Use of inline measures of l-lactate dehydrogenase for classification of posttreatment mammary Staphylococcus aureus infection status in dairy cows

Jørgensen, Claus; Kristensen, Anders Ringgaard; Østergaard, S.; Bennedsgaard, Torben Werner

doi:10.3168/jds.2016-10858

Cited by 13 publications

(6 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The highest DE expressed genes in the mastitic group were β-2microglobulin (B2M), CD74 molecule (CD74), major histocompatibility complex class II DR α (BoLA-DRA), serine dehydratase (SDS), and l-lactate dehydrogenase A chain (LDHA; Table 2). When an inflammatory process involving cell damage occurs, LDH is released from cells into the milk (Jørgensen et al, 2016); therefore, LDH activity increases with mastitis (Bogin et al, 1977;Harmon, 1994). This evidence supports the high expression values of LDHA gene in the SC milk samples from mastitic quarters.…”

Section: High Medium and Low De Genes In The Healthy And Mastitic Groupssupporting

confidence: 75%

Genetic mechanisms regulating the host response during mastitis

Asselstine

Miglior

Suárez-Vega

et al. 2019

Journal of Dairy Science

View full text Add to dashboard Cite

Mastitis is a very costly and common disease in the dairy industry. The study of the transcriptome from healthy and mastitic milk somatic cell samples using RNA-Sequencing technology can provide measurements of transcript levels associated with the immune response to the infection. The objective of this study was to characterize the Holstein milk somatic cell transcriptome from 6 cows to determine host response to intramammary infections. RNA-Sequencing was performed on 2 samples from each cow from 2 separate quarters, one classified as healthy (n = 6) and one as mastitic (n = 6). In total, 449 genes were differentially expressed between the healthy and mastitic quarters (false discovery rate <0.05, fold change >±2). Among the differentially expressed genes, the most expressed genes based on reads per kilobase per million mapped reads (RPKM) in the healthy group were associated with milk components (CSN2 and CSN3), and in the mastitic group they were associated with immunity (B2M and CD74). In silico functional analysis was performed using the list of 449 differentially expressed genes, which identified 36 significantly enriched metabolic pathways (false discovery rate <0.01), some of which were associated with the immune system, such as cytokine-cytokine interaction and cell adhesion molecules. Seven functional candidate genes were selected, based on the criteria of being highly differentially expressed between healthy and mastitic groups and significantly enriched in metabolic pathways that are relevant to the inflammatory process (GLYCAM1, B2M, CD74, BoLA-DRA, FCER1G, SDS, and NFK-BIA). Last, we identified the differentially expressed genes that are located in quantitative trait locus regions previously known to be associated with mastitis, specifically clinical mastitis, somatic cell count, and somatic cell score. It was concluded that multiple genes within quantitative trait locus regions could potentially affect host response to mastitis-causing agents, making some cows more susceptible to intramammary infections. The identification of potential candidate genes with functional, statistical, biological, and positional relevance associated with host defense to infection will contribute to a better understanding of the underlying genetic architecture associated with mastitis. This in turn will improve the sustainability of agricultural practices by facilitating the selection of cows with improved host defense leading to increased resistance to mastitis.

show abstract

Section: High Medium and Low De Genes In The Healthy And Mastitic Groupssupporting

confidence: 75%

Genetic mechanisms regulating the host response during mastitis

Asselstine

Miglior

Suárez-Vega

et al. 2019

Journal of Dairy Science

View full text Add to dashboard Cite

show abstract

“…Pyruvate is converted into L‐lactic acid by L‐lactate dehydrogenase (EC 1.1.1.27, 1.17‐fold) and into 2‐hydroxyethyl‐ThPP by pyruvate dehydrogenase (acetyl‐transferring) E1 (EC 1.2.4.1, 0.67‐fold). L‐lactate dehydrogenase catalyses the conversion of pyruvate into L‐lactate acid (Jørgensen et al ., 2016). Pyruvate enters into the citrate cycle through the pyruvate dehydrogenase.…”

Section: Resultsmentioning

confidence: 99%

Detection of nitrite degradation by Lactobacillus plantarum DMDL9010 through the anaerobic respiration electron transport chain using proteomic analysis

Yao

Liu

Liang

et al. 2020

Int J of Food Sci Tech

View full text Add to dashboard Cite

This study aimed to investigate the mechanism of nitrite degradation by Lactobacillus plantarum DMDL9010 using the proteomic technology. The results showed that 0.276 g L−1 nitrite was degraded completely by L. plantarum DMDL9010 in 24 h. Nitrite was transported into the pericytoplasm by a two‐component system. Reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide‐2 (FADH2) were produced during metabolism via these pathways of phosphotransferase system, glycolysis/gluconeogenesis and citrate cycle. NADH and FADH2 produced electrons catalysed by dehydrogenase. The electrons were transferred through the electron transport chain eventually to nitrite. Some molecules of nitrites gained electrons and were reduced to NH3 by nitrite reductase. Then NH3 from nitrite was converted into l‐glutamine catalysed by glutamine synthetase, which was one of the ways to generate l‐glutamine. This study can provide theoretical guidance to the research on the biological technique to reduce nitrite in food products.

show abstract

“…Denmark) was used in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). The Herd Navigator™ is programmed to collect milk samples automatically and analyze mP4 in individual cows through a dry-stick biosensor technology and enzyme immunoassay [19], based on a bio-model that establishes frequency and quantification of mP4 samples. The system modulated the frequency of assays at an average of six to seven progesterone analyses per cycle according to the postpartum period and the stage of the estrous cycle.…”

Section: Measurementsmentioning

confidence: 99%

Dynamic Changes on Progesterone Concentration in Cow’s Milk Determined by Inline Milk Analysis System Herd Navigator

Antanaitis¹,

Malašauskienė²,

Televičius³

et al. 2020

Preprint

View full text Add to dashboard Cite

The aim of the instant study was to evaluate relative inline progesterone dynamic changes according to parity and status of reproduction and to estimate the relationship with productivity in dairy cows by inline milk analysis system (IMAS) Herd Navigator. According to a progesterone assay, cows were divided into three periods: postpartum, after insemination, and pregnancy. In the first stage of the postpartum period (0-29 days), the progesterone level in milk was monitored every 6 days. The second stage of the postpartum period (30-65 days) lasted until cows were inseminated. In the third period (0-45 days) after cows were inseminated, progesterone scores were distributed according to whether or not cows became pregnant. The stability of progesterone dynamics was monitored in the last study period (45-90 days). For milk progesterone detection, the fully automated real-time progesterone analyzer Herd Navigator (Lattec I/S. Hillerød. Denmark) was used in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). The highest progesterone concentration in multiparous cows ranged from 1.08% (11-17 days postpartum) to 34.89% higher than that in cows of the first parity. The lowest progesterone concentrations in the milk of all cows were estimated during the first 5 postpartum days and between 18 and 23 days after calving. Peak milk progesterone concentrations were evaluated in the first stage of the experiment on days 24-29 after calving. In the 30-65-day period after calving, the level of milk progesterone was 2.02-2.08 times higher than that in the 24-29-day postpartum period. After insemination, the level of progesterone in milk increased by 10.77-22.54% compared with the level from cows on days 30-65 after calving. A higher (12.88%) concentration of progesterone in milk was evaluated in multiparous cows compared with that from cows of the first parity. In pregnant cows, milk progesterone within 0-45 days after insemination was 23.88% (in multiparous cows) and 32.54% (in primiparous cows) higher than that in non-pregnant cows. On days 31–35 after insemination, pregnant cows had higher milk progesterone levels, which can predict pregnancy success. According to our study results, we can suggest that an inline progesterone concentration determined by inline milk analysis system Herd Navigator and changes in its dynamics correlate with different reproductive statuses and milk yield of cows. Pregnant cows 11–15 days after insemination have higher milk progesterone levels, what positively, associated with a successful pregnancy.

show abstract

Use of inline measures of l-lactate dehydrogenase for classification of posttreatment mammary Staphylococcus aureus infection status in dairy cows

Cited by 13 publications

References 20 publications

Genetic mechanisms regulating the host response during mastitis

Genetic mechanisms regulating the host response during mastitis

Detection of nitrite degradation by Lactobacillus plantarum DMDL9010 through the anaerobic respiration electron transport chain using proteomic analysis

Dynamic Changes on Progesterone Concentration in Cow’s Milk Determined by Inline Milk Analysis System Herd Navigator

Contact Info

Product

Resources

About