<abstract xmlns="http://www.w3.org/1999/xhtml">

<sec>
<h3>Introduction</h3>
<p>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.</p>
</sec>
<sec>
<h3>Material and Methods</h3>
<p>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.</p>
</sec>
<sec>
<h3>Results</h3>
<p>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).</p>
</sec>
<sec>
<h3>Conclusion</h3>
<p>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.</p>
</sec>
</abstract>

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.

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

Journal of Veterinary Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Introduction
MicroRNAs (miRNAs), a class of noncoding small RNAs, have been recognised as potential biomarkers of mammary gland conditions, including bovine...

Pathogen	n	Prevalence (%)
Streptococcus uberis	6	9.23
Streptococcus dysgalactiae	1	1.54
Staphylococcus aureus	1	1.54
Coagulase-negative staphylococci	4	6.15
Escherichia coli	1	1.54
Klebsiella spp.	2	3.08
No growth	33	50.77
Contamination	17	26.15

Parameter	Three-class analysis			Two-class analysis
Parameter	Low	Medium	High	Low
Sensitivity	0.67	0.67	0.82	0.98
Specificity	0.85	0.75	0.98	0.95
Positive predictive value	0.63	0.62	0.95	0.98
Negative predictive value	0.87	0.79	0.91	0.95
Balanced accuracy	0.76	0.71	0.90	0.97

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

Data publikacji: 19 gru 2023

Zakres stron: 583 - 591

Otrzymano: 15 cze 2023

Przyjęty: 27 paź 2023

DOI: https://doi.org/10.2478/jvetres-2023-0062

Słowa kluczowe
biomarker, bovine mastitis, ddPCR, microRNA, raw milk

© 2023 Sebastian Smulski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig. 1.

Fig. 2.

Fig. 3.

Prevalence of pathogens isolated from mastitic-quarter milk samples

Performance of the K-nearest neighbour regression model, by somatic cell count class in healthy and mastitic milk samples

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

Data publikacji: 19 gru 2023

Zakres stron: 583 - 591

Otrzymano: 15 cze 2023

Przyjęty: 27 paź 2023

DOI: https://doi.org/10.2478/jvetres-2023-0062

Słowa kluczowebiomarker, bovine mastitis, ddPCR, microRNA, raw milk

© 2023 Sebastian Smulski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig. 1.

Fig. 2.

Fig. 3.

Prevalence of pathogens isolated from mastitic-quarter milk samples

Performance of the K-nearest neighbour regression model, by somatic cell count class in healthy and mastitic milk samples

Słowa kluczowe
biomarker, bovine mastitis, ddPCR, microRNA, raw milk