DOI: 10.5281/zenodo.15671363
title: V2: Supporting data and code for: Surveillance of zoonotic pathogens in small mammals across a gradient of forest anthropization in Eastern France

description: Data

For additional information regarding the MiSeq sequences, refer to DOI : https://zenodo.org/records/12518286  





Post-filtering Processing



A. Bacteria and Apicomplexa from 16s Metabarcoding 

sTable of abundance of OTUs for small mammals samples whose spleen have been sequenced

This biom file contains the abundance data, representing the number of reads obtained after data filtering, for each OTUs from the MiSeq runs and for each small mammal spleen sample (N=1270). It also includes taxonomy information for each OTUs (based on the Silva database). The results from the two PCR replicates per sample were summed and filtered using both negative and positive controls.

File name: 16S_spleen_taxa_run1to20_data.csv

B. Viruses from Serological Analysis

Presence/absence table for the selected pathogens across individual hosts

The CSV file includes presence/absence (1/0) data for the selected pathogens across individual hosts (N=1542), identified by their unique codes (NCHA-ID number). Orthopoxvirus (Poxv) is detected through IFA serological analyses. Pathogens are labeled as follows: Pox = Orthopoxvirus, orthohantaviruses (Puumala virus (PUUV) and Dobrava virus (DOBV), sum of seroprevalence = hantavirus ), and mammarenaviruses (LCMV), COVID (without info).

File name: virus_ifa_data.csv

C. Leptospirosis from Lip32 Gene Amplicon qPCR Analysis

Presence/absence table for the selected pathogens across individual hosts

The CSV file includes presence/absence data for the selected pathogens across individual hosts (N=1549), identified by their unique codes (NCHA-ID number). Pathogenic leptospirosis is detected through the LIP32 gene. Pathogens are labeled as follows: Lept = Leptospirosis.

File name: leptospira_lip32_data.csv

D. Supplementary Tables: Pathogen Characterization Using qPCR and Microfluidic Methods

The XLSX file contains multiple tables associated with different pathogen detection methods:

Table 1: Fluidigm-ANSES Tick-borne pathogens detected for 28 splenic DNA extraction and 10 replicates of DNA using the Fluidigm technology described in Michelet et al. (2014) 2. table.

Table 2: Francisella ANSES: Francisella tularensis confirmation for 69 splenic DNA extraction  using three PCRs as described in Kevin et al. (2021).

Table 3: Bartonella CBGP : Bartonella characterisation for 11 splenic DNA extraction and their replicate using gltA and rpoB metabarcoding. Taxonomic information as well as number of reads obtained for each sample are provided.

Table 4:  Leptospira-VetAgroSup: Leptospira characterisation for 18 kidney DNA extraction using multilocus analyses as described in Garcia-Lopez et al. (2023).

File_name : supplementary_pathogen_characterisation_data.xlsx

2. Final preprocess

The final preprocessed CSV file contains all the essential information for performing statistical analyses on sampling sites, host information and pathogen presence, with the following variables:





Code_Id: NCHA-IDnumber (N=1267)




Pathogens Presence/absence of pathogens (0/1) Code Name of pathogens (N=16), see table 1 for pathogens codes




Species: Species of small mammals (N=9)




Code_Species: Taxonomic abbreviation (first letter of the genus and the first three letters of the species)  Asyl = Apodemus sylvaticus, Afla = Apodemus flavicollis, Cgla = Clethrionomys (Myodes) glareolus,Crus = Crocidura russula, Cleu = Crocidura leucodon, Mmus = Mus musculus, Rnor = Rattus norvegicus, Ggli = Glis glis, Msub = Microtus subterraneus, Marv = Microtus arvalis, Magr = Microtus agrestis,, Nfod = Neomys fodiens, Svul = Sciurus vulgaris, Eeur = Erinaceus europaeus,, Sara = Sorex araneus, Scor = Sorex coronatus.




Code_Locality: Code for the studied localities ": Sampling locations, with codes such as FRFGLA (La Glacière) , FRFGRI (Griffe du Diable), FRFMIG (Mignovillard), FRFCOR (Cormaranche-en-Bugey), FRPDLL (Domaine Lacroix Laval), FRPLTO (Lyon Tête d’Or).(N=6)




Periods: Seasons (s = spring, f = fall) followed by the year (N=5)




Sex: Sex (F for female, M for male)




AgeClass: Age class representing the functional group (0 = immature/juvenile mature, 1 = adult mature)




Habitats: Habitats represent the type of sites sampled along an anthropization gradient, defined here as differences in forest and park management practices. Urban park forests are coded as follows: FRPLTO– Lyon, Parc de la Tête d'Or (Rhône); FRPDLL– Marcy l'Étoile, Domaine Lacroix-Laval (Rhône); rural managed forests are FRFCOR – Cormaranche-en-Bugey (Ain); FRFMIG – Mignovillard (Jura) and protected forests : FRFGLA – Esserval-Tartre, La Glacière (Jura); FRFGRI – Arvière, La Griffe au Diable (Ain);




SpecType: Species types reprents ecological types of small mammals along the anthropization gradient: avoiders, dwellers or adapters



File name: final_preprocess_sampling-pathogens_data.csv

3. Dataset of pathogen prevalence and individual counts in small mammal communities across species, periods, and localities

This dataset provides harmonized CSV files summarizing pathogen prevalence and the number of individuals sampled across ecological categories. It allows a direct overview of infection patterns and host community structure in small mammals from six sampling sites in Eastern France. Pathogen prevalence is aggregated at multiple scales: by species, locality, and sampling period (season × year). Individual count files provide the number of captured animals per species, site, and period, with filtering to ensure statistical robustness (categories with N > 5).

Small mammal species are identified using standardized taxonomic abbreviations based on the first letter of the genus and first three letters of the species: Asyl (Apodemus sylvaticus), Afla (A. flavicollis), Cgla (Clethrionomys glareolus ≡ Myodes glareolus), Crus (Crocidura russula), Cleu (C. leucodon), Mmus (Mus musculus), Rnor (Rattus norvegicus), Ggli (Glis glis), Msub (Microtus subterraneus), Marv (M. arvalis), Magr (M. agrestis), Nfod (Neomys fodiens), Svul (Sciurus vulgaris), Eeur (Erinaceus europaeus), Sara (Sorex araneus), and Scor (Sorex coronatus).

Sampling sites are coded as follows: FRFGLA (Esserval-Tartre – La Glacière), FRFGRI (Arvière – Griffe du Diable), FRFMIG (Mignovillard), FRFCOR (Cormaranche-en-Bugey), FRPDLL (Marcy-l’Étoile – Domaine Lacroix Laval), and FRPLTO (Lyon – Parc de la Tête d’Or), for a total of six localities.

Temporal sampling refers to season and year, with “s” for spring and “f” for fall (e.g., s2020, f2021). Five sampling periods are included: s2020, f2020, s2021, f2021, and s2022.

Pathogens are identified using the following codes: Sarco1 / Sarco2 (Sarcocystis spp.), Toxo (Toxoplasma gondii), Eime (Eimeria spp.), Bart (Bartonella spp.), Neoe (Neoehrlichia mikurensis), Anap (Anaplasma spp.), Fran (Francisella tularensis), Rick (Rickettsia spp.), Chla (Chlamydia spp.), Orie (Orientia spp.), Neis (Neisseria spp.), Lept (Leptospira spp.), Poxv (Orthopoxvirus antibodies), and Hanv (Orthohantavirus antibodies).

Included CSV files:• TabPrev_Species.csv – prevalence per pathogen by species• TabPrev_Locs.csv – prevalence per pathogen by sampling site• TabPrev_Periods.csv – prevalence per pathogen by sampling period• TabPrev_PeriodsLocs.csv – prevalence by site × period• TabPrev_PeriodsLocsSpecies.csv – prevalence by species × site × period• CountId_PeriodsLocsSpecies.csv – number of individuals per species × site × period • CountId_SpeciesbyPeriodsLocs.csv – number of individuals per species across sites and periods

Scripts 

RMarkdown scripts (.Rmd) for data preprocessing and pathogen surveillance analysis:





pathogen_data_preprocessing.Rmd : preprocessing and cleaning of raw pathogen detection data




pathogen_diversity_analysis.Rmd : analysis of pathogen diversity patterns across sites or habitats and hosts species or types of species




pathogen_prevalence_analysis.Rmd : estimation and comparison of pathogen prevalence