Grad Student Competition
Identifying protective and disease risk-associated fecal microbiomes in neonatal calves
| Date/Time: |
8/28/2026
08:30
|
| Author: |
Fabiola Oyervides |
| Clinic: |
Texas A&M University |
| City, State, ZIP: |
Canyon, TX 79015 |
F.A. Oyervides, BS, MS
1
;
B.T. Johnson, DVM, MS, PhD
2
;
E. Doster, DVM, PhD
1
;
R.J. Valeris-Chacin, DVM, PhD
1
;
P.S. Morley, DVM, PhD, DACVIM
1
;
M.A. Scott, DVM, PhD
1
;
1Veterinary Education, Research, and Outreach Program, Texas A&M University, Canyon, TX, 79015
2Texas Tech University School of Veterinary Medicine, Amarillo, TX, 79106
Introduction:
Preweaned calf diarrhea is a leading cause of morbidity and mortality in calves less than two months of age, resulting in substantial economic losses. Because the gut microbiome may influence susceptibility or resistance to enteric disease during this vulnerable stage of development, characterizing fecal microbial communities could improve understanding of disease dynamics and inform prevention strategies. This study explores the fecal microbial communities associated with gastrointestinal disease neonatal calves via 16S rRNA amplicon sequencing.
Materials and methods:
Ninety-eight pre-weaned crossbred beef-on-dairy calves were enrolled in a cross-sectional study identifying clinically diseased and matched with an apparently healthy cohort at approximately 10 days in hutch. Clinically diseased calves were defined as fecal scores ≤ 1 or fecal scores of 2 and refusing bottle milk replacer or showing signs of apparent disease (sunken abdomen, sunken eye-eyeball recession, lateral recumbency, apparent dehydration). Calves were sourced from five different origins and individually housed at a commercial calf-raising facility. Fecal samples were collected into sterile centrifuge tubes using standardized, non-invasive methods (i.e., free catch, floor swab, ground collection) and stored at -80°C until processing. Metadata were recorded at the time of sampling, including calf ID, sex, origin, age in days, fecal score, rectal temperature, time of collection, and clinical health status. DNA was extracted via DNeasy PowerSoil Pro kits and subjected to 16S rRNA gene amplicon sequencing targeting the V3-V4 hypervariable region via an Illumina MiSeq analyzer. Sequence data were processed through DADA2 for quality filtering and ASV inference, followed by taxonomic classification using the SILVA database. Statistical analyses included alpha (Shannon, ACE, Chao1 , Fisher, InvSimpson; Wilcoxon-Rank and Kruskal-Wallis tests) and beta (Jaccard, Bray-Curtis, Aitchison; PERMANOVA) diversity comparisons, and differential abundance testing to identify taxa or community patterns that predict disease status (FDR<0.05).
Results:
Alpha diversity analyses indicated no significant differences in microbial richness nor diversity between healthy and diseased calves. Richness indices (ACE, Chao1, Fisher) and diversity indices (Shannon, Inverse Simpson) exhibited overlapping distributions across health status groups. Similarly, richness metrics did not differ substantially by fecal score, evenness-weighted indices (Shannon, Inverse Simpson) suggested a minor upward trend with increasing fecal score. Collection method and geographic origin appeared to exert greater influence on alpha diversity than health status. Calves from Michigan and New Mexico exhibited lower diversity compared to calves from Texas, Georgia, and Idaho. Beta diversity analyses across Jaccard, Bray–Curtis, and Aitchison distance metrics revealed no clear separation of microbial communities by sex, health status, or fecal score. Calves with diarrhea scores (1-2) exhibited slightly higher variance compared to healthier calves (scores 4–5).
Significance:
Alpha diversity analysis showed no significant differences based on sex, health status, collection method, or origin. Beta diversity analyses showed considerable overlap across sex, health status, collection method, and origin, with no clear clustering. Here, none of the variables independently influenced alpha or beta diversity, although differences may still exist within groups. Limitations of the study include the cross-sectional design of calf raising and a limited sample size, which may have affected the ability to detect statistically significant effects. We identified that the microbiome from disease calves were more variable than that from healthy animals, which may indicate a need in better categorizing gastrointestinal disease.
