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Updated: Oct 26, 2026
Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing
Published on: March 19, 2018
In sickness and in health: profiling the bovine fecal eukaryome using optimized 18S metabarcoding with a
Iqra Zafar1, Riku Sakurai1, Yasuhiro Fukuda1
1Laboratory of Sustainable Animal Environment, Graduate School of Agricultural Science, Tohoku University, Osaki, Miyagi, Japan.
Introduction:
Calf diarrhea, caused by the apicomplexan pathogen Cryptosporidium parvum (C. parvum), poses significant economic and production challenges to the livestock industry. While 16S rRNA sequencing has advanced understanding of the bovine bacterial gut microbiota, the eukaryotic community remains underexplored due to methodological constraints, notably host DNA contamination. This study aimed to optimize an 18S rRNA metabarcoding workflow using mammal-blocking primers for bovine fecal eukaryome profiling and to characterize eukaryotic community differences between healthy and naturally C. parvum-infected diarrheic calves.
Methods:
We compared four 18S rRNA primer sets (V8f/1510R, TAReuk454FWD1/TAReukREV3, 528F/706R, and 616F/1132R) with two mammal-blocking primers using fecal samples from healthy (n = 28) and C. parvum-positive diarrheic calves (n = 24) across Japan. The optimal primer-blocker combination was selected based on host-read depletion and taxonomic recovery. Using this optimized workflow, we characterized and compared the fecal eukaryotic microbiota between healthy and C. parvum-infected calves via 18S rRNA amplicon sequencing.
Results:
The V8 primer-blocker demonstrated the most consistent host suppression (30-50% reduction), unmasking diverse eukaryotic taxa while improving evenness and preserving community richness. Cryptosporidium dominated the diarrheic group and was confirmed as C. parvum via nested GP60 PCR. Infected calves were associated with lower eukaryotic richness, with reduced Chao1 richness (p < 0.00001) and Shannon diversity (p < 0.041), and distinct community composition (Bray-Curtis: R 2 = 0.145, p = 0.001; Jaccard: R 2 = 0.060, p = 0.001). After accounting for geographic variation, clinical status remained significantly associated with community composition (PERMANOVA, R 2 = 0.129, p = 0.0001), whereas geography was not significant (p = 0.180). LEfSe identified Cryptosporidium (LDA score = 5.6) as the strongest discriminator in the Crypto group, while Kazachstania (4.35), Giardia (4.0), and Aspergillus (0.8) were enriched in healthy calves, reflecting complex interkingdom interactions.
Conclusion:
The optimized V8-mammal-blocking strategy provides an effective framework for bovine fecal eukaryome profiling by reducing host interference and improving recovery of clinically relevant microeukaryotes. C. parvum infection is associated with significant restructuring of the fecal eukaryotic community. This workflow strengthens livestock disease surveillance, facilitates future epidemiological studies, and advances our understanding of complex host-parasite and microeukaryome interactions.
