# Low Zoonotic Pathogen Burden in Free-Roaming Cats Revealed by 18S rRNA Metabarcoding: A Baseline Study from an Insular Natura 2000 Site in Spain

## TL;DR

Free-roaming cats on a Spanish island have low zoonotic pathogen levels, with high common parasite presence detected using DNA metabarcoding.

## Contribution

This study provides baseline data on eukaryotic pathogens in free-roaming cats using 18S rRNA metabarcoding, including dry faecal samples.

## Key findings

- Dipylidium caninum was detected in 74.3% of samples.
- Zoonotic protozoa like Toxoplasma gondii were found in less than 10% of samples.
- Fresh faecal samples showed higher richness of potentially pathogenic taxa compared to dry samples.

## Abstract

Free-roaming cats are often discussed in terms of public and environmental health, but robust baseline data are scarce in small, protected island settings. We used DNA metabarcoding (18S rRNA) to screen 152 faecal samples from community cats in La Graciosa Island (Natura 2000, Canary Islands), including fresh faeces collected from inside the traps/carriers of captured cats and dry environmental faecal deposits. We detected a high frequency of common feline parasites (Dipylidium caninum, about three-quarters; 74.3%) but a comparatively low detection frequency of major zoonotic protozoa (Toxoplasma gondii, <10%; 7.9%). Overall, these results support targeted parasite control within Trap–Neuter–Return (TNR) programmes and show that metabarcoding can provide scalable One Health surveillance, even from dry faeces.

Free-roaming cats may contribute to zoonotic risk via parasites and other eukaryotic taxa, yet surveillance in protected island settings is limited and conventional coprology can miss low-intensity or degraded signals. We conducted a cross-sectional 18S rRNA metabarcoding survey to establish a baseline profile of potentially pathogenic eukaryotes in community cats from La Graciosa (Natura 2000, Canary Islands, Spain) prior to large-scale antiparasitic interventions. We analysed 152 faecal samples, including fresh samples collected during a high-throughput TNR campaign (n = 37) and dry environmental deposits (n = 115). Host amplification was reduced using a feline 18S blocking primer; libraries were sequenced with Oxford Nanopore technology; and taxonomy was assigned using SILVA-based classifiers with downstream filtering for veterinary/zoonotic relevance. After quality control, 72 eukaryotic taxa were retained and DNA from at least 24 potentially pathogenic taxa was detected. Dipylidium caninum was most frequent (74.3%; 113/152), and opportunistic fungi/yeasts were common (e.g., Pichia kudriavzevii 42.4%, Diutina catenulata 31.5%). Zoonotic protozoa showed low-to-moderate detection frequency (Acanthamoeba castellanii 13.3%, Toxoplasma gondii 7.9%, Balamuthia mandrillaris 4.6%). Overall richness did not differ between fresh and dry samples (p > 0.05), but fresh samples contained higher richness of potentially pathogenic taxa (p < 0.01).