2007 in Italy (7), both vectorized by Ae. albopictus. Being able to better understand CHIKV intra-vector dynamics is still of major interest since not all chikungunya strain are explosive ones (8). 

In this study (9), the authors have evaluated the vector competence of a local strain of Aedes albopictus (collected in Lyon, France) for CHIKV. They evaluated infection, dissemination and transmission dynamics of CHIKV using different dose of virus in individual mosquitoes from day 2 to day 20 post exposure, by titration and quantification of CHIKV RNA load in the saliva. As highlighted by both reviewers, the most innovative idea in this study was the use of three different oral doses trying to span human viraemia detected in two published studies (10-11), doses that were estimated through their model of human CHIKV viremia in the blood.  They have found that CHIKV dissemination from the Ae. albopictus midgut depends on the interaction between time post-exposure and virus dose (already highlighted by other international publications).  Then their results were implemented in the agent-based model nosoi to estimate the epidemic potential of CHIKV in a French population of Ae. albopictus, using realistic vectorial capacity parameters.

To conclude, the authors have discussed the importance of other parameters that could influence vector competence as mosquito microbiota and temperature, parameters that need also to be estimated in local mosquito population to improve the risk assessment through modelling.  

As pointed out by both reviewers, this is a nice study, well written and easy to read. These results allow filling in another gap of our understanding of CHIKV intra-vector dynamics and highlight the epidemic potential of CHIKV upon transmission by Aedes albopictus in mainland France. For all these reasons, I chose to recommend this article for Peer Community In Infections.

References

1.       Marine Viglietta, Rachel Bellone, Adrien Albert Blisnick, Anna-Bella Failloux. (2021). Vector Specificity of Arbovirus Transmission. Front Microbiol Dec 9;12:773211. https://doi.org/10.3389/fmicb.2021.773211

2.       Schuffenecker I, Iteman I, Michault A, Murri S, Frangeul L, Vaney M-C, Lavenir R, Pardigon N, Reynes J-M, Pettinelli F, Biscornet L, Diancourt L, Michel S, Duquerroy S, Guigon G, Frenkiel M-P, Bréhin A-C, Cubito N, Desprès P, Kunst F, Rey FA, Zeller H, Brisse S. (2006). Genome Microevolution of Chikungunya viruses Causing the Indian Ocean Outbreak. 2006. PLoS Medicine, 3, e263. https://doi.org/10.1371/journal.pmed.0030263

3.       Bonilauri P, Bellini R, Calzolari M, Angelini R, Venturi L, Fallacara F, Cordioli P, 687 Angelini P, Venturelli C, Merialdi G, Dottori M. (2008). Chikungunya Virus in Aedes albopictus, Italy. Emerging Infectious 689 Diseases, 14, 852–854. https://doi.org/10.3201/eid1405.071144

4.       Pagès F, Peyrefitte CN, Mve MT, Jarjaval F, Brisse S, Iteman I, Gravier P, Tolou H, Nkoghe D, Grandadam M. (2009). Aedes albopictus Mosquito: The Main Vector of the 2007 Chikungunya Outbreak in Gabon. PLoS ONE, 4, e4691. https://doi.org/10.1371/journal.pone.0004691

5.       Paupy C, Kassa FK, Caron M, Nkoghé D, Leroy EM (2012) A Chikungunya Outbreak Associated with the Vector Aedes albopictus in Remote Villages of Gabon. Vector-Borne and Zoonotic Diseases, 12, 167–169. https://doi.org/10.1089/vbz.2011.0736

6.       Mombouli J-V, Bitsindou P, Elion DOA, Grolla A, Feldmann H, Niama FR, Parra H-J, Munster VJ. (2013). Chikungunya Virus Infection, Brazzaville, Republic of Congo, 2011. Emerging Infectious Diseases, 19, 1542–1543. https://doi.org/10.3201/eid1909.130451

7.       Venturi G, Luca MD, Fortuna C, Remoli ME, Riccardo F, Severini F, Toma L, Manso MD, Benedetti E, Caporali MG, Amendola A, Fiorentini C, Liberato CD, Giammattei R, Romi R, Pezzotti P, Rezza G, Rizzo C. (2017). Detection of a chikungunya outbreak in Central Italy, August to September 2017. Eurosurveillance, 22, 17–00646. https://doi.org/10.2807/1560-7917.es.2017.22.39.17-00646

8.       de Lima Cavalcanti, T.Y.V.; Pereira, M.R.; de Paula, S.O.; Franca, R.F.d.O. (2022). A Review on Chikungunya Virus Epidemiology, Pathogenesis and Current Vaccine Development. Viruses 2022, 14, 969. https://doi.org/10.3390/v14050969

9.       Barbara Viginier, Lucie Cappuccio, Celine Garnier, Edwige Martin, Carine Maisse, Claire Valiente Moro, Guillaume Minard, Albin Fontaine, Sebastian Lequime, Maxime Ratinier, Frederick Arnaud, Vincent Raquin. (2023). Chikungunya intra-vector dynamics in Aedes albopictus from Lyon (France) upon exposure to a human viremia-like dose range reveals vector barrier permissiveness and supports local epidemic potential. medRxiv, ver.3, peer-reviewed and recommended by Peer Community In Infections. https://doi.org/10.1101/2022.11.06.22281997

10.     Appassakij H, Khuntikij P, Kemapunmanus M, Wutthanarungsan R, Silpapojakul K (2013) Viremic profiles in CHIKV-infected cases. Transfusion, 53, 2567–2574. https://doi.org/10.1111/j.1537-2995.2012.03960.x

11.     Riswari SF, Ma’roef CN, Djauhari H, Kosasih H, Perkasa A, Yudhaputri FA, Artika IM, Williams M, Ven A van der, Myint KS, Alisjahbana B, Ledermann JP, Powers AM, Jaya UA (2015) Study of viremic profile in febrile specimens of chikungunya in Bandung, Indonesia. Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology, 74, 61–5. https://doi.org/10.1016/j.jcv.2015.11.017

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