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28 Oct 2022
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Development of nine microsatellite loci for Trypanosoma lewisi, a potential human pathogen in Western Africa and South-East Asia, and preliminary population genetics analyses

Preliminary population genetic analysis of Trypanosoma lewisi

Recommended by based on reviews by Gabriele Schönian and 1 anonymous reviewer

Trypanosoma lewisi is an atypical trypanosome species. Transmitted by fleas, it has a high prevalence and worldwide distribution in small mammals, especially rats [1]. Although not typically thought to infect humans, there has been a number of reports of human infections by T. lewisi in Asia including a case of a fatal infection in an infant [2]. The fact that the parasite is resistant to lysis by normal human serum [3] suggests that many people, especially immunocompromised individuals, may be at risk from zoonotic infections by this pathogen, particularly in regions where there is close contact with T. lewisi-infected rat fleas. Indeed, it is also possible that cryptic T. lewisi infections exist but have hitherto gone undetected. Such asymptomatic infections have been detected for a number of parasitic infections including the related parasite T. b. gambiense [4]. 
 
Despite the fact that T. lewisi parasites pose a risk to human health, very little is known about their population structure, reproductive mode, population size or dispersal. In the article [5], Ségard et al. presented the first attempt at examining the population structure of the parasite. They developed microsatellite markers and used them to analyse a small set of samples from West Africa and Southeast Asia. Although the number of microsatellite markers is not very high and they encountered problems of PCR amplification especially of the southeast Asian samples, they did provide preliminary data that hints at a clonal population structure with rare recombination and suggests population subdivisions occurring at a scale that is equal, and probably smaller than a neighborhood of several houses with a short generation time. These are very interesting preliminary findings that will need to be validated using a larger cohort with more markers or by whole genome sequencing.
 

References


[1] Hoare CA (1972) The trypanosomes of mammals. A zoological monograph. The trypanosomes of mammals. A zoological monograph.

[2] Truc P, Büscher P, Cuny G, Gonzatti MI, Jannin J, Joshi P, Juyal P, Lun Z-R, Mattioli R, Pays E, Simarro PP, Teixeira MMG, Touratier L, Vincendeau P, Desquesnes M (2013) Atypical Human Infections by Animal Trypanosomes. PLOS Neglected Tropical Diseases, 7, e2256. https://doi.org/10.1371/journal.pntd.0002256

[3] Lun Z-R, Wen Y-Z, Uzureau P, Lecordier L, Lai D-H, Lan Y-G, Desquesnes M, Geng G-Q, Yang T-B, Zhou W-L, Jannin JG, Simarro PP, Truc P, Vincendeau P, Pays E (2015) Resistance to normal human serum reveals Trypanosoma lewisi as an underestimated human pathogen. Molecular and Biochemical Parasitology, 199, 58–61. https://doi.org/10.1016/j.molbiopara.2015.03.007

[4] Büscher P, Bart J-M, Boelaert M, Bucheton B, Cecchi G, Chitnis N, Courtin D, Figueiredo LM, Franco J-R, Grébaut P, Hasker E, Ilboudo H, Jamonneau V, Koffi M, Lejon V, MacLeod A, Masumu J, Matovu E, Mattioli R, Noyes H, Picado A, Rock KS, Rotureau B, Simo G, Thévenon S, Trindade S, Truc P, Reet NV (2018) Do Cryptic Reservoirs Threaten Gambiense-Sleeping Sickness Elimination? Trends in Parasitology, 34, 197–207. https://doi.org/10.1016/j.pt.2017.11.008

[5] Ségard A, Roméro A, Ravel S, Truc P, Gauthier D, Gauthier P, Dossou H-J, Sylvestre B, Houéménou G, Morand S, Chaisiri K, Noûs C, De Meeûs T (2022) Development of nine microsatellite loci for Trypanosoma lewisi, a potential human pathogen in Western Africa and South-East Asia, and preliminary population genetics analyses. Zenodo, 6460010, ver. 3 peer-reviewed and recommended by Peer Community in Infections. https://doi.org/10.5281/zenodo.6460010

Development of nine microsatellite loci for Trypanosoma lewisi, a potential human pathogen in Western Africa and South-East Asia, and preliminary population genetics analysesAdeline Ségard, Audrey Romero, Sophie Ravel, Philippe Truc, Gauthier Dobigny, Philippe Gauthier, Jonas Etougbetche, Henri-Joel Dossou, Sylvestre Badou, Gualbert Houéménou, Serge Morand, Kittipong Chaisiri, Camille Noûs, Thierry deMeeûs<p><em>Trypanosoma lewisi</em> belongs to the so-called atypical trypanosomes that occasionally affect humans. It shares the same hosts and flea vector of other medically relevant pathogenic agents as Yersinia pestis, the agent of plague. Increasi...Animal diseases, Disease Ecology/Evolution, Ecology of hosts, infectious agents, or vectors, Eukaryotic pathogens/symbionts, Evolution of hosts, infectious agents, or vectors, Microbiology of infections, Parasites, Population genetics of hosts, in...Annette MacLeod2022-04-21 17:04:37 View
24 Jun 2024
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Differences in specificity, development time and virulence between two acanthocephalan parasites, infecting two cryptic species of Gammarus fossarum

Gammarid is not equal gammarid for acanthocephalan parasites

Recommended by based on reviews by 2 anonymous reviewers

The question on the role of different alternative hosts in the life cycle of acanthocephalan parasites has not been fully resolved to date. There is some information on the use of fish hosts in the genus Pomphorhynchus (Perrot-Minnot et al. 2019). It is known that acanthocephalans of the genus Pomphorhynchus can infect a number of different amphipod species (e.g. Bauer et al. 2000; Cornet et al. 2010; Dezfuli et al. 1999) but it is not clear if some host species might be more “advantageous” for the parasite, or if the parasite is more virulent to some host species than to others. Bauer et al. (2024) investigated different well characterized cryptic lineages of Gammarus fossarum (Weiss et al. 2013) for their susceptibility for two Pomphorhynchus sp. The results show that there is a difference in susceptibility to acanthocephalans between different linages of G. fossarum. Additionally, a parasite species specific difference was detected: the difference in susceptibility was more pronounced for P. tereticollis than for P. laevis. P. tereticollis was less virulent and developed slower than P. laevis (in G. fossarum).

Besides the improved understanding of the biology of acanthocephalan parasites, this study clearly points out that we have to be careful with putting the “generalist” label on parasites simply due to the number of alternative host species we find them in. Instead, we should always have in mind that some of these hosts might be less suitable for the parasite than others when comparing quantitative data on the infection success.

I highly appreciate the experimental approach taken that allows more profound conclusions than evaluations of field data. Experiments and analyses have been conducted well. I think this paper is significantly enhancing our knowledge on the specificity for the intermediate host. I find it highly remarkable that this was even found among different host lineages.

References

Bauer, A., Trouve, S., Gregoire, A., Bollache, L., Cezilly, F. (2000) Differential influence of Pomphorhynchus laevis (Acanthocephala) on the behaviour of native and invader gammarid species. International Journal for Parasitology, 30(14), 1453-1457. https://doi.org/10.1016/s0020-7519(00)00138-7

Bauer, A., Develay Nguyen, L., Motreuil, S., Teixeira, M., Debrosse, N., Rigaud, T. (2024) Experimental infections reveal differences in specificity, development time and virulence between the acanthocephalan parasite Pomphorhynchus tereticollis and its sympatric counterpart P. laevis, in two cryptic species of Gammarus fossarum. HAL, Ver. 2, Peer-Reviewed and Recommended by Peer Community in Infections, hal-04455823. https://hal.science/hal-04455823  

Cornet, S., Sorci, G., Moret, Y. (2010) Biological invasion and parasitism: invaders do not suffer from physiological alterations of the acanthocephalan Pomphorhynchus laevis. Parasitology, 137(1), 137-147. https://doi.org/10.1017/S0031182009991077 

Dezfuli, B.S., Rossetti, E., Bellettato, C.M., Maynard, B.J. (1999) Pomphorhynchus laevis in its intermediate host Echinogammarus stammeri in the River Brenta, Italy. Journal of Helminthology, 73(2), 95-102. https://doi.org/10.1017/S0022149X00700277 

Perrot-Minnot, M.J., Guyonnet, E., Bollache, L., Lagrue, C. (2019) Differential patterns of definitive host use by two fish acanthocephalans occurring in sympatry: Pomphorhynchus laevis and Pomphorhynchus tereticollis. International Journal for Parasitology: Parasites and Wildlife, 8, 135-144. https://doi.org/10.1016/j.ijppaw.2019.01.007 

Weiss, M., Macher, J.N., Seefeldt, M.A., Leese, F. (2013) Molecular evidence for further overlooked species within the Gammarus fossarum complex (Crustacea: Amphipoda). Hydrobiologia, 721(1), 165-184. https://doi.org/10.1007/s10750-013-1658-7

 

Differences in specificity, development time and virulence between two acanthocephalan parasites, infecting two cryptic species of *Gammarus fossarum*Alexandre Bauer, Lucie Develay Nguyen, Sébastien Motreuil, Maria Teixeira, Nelly Debrosse, Thierry Rigaud<p style="text-align: justify;">Multi-host parasites can exploit various host species that differ in abundance and susceptibility to infection, which will contribute unequally to their transmission and fitness. Several species of acanthocephalan m...Ecology of hosts, infectious agents, or vectors, Evolution of hosts, infectious agents, or vectors, Interactions between hosts and infectious agents/vectors, Molecular genetics of hosts, infectious agents, or vectors, Parasites, Resistance/Virulen...Daniel Grabner2024-02-14 13:39:19 View
02 Jun 2023
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Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission

What you eat can eliminate you: bloodmeal sources and mosquito fitness

Recommended by based on reviews by Francisco C. Ferreira and 1 anonymous reviewer

​​Diptera-borne pathogens rank among the most serious health threats to vertebrate organisms around the world, particularly in tropical areas undergoing strong human impacts – e.g., urbanization and farming –, where social unrest and poor economies exacerbate the risk (Allen et al. 2017; Robles-Fernández et al. 2022). Although scientists have acquired a detailed knowledge on the life-history of malaria parasites (Pacheco and Escalante 2023), they still do not have enough information about their insect vectors to make informed management and preventive decisions (Santiago-Alarcon 2022).

In this sense, I am pleased to recommend the study of Vantaux et al. (2023), where authors conducted an experimental and theoretical study to analyzed how the diversity of blood sources (i.e., human, cattle, sheep, and chicken) affected the fitness of the human malaria parasite – Plasmodium falciparum – and its mosquito vector – Anopheles gambiae s.l.

The study was conducted in Burkina Faso, West Africa. Interestingly, authors did not find a significant effect of blood meal source on parasite development, and a seemingly low impact on the fitness of mosquitoes that were exposed to parasites. However, mosquitoes’ feeding rate, survival, fecundity, and offspring size were negatively affected by the type of blood meal ingested. In general, chicken blood represented the worst meal source for the different measures of mosquito fitness, and sheep blood seems to be the least harmful. This result was supported by the theoretical model, where vectorial capacity was always better when mosquitoes fed on sheep blood compared to cow and chicken blood. Thus, the knowledge generated by this study provides a pathway to reduce human infection risk by managing the diversity of farm animals. For instance, transmission to humans can decrease when chickens and cows represent most of the available blood sources in a village.

These results along with other interesting details of this study, represent a clear example of the knowledge and understanding of insect vectors that we need to produce in the future, particularly to manage and prevent hazards and risks (sensu Hoseini et al. 2017).

REFERENCES

Allen T., et al., Global hotspots and correlates of emerging zoonotic diseases. Nat. Commun. 8, 1124. (2017). https://doi.org/10.1038/s41467-017-00923-8

Hosseini P.R., et al., Does the impact of biodiversity differ between emerging and endemic pathogens? The need to separate the concepts of hazard and risk. Philos. Trans. R. Soc. Lond. B Biol. Sci. 372, 20160129 (2017). https://doi.org/10.1098/rstb.2016.0129

Pacheco M.A., and Escalante, A.A., Origin and diversity of malaria parasites and other Haemosporida. Trend. Parasitol. (2023) https://doi.org/10.1016/j.pt.2023.04.004

Robles-Fernández A., et al., Wildlife susceptibility to infectious diseases at global scales. PNAS 119: e2122851119. (2022). https://doi.org/10.1073/pnas.2122851119

Santiago-Alarcon D. A meta-analytic approach to investigate mosquitoes’ (Diptera: Culicidae) blood feeding preferences from non-urban to urban environments. In: Ecology and Control of Vector-borne Diseases, vol. 7 (R.G. Gutiérrez-López, J.G. Logan, Martínez-de la Puente J., Eds). Pp. 161-177. Wageningen Academic Publishers. eISBN: 978-90-8686-931-2 | ISBN: 978-90-8686-379-2 (2022).

Vantaux A. et al. Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Infections (2023). https://doi.org/10.1101/2023.02.10.527988

Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmissionAmélie Vantaux, Nicolas Moiroux, Kounbobr Roch Dabiré, Anna Cohuet, Thierry Lefèvre<p style="text-align: justify;">The transmission of malaria parasites from mosquito to human is largely determined by the dietary specialization of <em>Anopheles mosquitoes</em> to feed on humans. Few studies have explored the impact of blood meal...Ecology of hosts, infectious agents, or vectors, Parasites, VectorsDiego Santiago-Alarcon2023-02-13 11:02:58 View
21 Sep 2023
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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

Fill in one gap in our understanding of CHIKV intra-vector dynamics

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

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

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 potentialBarbara Viginier, Lucie Cappuccio, Celine Garnier, Edwige Martin, Carine Maisse, Claire Valiente Moro, Guillaume Minard, Albin Fontaine, Sebastian Lequime, Maxime Ratinier, Frederick Arnaud, Vincent Raquin<p>Arbovirus emergence and epidemic potential, as approximated by the vectorial capacity formula, depends on host and vector parameters, including the vector intrinsic ability to replicate then transmit the pathogen known as vector competence. Vec...Epidemiology, Vectors, VirusesSara Moutailler2023-06-17 15:59:17 View
06 Apr 2023
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Evolution within a given virulence phenotype (pathotype) is driven by changes in aggressiveness: a case study of French wheat leaf rust populations

Changes in aggressiveness in pathotypes of wheat leaf rust

Recommended by based on reviews by 2 anonymous reviewers

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

Evolution within a given virulence phenotype (pathotype) is driven by changes in aggressiveness: a case study of French wheat leaf rust populationsCécilia FONTYN, Kevin JG MEYER, Anne-Lise BOIXEL, Ghislain DELESTRE, Emma PIAGET, Corentin PICARD, Frédéric SUFFERT, Thierry C MARCEL, Henriette GOYEAU<p style="text-align: justify;">Plant pathogens are constantly evolving and adapting to their environment, including their host. Virulence alleles emerge, and then increase, and sometimes decrease in frequency within pathogen populations in respon...Coevolution, Epidemiology, Evolution of hosts, infectious agents, or vectors, Interactions between hosts and infectious agents/vectors, Pathogenic/Symbiotic Fungi, Phytopathology, Plant diseases, Population dynamics of hosts, infectious agents, or...Pierre Gladieux Emerson Del Ponte , Jacqui Shykoff, Leïla Bagny Beilhe , Alexey Mikaberidze 2022-09-29 20:01:57 View
19 Jul 2023
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A soft tick vector of Babesia sp. YLG in Yellow-legged gull (Larus michahellis) nests

A four-year study reveals the potential role of the soft tick Ornithodoros maritimus in the transmission and circulation of Babesia sp. YLG in Yellow-legged gull colonies.

Recommended by based on reviews by Hélène Jourdan-Pineau and Tahar Kernif

Worldwide, ticks and tick-borne diseases are a persistent example of problems at the One Health interface between humans, wildlife, and environment (1, 2). The management and prevention of ticks and tick-borne diseases require a better understanding of host, tick and pathogen interactions and thus get a better view of the tick-borne pathosystems.

In this study (3), the tick-borne pathosystem included three component species: first a seabird host, the Yellow-legged gull (YLG - Larus michahellis, Laridae), second a soft nidicolous tick (Ornithodoros maritimus, Argasidae, syn. Alectorobius maritimus) known to infest this host and third a blood parasite (Babesia sp. YLG, Piroplasmidae). In this pathosystem, authors investigated the role of the soft tick, Ornithodoros maritimus, as a potential vector of Babesia sp. YLG. They analyzed the transmission of Babesia sp. YLG by collecting different tick life stages from YLG nests during 4 consecutive years on the islet of Carteau (Gulf of Fos, Camargue, France). Ticks were dissected and organs were analyzed separately to detect the presence of Babesia sp DNA and to evaluate different transmission pathways.

While the authors detected Babesia sp. YLG DNA in the salivary glands of nymphs, females and males, this result reveals a strong suspicion of transmission of the parasite by the soft tick. Babesia sp. YLG DNA was also found in tick ovaries, which could indicate possible transovarial transmission. Finally, the authors detected Babesia sp. YLG DNA in several male testes and in endospermatophores, and notably in a parasite-free female (uninfected ovaries and salivary glands). These last results raise the interesting possibility of sexual transmission from infected males to uninfected females.

As pointed out by both reviewers, this is a nice study, well written and easy to read. All the results are new and allow to better understand the role of the soft tick, Ornithodoros maritimus, as a potential vector of Babesia sp. YLG. They finally question about the degree to which the parasite can be maintained locally by ticks and the epidemiological consequences of infection for both O. maritimus and its avian host. For all these reasons, I chose to recommend this article for Peer Community In Infections.

References

  1. Dantas-Torres et al (2012). Ticks and tick-borne diseases: a One Health perspective. Trends Parasitol. 28:437. https://doi.org/10.1016/j.pt.2012.07.003 
  2. Johnson N et al (2022). One Health Approach to Tick and Tick-Borne Disease Surveillance in the United Kingdom. Int J Environ Res Public Health. 19:5833. https://doi.org/10.3390/ijerph19105833
  3. Bonsergent C, Vittecoq M, Leray C, Jouglin M, Buysse M, McCoy KD, Malandrin L. A soft tick vector of Babesia sp. YLG in Yellow-legged gull (Larus michahellis) nests. bioRxiv, 2023.03.24.534071, ver. 3 peer-reviewed and recommended by Peer Community in Infections. https://doi.org/10.1101/2023.03.24.534071
A soft tick vector of *Babesia* sp. YLG in Yellow-legged gull (*Larus michahellis*) nestsClaire Bonsergent, Marion Vittecoq, Carole Leray, Maggy Jouglin, Marie Buysse, Karen D. McCoy, Laurence Malandrin<p style="text-align: justify;"><em>Babesia </em>sp. YLG has recently been described in Yellow-legged gull (<em>Larus michahellis</em>) chicks and belongs to the Peircei clade in the new classification of Piroplasms. Here, we studied <em>Babesia <...Ecology of hosts, infectious agents, or vectors, Eukaryotic pathogens/symbionts, Interactions between hosts and infectious agents/vectors, Parasites, VectorsThomas Pollet2023-03-29 14:33:40 View
17 Jan 2024
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Assessing the dynamics of Mycobacterium bovis infection in three French badger populations

From disease surveillance to public action. Re-inforcing both epidemiological surveillance and data analysis: an illustration with Mycobacterium bovis

Recommended by ORCID_LOGO based on reviews by Rowland Kao and 1 anonymous reviewer

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 

Assessing the dynamics of *Mycobacterium bovis* infection in three French badger populationsClement CALENGE, Ariane PAYNE, Edouard REVEILLAUD, Celine RICHOMME, Sebastien GIRARD, Stephanie DESVAUX<p>The Sylvatub system is a national surveillance program established in 2011 in France to monitor infections caused by <em>Mycobacterium bovis</em>, the main etiologic agent of bovine tuberculosis, in wild species. This participatory program, inv...Animal diseases, Ecohealth, Ecology of hosts, infectious agents, or vectors, Epidemiology, Geography of infectious diseases, Pathogenic/Symbiotic Bacteria, ZoonosesJean-Francois Guégan2023-06-05 10:50:49 View
14 Feb 2024
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A Bayesian analysis of birth pulse effects on the probability of detecting Ebola virus in fruit bats

Epidemiological modeling to optimize the detection of zoonotic viruses in wild (reservoir) species

Recommended by ORCID_LOGO based on reviews by Hetsron Legrace NYANDJO BAMEN and 1 anonymous reviewer

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

A Bayesian analysis of birth pulse effects on the probability of detecting Ebola virus in fruit batsDavid R.J. Pleydell, Innocent Ndong Bass, Flaubert Auguste Mba Djondzo, Dowbiss Meta Djomsi, Charles Kouanfack, Martine Peeters, Julien Cappelle <p>Since 1976 various species of Ebolavirus have caused a series of zoonotic outbreaks and public health crises in Africa. Bats have long been hypothesised to function as important hosts for ebolavirus maintenance, however the transmission ecology...Animal diseases, Disease Ecology/Evolution, Ecohealth, Ecology of hosts, infectious agents, or vectors, Epidemiology, Population dynamics of hosts, infectious agents, or vectors, Reservoirs, Viruses, ZoonosesAurelien Tellier2023-08-16 16:57:05 View
23 Mar 2023
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The helper strategy in vector-transmission of plant viruses

The intriguing success of helper components in vector-transmission of plant viruses.

Recommended by based on reviews by Jamie Bojko and Olivier Schumpp

Most plant-infecting viruses rely on an animal vector to be transmitted from one sessile host plant to another. A fascinating aspect of virus-vector interactions is the fact that viruses from different clades produce different proteins to bind vector receptors (1). Two major processes are described. In the “capsid strategy”, a motif of the capsid protein is directly binding to the vector receptor. In the “helper strategy”, a non-structural component, the helper component (HC), establishes a bridge between the virus particle and the vector’s receptor.   

In this exhaustive review focusing on hemipteran insect vectors, Di Mattia et al. (2) are revisiting the helper strategy in light of recent results. The authors first place the discoveries of the HC strategy in a historical context, suggesting that HC are exclusively found in non-circulative viruses (viruses that only attach to the vector). They present an overview of the nature and modes of action of helper components in the major virus clades of non-circulative viruses (Potyviruses and Caulimoviruses). Authors then detail recent advances, to which they have significantly contributed, showing that the helper strategy also appears widespread in circulative transmission categories (Tenuiviruses, Nanoviruses). 

In an extensive perspective section, they raise the question of the evolutionary significance of the existence of HC in numerous unrelated viruses, transmitted by unrelated vectors through different mechanisms. They explore the hypothesis that the helper strategy evolved several times independently in distinct viral clades and for different reasons. In particular, they present several potential benefits of plant virus HC related to virus cooperation, collective transmission and effector-driven infectivity.

As pointed out by both reviewers, this is a very clear and synthetic review. Di Mattia et al. present an exhaustive overview of virus HC-vector molecular interactions and address functionally and evolutionarily important questions. This review should benefit a large audience interested in host-virus interactions and transmission processes.

REFERENCES

(1) Ng JCK, Falk BW (2006) Virus-Vector Interactions Mediating Nonpersistent and Semipersistent Transmission of Plant Viruses. Annual Review of Phytopathology, 44, 183–212. https://doi.org/10.1146/annurev.phyto.44.070505.143325

(2) Di Mattia J, Zeddam J-L, Uzest M, Blanc S (2023) The helper strategy in vector-transmission of plant viruses. Zenodo, ver. 2 peer-reviewed and recommended by Peer Community In Infections. https://doi.org/10.5281/zenodo.7709290

The helper strategy in vector-transmission of plant virusesDi Mattia Jérémy, Zeddam Jean Louis, Uzest Marilyne and Stéphane Blanc<p>An intriguing aspect of vector-transmission of plant viruses is the frequent involvement of a helper component (HC). HCs are virus-encoded non-structural proteins produced in infected plant cells that are mandatory for the transmission success....Evolution of hosts, infectious agents, or vectors, Interactions between hosts and infectious agents/vectors, Molecular biology of infections, Molecular genetics of hosts, infectious agents, or vectors, Plant diseases, Vectors, VirusesChristine Coustau2022-10-28 17:32:39 View
08 Dec 2022
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Zoonotic emergence at the animal-environment-human interface: the forgotten urban socio-ecosystems

Zoonotic emergence and the overlooked case of cities

Recommended by based on reviews by Eric Dumonteil, Nicole L. Gottdenker and 1 anonymous reviewer

Zoonotic pathogens, those transmitted from animals to humans, constitute a major public health risk with high associated global economic costs. Diseases associated with these pathogens represent more than 60% of emerging infectious diseases and predominantly originate in wildlife (1). Over the last decades, the emergence and re-emergence of zoonotic pathogens have led to an increasing number of epidemics, as illustrated by the current Covid-19 pandemic. There is ample evidence that human impact on native ecosystems such as deforestation, agricultural development, and urbanization, is linked to spillover of pathogens from animals to humans (2). However, research and calls to action have mainly focused on the importance of surveillance and prevention of zoonotic emergences along landscape interfaces, with special emphasis on tropical forests and agroecosystems, and studies and reviews pointing out the zoonotic risk associated with cities are scarce.  Additionally, cities are sometimes wrongly seen as one homogeneous ecosystem, almost exclusively human, with a Northern hemisphere-biased perception of what a city is, which fails to take into account the ecological and socio-economic diversities that can constitute an urban area.

Here, Dobigny and Morand (3) aim to draw attention to the importance of urban ecosystems in zoonotic risk and advocate that further attention should be paid to urban, peri-urban and suburban areas. In this well-organized and well-documented review, the authors show, using updated literature, that cities are places where massive contacts occur between wildlife, domestic animals, and human inhabitants (thus constituting spillover opportunities), and that it is even likely that human and wildlife contact in urban centers is more prevalent than in wild areas, perhaps contrary to intuition. Indeed, cities currently constitute the most important environment of human life and are places for millions of close interactions between humans and animals, including pets and domestic animals, wild animals through the intrusion of wild urban-adapted species (e.g., some bat, rodent, or bird species among others), manipulation and consumption of wildlife meat, and the existence of wildlife meat markets, which all constitute a major risk for zoonotic spillover. In cities, lab escapees of zoonotic pathogens also exist, and trends of adaptation to urban ecological conditions of many vectors of primary health importance is also a concern. The authors further argue that cities are predominant places for both epidemic amplification of human-human transmitted pathogens, because they are places with high human densities and population growth, and for dissemination of reservoirs, vectors and pathogens, as they are transport hubs. Dobigny & Morand further predict, likely correctly, that cities may be important places for pathogen evolution.  Finally, they propose actions and recommendations to limit the risk of zoonotic spillover events from urban ecosystems and future directions for research aiming at assessing this risk. 

The reviewers found the manuscript well-organized and presented, timely, and bringing novel contributions to the field of zoonotic emergence. I strongly recommend this article, which should benefit a large audience, particularly in the context of the current Covid-19 pandemics and the ongoing One Health initiatives aiming at preventing future zoonotic disease emergence (4). 

References

(1) Jones KE, Patel NG, Levy MA, Storeygard A, Balk D, Gittleman JL, Daszak P (2008) Global trends in emerging infectious diseases. Nature, 451, 990–993. https://doi.org/10.1038/nature06536

(2) White RJ, Razgour O (2020) Emerging zoonotic diseases originating in mammals: a systematic review of effects of anthropogenic land-use change. Mammal Review, 50, 336–352. https://doi.org/10.1111/mam.12201

(3) Dobigny G, Morand S (2022) Zoonotic emergence at the animal-environment-human interface: the forgotten urban socio-ecosystems. Zenodo, 6444776, ver. 3 peer-reviewed and recommended by Peer Community in Infections. https://doi.org/10.5281/zenodo.6444776

(4) Morand S, Lajaunie C (2021) Biodiversity and COVID-19: A report and a long road ahead to avoid another pandemic. One Earth, 4, 920–923. https://doi.org/10.1016/j.oneear.2021.06.007

Zoonotic emergence at the animal-environment-human interface: the forgotten urban socio-ecosystemsDobigny, G. & Morand, S.<p style="text-align: justify;">Zoonotic emergence requires spillover from animals to humans, hence animal-human interactions. A lot has been emphasized on human intrusion into wild habitats (e.g., deforestation, hunting) and the development of ag...Disease Ecology/Evolution, Ecohealth, Ecology of hosts, infectious agents, or vectors, Evolution of hosts, infectious agents, or vectors, One Health, ZoonosesEtienne Waleckx2022-04-11 11:39:11 View