Potential role of MicroRNA as a diagnostic tool in the detection of bovine mastitis

Milk miRNA expression in buffaloes as a potential biomarker for mastitis

BACKGROUND

Buffaloes have the highest potential for production due to a promising gene pool that is being enhanced and upgraded. Mastitis is a significant health impediment that greatly diminishes milk yield and quality, affecting rural farmers' livelihoods. The traditional gold standard used for diagnosing mastitis or subclinical mastitis is CMT, but it has the drawback of false positive or negative results. Subclinical mastitis, if not treated promptly, can lead to mammary tumors. To address the gap in early diagnosis of subclinical mastitis in CMT-negative milk of buffaloes, we performed a retrospective analysis and evaluated the milk miRNA expression profiles as potential biomarkers.

RESULTS

Thirty buffalo milk samples based on clinical signs and CMT were divided into normal, subclinical, and clinical mastitis. SCC evaluation showed significant differences between the groups. The data analysis demonstrated that the elevation of miR-146a and miR-383 differed substantially between normal, subclinical, and clinical mastitis milk of buffaloes with 100% sensitivity and specificity. The relationship of SCC with miR-146a and miR-383 in normal/healthy and subclinical mastitis was positively correlated.

CONCLUSION

The overexpression of miR-146a and miR-383 is associated with inflammation. It can be a valuable prognostic and most sensitive biomarker for early mastitis detection in buffaloes with SCC below 2 lakhs and CMT-ve, enhancing the accuracy of subclinical mastitis diagnosis.

The prevalence of adhesion and biofilm genes in Staphylococcus aureus isolates from bovine mastitis: A comprehensive meta-analysis

BACKGROUND

Mastitis poses significant challenges to the dairy industry, resulting in economic losses and increased veterinary expenses. Staphylococcus aureus is a common cause of bovine mastitis, relying on efficient adhesion and biofilm formation for infection.

OBJECTIVES

This study aimed to employ meta-analysis to investigate the occurrence of adhesion and biofilm genes in S. aureus associated with bovine mastitis, as documented in previous studies.

METHODS

This meta-analysis was done according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, examined 22 eligible articles and revealed varying prevalence rates of adhesion and biofilm genes in S. aureus isolates from bovine mastitis.

RESULTS

Among the genes, clfB showed the highest prevalence (p-estimate = 0.905), followed by fnbA (p-estimate = 0.689) and fnbB (p-estimate = 0.502). The icaA and icaD genes also showed a relatively high prevalence (p-estimate = 0.694 and 0.814, respectively). Conversely, the biofilm-associated proteins gene had the lowest prevalence (p-estimate = 0.043). Subgroup analyses based on mastitis types and publication years revealed no significant differences in gene prevalence. Insufficient data hindered the analysis of fib, sasG , eno and bbp genes.

CONCLUSION

This study provides valuable insights for managing S. aureus-induced bovine mastitis. Additionally, larger-scale research, particularly on less-studied genes, is necessary to comprehend the molecular roles of adhesion and biofilm genes in S. aureus-induced bovine mastitis.

Milk as diagnostic fluid for udder health management

BACKGROUND

Mastitis is the major disease affecting milk production of dairy cattle, and milk is an obvious substrate for the detection of both the inflammation and its causative infectious agents at quarter, cow, or herd levels. In this review, we examine the use of milk to detect inflammation based on somatic cell count (SCC) and other biomarkers, and for the detection of mastitis pathogens through culture-based and culture-free methods.

FINDINGS

The use of SCC at a cow or bulk milk level to guide udder health management in lactation is well-established, and SCC is increasingly used to guide selective dry cow treatment. Other markers of inflammation include electrical conductivity, which is used commercially, and markers of disease severity such as acute phase proteins but are not pathogen-specific. Some pathogen-specific markers based on humoral immune responses are available, but their value in udder health management is largely untested. Commercial pathogen detection is based on culture or polymerase chain reaction, with other tests, for example, loop-mediated isothermal amplification or 16S microbiome analysis still at the research or development stage. Matrix-assisted laser desorption ionisation time of flight (MALDI-ToF) is increasingly used for the identification of cultured organisms whilst application directly to milk needs further development. Details of test sensitivity, specificity, and use of the various technologies may differ between quarter, cow, and bulk milk applications.

CONCLUSIONS

There is a growing array of diagnostic assays that can be used to detect markers of inflammation or infection in milk. The value of some of these methods in on-farm udder health improvement programs is yet to be demonstrated whilst methods with proven value may be underutilised.

Considering potential roles of selected MicroRNAs in evaluating subclinical mastitis and Milk quality in California mastitis test (+) and infected bovine milk

This study investigates the relationships between subclinical mastitis and milk quality with selected microRNAs in cow milk. California Mastitis Test (CMT)-positive (n = 20) and negative (n = 20) samples were compared (Experiment I). Additionally, samples with CMT-positive but microbiological-negative, as well as positive for only Staphylococcus subspecies (Staph spp.) and only Streptococcus subspecies (Strep spp.) were examined (Experiment II). Four groups were formed in Experiment II: Group I (CMT and microbiological-negative) (n = 20), Group II (CMT-positive but microbiological-negative) (n = 10), Group III (Staph spp.) (n = 5), Group IV (Strep spp.) (n = 5). While electrical conductivity, somatic cell count (SCC), malondialdehyde (MDA) increased, miR-27a-3p and miR-223 upregulated and miR-125b downregulated in the CMT-positive group in Experiment I. SCC and MDA were higher in CMT-positive groups. miR-27a-3p and miR-223 upregulated in Groups III and IV. While miR-155 is upregulated, miR-125b downregulated in Group IV. Milk fat is positively correlated with miR-148a and miR-223. As miR-27a-3p positively correlated with SCC and MDA, miR-125b negatively correlated with electrical conductivity and SCC. miR-148a and MDA were positively correlated. miR-155 was correlated with fat-free dry matter, protein, lactose, and freezing point. miR-223 was positively correlated with SCC and miR-148a. Results particularly highlight miR-27a-3p and miR-223 as potential biomarkers in subclinical mastitis, especially those caused by Staph spp. and Strep spp., while miR-148a, miR-155, and miR-223 stand out in determining milk quality.

Droplet digital PCR quantification of selected microRNAs in raw mastitic cow's milk from the west of Poland

Introduction

MicroRNAs (miRNAs), a class of noncoding small RNAs, have been recognised as potential biomarkers of mammary gland conditions, including bovine mastitis diagnosis. The aim of this study was to quantify selected miRNAs in the milk of mastitic cows.

Material and Methods

Milk samples (n = 90) were collected from healthy and mastitic dairy cows originating from local dairy cattle farms located in the west of Poland. MicroRNAs of the miR-21a, miR-92a, miR-146a and miR-383 species were quantified using the highly sensitive droplet digital PCR method. Direct measurement of somatic cell count (SCC) was performed using a cell counter. Cows were divided into three groups: those with an SCC below 200,000/mL were designated Low (n = 25), those with an SCC between 200,000 and 999,999 were Medium (n = 34), and those with an SCC of 1,000,000 or higher were High (n = 31). Microbiological analyses were performed using standard culture testing.

Results

The level of miR-383 was very low and this miRNA was excluded from analysis. The miR-92a was used to normalise miR-21a and miR-146a expression levels. The obtained results of expression of miR-21a and miR-146a correlated with somatic cell number (R = 0.53 and 0.79, respectively).

Conclusion

These results show that ddPCR is a useful method for quantifying miRNAs in raw cow milk. It seems that miR-146a is a promising marker for bovine mastitis, although further studies are needed to select a panel of miRNAs that can be used in mastitis monitoring in Poland.

Exploring the potential immunomodulatory effects of gallic acid on milk phagocytes in bovine mastitis caused by Staphylococcus aureus

Bovine mastitis caused by Staphylococcus aureus may exacerbate by resulting in significant economic losses and impacting milk quality. To date, the use of gallic acid, a phenolic compound naturally occurring in various plants, holds promise due to its potent anti-oxidant and anti-inflammatory effects in many pieces of literature, thus, making it a subject of interest in bovine innate immunity research. Here we used gallic acid to assess its potential immunomodulation on milk phagocytes in vitro challenges with mastitis-causing bacteria. Our findings indicated that cells exposed to gallic acid showed no harm to cell viability but might maintain the longevity of cells during the bacterial infection. Gallic acid-treated cells displayed reduced cell migration, phagocytosis, and bacterial killing ability, while showing an increase in ROS production, all of which are undoubtedly linked to the intracellular killing abilities of the cells. Nonetheless, the extracellular structure called neutrophil extracellular traps (NETs) was significantly released after receiving gallic acid, representing extracellular killing. We also reported that gallic acid neutralizes inflammation by regulating specific pro-inflammatory genes (IL1B, IL6, TNF) and ROS-generating genes (CYBA, LAMP1, RAC1), subsequently preventing tissue damage. Regarding apoptosis-related genes and proteins, the increased production of caspase-3 and Bcl-2 family proteins could potentially promote the longevity of cells, implicated in the mechanism of combating bacterial invasion during udder inflammation and infection. The novel role of gallic acid on milk phagocytes highlights its potential immunomodulatory properties and contributes to our understanding of its effects on bacterial-host interactions, and provides valuable molecular insights.

Regulatory Role of microRNA of Milk Exosomes in Mastitis of Dairy Cows

The aim of this study was to compare the cargos of miRNA in exosomes isolated from the milk of healthy (H) cows, cows at risk of mastitis (ARM), and cows with subclinical mastitis (SCM). Based on the number of somatic cells and the percentage of polymorphonuclear cells, 10 cows were assigned to group H, 11 to group ARM, and 11 to group SCM. After isolating exosomes in milk by isoelectric precipitation and ultracentrifugation, the extracted RNA was sequenced to 50 bp long single reads, and these were mapped against Btau_5.0.1. The resulting 225 miRNAs were uploaded to the miRNet suite, and target genes for Bos taurus were identified based on the miRTarBase and miRanda databases. The list of differentially expressed target genes resulting from the comparisons of the three groups was enriched using the Function Explorer of the Kyoto Encyclopedia of Genes and Genomes. A total of 38, 18, and 12 miRNAs were differentially expressed (DE, p < 0.05) in the comparisons of H vs. ARM, ARM vs. SCM, and H vs. SCM, respectively. Only 1 DE miRNA was shared among the three groups (bta-mir-221), 1 DE miRNA in the H vs. SCM comparison, 9 DE miRNAs in the ARM vs. SCM comparison, and 21 DE miRNAs in the H vs. ARM comparison. A comparison of the enriched pathways of target genes from the H, SCM, and ARM samples showed that 19 pathways were differentially expressed in the three groups, while 56 were expressed in the H vs. SCM comparison and 57 in the H vs. ARM comparison. Analyzing milk exosome miRNA cargos can be considered as a promising approach to study the complex molecular machinery set in motion in response to mastitis in dairy cows.

Emerging Roles of Noncoding RNAs in Bovine Mastitis Diseases

Non-coding RNAs (ncRNAs) are an abundant class of RNA with varying nucleotide lengths. They have been shown to have great potential in eutherians/human disease diagnosis and treatments and are now gaining more importance for the improvement of diseases in livestock. To date, thousands of ncRNAs have been discovered in the bovine genome and the continuous advancement in deep sequencing technologies and various bioinformatics tools has enabled the elucidation of their roles in bovine health. Among farm animals' diseases, mastitis, a common inflammatory disease in cattle, has caused devastating economic losses to dairy farmers over the last few decades. Here, we summarize the biology of bovine mastitis and comprehensively discuss the roles of ncRNAs in different types of mastitis infection. Based on our findings and relevant literature, we highlighted various evidence of ncRNA roles in mastitis. Different approaches (in vivo versus in vitro) for exploring ncRNA roles in mastitis are emphasized. More particularly, the potential applications of emerging genome editing technologies, as well as integrated omics platforms for ncRNA studies and implications for mastitis are presented.

MiRNAs in milk can be used towards early prediction of mammary gland inflammation in cattle

Considering the importance of early disease detection for reducing the huge financial and animal welfare impact of bovine mastitis globally, improved tools are urgently needed that can accurately detect early mammary inflammation. MiRNAs have demonstrated value as disease biomarkers, however, their potential for accurately detecting early mammary inflammation has not been examined in detail. To address this, we investigated the association between levels of four inflammation-associated miRNAs (bta-miR-26a, bta-miR-142-5p, bta-miR-146a and bta-miR-223) and CMT scores (0 to 3) obtained from a large number of individual quarter milk samples (n = 236) collected from dairy cows at different lactations (1 to 4). Initial analyses (n = 21 samples) confirmed that the levels of each of bta-miR-142-5p, bta-miR-146a and bta-miR-223 in whole milk were significantly correlated with mRNA levels of known inflammatory markers (HP, TNF, CXCL8 and IL1B) in milk cells (Rho ≥ 0.49, P < 0.005). Subsequent analyses (n = 215 samples) revealed a significant effect of CMT score on each of the four miRNAs analysed (P < 0.0001), characterised by a progressive increase in miRNA levels in milk as CMT score increase from 0 to > 1. Moreover, a significant effect of lactation number (P < 0.01) for bta-miR-26a, bta-miR-142-5p and bta-miR-146a was attributed to higher miRNA levels during lactation 1 than later lactations. Finally, by generating ROC curves we showed that bta-miR-223 and bta-miR-142-5p levels could identify early inflammatory changes in individual quarter milk samples (CMT1) with high accuracy (100% sensitivity, > 81% specificity). Our results provide novel proof of the value of miRNAs as early diagnostic biomarkers of bovine mastitis.

Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study

Machine learning applications are becoming more ubiquitous in dairy farming decision support applications in areas such as feeding, animal husbandry, healthcare, animal behavior, milking and resource management. Thus, the objective of this mapping study was to collate and assess studies published in journals and conference proceedings between 1999 and 2021, which applied machine learning algorithms to dairy farming-related problems to identify trends in the geographical origins of data, as well as the algorithms, features and evaluation metrics and methods used. This mapping study was carried out in line with PRISMA guidelines, with six pre-defined research questions (RQ) and a broad and unbiased search strategy that explored five databases. In total, 129 publications passed the pre-defined selection criteria, from which relevant data required to answer each RQ were extracted and analyzed. This study found that Europe (43% of studies) produced the largest number of publications (RQ1), while the largest number of articles were published in the Computers and Electronics in Agriculture journal (21%) (RQ2). The largest number of studies addressed problems related to the physiology and health of dairy cows (32%) (RQ3), while the most frequently employed feature data were derived from sensors (48%) (RQ4). The largest number of studies employed tree-based algorithms (54%) (RQ5), while RMSE (56%) (regression) and accuracy (77%) (classification) were the most frequently employed metrics used, and hold-out cross-validation (39%) was the most frequently employed evaluation method (RQ6). Since 2018, there has been more than a sevenfold increase in the number of studies that focused on the physiology and health of dairy cows, compared to almost a threefold increase in the overall number of publications, suggesting an increased focus on this subdomain. In addition, a fivefold increase in the number of publications that employed neural network algorithms was identified since 2018, in comparison to a threefold increase in the use of both tree-based algorithms and statistical regression algorithms, suggesting an increasing utilization of neural network-based algorithms.

MicroRNAs: Potential biomarkers for reproduction, diagnosis, prognosis, and therapeutic in domestic animals

MicroRNA (miRNAs) are small non-coding RNA molecules involved in a wide range of biological processes through the post-transcriptional regulation of gene expression. Most studies evaluated microRNA expression in human, and despite fewer studies in veterinary medicine, this topic is one of the most exciting areas of modern veterinary medicine. miRNAs showed to be part of the pathogenesis of diseases and reproduction physiology in animals, making them biomarkers candidates. This review provides an overview of the current knowledge regarding miRNAs' role in reproduction and animal diseases, diagnostic and therapy.

Potential Novel Biomarkers for Mastitis Diagnosis in Sheep

Simple Summary

Inflammation of the mammary gland (mastitis) is an important disease of dairy sheep. Mastitis management depends mainly on the diagnosis. Conventional diagnostic methods including somatic cell count, California Mastitis Test, and microbial culture have limitations. Therefore researchers are looking for new diagnostic biomarkers of mastitis including specific proteins produced by the liver in case of disease (acute phase proteins), unique genetic sequences (miRNAs), or antimicrobial peptides produced by immune cells during inflammation (cathelicidines).

Abstract

This review aims to characterize promising novel markers of ovine mastitis. Mastitis is considered as one of the primary factors for premature culling in dairy sheep and has noticeable financial, productional, and animal welfare-related implications. Furthermore, clinical, and subclinical mammary infections negatively affect milk yield and alter the milk composition, thereby leading to lowered quality of dairy products. It is, therefore, crucial to control and prevent mastitis through proper diagnosis, treatment or culling, and appropriate udder health management particularly at the end of the lactation period. The clinical form of mastitis is characterized by abnormalities in milk and mammary gland tissue alteration or systemic symptoms consequently causing minor diagnostic difficulties. However, to identify ewes with subclinical mastitis, laboratory diagnostics is crucial. Mastitis control is primarily dependent on determining somatic cell count (SCC) and the California Mastitis Test (CMT), which aim to detect the quantity of cells in the milk sample. The other useful diagnostic tool is microbial culture, which complements SCC and CMT. However, all mentioned diagnostic methods have their limitations and therefore novel biomarkers of ovine subclinical mastitis are highly desired. These sensitive indicators include acute-phase proteins, miRNA, and cathelicidins measurements, which could be determined in ovine serum and/or milk and in the future may become useful in early mastitis diagnostics as well as a preventive tool. This may contribute to increased detection of ovine mammary gland inflammation in sheep, especially in subclinical form, and consequently improves milk quality and quantity.

miRNA‑7515 suppresses pancreatic cancer cell proliferation, migration and invasion via downregulating IGF‑1 expression

Pancreatic cancer (PC) is a lethal malignancy of the gastrointestinal tract. Previous studies have reported that microRNAs (miRNAs/miRs) are involved in the tumorigenesis of PC. Therefore, the present study aimed to determine the effects of miR‑7515 on PC cell proliferation, invasion and migration in vitro and in vivo, and investigate its underlying molecular mechanism using bioinformatics, double luciferase assay and western blotting. The results revealed that the expression levels of miR‑7515 were downregulated in PC, which predicted a poor clinical outcome. The overexpression of miR‑7515 significantly decreased the proliferation, invasive and migratory abilities of PC cells in vitro and in vivo, while the knockdown of miR‑7515 exerted the opposite effects. miR‑7515 was identified to directly bind to insulin‑like growth factor 1 (IGF‑1) and downregulate its expression, which subsequently downregulated the Ras/Raf/MEK/ERK signalling pathway. The overexpression of IGF‑1 reversed the inhibitory effects of miR‑7515 overexpression on PC cells. In conclusion, the findings of the present study indicated that miR‑7515 may act as a tumor suppressor in PC, as it repressed PC cell proliferation invasion and migration via downregulating the expression of IGF‑1 and the activity of the Ras/Raf/MEK/ERK signalling pathways.

Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cows

Bovine mastitis is one of the most important economic and health issues in dairy farms. Data collection during routine recording procedures and access to large datasets have shed the light on the possibility to use trained machine learning algorithms to predict the udder health status of cows. In this study, we compared eight different machine learning methods (Linear Discriminant Analysis, Generalized Linear Model with logit link function, Naïve Bayes, Classification and Regression Trees, k-Nearest Neighbors, Support Vector Machines, Random Forest and Neural Network) to predict udder health status of cows based on somatic cell counts. Prediction accuracies of all methods were above 75%. According to different metrics, Neural Network, Random Forest and linear methods had the best performance in predicting udder health classes at a given test-day (healthy or mastitic according to somatic cell count below or above a predefined threshold of 200,000 cells/mL) based on the cow’s milk traits recorded at previous test-day. Our findings suggest machine learning algorithms as a promising tool to improve decision making for farmers. Machine learning analysis would improve the surveillance methods and help farmers to identify in advance those cows that would possibly have high somatic cell count in the subsequent test-day.

MicroRNAs as Biomarkers for Animal Health and Welfare in Livestock

MicroRNAs (miRNAs) are small and highly conserved non-coding RNA molecules that orchestrate a wide range of biological processes through the post-transcriptional regulation of gene expression. An intriguing aspect in identifying these molecules as biomarkers is derived from their role in cell-to-cell communication, their active secretion from cells into the extracellular environment, their high stability in body fluids, and their ease of collection. All these features confer on miRNAs the potential to become a non-invasive tool to score animal welfare. There is growing interest in the importance of miRNAs as biomarkers for assessing the welfare of livestock during metabolic, environmental, and management stress, particularly in ruminants, pigs, and poultry. This review provides an overview of the current knowledge regarding the potential use of tissue and/or circulating miRNAs as biomarkers for the assessment of the health and welfare status in these livestock species.