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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #351769

Research Project: Antimicrobial Resistance and Ecology of Zoonotic Foodborne Pathogens in Dairy Cattle

Location: Environmental Microbial & Food Safety Laboratory

Title: Age-dependent differences in gut microbial communities and resistomes of veal calves

item SALAHEEN, SERAJUS - US Department Of Agriculture (USDA)
item KIM, SEON-WOO - US Department Of Agriculture (USDA)
item HOVINGH, ERNEST - Pennsylvania State University
item Haley, Bradd
item Van Kessel, Jo Ann

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/4/2018
Publication Date: 4/25/2018
Citation: Salaheen, S., Kim, S., Hovingh, E., Haley, B.J., Van Kessel, J.S. 2018. Age-dependent differences in gut microbial communities and resistomes of veal calves. BARC Poster Day. p. 1.

Interpretive Summary:

Technical Abstract: Antibiotic resistance (AR) remains a significant public health concern on a global scale. The use of antibiotics in agriculture has been implicated as a causal factor in the rise of antibiotic resistant human infections, but definitive evidence demonstrating this is lacking. Thus, there is a need to further investigate trends in AR across agricultural practices. Previous studies have demonstrated age-associated differences in the carriage of resistant bacteria: antibiotic resistance was reported to be more prevalent in younger farm animals indicating the presence of a neonate-adapted microbial consortium that may change over time in older animals. In this study, we used shotgun metagenomic sequencing followed by network analysis and machine-learning approaches to investigate age-associated differences in the microbial communities and resistomes of feces collected from veal calves. Fecal samples (n=24) were collected from milk-fed calves at four operations on two sampling dates roughly three months apart. Shotgun sequencing was conducted on extracted DNA. Supervised machine-learning was used to differentiate fecal community composition between younger and older calves. High levels of alpha (ACE, Shannon, and Fisher) and beta diversity in fecal samples demonstrated that microbial profiles of veal calves were quite diverse. Non-metric multidimensional scaling and PERMANOVA analysis on Bray-Curtis distance among the taxa and the resistomes revealed clear separation of the microbial communities and the resistomes when samples were grouped by age (p < 0.05). Major discriminatory taxa and AR genes that separated the microbiomes in younger and older veal calves were identified. Discriminatory microbial taxa included Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, and bacteriophages (order Caudovirales), and resistomes included genes conferring resistance to ß-lactams, tetracyclines, aminoglycosides, macrolides-lincosamides-streptogramins, multidrugs, and glycopeptide antibiotics. A correlation matrix was generated by calculating all possible pairwise Spearman’s rank correlations between the taxa and AR genes. The matrix was visualized in a network interface that showed possible co-occurrence between certain Proteobacteria (e.g., Escherichia, Salmonella, and others) and bacteriophage Caudovirales and AR genes that confer resistance to ß-lactams, multidrugs, and polymyxin antibiotics. Findings from this study suggested an age-dependent shift in the fecal microbial community and resistome structures in veal calves and may lead to the discovery of a novel control points in the gut ecology that could be leveraged to interrupt detrimental AR occurrence in dairy animals.