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Microbiome and resistome characterization of colostrum from selectively treated dry cows.

A. K. Vasquez

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06-23-2020

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Abstract:

T24
Microbiome and resistome characterization of colostrum from selectively treated dry cows.
A. K. Vasquez*1, D. V. Nydam1, C. Foditsch1, L. Warnick1, P. Morley2, E. Doster3. 1Cornell University Ithaca, NY, 2Texas A&M College Station, TX, 3Colorado State University Fort Collins, CO.

Few studies evaluate the impact of selective dry cow therapy on preservation of milk microbiome or the presence of antimicrobial resistance (AMR) genes at freshening. Objectives were to characterize the microbiome and resistome in colostrum of low somatic cell count (SCC) cows that were treated or not treated with antibiotics at dry-off. Cows eligible for dry-off on 1 NY dairy, with histories of SCC ≤ 200k were enrolled. Cows were randomly assigned to receive intramammary antibiotics and teat sealant (ABXTS) or sealant only (TS) at dry-off. Composite colostrum samples (within 4h of freshening) and quarter milk samples (1—7 DIM) were subjected to culture. DNA extraction was performed on culture negative samples (ABXTS = 43; TS = 33). After DNA from cows of the same treatment group and parity was pooled (26 pools; ABXTS = 12; TS = 14), amplification using V4 universal primers and shotgun sequencing were performed. The resistome was captured using a custom RNA bait library. Reads were aligned to resistance and taxonomic databases. Analysis was performed in R: diversity measures were compared; differences in composition were tested with analysis of similarities (ANOSIM). The most abundant phyla were Firmicutes (70%), Proteobacteria (24%), and Bacteroidetes (3%). Shannon and richness diversity means were not different between TS and ABXTS (P = 0.6, 0.6). Overall microbiome composition was not different at the phylum (ANOSIM R = 0.004, P = 0.4), class (ANOSIM R = 0.04, P = 0.2), or order (ANOSIM R = 0.005, P = 0.4) levels. AMR gene accessions identified 9 classes of AMR in 14 samples (TS = 9, ABXTS = 5). The majority of reads aligned to gene accessions that confer resistance to aminoglycoside (TS = ABXTS each 35% abundance), tetracycline (TS = 22%, ABXTS = 54%), and β-lactam classes (TS = 15%, ABXTS = 12%). Shannon and richness diversity means for AMR class were not different between TS and ABXTS (P = 0.03, 0.06). Resistome composition was not different between groups at the class (ANOSIM R = −0.20, P = 1) or mechanism levels (ANOSIM R = 0.01, P = 0.5). While no differences were found for the microbiome or resistome in this study, a larger sample size, deeper sequencing, and additional methodology may be needed.

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