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Comparison of Ecological Indices of Bacterial Communities in Bovine Milk Varying in Somatic Cell Count
Somatic cell count (SCC) of milk is often used to determine the health status of the mammary gland. However, little is known about the bacterial community structure within milk of varying SCC. Next generation sequencing technology has provided researchers the opportunity to characterize the bacterial diversity and community structure within bovine milk. We hypothesized that the bacterial diversity and community structure would be different among milk with low (<200,000 cells/mL), medium (200,000 – 400,000 cells/mL), and high (> 400,000 cells/mL) SCC. Utilizing ecological indices that describe bacterial diversity, we analyzed 16S rRNA (V1-V3 region) sequencing data from quarter milk samples collected from 15 Holstein cows. Comparisons among quarter milk samples with different SCC were carried out using analysis of variance and mixed model procedures of SAS (v9.3) and significance was declared at p ≤ 0.05. Additionally effects of SCC status were compared using predetermined contrasts of milk with low versus medium and high, as well as medium versus high levels of SCC. Based upon richness estimators (Chao1 and abundance-based coverage estimators [ACE]), milk with high SCC had a bacterial community less rich and diverse than milk with low or medium SCC. Also, according to Shannon’s and Simpson’s diversity indices when SCC is medium and high, there is a decrease in number of bacterial genera present as well as a decrease in the evenness of the bacterial community membership compared to milk with low SCC. While milk categorized as high SCC is different from milk with low and medium SCC, the bacterial diversity and community structure in low SCC milk is not different from milk with medium SCC. Future studies are needed to explore how bacterial community membership among milk samples differs with varying SCC. This work was supported by the Idaho Agricultural Experiment Station, NIH grants P20 RR15587 and P20 RR016454 and the Institute for Bioinformatics and Evolutionary Studies (IBEST) at the University of Idaho.
Keywords: Milk, microbiome, diversity