Effect of Chitosan Microparticles on the Uterine Microbiome of Dairy Cows with Metritis

The objective of this study was to evaluate the effect of chitosan microparticles on the uterine microbiome of cows with metritis. Dairy cows with metritis (n = 89) were assigned to 1 of 3 treatments: chitosan microparticles (n = 21), in which the cows received an intrauterine infusion of chitosan microparticles at metritis diagnosis (day 0), day 2, and day 4; ceftiofur (n = 25), in which the cows received a subcutaneous injection of ceftiofur on day 0 and day 3; and no intrauterine or subcutaneous treatment (n = 23). Nonmetritic cows (n=20) were healthy cows matched with cows with metritis by the number of days postpartum at metritis diagnosis. Uterine swab samples collected on days 0, 3, 6, 9, and 12 were used for 16S rRNA gene sequencing and 16S RNA gene copy number quantification by quantitative PCR. Principal-coordinate analysis showed that the microbiome of the ceftiofur-treated and metritic untreated groups progressed toward that of the nonmetritic group by day 3, whereas that of the chitosan microparticletreated group remained unchanged. The differences on day 3 were mainly due to a greater relative abundance of Fusobacteria, particularly Fusobacterium, in the chitosan microparticle-treated group than in the ceftiofur-treated and metritic untreated groups. Furthermore, the microbiome of the ceftiofur-treated group became similar to that of the nonmetritic group by day 9, whereas the microbiome of the chitosan microparticle-treated and metritic untreated groups became similar to that of the nonmetritic group only by day 12. The total bacterial 16S rRNA gene counts in the chitosan microparticle-treated group were greater than those in the metritic untreated controls on days 6 and 9, whereas the ceftiofur treatment group was the only group in which the total bacterial 16S rRNA gene count became similar to that in the nonmetritic group by day 12. In summary, chitosan microparticles slowed the progression of the uterine microbiome toward a healthy state, whereas ceftiofur hastened the progression toward a healthy state.Fil: Galvão, Klibs N.. University of Florida; Estados UnidosFil: de Oliveira, Eduardo B.. University of Florida; Estados UnidosFil: Cunha, Federico. University of Florida; Estados UnidosFil: Daetz, Rodolfo. University of Florida; Estados UnidosFil: Jones, Kristi. University of Florida; Estados UnidosFil: Ma, Zhengxin. University of Florida; Estados UnidosFil: Jeong, Kwangcheol C.. University of Florida; Estados UnidosFil: Bicalho, Rodrigo C.. Cornell University; Estados UnidosFil: Higgins, Catherine H.. Cornell University; Estados UnidosFil: Rodrigues, Marjory X.. Cornell University; Estados UnidosFil: Gonzalez Moreno, Candelaria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; ArgentinaFil: Jeon, Soojin. Long Island University; Estados Unido

Milk production and energy indicators in semi-housed dairy cows treated with low doses of recombinant bovine somato tropinduring transition period

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Uterine Microbiota and Immune Parameters Associated with Fever in Dairy Cows with Metritis

<div><p>Objective</p><p>This study aimed to evaluate bacterial and host factors causing a fever in cows with metritis. For that, we investigated uterine microbiota using a metagenomic sequencing of the 16S rRNA gene (Study 1), and immune response parameters (Study 2) in metritic cows with and without a fever.</p><p>Principal Findings (Study1)</p><p>Bacterial communities were similar between the MNoFever and MFever groups based on distance metrics of relative abundance of bacteria. Metritic cows showed a greater prevalence of Bacteroidetes, and <i>Bacteroides</i> and <i>Porphyromonas</i> were the largest contributors to that difference. A comparison of relative abundance at the species level pointed to <i>Bacteroides pyogenes</i> as a fever-related species which was significantly abundant in the MFever than the MNoFever and Healthy groups; however, absolute abundance of <i>Bacteroides pyogenes</i> determined by droplet digital PCR (ddPCR) was similar between MFever and MNoFever groups, but higher than the Healthy group. The same trend was observed in the total number of bacteria.</p><p>Principal Findings (Study2)</p><p>The activity of polymorphonuclear leukocyte (PMN) and the production of TNFα, PGE₂ metabolite, and PGE₂ were evaluated in serum, before disease onset, at 0 and 3 DPP. Cows in the MNoFever had decreased proportion of PMN undergoing phagocytosis and oxidative burst compared with the MFever. The low PMN activity in the MNoFever was coupled with the low production of TNFα, but similar PGE₂ metabolite and circulating PGE₂.</p><p>Conclusion/Significance</p><p>Our study is the first to show a similar microbiome between metritic cows with and without a fever, which indicates that the host response may be more important for fever development than the microbiome. <i>Bacteroides pyogenes</i> was identified as an important pathogen for the development of metritis but not fever. The decreased inflammatory response may explain the lack of a febrile response in the MNoFever group.</p></div

Diversity of uterine microbiota from the Healthy (n = 11), MNoFever (n = 12), and MFever (n = 11) groups.

<p>(A) Number of reads. There is no significant difference among groups. (B) Chao1 richness index. Chao1 richness estimates the total number of species in a sample based on the number of singleton and doubleton taxa. (C) Shannon diversity index. Shannon index takes into account both the species richness and evenness. Data represent the mean ± SEM. Data labeled “a” are statistically different (<i>P</i> ≤ 0.05) from data labeled “b”.</p

Associations of <i>Bacteroides pyogenes</i> with a fever.

<p>(A) Relative abundance of <i>B</i>. <i>pyogenes</i> based on metagenomic sequencing. Bars represent the mean ± SEM. (B) Absolute abundance of total bacteria and <i>B</i>. <i>pyogenes</i> based on droplet digital PCR. The log₁₀ number of total bacteria (black circles) and <i>B</i>. <i>pyogenes</i> (blue squares) were quantified in uterine swab samples using the 16S rRNA gene and <i>recA</i> gene, respectively. Each symbol represents an individual cow and error bars indicate the means ± SEM. Data labeled “a” are statistically different (<i>P</i> ≤ 0.05) from data labeled “b”.</p

Immune function.

<p>(A) In vitro proportion of PMN with phagocytic activity (Healthy = 58, MNoFever = 19, MFever = 33). (B) In vitro proportion of PMN mediated oxidative burst (Healthy = 58, MNoFever = 19, MFever = 33). (C) In vivo serum TNFα (14 cows per group). (D) In vivo serum PGE₂ metabolite (14 cows per group). Data represent the mean ± SEM. Data labeled “a” are statistically different (<i>P</i> ≤ 0.05) from data labeled “b”. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0165740#pone.0165740.s007" target="_blank">S1 Table</a> for sample information.</p

Heat map analysis with the dendrogram based on Euclidean distance.

<p>Columns represent individual cows and rows represent 20 bacterial species. The relative abundance of bacteria was presented by color in each cell. Under the dendrogram the first bar shows whether cows had fever and the second bar indicates whether cows had metritis.</p