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1.
Anim Microbiome ; 3(1): 15, 2021 Jan 28.
Article in English | MEDLINE | ID: mdl-33509303

ABSTRACT

BACKGROUND: Metritis is an inflammatory uterine disease found in ~ 20% of dairy cows after parturition and associated with uterine microbiota with high abundance of Fusobacterium, Bacteroides, and Porphyromonas. Ceftiofur is a common treatment, but the effect on uterine microbiota is poorly understood. Herein, we investigated the short-term impact of ceftiofur on uterine microbiota structure and function in cows with metritis. Eight cows received ceftiofur (CEF) and 10 remained untreated (CON). Uterine swabs were collected for PCR and metagenomic analysis at diagnosis before treatment (5 ± 1 DPP) and 2 days after diagnosis/treatment (7 ± 1 DPP) from the same individuals. Seven CEF and 9 CON passed quality control and were used for 16S rRNA gene sequencing. RESULTS: Ceftiofur treatment resulted in uterine microbiota alteration, which was attributed to a decrease in relative abundance of Fusobacterium and in gene contents involved in lipopolysaccharide biosynthesis, whereas uterine microbiota diversity and genes involved in pantothenate and coenzyme A biosynthesis increased. Ceftiofur treatment also reduced rectal temperature and tended to reduce total bacteria in the uterus. However, other uterine pathogens such as Bacteroides and Porphyromonas remained unchanged in CEF. The blaCTX-M gene was detected in 37.5% of metritic cows tested but was not affected by CEF. We found that ß-hydroxybutyric acid, pyruvic acid, and L-glutamine were preferentially utilized by Fusobacterium necrophorum according to metabolic activity with 95 carbon sources. CONCLUSIONS: Ceftiofur treatment leads to alterations in the uterine microbiota that were mainly characterized by reductions in Fusobacterium and genes involved in LPS biosynthesis, which may be associated with a decrease in rectal temperature. The increase in pantothenate and coenzyme A biosynthesis indicates microbial response to metabolic stress caused by ceftiofur. Preference of Fusobacterium for ß-hydroxybutyric acid may help to explain why this strain becomes dominant in the uterine microbiota of cows with metritis, and it also may provide a means for development of new therapies for the control of metritis in dairy cows.

2.
Appl Environ Microbiol ; 86(18)2020 09 01.
Article in English | MEDLINE | ID: mdl-32651210

ABSTRACT

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 microparticle-treated 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.IMPORTANCE Third-generation cephalosporins, such as ceftiofur, are commonly used to treat metritis in dairy cows. Chitosan microparticles has been shown to have a broad spectrum of activity in vitro and to be effective against uterine pathogens in vivo; therefore, they have been hailed as a possible alternative to traditional antibiotics. Nonetheless, in the present study, we saw that chitosan microparticle treatment slowed the progression of the uterine microbiome of cows with metritis toward a healthy state, whereas ceftiofur treatment hastened the progression toward a healthy state. Given the lack of an effective alternative to traditional antibiotics and an increased concern about antimicrobial resistance, a greater effort should be devoted to the prevention of metritis in dairy cows.


Subject(s)
Cattle Diseases/prevention & control , Chitosan/administration & dosage , Endometritis/veterinary , Microbiota/drug effects , Nanoparticles/administration & dosage , Uterus/microbiology , Animals , Cattle , Endometritis/prevention & control , Female , Protective Agents/administration & dosage
3.
Theriogenology ; 114: 25-33, 2018 Jul 01.
Article in English | MEDLINE | ID: mdl-29574306

ABSTRACT

Metritis is caused by polymicrobial infection; however, recent metagenomic work challenges the importance of known pathogens such as Escherichia coli and Trueperella pyogenes while identifying potential new pathogens such as Bacteroides pyogenes, Porphyromonas levii and Helcococcus ovis. This study aims to quantify known and emerging uterine pathogens, and to evaluate their association with metritis and fever in dairy cows. Metritis was diagnosed at 6 ±â€¯2 days postpartum, a uterine swab was collected and rectal temperature was measured. 39 cows were classified into three groups: Healthy (n = 14), Metritis without fever (MNoFever; n = 12), and Metritis with fever (MFever; n = 13). Absolute copy number was determined for total bacteria and for 8 potentially pathogenic bacteria using droplet digital PCR. Both MNoFever and MFever cows had higher copy number of total bacteria, Fusobacterium necrophorum, Prevotella melaninogenica, Bacteroides pyogenes, Porphyromonas levii, and Helcococcus ovis than Healthy cows. MNoFever and MFever groups were similar. There was no difference among groups in copy number of Escherichia coli, Trueperella pyogenes, and Bacteroides heparinolyticus, and they all had low copy numbers. Our work confirms the importance of some bacteria identified by culture-based studies in the pathogenesis of metritis such as Fusobacterium necrophorum and Prevotella melaninogenica; however, it challenges the importance of others such as Escherichia coli and Trueperella pyogenes at the time of metritis diagnosis. Additionally, Bacteroides pyogenes, Porphyromonas levii, and Helcococcus ovis were recognized as emerging pathogens involved in the etiology of metritis. Furthermore, fever was not associated with the total bacterial load or specific bacteria.


Subject(s)
Bacterial Infections/veterinary , Cattle Diseases/microbiology , Endometritis/veterinary , Fever/veterinary , Uterus/microbiology , Animals , Bacteria/classification , Bacteria/isolation & purification , Bacterial Infections/microbiology , Bacterial Infections/pathology , Cattle , Cattle Diseases/pathology , Endometritis/microbiology , Female , Fever/microbiology
4.
PLoS One ; 11(11): e0165740, 2016.
Article in English | MEDLINE | ID: mdl-27802303

ABSTRACT

OBJECTIVE: 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. PRINCIPAL FINDINGS (STUDY1): 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 Bacteroides and Porphyromonas were the largest contributors to that difference. A comparison of relative abundance at the species level pointed to Bacteroides pyogenes as a fever-related species which was significantly abundant in the MFever than the MNoFever and Healthy groups; however, absolute abundance of Bacteroides pyogenes 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. PRINCIPAL FINDINGS (STUDY2): 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. CONCLUSION/SIGNIFICANCE: 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. Bacteroides pyogenes 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.


Subject(s)
Cattle Diseases , Dairying , Fever/immunology , Fever/microbiology , Microbiota , Uterus/immunology , Uterus/microbiology , Animals , Cattle , Female , Fever/complications , Respiratory Burst
5.
Appl Environ Microbiol ; 81(18): 6324-32, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26150453

ABSTRACT

The objective of this study was to evaluate the progression of the uterine microbiota from calving until establishment of metritis. Uterine swabs (n = 72) collected at 0, 2, and 6 ± 2 days postpartum (dpp) from 12 metritic and 12 healthy cows were used for metagenomic sequencing of the 16S rRNA gene on the Illumina MiSeq platform. A heat map showed that uterine microbiota was established at calving. The microbiota changed rapidly from 0 to 6 ± 2 dpp, with a decrease in the abundance of Proteobacteria and an increase in the abundance of Bacteroidetes and Fusobacteria, which were dominant in metritic cows. Uterine microbiota composition was shared; however, metritic and healthy cows could be discriminated using relative abundance of bacterial genera at 0, 2, and 6 ± 2 dpp. Bacteroides was the main genus associated with metritis because it was the only genus that showed significantly greater abundance in cows with metritis. As the abundance of Bacteroides organisms increased, the uterine discharge score, a measure of uterine health, worsened. Fusobacterium was also an important genus associated with metritis because Fusobacterium abundance increased as Bacteroides abundance increased and the uterine discharge score worsened as the abundance increased. The correlation with uterine discharge score and the correlation with Bacteroides or Fusobacterium showed that other bacteria, such as Helcoccocus, Filifactor, and Porphyromonas, were also associated with metritis. There were also bacteria associated with uterine health, such as "Candidatus Blochmannia," Escherichia, Sneathia, and Pedobacter.


Subject(s)
Cattle Diseases/microbiology , Cattle/microbiology , Endometritis/veterinary , Microbiota , Postpartum Period , Uterus/microbiology , Animals , Bacteria/classification , Bacteria/isolation & purification , Bacteroidetes/isolation & purification , Endometritis/microbiology , Female , Fusobacteria/isolation & purification , High-Throughput Nucleotide Sequencing , Microbial Interactions , Proteobacteria/isolation & purification , RNA, Ribosomal, 16S/genetics , Time Factors
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