Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution Models
The continuous increase of Coccidioidomycosis cases requires reliable detection methods of the causal agent, <i>Coccidioides</i> spp., in its natural environment. This has proven challenging because of our limited knowledge on the distribution of this soil-dwelling fungus. Knowing the pa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Journal of Fungi |
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| Online Access: | https://www.mdpi.com/2309-608X/6/4/320 |
| _version_ | 1797546464792018944 |
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| author | Pamela Ocampo-Chavira Ricardo Eaton-Gonzalez Meritxell Riquelme |
| author_facet | Pamela Ocampo-Chavira Ricardo Eaton-Gonzalez Meritxell Riquelme |
| author_sort | Pamela Ocampo-Chavira |
| collection | DOAJ |
| description | The continuous increase of Coccidioidomycosis cases requires reliable detection methods of the causal agent, <i>Coccidioides</i> spp., in its natural environment. This has proven challenging because of our limited knowledge on the distribution of this soil-dwelling fungus. Knowing the pathogen’s geographic distribution and its relationship with the environment is crucial to identify potential areas of risk and to prevent disease outbreaks. The maximum entropy (Maxent) algorithm, Geographic Information System (GIS) and bioclimatic variables were combined to obtain current and future potential distribution models (DMs) of <i>Coccidioides</i> and its putative rodent reservoirs for Arizona, California and Baja California. We revealed that <i>Coccidioides</i> DMs constructed with presence records from one state are not well suited to predict distribution in another state, supporting the existence of distinct phylogeographic populations of <i>Coccidioides</i>. A great correlation between <i>Coccidioides</i> DMs and United States counties with high Coccidioidomycosis incidence was found. Remarkably, under future scenarios of climate change and high concentration of greenhouse gases, the probability of habitat suitability for <i>Coccidioides</i> increased. Overlap analysis between the DMs of rodents and <i>Coccidioides</i>, identified <i>Neotoma lepida</i> as one of the predominant co-occurring species in all three states. Considering rodents DMs would allow to implement better surveillance programs to monitor disease spread. |
| first_indexed | 2024-03-10T14:29:54Z |
| format | Article |
| id | doaj.art-77b22680256e4984807f1f9e67f53ecc |
| institution | Directory Open Access Journal |
| issn | 2309-608X |
| language | English |
| last_indexed | 2024-03-10T14:29:54Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Fungi |
| spelling | doaj.art-77b22680256e4984807f1f9e67f53ecc2023-11-20T22:40:23ZengMDPI AGJournal of Fungi2309-608X2020-11-016432010.3390/jof6040320Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution ModelsPamela Ocampo-Chavira0Ricardo Eaton-Gonzalez1Meritxell Riquelme2Department of Microbiology, Centro de Investigación Científica y Educación Superior de Ensenada (CICESE), Ctra. Ensenada-Tijuana No. 3918, Ensenada, Baja California 22860, MexicoAcademic Unit of Ensenada, Universidad Tecnológica de Tijuana, Ctra. a la Bufadora KM. 1, Maneadero Parte Alta, Ensenada, Baja California 22790, MexicoDepartment of Microbiology, Centro de Investigación Científica y Educación Superior de Ensenada (CICESE), Ctra. Ensenada-Tijuana No. 3918, Ensenada, Baja California 22860, MexicoThe continuous increase of Coccidioidomycosis cases requires reliable detection methods of the causal agent, <i>Coccidioides</i> spp., in its natural environment. This has proven challenging because of our limited knowledge on the distribution of this soil-dwelling fungus. Knowing the pathogen’s geographic distribution and its relationship with the environment is crucial to identify potential areas of risk and to prevent disease outbreaks. The maximum entropy (Maxent) algorithm, Geographic Information System (GIS) and bioclimatic variables were combined to obtain current and future potential distribution models (DMs) of <i>Coccidioides</i> and its putative rodent reservoirs for Arizona, California and Baja California. We revealed that <i>Coccidioides</i> DMs constructed with presence records from one state are not well suited to predict distribution in another state, supporting the existence of distinct phylogeographic populations of <i>Coccidioides</i>. A great correlation between <i>Coccidioides</i> DMs and United States counties with high Coccidioidomycosis incidence was found. Remarkably, under future scenarios of climate change and high concentration of greenhouse gases, the probability of habitat suitability for <i>Coccidioides</i> increased. Overlap analysis between the DMs of rodents and <i>Coccidioides</i>, identified <i>Neotoma lepida</i> as one of the predominant co-occurring species in all three states. Considering rodents DMs would allow to implement better surveillance programs to monitor disease spread.https://www.mdpi.com/2309-608X/6/4/320<i>Coccidioides</i> spp.distribution modelingMaxentGISbiological variables |
| spellingShingle | Pamela Ocampo-Chavira Ricardo Eaton-Gonzalez Meritxell Riquelme Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution Models Journal of Fungi <i>Coccidioides</i> spp. distribution modeling Maxent GIS biological variables |
| title | Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution Models |
| title_full | Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution Models |
| title_fullStr | Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution Models |
| title_full_unstemmed | Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution Models |
| title_short | Of Mice and Fungi: <i>Coccidioides</i> spp. Distribution Models |
| title_sort | of mice and fungi i coccidioides i spp distribution models |
| topic | <i>Coccidioides</i> spp. distribution modeling Maxent GIS biological variables |
| url | https://www.mdpi.com/2309-608X/6/4/320 |
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