Using the microbiota to study connectivity at human–animal interfaces

Interfaces between humans, livestock, and wildlife, mediated by the environment, are critical points for the transmission and emergence of infectious pathogens and call for leveraging the One Health approach to understanding disease transmission. Current research on pathogen transmission often focus...

Descripción completa

Detalles Bibliográficos
Autores principales: Muloi, Dishon M., Caron, Alexandre, Berkley, J.A., Hassell, James M., Brito, I.L., King, K., Moodley, Arshnee, Fèvre, Eric M.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/175067
_version_ 1855528888880332800
author Muloi, Dishon M.
Caron, Alexandre
Berkley, J.A.
Hassell, James M.
Brito, I.L.
King, K.
Moodley, Arshnee
Fèvre, Eric M.
author_browse Berkley, J.A.
Brito, I.L.
Caron, Alexandre
Fèvre, Eric M.
Hassell, James M.
King, K.
Moodley, Arshnee
Muloi, Dishon M.
author_facet Muloi, Dishon M.
Caron, Alexandre
Berkley, J.A.
Hassell, James M.
Brito, I.L.
King, K.
Moodley, Arshnee
Fèvre, Eric M.
author_sort Muloi, Dishon M.
collection Repository of Agricultural Research Outputs (CGSpace)
description Interfaces between humans, livestock, and wildlife, mediated by the environment, are critical points for the transmission and emergence of infectious pathogens and call for leveraging the One Health approach to understanding disease transmission. Current research on pathogen transmission often focuses on single-pathogen systems, providing a limited understanding of the broader microbial interactions occurring at these interfaces. In this review, we make a case for the study of host-associated microbiota for understanding connectivity between host populations at human–animal interfaces. First, we emphasize the need to understand changes in microbiota composition dynamics from interspecies contact. Then, we explore the potential for microbiota monitoring at such interfaces as a predictive tool for infectious disease transmission and as an early-warning system to inform public health interventions. We discuss the methodological challenges and gaps in knowledge in analyzing microbiota composition dynamics, the functional meaning of these changes, and how to establish causality between microbiota changes and health outcomes. We posit that integrating microbiota science with social-ecological systems modeling is essential for advancing our ability to manage health risks and harness opportunities arising from interspecies interactions.
format Journal Article
id CGSpace175067
institution CGIAR Consortium
language Inglés
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher Elsevier
publisherStr Elsevier
record_format dspace
spelling CGSpace1750672025-12-08T09:54:28Z Using the microbiota to study connectivity at human–animal interfaces Muloi, Dishon M. Caron, Alexandre Berkley, J.A. Hassell, James M. Brito, I.L. King, K. Moodley, Arshnee Fèvre, Eric M. health microbial flora Interfaces between humans, livestock, and wildlife, mediated by the environment, are critical points for the transmission and emergence of infectious pathogens and call for leveraging the One Health approach to understanding disease transmission. Current research on pathogen transmission often focuses on single-pathogen systems, providing a limited understanding of the broader microbial interactions occurring at these interfaces. In this review, we make a case for the study of host-associated microbiota for understanding connectivity between host populations at human–animal interfaces. First, we emphasize the need to understand changes in microbiota composition dynamics from interspecies contact. Then, we explore the potential for microbiota monitoring at such interfaces as a predictive tool for infectious disease transmission and as an early-warning system to inform public health interventions. We discuss the methodological challenges and gaps in knowledge in analyzing microbiota composition dynamics, the functional meaning of these changes, and how to establish causality between microbiota changes and health outcomes. We posit that integrating microbiota science with social-ecological systems modeling is essential for advancing our ability to manage health risks and harness opportunities arising from interspecies interactions. 2025-10 2025-06-12T04:22:28Z 2025-06-12T04:22:28Z Journal Article https://hdl.handle.net/10568/175067 en Open Access Elsevier Muloi, D.M., Caron, A., Berkley, J.A., Hassell, J.M., Brito, I.L., King, K., Moodley, A. and Fèvre, E.M. 2025. Using the microbiota to study connectivity at human–animal interfaces. Trends in Microbiology 33(10): 1110–1120.
spellingShingle health
microbial flora
Muloi, Dishon M.
Caron, Alexandre
Berkley, J.A.
Hassell, James M.
Brito, I.L.
King, K.
Moodley, Arshnee
Fèvre, Eric M.
Using the microbiota to study connectivity at human–animal interfaces
title Using the microbiota to study connectivity at human–animal interfaces
title_full Using the microbiota to study connectivity at human–animal interfaces
title_fullStr Using the microbiota to study connectivity at human–animal interfaces
title_full_unstemmed Using the microbiota to study connectivity at human–animal interfaces
title_short Using the microbiota to study connectivity at human–animal interfaces
title_sort using the microbiota to study connectivity at human animal interfaces
topic health
microbial flora
url https://hdl.handle.net/10568/175067
work_keys_str_mv AT muloidishonm usingthemicrobiotatostudyconnectivityathumananimalinterfaces
AT caronalexandre usingthemicrobiotatostudyconnectivityathumananimalinterfaces
AT berkleyja usingthemicrobiotatostudyconnectivityathumananimalinterfaces
AT hasselljamesm usingthemicrobiotatostudyconnectivityathumananimalinterfaces
AT britoil usingthemicrobiotatostudyconnectivityathumananimalinterfaces
AT kingk usingthemicrobiotatostudyconnectivityathumananimalinterfaces
AT moodleyarshnee usingthemicrobiotatostudyconnectivityathumananimalinterfaces
AT fevreericm usingthemicrobiotatostudyconnectivityathumananimalinterfaces