Milk-derived miRNA as indicator of stress in bovine animals

Abstract

The present invention relates to miRNA biomarkers from milk, such as exosome-derived microRNAs from milk, as an indicator of welfare in bovine animals. In particular, the present invention relates to the identification of heat stress in bovine animals, allowing management measures to be proposed to improve productive animal welfare at individual or veterinary levels.

Description

Technical Field

[0001] The present invention relates to the use of milk-derived microRNA from dairy cow milk as an indicator of animal welfare, such as an indicator of stress (such as heat stress). Background Art

[0002] International regulatory frameworks recommend observing changes in animal health and behavior to define stress and recommend improvements in animal welfare management. However, visual observation alone is subjective and does not consider specific physiological markers of stress.

[0003] Currently, different indicators are used to assess whether an animal has or is experiencing a stressful condition. These include

[0004] - Observation of changes in the health status and behavior of animals, which is currently considered a reference tool for monitoring and detecting early warning signs of deterioration in animal health and welfare;

[0005] - Changes in blood parameters, such as blood sugar, blood cell count, hormone and metabolite levels. However, these parameters are highly variable among different animal species, ages, and life stages. In addition, the levels of hormones in milk (such as cortisol) vary greatly, and therefore classical biomarkers are not suitable specific indicators of stress.

[0006] In contrast, the expression of miRNAs is specific to cells and tissues and is well-regulated.

[0007] Ioannidis et al. disclosed the association of plasma microRNA expression with age, genetic background and functional traits in dairy cows (SCIENTIFIC REPORTS|(2018)8:12955).

[0008] Miretti et al. disclosed microRNAs as biomarkers of animal health and welfare in livestock (Front. Vet. Sci. 7:578193).

[0009] Billa et al. published that nutrigenomic analysis revealed miRNAs and mRNAs affected by dietary restriction in the mammary gland of mid-lactation dairy cows (PLoS ONE 16(4):e0248680).

[0010] Li et al. (BMC Genomics (2018) 19:975) disclosed the characterization of miRNA profiles in response to heat stress in mammary tissue of dairy cows.

[0011] Hence, improved methods of non-invasively determining animal welfare would be advantageous, and in particular more efficient and / or reliable methods of determining animal stress, such as heat stress, would be advantageous.The present invention addresses this need. Summary of the Invention

[0012] The present invention relates to miRNA biomarkers from milk, such as exosome-derived microRNAs from milk, as indicators of cattle welfare or welfare parameters. In particular, the present invention relates to the identification of stress, particularly heat stress, in cattle, which in turn means that measures can be taken to manage and improve production animal welfare at the individual or herd level.

[0013] Therefore, one object of the present invention relates to providing miRNA biomarkers that can be indicative of welfare parameters of cattle, preferably dairy cattle.

[0014] In particular, one object of the present invention is to provide miRNA biomarkers from milk-derived exosomes that can indicate heat stress in (dairy) cattle and which can be used across different breeds of (dairy) cattle.

[0015] Example 1 shows the characterization of physiological parameters and oxidative and inflammatory markers in biological samples from two breeds of dairy cows under thermal comfort conditions and under heat stress. This example shows that heat stress affects the welfare of cows and influences production parameters.

[0016] Example 2 is an analysis of the miRNA profiles of milk-derived exosomes in milk from two different breeds of cows under thermal comfort conditions and heat stress using next generation sequencing (NGS).

[0017] Example 3 shows the identification of differentially expressed miRNAs in milk from two breeds of heat-stressed cows.

[0018] Example 4 shows the identification of similarly expressed miRNAs in milk from two breeds of heat-stressed cows.

[0019] Thus, one aspect of the present invention relates to a method of determining at least one welfare parameter of at least one cattle, the method comprising

[0020] i. Determining the level of (at least) at least one miRNA that regulates the cell cycle in a milk sample, wherein the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 81, 134,

[0021] 85, 74, 83, 113, 1, 132, 112 and 111 or their functional variants, wherein the functional variants are respectively the same as SEQ ID NO: 94, 123, 93, 84, 81, 134, 85,

[0022] 74, 83, 113, 1, 132, 112, and 111 have at least 60% overall sequence identity; and

[0023] ii. comparing the level of the at least one miRNA to a reference level, wherein if the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1,

[0024] If the one or more miRNAs selected from SEQ ID NOs: 132, 112 and 111 are above the reference level, then at least one welfare parameter of the at least one cow has been compromised or is compromised, or if the one or more miRNAs selected from SEQ ID NOs: 81 and 134 are below the reference level, then at least one welfare parameter of the at least one cow has been compromised or is compromised.

[0025] In another aspect of the present invention, there is provided a method of improving at least one welfare parameter of at least one cattle, the method comprising

[0026] i. Determining the level of at least one miRNA that regulates the cell cycle in the first milk sample, wherein the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 81, 134, 85,

[0027] 74, 83, 113, 1, 132, 112 and 111 or their functional variants, wherein the functional variants are respectively the same as SEQ ID NO: 94, 123, 93, 84, 81, 134, 85, 74,

[0028] 83, 113, 1, 132, 112, and 111 have at least 60% sequence identity;

[0029] ii. comparing the level of the at least one miRNA to a reference level, wherein if the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1,

[0030] if the one or more miRNAs selected from SEQ ID NOs: 132, 112 and 111 are above the one or more reference levels, then at least one welfare parameter of the at least one cattle has been compromised, or if the one or more miRNAs selected from SEQ ID NOs: 81 and 134 are below the one or more reference levels, then at least one welfare parameter of the at least one cattle has been compromised;

[0031] iii. improving the welfare of the at least one cattle;

[0032] iv. Determine the second milk sample selected from SEQ ID NO: 94, 123, 93, 84, 81, 134,

[0033] The level of at least one miRNA of SEQ ID NO: 85, 74, 83, 113, 1, 132, 112 and 111 or its functional variants, wherein the functional variants correspond to SEQ ID NO: 94, 123,

[0034] 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112, and 111 have at least 60% sequence identity; and

[0035] v. comparing the level of the at least one miRNA in the first milk sample with the level in the second milk sample, wherein the welfare of the one cow has been improved if the level of SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112 and 111 or 55 or a functional variant thereof in the second milk sample is lower than the level in the first milk sample or lower than the level in the reference sample, wherein the functional variant corresponds to SEQ ID NO: 94, 123, 93, 84, 85, 74, 83,

[0036] 113, 1, 132, 112 and 111 have at least 60% sequence identity; or if the level of SEQ ID NO: 81 or 134 in the second milk sample is higher than the level in the first milk sample or higher than the reference sample, the welfare of the one cow has been improved.

[0037] In one embodiment, improving the welfare of at least one cattle comprises one or more of modifying heat exposure, improving access to additional water, modifying feed, reducing animal density, and providing a cooling system.

[0038] In other aspects of the present invention, there is provided a method of improving at least one of milk production, milk quality, meat production or meat quality of at least one cow, the method comprising

[0039] i. Determining the level of at least one miRNA involved in regulating the cell cycle in the first milk sample, wherein the miRNA is selected from SEQ ID NO: 94, 123, 93, 84, 85, 74,

[0040] 83, 113, 1, 132, 112 and 111 or a functional variant thereof, wherein the functional variant is identical to SEQ ID NO: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113,

[0041] 1, 132, 112, and 111 have at least 60% sequence identity;

[0042] ii. comparing the level of the at least one miRNA to a reference level, wherein if the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1,

[0043] and if the one or more miRNAs selected from SEQ ID NOs: 132, 112 and 111 are above the one or more reference levels, then at least one welfare parameter of the at least one cattle has been compromised or is compromised, or if the one or more miRNAs selected from SEQ ID NOs: 81 and 134 are below the one or more reference levels, then at least one welfare parameter of the at least one cattle has been compromised;

[0044] iii. improving the welfare of the at least one cow; wherein improving the welfare of the at least one cow improves at least one of milk production, milk quality, meat production and meat quality.

[0045] In another aspect of the present invention, there is provided a method for determining at least one welfare parameter of at least one cattle, the method comprising determining the level of at least one miRNA, wherein the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 120, 48, 112, 111, 31, 87 and 55 or functional variants thereof, wherein the functional variants have at least 60% overall sequence identity to SEQ ID NO: 94, 123, 93, 84, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 120, 48, 112, 111, 31, 87 and 55, respectively; NO:94, 123, 93, 84, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 120, 48, 112, 111, 31, 87 and 55 or their functional variants are increased by 1 log2FC (1 log fold change) or more compared to the reference level, or wherein the level of SEQ ID NO:2, 81 or 134 is decreased by -1 log2FC or more compared to the reference level, at least one welfare parameter of the at least one cattle has been compromised or not compromised.

[0046] In one embodiment, at least one welfare parameter of at least one cattle has been compromised if the level of SEQ ID NO: 94 or a functional variant thereof is above said one or more reference levels.

[0047] In one embodiment, the welfare parameter of at least one cow may be or include at least one type of stress, examples of which include but are not limited to heat stress, social stress, metabolic stress, disease stress, or a combination thereof.

[0048] In one embodiment, the cattle are dairy cattle, preferably bovines. In another embodiment, the cattle are of a breed selected from the group consisting of Holstein and / or Brown Swiss.

[0049] In one embodiment, the milk sample is from a herd of cattle.

[0050] The method may comprise determining the levels of all of SEQ ID NOs: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112 and 111, or functional variants thereof, said functional variants having at least 60% sequence identity to SEQ ID NOs: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112 and 111, respectively.

[0051] The reference level may be the level of one or more miRNAs in a milk sample from at least one cow, wherein the welfare of the cow is not or has not been compromised, or wherein the reference level is an average level from cows, wherein the welfare of the cows is not or has not been compromised.

[0052] The method may further comprise determining the level of a physiological parameter in a milk sample from the cow head, wherein the physiological parameter may be selected from one or more of heat shock protein 70, serum protein profile, blood urea nitrogen, blood uric acid, serum chloride, serum phosphorus, serum triglycerides, and serum magnesium.

[0053] In one embodiment, the method comprises determining the level of heat shock protein 70 in a milk sample from the one cow, comparing the level to a corresponding reference level of heat shock protein 70 (reference level is defined herein), wherein when the level of heat shock protein 70 is increased compared to the reference level, it indicates that at least one welfare parameter (i.e., welfare) of the at least one cow has been compromised.

[0054] In one embodiment, the method comprises determining a serum protein profile in a milk sample from said cow, comparing said levels to a corresponding reference serum protein profile (reference levels are defined herein), wherein if total protein is increased compared to the reference level, it indicates that at least one welfare parameter (i.e. welfare) of at least one cow has been compromised.

[0055] In one embodiment, the method comprises determining the level of blood urea nitrogen in a milk sample from the one cow, comparing the level to a corresponding reference level of blood urea nitrogen (reference level is defined herein), wherein when the level of blood urea nitrogen is increased compared to the reference level, it indicates that at least one welfare parameter (i.e. welfare) of the at least one cow has been compromised.

[0056] In one embodiment, the method comprises determining the level of blood uric acid in a milk sample from the one cow, comparing the level with a corresponding reference level of blood uric acid (reference level is defined herein), wherein when the level of blood uric acid is reduced compared to the reference level, it indicates that at least one welfare parameter (i.e., welfare) of the at least one cow has been impaired.

[0057] In one embodiment, the method comprises determining the level of serum chloride in a milk sample from the one cow, comparing the level to a corresponding reference level of serum chloride (reference level is defined herein), wherein when the level of serum chloride is increased compared to the reference level, it indicates that at least one welfare parameter (i.e., welfare) of the at least one cow has been compromised.

[0058] In one embodiment, the method comprises determining the level of serum phosphorus in a milk sample from the one cow, comparing the level to a corresponding reference level of serum phosphorus (reference level is defined herein), wherein when the level of serum phosphorus is increased compared to the reference level, it indicates that at least one welfare parameter (i.e., welfare) of the at least one cow has been compromised.

[0059] In one embodiment, the method comprises determining the level of serum magnesium in a milk sample from the one cow, comparing the level to a corresponding reference level of serum magnesium (reference level is defined herein), wherein when the level of serum magnesium is reduced compared to the reference level, it indicates that at least one welfare parameter (i.e., welfare) of the at least one cow has been compromised.

[0060] In one embodiment, the method comprises determining the level of serum triglycerides in a milk sample from the one cow, comparing the level to a corresponding reference level of serum triglycerides (reference level is defined herein), wherein when the level of serum triglycerides is reduced compared to the reference level, it indicates that at least one welfare parameter (i.e., welfare) of the at least one cow has been compromised.

[0061] In another aspect of the invention, there is provided an apparatus or system adapted to determine whether at least one welfare parameter of at least one cattle has been compromised or is compromised, the apparatus comprising:

[0062] - a unit capable of determining the level of one or more miRNAs as described herein;

[0063] - a processor configured with a reference table corresponding to reference levels of one or more miRNAs according to Table 4;

[0064] - wherein said device or system is suitable for

[0065] - receiving milk samples;

[0066] - determining the level of said one or more miRNAs;

[0067] - comparing the determined levels of said one or more miRNAs with said reference table;

[0068] as well as

[0069] - Determining whether the welfare of said at least one cattle has been or is being compromised.

[0070] In another aspect of the present invention, there is provided a computer-implemented method of determining whether the welfare of at least one cattle has been compromised, the method comprising:

[0071] - providing the levels of one or more miRNAs from a bovine milk sample selected from Table 4;

[0072] - providing a mathematical model comprising reference levels of one or more corresponding miRNAs selected from Table 4;

[0073] - determining, using the mathematical model, whether the provided level deviates significantly from the reference level; and

[0074] - providing a determination to the system or user whether the welfare of said at least one cattle has been or is being compromised.

[0075] In another aspect of the present invention, there is provided a kit for assessing at least one welfare parameter of at least one cattle, the kit comprising the device of the present invention and instructions for use.

[0076] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 2 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 2.

[0077] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 52 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 52.

[0078] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 6 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 6.

[0079] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 70 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 70.

[0080] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 69 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 69.

[0081] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 120 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 120.

[0082] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 48 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 48.

[0083] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 31 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 31.

[0084] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 87 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 87.

[0085] In other embodiments of any of the above methods, uses and devices or systems, the miRNA may alternatively be a miRNA defined in SEQ ID NO: 55 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 55.

[0086] The present invention will now be described in more detail in the following paragraphs. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 A schematic diagram of the experimental design used is shown. DETAILED DESCRIPTION

[0088] definition

[0089] Before discussing the present invention in further detail, the following terms and conventions are first defined.

[0090] cow

[0091] At least one cow is an animal of unspecified age or sex.

[0092] dairy cows

[0093] Dairy cattle (also called dairy cows) are cattle bred for their ability to produce large quantities of milk, from which dairy products are made. Dairy cattle are typically the species Bos taurus.

[0094] Functional variants

[0095] The term " variant " or " functional variant " refers to a miRNA sequence, wherein the nucleotide of the miRNA is substantially identical to a sequence in the sequence. Variant can be achieved by modification (such as insertion, substitution or deletion of one or more nucleotides). In a preferred embodiment, the variant and the sequence, such as any one of SEQ ID NO 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55 and 93, preferably have at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% homogeneity over the total length of the sequence. In one embodiment, the sequence identity is at least 90%. In another embodiment, the sequence identity is 100%. Sequence identity can be determined by any sequence alignment program known in the art. For the avoidance of doubt, functional variants perform the same function as the non-variant sequence. For example, functional variants of miRNAs that regulate the cell cycle also regulate the cell cycle in the same manner as the non-variant sequence.

[0096] Increase

[0097] In the context of the present invention, an increase is an increase in the level of a miRNA by at most or more than 1%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or 100% compared to a reference level. Alternatively, as used herein, an increase is an increase by at most or at least 1 log2FC, 1.5 log2FC, 2 log2FC, 3 log2FC, 4 log2FC, 5 log2FC, 6 log2FC, 7 log2FC 8 log2FC, 9 log2FC, 10 log2FC or more compared to a reference level.

[0098] reduce

[0099] In the context of the present invention, reduction is a reduction in miRNA levels by at most or at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or 95% compared to a reference level. Alternatively, as used herein, reduction is a reduction by at most or at least -1 log2FC, -1.5 log2FC, -2 log2FC, -3 log2FC, -4 log2FC, -5 log2FC, -6 log2FC, -7 log2FC, -8 log2FC, -9 log2FC, -10 log2FC or more compared to a reference level.

[0100] Log2FC

[0101] Log2FC stands for log2 fold change, a statistical measure used to quantify changes in nucleic acid expression between two conditions. The fold change is simply the ratio of nucleic acid expression levels under two conditions, and the log2 transformation is used to normalize the data for interpretation. A log2FC of 1 indicates a doubling of miRNA expression, while a log2FC of 2 indicates a fourfold increase in miRNA expression. Log2FC is used to identify differentially expressed miRNAs under different conditions.

[0102] Welfare

[0103] Welfare is a broad term that encompasses many elements that contribute to an animal's quality of life, including those mentioned in the Five Freedoms:

[0104] I. Freedom from hunger, thirst, and malnutrition;

[0105] II. Freedom from fear and pain;

[0106] III. Freedom from physical and thermal (heat) discomfort;

[0107] IV. Freedom from pain, injury, and disease; and

[0108] V. Freedom to express normal patterns of behavior.

[0109] If one of the five freedoms ("welfare parameters") is not met, then the freedom or welfare parameter is considered or has been compromised. For example, if an animal is exposed to heat stress, then the parameter is considered to be compromised. Therefore, in this context, the term "compromised welfare parameter" means that one of the five freedoms is not met for an animal or a group of animals. "Already included" may mean that welfare is included for the animal. The phrases "at least one welfare parameter" and "welfare" are used interchangeably.

[0110] When welfare parameters are compromised, it means the animals are not receiving the level of welfare they should be receiving. Welfare parameters include, but are not limited to, nutritional welfare, physical welfare, behavioral welfare, and environmental welfare. Actions can then be taken to improve the welfare of one or more animals.

[0111] Animal welfare means the physical and mental state of an animal in relation to the conditions in which it lives and dies. An animal experiences good welfare if it is healthy, comfortable, well-nourished, safe, not suffering from unpleasant conditions such as pain, fear and distress (such as heat stress), and is able to perform behaviours that are important to its physical and mental state.

[0112] Some measures of animal welfare involve assessing the extent to which function is impaired in relation to injury, disease and malnutrition. Other measures provide information about the animal's needs and emotional states (such as hunger, pain and fear), often by measuring the intensity of the animal's preferences, motivations and aversions. Others assess the physiological, behavioural and immune changes or effects that animals display in response to various challenges.

[0113] Such measurements can produce standards and indicators that help evaluate how different approaches to managing animals affect their welfare.

[0114] Many aspects of the environment can affect animal welfare. Heat stress risk in cattle is influenced by environmental factors including air temperature, relative humidity, wind speed, animal density (area and volume available per animal), shade availability, animal factors including breed, age, body condition, metabolic rate and stage of lactation, and coat colour and density.

[0115] In a preferred embodiment, compromised welfare is determined as cattle being exposed to heat stress.Heat stress can be defined by the "Temperature Humidity Index (THI)".

[0116] Temperature-Humidity Index (THI)

[0117] The temperature-humidity index (THI) is a single value that expresses the combined effect of air temperature and humidity in relation to the level of heat stress. The index has been developed as a weather safety index to monitor and reduce losses associated with heat stress. Different animal species and humans have different sensitivities to ambient temperature and the amount of moisture in the air. In hot and humid climates, the natural ability of cattle to dissipate the heat load by sweating and rapid breathing is impaired and heat stress occurs. At THI values of 75 to 78, the animal organism is under heat stress, but the thermoregulatory mechanisms still manage to cope, while at THI values above 78, it is assumed that the stress is so high that it is impossible to maintain the thermoregulatory mechanisms or normal body temperature.

[0118] Thus, in one embodiment, heat stress is defined as cattle having been exposed to a THI of 75 or higher, preferably 76 or higher, such as 75-78 or 76-78.

[0119] microRNA (miRNA)

[0120] MicroRNAs (miRNAs) are small, single-stranded, non-coding RNA molecules containing approximately 21 to 23 nucleotides.

[0121] The level of any given miRNA can be measured using techniques known in the art, including but not limited to northern blots, microarray assays, RT-PCR, RNA-SEQ, and miRNA-SEQ. These are standard assays in the art.

[0122] exosomes

[0123] Exosomes are membrane-bound extracellular vesicles (EVs) produced in the endosomal compartment of most eukaryotic cells. Herein, the terms "exosomes," "extracellular vesicles," and "EVs" are used interchangeably.

[0124] Reference Level

[0125] In the context of the present invention, the term "reference level" relates to a standard related to an amount to which other values or characteristics can be compared.

[0126] The reference level can be selected in different ways known to those skilled in the art. In one embodiment, the reference level is the level of one or more miRNAs in a milk sample from a cow with normal welfare or the average level of several cows with normal welfare. Preferably, it is from a dairy cow.

[0127] In another embodiment, the reference level is the level of one or more miRNAs in a milk sample from a (dairy) cow that is not or has not been exposed to heat stress or an average level from several (dairy) cows that have not been exposed to heat stress.

[0128] In one embodiment of the invention, it is possible to determine a reference level by studying the abundance of one or more biomarkers according to the invention in milk samples from (dairy) cows that are considered to have normal welfare (i.e., not subjected to one or more forms of stress discussed herein). By applying different statistical methods, such as multivariate analysis, one or more reference levels can be calculated.

[0129] Based on these results, cut-off values can be obtained that show a relationship between the detected levels and (dairy) cattle considered to be at risk of not having normal welfare. Thus, the cut-off values can be used to determine the amount of one or more biomarkers that corresponds to an increased risk of, for example, cattle not having normal welfare.

[0130] A variety of methods can be used to establish cutoff levels, including: multivariate statistical tests (such as partial least squares discriminant analysis (PLS-DA), random forest, support vector machines, etc.), percentiles, mean plus or minus standard deviation; median; fold change.

[0131] Multivariate discriminant analysis and other risk assessments can be performed on free or commercially available computer statistical software packages (SAS, SPSS, Matlab, R, etc.) or other statistical software packages or screening software known to those skilled in the art.

[0132] It will be apparent to one skilled in the art that, in any of the above embodiments, changing the risk cutoff level can change the results of the discriminant analysis for each sample tested.

[0133] Statistics enables the significance of each biomarker level to be assessed. Common statistical tests applied to data sets include t-tests, f-tests, or even more advanced tests and methods for comparing data. Using such tests or methods, it is possible to determine whether two or more samples are significantly different.

[0134] Significance can be determined by standard statistical methods known to those skilled in the art.

[0135] The reference level selected may vary depending on the particular sample for which the assay is being applied.

[0136] If desired, the selected reference level can be varied to give different specificities or sensitivities as known in the art. Sensitivity and specificity are widely used statistics to describe and quantify how good and reliable a biomarker or diagnostic test is. Sensitivity assesses how good a biomarker or diagnostic test is at detecting a disease or health state, while specificity estimates the likelihood that a tested cattle or group of cattle (i.e., controls, cattle with normal welfare) will be correctly identified as having normal welfare.

[0137] Certain terms are used in conjunction with the description of sensitivity and specificity: true positive (TP), true negative (TN), false negative (FN), and false positive (FP). If impaired welfare is confirmed to be present in cattle with impaired welfare, the test result is considered TP. If impaired welfare is not present in cattle (i.e., controls, without disease), and the test confirms the absence of impaired welfare, the test result is TN. If the test indicates the presence of impaired welfare in cattle without such impaired welfare, the test result is FP. Finally, if the test indicates the absence of impaired welfare in cattle with impaired welfare, the test result is FN.

[0138] Sensitivity

[0139] Sensitivity = TP / (TP+FN) = number of true positive assessments / number of all samples from cattle with compromised welfare.

[0140] As used herein, sensitivity refers to a measure of the proportion of actual positives that are correctly identified - analogous to a diagnostic test, ie, the percentage of cattle with subnormal welfare that are identified as having subnormal welfare.

[0141] Specificity

[0142] Specificity = TN / (TN+FP) = number of true negative assessments / number of all samples from controls.

[0143] As used herein, specificity is a measure of the proportion of negatives that are correctly identified, i.e., the percentage of cattle with normal welfare that are identified as having normal welfare. The relationship between sensitivity and specificity can be assessed using a receiver operating characteristic (ROC) curve. This graphical representation helps determine the best model by determining the optimal threshold or cutoff value for a test or biomarker candidate.

[0144] As will generally be understood by those skilled in the art, screening methods are decision-making processes and therefore the specificity and sensitivity chosen depends on what a given animal manager / farmer / personnel or purchaser of milk from the cow or dairy product in question considers to be the best outcome.

[0145] It will be apparent to one skilled in the art that in most cases it may be advantageous to choose higher sensitivity at the expense of lower specificity in order to identify as many diseased patients as possible.

[0146] In a preferred embodiment, the invention relates to a method with high specificity, such as at least 70%, such as at least 80%, such as at least 90%, such as at least 95%, such as 100%.

[0147] In another preferred embodiment, the present invention relates to a method with high sensitivity, such as at least 80%, such as at least 90%, such as 100%.

[0148] In a preferred embodiment, the compromised welfare is determined to be exposure of cattle to heat stress.

[0149] Methods for assessing welfare parameters of cattle

[0150] As also mentioned above, the present invention relates to miRNA biomarkers obtained by non-invasive techniques, such as extracellular vesicle / exosome-derived microRNAs from milk samples, as indicators of whether welfare parameters have been compromised, such as whether an animal has been exposed to heat stress. Thus, one aspect of the present invention relates to a method for assessing at least one welfare parameter of cattle, preferably bovines, comprising:

[0151] - determining the presence of a gene selected from the group consisting of SEQ ID NO: 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48,

[0153] The level of one or more miRNAs in the group consisting of SEQ ID NO: 94, 123, 112, 84, 111, 31, 87, 55 and 93 or their functional variants, wherein the functional variants are the same as SEQ ID NO: 94, 123, 93, 84, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69,

[0155] 132, 120, 48, 112, 111, 31, 87, and 55 have at least 60% sequence identity;

[0156] - comparing the one or more levels to one or more corresponding reference levels;

[0157] ●Wherein if the SEQ ID NO:94, 85, 52, 74, 83, 6, 113,

[0158] 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55 and 93 or a functional variant thereof above the one or more reference levels indicates that at least one welfare parameter of the cattle is impaired, wherein the functional variant is the same as SEQ ID NO: 94, 123, 93, 84, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 120, 48, 112, 111,

[0160] 31, 87 and 55 have at least 60% sequence identity; and

[0161] ●Wherein if the SEQ ID NO:94, 85, 52, 74, 83, 6, 113,

[0162] 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55 and 93 or a functional variant thereof, which has the same or similar miRNA level as SEQ ID NO: 94, 123, 93, 84, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 120, 48, 112,

[0164] 111, 31, 87, and 55 have at least 60% sequence identity;

[0165] wherein if the level of one or more miRNAs of SEQ ID NO: 2, 81 or 134 or a functional variant is equal to or greater than the one or more reference levels, it indicates that at least one welfare parameter of the cattle is not compromised, wherein the functional variant has at least 60% overall sequence identity to SEQ ID NO: 2, 81 or 134; and

[0166] wherein if the level of one or more miRNAs of SEQ ID NO: 2, 81 or 134 or a functional variant thereof is below the one or more reference levels, it indicates that at least one welfare parameter of the cattle is impaired, wherein the functional variant is different from SEQ ID NO: 2, 81 or 134 or a functional variant thereof

[0167] NO: 2, 81 or 134 has an overall sequence identity of at least 60%.

[0168] Welfare

[0169] The methods of the present invention can be used to assess various well-being parameters. Thus, in one embodiment, at least one impaired well-being parameter is caused by a parameter selected from the group consisting of heat stress, social stress, metabolic stress, disease stress, and combinations thereof, preferably heat stress. For example, in Examples 2 to 4, miRNA biomarkers associated with heat stress have been identified.

[0170] Thus, in a preferred embodiment, the impaired welfare parameter is caused by heat stress.

[0171] ox

[0172] The method of the present invention can be used to evaluate different types of cattle. Thus, in one embodiment, the cattle are dairy cattle. In a related embodiment, the cattle are bovines, such as domestic cattle, more preferably bovine dairy cattle.

[0173] The method of the present invention can be used for a single cow or a group of cows or a herd of cows. Therefore, in one embodiment, the cow is an individual cow (as referred to herein as a "cow") or a group of cows, preferably a group of cows.

[0174] In a related embodiment, the milk sample is from a single cow or a pooled milk sample from a herd of cows.

[0175] As outlined in the Examples section, Applicants have identified a number of biomarkers that can be used regardless of breed. However, in one embodiment, the cattle are of the breeds Brown Swiss and / or Holstein.

[0176] Milk samples

[0177] Different types of milk samples can be used in the method of the present invention. Thus, in one embodiment, the milk sample is in the form of raw milk, skim milk, milk powder, or a food product or food ingredient comprising milk, a milk-containing product (such as infant formula, cheese or yogurt), or is in the form of a food product or food ingredient derived from such a food product.

[0178] If a milk sample is a composite sample from several individual milk samples, it may also be considered "bulk milk".

[0179] In one embodiment, the level of miRNA is the level of miRNA in milk-derived exosomes. In Examples 2 to 4, the level of miRNA has been determined from milk-derived exosomes.

[0180] In a preferred embodiment, the miRNA is derived from milk-derived exosomes expressing CD9 and / or TSG101.

[0181] Biomarkers

[0182] As shown in Example 4, different individual biomarkers have been identified that can be used for hybrids. To improve the overall robustness of the method, it may be advantageous to use more than one biomarker. Thus, in one embodiment, the method is performed for at least 5 miRNAs, such as at least 10 miRNAs, preferably at least 15 miRNAs, more preferably at least 20 miRNAs, and most preferably for all 24 biomarkers.

[0183] Based on the pathways involved, it may also be advantageous to include at least some of the listed biomarkers in the method. As summarized in Table 3 in Example 4, the identified miRNAs were also found to be involved in different pathways. In one embodiment, the method includes determining the levels of miRNAs that regulate the cell cycle. In an alternative embodiment, it may be advantageous to include miRNAs that are combined and participate in two or more, such as three or more, preferably such as four or more or more preferably all pathways selected from the group consisting of cell cycle / cell cycle arrest, fatty acid synthesis, pain and stress, insulin signaling and reproduction. In a preferred embodiment, the miRNA is at least involved in regulating the cell cycle, or regulating the cell cycle, more preferably cell cycle arrest.

[0184] The cell cycle is the series of events that occur in a cell as it grows and divides into two genetically identical daughter cells. It is a highly regulated process that consists of several phases:

[0185] G1: Metabolic changes prepare the cell for division; the cell physically grows larger.

[0186] And the organelles are replicated.

[0187] ●S phase: DNA is replicated.

[0188] G2 phase: The cell grows more, makes proteins and organelles, and begins to reorganize its contents in preparation for mitosis.

[0189] M phase: The cell's nuclear DNA condenses into visible chromosomes and is pulled apart by the mitotic spindle (a specialized structure composed of microtubules). Mitosis occurs in five phases: prophase, prometaphase, metaphase, anaphase, and telophase.

[0190] ●Cytokinesis: The cytoplasm divides into two, producing two separate cells.

[0191] Cyclins and cyclin-dependent kinases (CDKs) are regulatory molecules that determine how cells progress through the cell cycle. When activated by bound cyclins, CDKs phosphorylate target proteins to activate or inactivate them, leading to coordinated progression through the cell cycle.

[0192] As used herein, "regulate" or "regulation" of the cell cycle refers to the mechanism that controls the orderly progression of the cell cycle. Positive regulation of the cell cycle drives its progression, while negative regulation of the cell cycle slows its progression or arrests the cell cycle.

[0193] Cell cycle arrest refers to the temporary or permanent halt of the cell cycle, preventing cells from progressing through the normal stages of cell division.

[0194] miRNAs can act as either positive or negative regulators of cell cycle progression. When miRNAs target and downregulate genes encoding cell cycle proteins, they can inhibit cell cycle progression and promote cell cycle arrest. Conversely, when miRNAs target genes encoding proteins that inhibit the cell cycle, they can promote cell cycle progression and proliferation. This delicate balance of miRNA-mediated regulation is important for normal cell growth.

[0195] Cell cycle can be measured using a variety of commercially available assays. For example, DNA content distribution can be measured using DyeCycle dyes and analyzed by flow cytometry. Alternatively, antibodies for cell cycle analysis are also available, which can be analyzed using flow cytometry or imaging.

[0196] In one embodiment, the one or more miRNAs are selected from the group listed in Table 3. Regulation is as indicated in Tables 1 to 2 and the corresponding text.

[0197] In another embodiment, the one or more miRNAs are selected from the group listed in Table 1, with the proviso that the cattle is a Swiss Brown cattle. Regulation is as indicated in Table 1 and the corresponding text.

[0198] In yet another embodiment, the one or more miRNAs are selected from the group listed in Table 2, with the proviso that the cattle is a Holstein cattle. Modulation is as indicated in Table 2 and the corresponding text.

[0199] The levels of miRNA can be determined using methods known to those skilled in the art. Thus, in one embodiment, the levels are determined by a method selected from the group consisting of NGS, qPCR, dPCR and ELISA miRNA.

[0200] Identify improvements

[0201] By comparing different samples obtained at different time points (minutes or hours), it is possible to assess whether any improvement in animal welfare has occurred. Thus, one aspect of the present invention relates to a method for assessing whether at least one welfare parameter of cattle has improved, the method comprising:

[0202] - determining a first milk sample from said cow selected from the group consisting of SEQ ID NO: 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48,

[0204] The level of one or more miRNAs in the group consisting of SEQ ID NO: 94, 123, 112, 84, 111, 31, 87, 55 and 93 or their functional variants, wherein the functional variants are the same as SEQ ID NO: 94, 123, 93, 84, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69,

[0206] 132, 120, 48, 112, 111, 31, 87, and 55 have at least 60% sequence identity;

[0207] - determining a second milk sample from said cow selected from the group consisting of SEQ ID NO: 94, 2, 81,

[0208] 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55 and 93 or their functional variants, wherein the functional variants are the same as SEQ ID NO: 94, 123, 93, 84, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69,

[0209] 132, 120, 48, 112, 111, 31, 87 and 55 have at least 60% sequence identity; wherein the second milk sample is obtained later in time than the first milk sample;

[0210] - comparing the one or more levels in the first sample to one or more levels in the second sample

[0211] Compare corresponding levels;

[0212] ● If the second sample has SEQ ID NO: 94, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111,

[0214] If one or more corresponding levels of SEQ ID NO: 31, 87, 55 and 93 or their functional variants are equal to or higher than the level in the first sample, it indicates that the welfare parameter has not been improved, wherein the functional variants correspond to SEQ ID NO: 94, 123, 93, 84, 85, 52, 74,

[0215] 83, 6, 113, 70, 1, 69, 132, 120, 48, 112, 111, 31, 87, and 55 have at least 60% sequence identity; and

[0216] ● If the second sample has SEQ ID NO: 94, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111,

[0218] 31, 87, 55 and 93 or their functional variants are lower than the level in the first sample, indicating that the welfare parameter has improved, wherein the functional variants are the same as SEQ ID NO: 94, 123, 93, 84, 85, 52, 74, 83, 6,

[0219] 113, 70, 1, 69, 132, 120, 48, 112, 111, 31, 87, and 55 have at least 60% sequence identity;

[0220] wherein if one or more corresponding levels of SEQ ID NO: 2, 81 or 134 or a functional variant thereof in the second sample are equal to or lower than the level in the first sample, it indicates that the welfare parameter of the cattle has not improved, wherein the functional variant has at least 60% overall sequence identity to SEQ ID NO: 2, 81 or 134; and

[0221] ●Wherein if one or more corresponding levels of SEQ ID NO:2, 81 or 134 or a functional variant thereof in the second sample are higher than the level in the first sample, it indicates that the welfare parameters of the cattle have improved, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO:2, 81 or 124.

[0222] In one embodiment, proactive measures are taken between the taking of the first sample and the taking of the second sample to improve one or more welfare parameters of the cattle.

[0223] In yet another embodiment, the welfare parameter is heat stress.

[0224] Heat stress occurs when body temperature rises above normal due to an inability to effectively dissipate heat. This can occur when ambient temperature is high, air movement is low, or humidity is high. Cattle rely on a variety of mechanisms to regulate their body temperature, including rapid breathing, sweating, and behavioral changes. Signs and symptoms of heat stress in cattle include, but are not limited to, increased respiratory rate, increased salivation, loss of appetite, decreased milk production, and increased susceptibility to illness.

[0225] Table 1: Common parameters for determining heat stress :

[0226]

[0227] In yet another embodiment, the proactive measures are selected from the group consisting of: changes in heat exposure, such as a reduction in temperature; installation of fans; possibilities for shelter; installation of sprinklers; improved access to additional water; changes in feed; reduction in animal density; provision of cooling systems appropriate to local conditions; changes in cattle movement; and a less stressful environment.

[0228] In some embodiments, there is a method of improving at least one of milk yield, milk quality, meat yield, meat quality from at least one cow, the method comprising

[0229] i. Determine the first milk sample from at least one cow as SEQ ID NO: 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120,

[0231] The level of at least one miRNA as defined in SEQ ID NO: 48, 112, 84, 111, 31, 87, 55, 93 or a functional variant thereof, wherein the functional variant is the same as SEQ ID NO: 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120,

[0233] 48, 112, 84, 111, 31, 87, 55, or 93 having at least 60% overall sequence identity;

[0234] ii. comparing the level of the at least one miRNA to a reference level; wherein the welfare of the at least one cow is impaired when the level of the at least one miRNA is above the reference;

[0235] iii. improving the welfare of the at least one cattle;

[0236] iv. Determine the second milk sample from the same at least one cow as SEQ ID NO: 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120,

[0238] The level of at least one miRNA as defined in SEQ ID NO: 48, 112, 84, 111, 31, 87, 55, 93 or a functional variant thereof, wherein the functional variant is the same as SEQ ID NO: 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120,

[0240] 48, 112, 84, 111, 31, 87, 55, or 93 have at least 60% overall sequence identity; and

[0241] v. comparing the level in the first milk sample to the level in the second milk sample, wherein if the level of SEQ ID NO: 94, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31,

[0243] If the level of SEQ ID NO: 87, 55 or 93 or its functional variant in the second milk sample is lower than the level in the first milk sample or lower than the reference level, the welfare of the cow from at least one of the milk production, milk quality, meat production and meat quality has been improved, wherein the functional variant has at least 60% overall sequence identity with the non-variant sequence, and / or if the level of SEQ ID NO: 2, 81 or 134 or its functional variant in the second milk sample is higher than the level in the first milk sample or higher than the reference level, the welfare of the cow from at least one of the milk production, milk quality, meat production and meat quality has been improved, wherein the functional variant has at least 60% overall sequence identity with the non-variant sequence.

[0244] Milk yield refers to the amount of milk an animal produces in a given period of time. Improving milk yield means increasing the amount of milk produced in a given period of time.

[0245] Meat yield refers to the amount of meat that can be obtained from an animal after slaughter. Meat yield is usually expressed as a percentage of the animal's live weight or carcass weight.

[0246] Milk quality is a concept that encompasses multiple factors, such as sensory quality, composition, and bacterial safety. High-quality milk is a rich source of protein, fat, calcium, and other nutrients, such as branched-chain fatty acids (BCA). High-quality milk is also free of contaminants, has a low bacterial count, and is a rich, creamy white color with a clean, fresh smell and a mild taste.

[0247] Meat quality is a complex concept encompassing many factors, including:

[0248] - Appearance: High quality meat has a bright, attractive color, a uniform texture and no signs of discoloration.

[0249] - Texture: High-quality meat is tender and easy to chew, while low-quality meat is chewy and / or tough.

[0250] -Flavor: High-quality meat has a richer and more complex flavor than lower-quality meat.

[0251] use

[0252] Yet another aspect of the present invention relates to the use of the levels of one or more miRNAs selected from the group consisting of SEQ ID NO: 94, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55 and 93 in a bovine milk sample for assessing the status of welfare parameters in cattle.

[0253] In one embodiment, the welfare parameter is heat stress.

[0254] Device

[0255] The method of the present invention may also be implemented in a device or system. Therefore, a further aspect of the present invention relates to a device or system suitable for determining whether at least one welfare parameter of a cow, preferably a bovine, has been compromised in a milk sample or a milk-derived sample, the device comprising:

[0256] - a unit capable of determining the level of one or more miRNAs in a milk sample or a milk-derived sample;

[0257] - a processor configured with a reference table corresponding to reference levels of one or more miRNAs according to Table 4;

[0258] wherein the device or system is suitable for

[0259] - receiving said milk sample or milk-derived sample;

[0260] - determining the level of said one or more miRNAs;

[0261] - comparing the determined levels of said one or more miRNAs with said reference table;

[0262] as well as

[0263] - determining whether at least one welfare parameter of said cattle has been compromised.

[0264] In one embodiment, the reference table comprises corresponding miRNA values from cattle, wherein the corresponding welfare parameter has not been compromised.

[0265] In another embodiment, the device or system comprises a user interface adapted to receive input from a user regarding one or more of the miRNA being tested, the species from which the milk sample is derived, and the type of milk sample.

[0266] Computer-implemented methods

[0267] The method of the present invention may also be computer-implemented. Thus, another aspect of the present invention relates to a computer-implemented method for determining whether at least one welfare parameter of a cow (preferably a bovine) has been compromised in a milk sample or a milk-derived sample, the method comprising:

[0268] - providing the level of one or more miRNAs from a bovine milk sample or a milk-derived sample selected from Table 4;

[0269] - providing a mathematical model comprising reference levels of one or more corresponding miRNAs selected from Table 4;

[0270] - using the mathematical model to determine whether the provided level deviates (significantly) from the reference level; and

[0271] - providing a determination to the system or user as to whether at least one welfare parameter of the cattle has been compromised.

[0272] In one embodiment, the reference table comprises corresponding miRNA values from cattle, wherein the corresponding welfare parameter has not been compromised.

[0273] Yet another aspect of the invention relates to a computer system comprising an input / output device and a processor, the system being capable of executing the computer-implemented method according to the invention on the processor.

[0274] It should be noted that embodiments and features described in the context of one aspect of the invention may also apply to the other aspects of the invention.

[0275] All patent and non-patent references cited in this application are hereby incorporated by reference in their entirety.

[0276] The present invention will now be described in further detail in the following non-limiting examples.

[0277] Example

[0278] Example 1 - Physiological changes in biological samples from two breeds of dairy cows under thermal comfort conditions and heat stress Characterization of parameters, oxidative and inflammatory markers .

[0279] Study Objectives

[0280] To investigate changes in physiological parameters, oxidative and inflammatory markers in biological samples of Holstein (H) and / or Brown Swiss (BS) cows under thermal comfort conditions and during heat stress.

[0281] Materials and methods

[0282] Ethics Statement:

[0283] The trials, to be conducted by the University of Milan during the summer of 2021, have been approved by the Ethical Committee for Animal Experimentation of the Faculty of Veterinary Medicine of the University of Bari.

[0284] Experimental conditions:

[0285] The experimental design of the study is shown in Figure 1 In vivo experiments were conducted in Apulia during the summer of 2021 to investigate the adaptive responses of H and BS under farm conditions. Each group included 18 prolific mid-lactation H and 18 BS, balanced for parity and days in milk (DIM - between 80 and 160 DIM), and were housed on the same commercial farm.

[0286] Environmental conditions were monitored using specialized equipment to measure the temperature-humidity index. A time-lapse video recording system was set up to provide a collection of images throughout the trial to assess all feeding, resting, and other major activity and behavior patterns. The lactating cows were housed in stalls equipped with fan coolers and automatic sprinklers in the feeding area and roof fans in the stall resting areas.

[0287] During the warmest weeks of summer 2021, the cooling system was shut down for four consecutive days and then restarted. Throughout the test period, ambient temperature and relative humidity were recorded every 30 seconds using a Hobo Pro series temperature probe (Onset Computer Corp., Pocasset, MA, USA) to calculate the Temperature-Humidity Index (THI). The Temperature-Humidity Index ranged from 68 to 86.

[0288] During the experimental period, the cows were fed a standard total mixed ration. All physiological patterns were recorded daily and biological samples were collected during the heat stress days (four days and then another four days after three days of cooling).

[0289] Physiological parameters:

[0290] All physiological data were collected at 4.00am, 3.00pm and 9pm on each of the four days of the experiment (Day 1 to Day 4).

[0291] Respiratory rate measurements were performed visually by an expert who observed the animal's chest movements for 20 seconds. The measurements were then multiplied by 3 to quantify the number of breaths per minute (bpm).

[0292] Rectal temperature was measured by a digital rectal thermometer. Images of eye, nose, mouth, skin, and vaginal temperature were collected using a portable infrared thermal imaging camera (ThermaCam i700, FLIR Systems AB, Danderyd, Sweden). To calibrate the camera results, a digital thermometer ( 44550) to record ambient temperature and relative humidity. To determine temperature, image analysis software ThermaCam Researcher Pro 2.8SR-2 (FLIR Systems AB, Sweden) was used to measure the maximum temperature within an elliptical area drawn around the anatomical site. This maximum temperature was included in the analysis. Two images were collected for each measurement, and the average of the two images was used for analysis.

[0293] Milk production was recorded and milk samples were taken during morning and evening milking (at 4:00 am and 5:00 pm). 100 ml of milk was sampled from each cow and supplemented with 2% 2-bromo-2-nitro-1,2-propanediol as a preservative, refrigerated at 4°C, transferred to the laboratory, and analyzed within 2 hours for fat, protein, lactose, dry matter, urea, and BHB using near-infrared spectroscopy (ISO 9622:2013 (IDF 141:2013)).

[0294] From these data, the FCM production recorded on each test day (normalized to 4% fat) was calculated according to the following formula (Gaines, WL; Davidson, 1923):

[0295] 4% FCM = 0.4 x milk + 15 x fat

[0296] In addition, energy-corrected milk (ECM) yield was calculated according to the reported formula (Yan et al., 2011):

[0297] ECM = milk × [0.25 + (0.122 × fat %) + (0.077 × protein %)]

[0298] Blood sampling and analysis:

[0299] Blood samples were collected from each cow at 4:00 am, 3:00 pm, and 9:00 pm from day 1 to day 4. Blood was drawn from the tail vein in sterile Vacutainer tubes (Becton Dickinson and Co.) 4 with lithium-heparin and clot activator tubes. All tubes were centrifuged on the farm, and serum and plasma were immediately stored at -20°C until analysis.

[0300] Clinical biochemistry parameters were obtained from serum samples using an automated biochemical analyzer (CS-300B; Dirui, Changchun, China). The following parameters were assessed: alanine aminotransferase, aspartate aminotransferase, creatine phosphokinase, lactate dehydrogenase, alkaline phosphatase, glucose, blood urea nitrogen, creatinine, total serum protein, albumin, cholesterol, triglycerides, non-esterified fatty acids, calcium, phosphate, magnesium, and chloride (Gesan Production Kit, Campobello di Mazara, Trapani, Italy). Globulin and albumin / globulin ratio were calculated from total protein and albumin parameters. The multiparameter analyzer was calibrated using specific standards (Seracal, Gesan Production Kit, Campobello di Mazara, Trapani, Italy). After setting the calibration curve, two multiparameter control sera (Seracontrol N and Seracontrol P, Gesan Production Kit, Campobello di Mazara, Trapani, Italy) were used to verify the internal accuracy, which was less than 3.00%, in line with the manufacturer's declared value. Each sample was analyzed in triplicate, and their average value was used for further analysis.

[0301] Plasma oxidation profile and total antioxidant capacity:

[0302] Plasma (0.5 ml) was placed in a 50 mL test tube and homogenized with 15 mL of deionized distilled water (DDW). The homogenate (1 mL) was transferred to a glass tube for thiobarbituric acid reactive substances (TBARS) assay, and 0.05 mL of butylated hydroxytoluene (7.2% in ethanol) and 1.950 mL of thiobarbituric acid (TBA) / trichloroacetic acid (TCA) / HCl (0.375% TBA, 15% TCA, and 0.25 N HCl) were added. The sample solution was shaken and then incubated at 90° C. in a thermostatic bath for 15 minutes. The sample was cooled to room temperature (15° C.-30° C.) and then centrifuged at 2000 × g for 15 minutes. The absorbance of the supernatant (λ) was measured. 531nm ); the negative control solution was TBA / TCA / HCl (2 ml + 1 ml DDW). TBARS was calculated using a standard curve designed with 1,1,3,3-tetramethoxypropane, and the concentration of lipid oxidation was expressed as mg of malondialdehyde per 1 ml of plasma.

[0303] For hydroperoxides, 4 mL of CH3OH and 2 mL of CHCl3 were added to 0.5 mL of plasma. The sample was vortexed for 30 seconds, 2 mL of CHCl3 and 1.6 mL of 0.9% NaCl were added, vortexed for 1 minute, and then centrifuged at 3500 × g for 10 minutes at 4°C. Two milliliters of lipid extract were sampled from the lower chloroform phase and then treated with 1 mL of CH3COOH / CHCl3 and 50 μL of KI (1.2 g / L mL distilled water). The sample was stored in a dark room for 5 minutes, 3 mL of 0.5% CH3COOCd was added, vortexed, and centrifuged at 4500 × g for 10 minutes at 40°C. Absorbance (λ 353nm ) are measured relative to a blank tube in which the plasma was replaced by 2 mL of distilled water. Results are expressed in μmol / mL.

[0304] Plasma (0.5 ml) was placed in 20 mL of 0.15 M KCl for 2 minutes. 1 mL of 10% TCA was added to two equal portions of homogenate (50 μL each) and then centrifuged at 1200 × g for 3 minutes at 4 ° C to measure protein oxidation. The first aliquot was used as a standard and 1 mL of 2M HCl solution was added. 1 mL of 2M HCl containing 10 mM 2,4-dinitrophenylhydrazine (DNPH) was added to the second aliquot. The sample was incubated at room temperature (15 ° C to 30 ° C) for 1 hour and vortexed every 20 minutes. Then, 1 mL of 10% TCA was added. The sample was vortexed for 30 seconds and centrifuged at 1200 × g for 3 minutes at 4 ° C, and the supernatant was removed. The precipitation was 1 mL of ethanol: ethyl acetate (1: 1), shaken, and centrifuged at 1200 × g for 3 minutes at 4 ° C, and the supernatant was removed. The precipitate was then dissolved in 1 mL of 20 mM sodium phosphate 6 M guanidine hydrochloride buffer. The sample was then shaken and centrifuged at 1200 × g for 3 minutes at 4°C. The carbonyl concentration of the DNPH-treated samples was calculated at 360 nm using a Beckman Coulter DU800 (Beckman Instruments Inc., Brea, CA, USA) and expressed as nanomoles carbonyls / mg protein. Protein concentration was calculated according to the biuret assay.

[0305] The total antioxidant capacity (FRAP) assay was used to measure the total antioxidant potential as described (Benzie and Strain, 1996) with minor modifications. Three milliliters of freshly prepared FRAP reagent (1 mL of 10 mM TPTZ solution in 40 mM HCl plus 1 mL of 20 mM FeCl3 in 10 mL of H2O solution and 10 mL of 300 mM acetate buffer, pH 3.6) were incubated at 37°C for 40 minutes after mixing with 100 μL of plasma sample or supernatant. The absorbance of the reaction mixture was recorded (λ734593 nm), and the antioxidant capacity was expressed as μmol Trolox equivalents / ml. 2,2'-Azino-bis[3-ethylbenzothiazoline-6-sulfonic acid] (ABTS) radical scavenging activity was determined according to a previously described procedure (Re et al., 1999) with some modifications. Briefly, ABTS radical cations were generated by mixing 7 mM ABTS stock solution with 2.45 mM potassium persulfate and keeping the mixture at 25°C in the dark for 12 to 16 hours. The solution was then diluted in PBS to achieve an absorbance value of 0.70 ± 0.02 at 734 nm. 10 μL of plasma sample was then added to 990 μL of the diluted ABTS radical cation solution and incubated at 30°C for 5 minutes. A reagent blank was prepared by adding 10 μL of PBS instead of the sample. The scavenging of ABTS radical cations was measured spectrophotometrically (λ 734nm ) determination.

[0306] The antioxidant activity was expressed as the percentage inhibition of ABTS radical cation and calculated by the following equation:

[0307] Inhibition % = 100 x (absorbance 734 control - absorbance 734 sample) / absorbance 734 control.

[0308] Each sample was analyzed in triplicate.

[0309] Statistical analysis:

[0310] Statistical analyses were performed in SAS v.9.4 (SAS Institute, Cary, NC, USA, 2011). Shapiro-Wilk tests of the collected data revealed no deviation from normality for all stress variables used (results not shown), so parametric statistics were used. Continuous data (i.e., physiological and milk parameters) were analyzed using generalized linear mixed models with PROC MIXED as fixed effects for breed, time (day or time of day as repeated measures), and their interactions. Blood parameters were analyzed using generalized linear mixed models with PROC MIXED as fixed effects for breed, time (considering only the first blood sampling as the thermal comfort condition and the last blood sampling as the heat stress condition), and their interactions. Significance was set at P < 0.05.

[0311] result

[0312] 1. Physiological Parameters. Both breeds (H and BS) showed similar trends during the experimental trial. Cows exhibited higher rectal temperature, respiratory rate, and vaginal and skin temperature values, with these values increasing during the daytime in line with higher THI values and decreasing during the nighttime when THI values were at their lowest (data not shown).

[0313] 2. Milk yield, fat-corrected milk and energy-corrected milk were negatively affected by heat stress (data not shown).

[0314] 3. Fat percentage, protein concentration and casein were affected by heat stress (data not shown).

[0315] 4. Serum protein profiles showed differences due to heat stress. Total protein was higher in both breeds. Furthermore, blood urea nitrogen (BUN) and uric acid were affected by both heat stress and breed. Specifically, BUN increased after heat stress, while uric acid decreased in both breeds (data not shown).

[0316] 5. Electrolyte serum profiles were partially affected by heat stress; chloride concentration in H increased, phosphorus concentration increased, and the amount of magnesium decreased after heat stress (data not shown).

[0317] 6. Serum lipid profiles were affected by heat stress. Cholesterol was lower in H, but heat stress did not affect its levels. Triglycerides decreased after heat stress in both breeds, resulting in similar values. Unesterified fatty acids were higher in BS compared to H under thermal comfort conditions but decreased after heat stress to similar values (data not shown).

[0318] 7. Heat stress and breed did not affect serum enzyme profiles (data not shown).

[0319] 8. After heat stress, heat shock protein 70 increased in both strains. Similarly, serum amyloid decreased with heat stress; haptoglobin decreased in H and increased in BS after heat stress (data not shown).

[0320] 9. Oxidative profiles were affected by variety and heat stress. In BS, thiobarbituric acid reactive substances decreased after heat stress and increased in H, showing opposite trends.

[0321] However, hydroperoxides and protein carbonyl compounds increased only in BS (data not shown).

[0322] in conclusion

[0323] The physiological parameters studied confirmed that both breeds of cows suffered from heat stress and dissipated heat similarly. Quantitative and qualitative milk parameters were affected by heat stress.

[0324] Example 2 - Use of the next generation in milk from two breeds of cows under thermal comfort conditions and heat stress Analysis of miRNA profiles of milk-derived exosomes by sequencing

[0325] Study Objectives

[0326] To investigate the milk microRNA profiles in exosomes derived from single animal milk collected from Holstein (H) and Brown Swiss (BS) cows under thermal comfort conditions and during heat stress.

[0327] Materials and methods

[0328] Experimental conditions and milk sample collection:

[0329] See Example 1.

[0330] Extracellular vesicle (exosome) isolation:

[0331] Extracellular vesicles (EVs) were purified from 10 ml of milk by ultracentrifugation and size exclusion chromatography (SEC). Skim milk was centrifuged at 10,000 g for 30 minutes at 4 ° C to remove residual fat and cell debris. The supernatant was transferred to an ultracentrifuge tube and ultracentrifuged at 100,000 g for 1 hour at 4 ° C using a fixed rotor (Beckman Coulter TY65 fixed angle rotor, Pasadena, USA). The exosome pellet was carefully collected on top of the casein pellet and deposited in a 2 mL tube without disturbing it. The collected exosomes were resuspended and further purified by SEC using a qEVoriginal 35 nm column (Izon) according to the manufacturer's instructions. After the void volume (3 mL), 4 fractions of 500 μL each were collected. Fractions 2 and 3, which were expected to contain exosomes, were combined. Column equilibration and fraction elution were performed using sterile triple-filtered (0.22 μm) ammonium bicarbonate buffer 20 mM pH 7.5.

[0332] Exosome characterization:

[0333] 1. Nanoparticle Tracking Analysis

[0334] EV size and concentration were assessed immediately after filtration using a NanoSight NS300 (Malvern Panalytical). Purified exosomes were diluted 50-fold or 100-fold using fresh, triple-filtered PBS (0.22 μm). Particles were visualized and analyzed using NTA 3.3 Dev Build 3.3.301 software. The instrument was set to operate at 22°C with a syringe pump speed of 30 AU, and for each sample, five videos of 60 seconds each were recorded; the results are the average of five measurements.

[0335] 2. Transmission electron microscopy (TEM)

[0336] To assess morphology, exosomes were visualized by TEM using negative staining. A few microliters of sample were adsorbed onto glow-discharged carbon-coated polyvinyl acetate (Formvar) copper grids, contrasted with 2% uranyl acetate, air-dried, and observed in a FETalos 120 kV transmission electron microscope (FEI Company, Netherlands). Images of the exosomes were acquired using a 4k×4k Ceta CMOS camera.

[0337] 3. Western blot analysis

[0338] Milk exosome protein concentration was determined by Pierce bicinchoninic acid (BCA) protein assay kit (ThermoScientific, Illinois, USA). Exosome protein (2 μg) was loaded onto sodium dodecyl sulfate-polyacrylamide electrophoresis (SDS-PAGE) gel and Western blotted onto nitrocellulose membrane using Trans-Blot Turbo Midi 0.2 μm nitrocellulose transfer kit (Bio-Rad Laboratories, California, USA) and Trans-Blot Turbo transfer system (Bio-Rad Laboratories). The membrane was blocked with Block 1X (Carlroth, catalog number A151.1) for 1 hour, incubated overnight at 4°C with a primary antibody anti-CD9 (Biorad, MCA469GT, 1:1500), and then incubated at room temperature for 1 hour with a secondary antibody polyclonal anti-mouse peroxidase (Dako, P0260, 1:2000); or incubated overnight at 4°C with a primary antibody anti-TSG101 (Abcam, ab225877, 1:2000), and incubated at room temperature for 1 hour with a secondary antibody polyclonal anti-rabbit peroxidase (Vector, PI-1000, 1:3000). Immunoreactive bands were visualized by enhanced chemiluminescence (Millipore, catalog number WBKLS0050).

[0339] EV miRNA extraction and sequencing:

[0340] Small RNA was extracted using the MicroRNA Concentrator Kit (A&A Biotechnology, catalog number 035-25) following the manufacturer's instructions. After SEC, only EVs were eluted in the second and third fractions. RNA quality and quantity were verified according to the MIQE guidelines (Bustin et al., 2009). For all samples, the ELISA kit was used. MicroRNA Assay Kit (Invitrogen, catalog number Q32880) RNA concentration was quantified using a 2.0 fluorometer. Small RNA transcripts were converted into barcoded cDNA libraries. As previously reported (Pardini et al., 2018), libraries were prepared using Illumina's NEBNext Multiple Small RNA Library Preparation Set (Cat. No. NEB#E7560) and run on a NextSeq500 (Illumina Inc., USA). Samples from H and BS were loaded and mixed on a flow cell to balance thermal comfort conditions and heat stress.

[0341] The output of the NextSeq500 Illumina sequencer was demultiplexed using the bcl2fastq Illumina software embedded in the docker4seq package (Cordero et al., 2012) (Pardini et al., 2018). MiRNA expression quantification was performed using a previously described workflow (Pardini et al., 2018) and the described protocol (Beccuti et al., 2018). Sequences were mapped to the bovine precursor miRNAs available in miRBase 22.1 (http: / / www.mirbase.org / ) using SHRIMP (Rumble et al., 2009). Differential expression (DE) analysis was performed using count tables, using an adjusted P value ≤ 0.1 and an absolute log2 fold change (log2FC) ≥ 1 as thresholds. CPM (counts per million reads) tables were used for heatmap generation and PCA (data not shown).

[0342] miRNA target prioritization:

[0343] MiRWalk 3.0 (Sticht et al., 2018) was used to predict the target genes of DE-miRNAs, which includes three miRNA target prediction programs (miRDB (Wong and Wang, 2015), miRTarBase (Hsu et al., 2011), and Targetscan (Agarwal et al., 2015)). The analysis targeted the entire gene sequence (5'UTR, CDS, and 3'UTR). The target gene lists predicted by the three tools were included in further analysis. Functional mRNA enrichment was performed using the DAVID (Database for Annotation, Visualization, and Integrated Discovery) bioinformatics resource (Huang et al., 2009a, 2009b), and enrichment of biological pathways in KEGG (Kyoto Encyclopedia of Genes and Genomes) (Kanehisa et al., 2012) was examined.

[0344] Statistical analysis:

[0345] Statistical analyses were performed using XLStat for Windows (Addinsoft, New York, USA), IBM SPSS Statistics 25 software (IBM Corp., 2017), and MedCalc 14.0 (MedCalc Software bvba, Ostend, Belgium). Differential expression (DE) analysis was performed using DESeq2 (Ferrero et al., 2018) implemented in docker4seq. DE analysis was performed using paired samples (i.e., day 1 and day 4 of the same animal). Statistical significance was accepted at p < 0.05. P values were adjusted using the Bonferroni correction.

[0346] Hierarchical clustering (Euclidean distance, average linkage, gene-only clustering, after Z-score transformation of log2CPM) was performed to identify heat stress-specific signatures. Using log2CPM data, principal component analysis (PCA) was performed using the cluster analysis R package.

[0347] result

[0348] Extracellular vesicle characterization

[0349] EVs from milk of thermally comfortable and heat-stressed cows (six animals, three H and three BS) were isolated by ultracentrifugation and size exclusion chromatography. The particle size distribution was assessed by nanoparticle tracking analysis (NTA), revealing that the EV population was characterized by small vesicles. The modal means of the six cows were 136.15 nm ± 23.74 nm and 139.6 nm ± 22.7 nm, and the concentrations were 4.56E+11 and 1.5E+11 under thermal comfort and heat stress, respectively.

[0350] Under thermal comfort conditions and heat stress, the modal means of EVs under thermal comfort conditions and heat stress were 131.53 nm ± 26.95 nm and 134.95 nm ± 33.17 nm for H, respectively, and 140.8 nm ± 24.87 nm and 144.2 nm ± 11.1 nm for BS, respectively. The concentrations of isolated EVs under thermal comfort conditions and heat stress were 6.92E+11 particles / ml and 1.03E+11 particles / ml for H, respectively, and 2.15E+11 particles / ml and 1.98E+11 particles / ml for BS, respectively. No statistical differences were identified in size or concentration.

[0351] The shape and integrity of EVs were assessed by transmission electron microscopy, which revealed the presence of intact, undamaged small EVs. Western blot analysis was performed to examine the expression of different exosomal markers in exosomes derived from milk of thermally comfortable and heat-stressed cows. Two different exosomal markers were identified: one expressed on the exosome membrane, the tetraspanin CD9, and the other delivered within the lumen of EVs, TSG101.

[0352] Identification of miRNAs using bovine precursor mapping

[0353] After RNA extraction, small RNA was sequenced on a NextSeq500 sequencer (Illumina). Many reads were obtained for each sample, ranging from 2,053,467 (sample h16d1) to 130,228,352 (sample h2978d4). The miRNA precursors (miRbase 22) were mapped and miRNA quantified using the miRNA pipeline implemented in docker4seq, and quality control was performed using MultiQC. Relatively low mapping was expected because small RNA was extracted from milk EVs.

[0354] in conclusion

[0355] This analysis revealed the expression of 1998 and 1882 miRNAs in milk EVs from H and BS cattle, respectively, excluding lowly expressed miRNAs (baseline mean ≤ 1).

[0356] Example 3 - Identification of miRNAs differentially expressed in milk from two breeds of heat-stressed cows

[0357] Study Objectives :

[0358] To investigate differentially expressed microRNAs in milk from Holstein (H) and Brown Swiss (BS) cows under thermal comfort conditions and during heat stress.

[0359] Materials and methods

[0360] The experimental conditions and the collection of milk samples are described in Example 1. For differential expression analysis (DE), the results of 1998 and 1882 bovine miRNAs disclosed in Example 2 were used.

[0361] Differential expression analysis between miRNAs in milk from dairy cows under thermal comfort conditions and under heat stress:

[0362] Differential expression (DE) analysis was performed using DESeq2 implemented in docker4seq. DE analysis was performed using paired samples (i.e., day 1 and day 4 of the same animal), and the results are provided in the NGS overview. Hierarchical clustering (Euclidean distance, average linkage, gene-only clustering, log2 CPM Z-score transformation) was performed to identify heat stress-specific signatures.

[0363] result

[0364] Swiss Brown Cattle:

[0365] To determine the differences in exosomal miRNA expression profiles between thermally comfortable and heat-stressed milk, differential expression (DE) analysis was performed using DESeq2 with a threshold-adjusted P value < 0.1 and |log2FC| > 1. Differences in miRNA profiles were observed, suggesting molecular changes due to heat stress.

[0366] Comparing milk-exosome profiles in thermal comfort conditions and heat stress, 132 miRNAs were significantly altered. The levels of 80 miRNAs increased after heat stress (1 to 2.44 log2 FC), and the levels of 52 miRNAs decreased after heat stress (-1 to -1.64 log2 FC) (Table 2).

[0367] Table 2: 132 milk-derived miRNAs identified as significantly dysregulated in Swiss Brown cattle under heat stress .

[0368]

[0369]

[0370]

[0371]

[0372] Holstein cattle:

[0373] To determine the differences in exosomal miRNA expression profiles between thermally comfortable and heat-stressed milk, differential expression (DE) analysis was performed using DESeq2 with a threshold-adjusted P value < 0.1 and |log2FC| > 1. Differences in miRNA profiles were observed, suggesting molecular changes due to heat stress.

[0374] Comparing milk-exosome profiles in thermal comfort conditions and heat stress, 32 miRNAs were significantly altered. The levels of 25 miRNAs increased after heat stress (1 to 2.24 log2 FC), and the levels of 7 miRNAs decreased after heat stress (-1 to -1.33 log2 FC) (Table 3).

[0375] Table 3: 25 milk-derived miRNAs identified as significantly dysregulated in Holstein cattle under heat stress .

[0376]

[0377]

[0378] in conclusion

[0379] 132 miRNAs from Brown Swiss cows and 32 miRNAs from Holstein cows were revealed to be altered in milk by heat stress.

[0380] Example 4 - Identification of similarly expressed miRNAs in milk from two breeds of heat-stressed cows

[0381] Study objectives:

[0382] MicroRNAs that are similarly expressed in milk from Holstein (H) and Brown Swiss (BS) cows during heat stress conditions were investigated.

[0383] Materials and methods

[0384] Experimental conditions and collection of milk samples are described in Example 1. In order to identify common heat stress characteristics between the two breeds, the results from Example 3 were subjected to Venn analysis.

[0385] result:

[0386] The results showed that 24 miRNAs were dysregulated in BS and H, the levels of 3 differentially expressed miRNAs were decreased after heat stress, while the levels of 21 were increased after heat stress (Table 4).

[0387] Table 4: 24 milk miRNAs identified as dysregulated in Holstein and Brown Swiss cattle under heat stress .

[0388]

[0389]

[0390] in conclusion

[0391] The data showed that surprisingly, 24 miRNAs have been identified that are dysregulated in different bovine breeds under heat stress. Thus, when determining / assessing whether dairy cattle have been exposed to heat stress, biomarkers have been identified that do not require consideration of breed.

[0392] The present invention will now be further described with reference to the following clauses.

[0393] Clause 1. A method for assessing at least one welfare parameter of cattle, preferably bovines, the method comprising:

[0394] - determining the presence of a gene selected from the group consisting of SEQ ID NO: 2, 81, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84,

[0396] the level of one or more miRNAs from the group consisting of 111, 31, 87, 55, 93, and 94;

[0397] - comparing the one or more levels to one or more corresponding reference levels;

[0398] ●Wherein if the SEQ ID NO: 85, 52, 74, 83, 6, 113, 70, 1,

[0399] a level of one or more miRNAs 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55, 93, and 94 above the one or more reference levels indicates that at least one welfare parameter of the cattle has been compromised; and

[0400] ●Wherein if the SEQ ID NO: 85, 52, 74, 83, 6, 113, 70, 1,

[0401] a level of one or more miRNAs 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55, 93, and 94 being equal to or lower than the one or more reference levels, indicating that the at least one welfare parameter of the cattle has not been compromised;

[0402] ● wherein if the level of said one or more miRNAs of SEQ ID NO: 2, 81 is equal to or above said one or more reference levels, it indicates that said at least one welfare parameter of said cattle has not been compromised; and

[0403] ● wherein if the level of said one or more miRNAs of SEQ ID NO: 2, 81 is below said one or more reference levels, it indicates that said at least one welfare parameter of said cattle has been compromised;

[0404] Clause 2. The method according to clause 1, wherein the at least one impaired welfare parameter is caused by a parameter selected from the group consisting of heat stress, social stress, metabolic stress, disease stress and combinations thereof, preferably wherein the parameter is heat stress.

[0405] Clause 3. The method of clause 1 or 2, wherein the impaired welfare parameter is caused by heat stress.

[0406] Clause 4. The method according to any one of the preceding clauses, wherein the cattle are dairy cattle.

[0407] Clause 5. The method according to any one of the preceding clauses, wherein the milk sample is from a single cow or a pooled milk sample from a group of cows.

[0408] Clause 6. The method according to any one of the preceding clauses 1 to 4, wherein the milk sample is from a herd of cattle.

[0409] Clause 7. The method according to any one of the preceding clauses, wherein the level of miRNA is the level of miRNA in milk-derived exosomes.

[0410] Clause 8. The method according to any of the preceding clauses, wherein the method is performed on at least 5 miRNAs, such as at least 10 miRNAs, preferably at least 15 miRNAs, more preferably at least 20 miRNAs, most preferably all 23 biomarkers.

[0411] Clause 9. The method according to any one of the preceding clauses, wherein the reference level is the level of one or more miRNAs in a milk sample from a cow with normal welfare or the average level from several dairy cows with normal welfare.

[0412] Clause 10. A method for assessing whether at least one welfare parameter of cattle has improved, the method comprising:

[0413] - determining a first milk sample from said cow selected from the group consisting of SEQ ID NO: 2, 81, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84,

[0415] the level of one or more miRNAs from the group consisting of 111, 31, 87, 55, 93, and 94;

[0416] - determining a second milk sample from said cow selected from the group consisting of SEQ ID NO: 2, 81, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84,

[0418] the level of one or more miRNAs from the group consisting of 111, 31, 87, 55, 93, and 94;

[0419] wherein the second milk sample is obtained later in time than the first milk sample;

[0420] - comparing the one or more levels in the first sample with one or more corresponding levels in the second sample;

[0421] ● If the second sample has SEQ ID NO: 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31,

[0423] one or more corresponding levels of 87, 55, 93, and 94 are equal to or higher than the levels in the first sample, indicating that the welfare parameter has not improved; and

[0424] ● If the second sample contains SEQ ID NO: 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111,

[0426] one or more corresponding levels of 31, 87, 55, 93, and 94 are lower than the level in the first sample, indicating that the welfare parameter has improved;

[0427] wherein if the corresponding level of one or more of SEQ ID NOs: 2 and 81 in the second sample is equal to or lower than the level in the first sample, then this indicates that the welfare parameter of the cattle has not improved; and

[0428] • wherein if the corresponding levels of one or more of SEQ ID NOs: 2 and 81 in the second sample are higher than the levels in the first sample, then this indicates that the welfare parameter of the cattle has improved.

[0429] Clause 11. A method according to clause 10, wherein active measures are taken between the taking of the first sample and the taking of the second sample to improve one or more welfare parameters of the cattle, such as wherein the active measures are selected from the group consisting of: changes in heat exposure, such as a reduction in temperature; installation of fans; possibility of shelter; installation of sprinklers; improved access to additional water; changes in feed; reduction in animal density; provision of a cooling system appropriate to local conditions; changes in movement of cattle; and a less stressful environment.

[0430] Clause 12. Use of the level of one or more miRNAs selected from the group consisting of SEQ ID NO: 2, 81, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 123, 120, 48, 112, 84, 111, 31, 87, 55, 93 and 94 in a bovine milk sample for assessing the status of a welfare parameter in a bovine.

[0431] Clause 13. Use according to Clause 12, wherein the welfare parameter is heat stress.

[0432] Clause 14. Apparatus or system suitable for determining whether at least one welfare parameter of a cow, preferably a bovine, has been compromised in a milk sample or a milk-derived sample, the apparatus comprising:

[0433] - a unit for determining the level of one or more miRNAs in a milk sample or a milk-derived sample;

[0434] - a processor configured with a reference table corresponding to reference levels of one or more miRNAs according to Table 4;

[0435] wherein the device or system is suitable for

[0436] - receiving a sample of milk origin of said milk sample;

[0437] - determining the level of said one or more miRNAs;

[0438] - comparing the determined levels of said one or more miRNAs with said reference table;

[0439] as well as

[0440] - determining whether at least one welfare parameter of said cattle has been compromised.

[0441] Clause 15. A computer-implemented method for determining whether at least one welfare parameter of a cow (preferably a bovine) has been compromised in a milk sample or a milk-derived sample, the method comprising:

[0442] - providing the level of one or more miRNAs from a bovine milk sample or a milk-derived sample selected from Table 4;

[0443] - providing a mathematical model comprising reference levels of one or more corresponding miRNAs selected from Table 4;

[0444] - using the mathematical model to determine whether the provided level deviates significantly from the reference level

[0445] and

[0446] - providing a determination to the system or user as to whether at least one welfare parameter of the cattle has been compromised.

Claims

1. A method for determining at least one welfare parameter of at least one cattle, the method comprising: i. determining the level of at least one miRNA that regulates the cell cycle in a milk sample, wherein the miRNA is selected from the group consisting of SEQ ID NOs: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112, and 111, or functional variants thereof, wherein the functional variants have at least 60% overall sequence identity to SEQ ID NOs: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112, and 111, respectively; and ii. comparing the level of the at least one miRNA to a reference level, wherein if the one or more miRNAs selected from the group consisting of SEQ ID NOs: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112 and 111 are above the reference level, then at least one welfare parameter of the at least one cattle has been compromised or is compromised, or if the one or more miRNAs selected from the group consisting of SEQ ID NOs: 81 and 134 are below the reference level, then at least one welfare parameter of the at least one cattle has been compromised or is compromised.

2. A method for improving at least one welfare parameter of at least one cow, the method comprising: i. determining the level of at least one miRNA that regulates the cell cycle in the first milk sample, wherein the miRNA is selected from the group consisting of SEQ ID NOs: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112, and 111, or functional variants thereof, wherein the functional variants have at least 60% sequence identity to SEQ ID NOs: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112, and 111, respectively; ii. comparing the level of the at least one miRNA to a reference level, wherein if the one or more miRNAs selected from the group consisting of SEQ ID NOs: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112 and 111 are above the one or more reference levels, at least one welfare parameter of the at least one cattle has been compromised, or if the one or more miRNAs selected from the group consisting of SEQ ID NOs: 81 and 134 are below the one or more reference levels, at least one welfare parameter of the at least one cattle has been compromised; iii. improving the welfare of the at least one cattle; iv. Determine the second milk sample selected from SEQ ID NO: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112 and 111 or a functional variant thereof, wherein the functional variant has at least 60% sequence identity to SEQ ID NO: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112 and 111, respectively; and v. comparing the level of the at least one miRNA in the first milk sample with the level in the second milk sample, wherein the welfare of the one cow has improved if the level of SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112 and 111 or 55 or a functional variant thereof in the second milk sample is lower than the level in the first milk sample or lower than the level in the reference sample, wherein the functional variant has at least 60% sequence identity to SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112 and 111, respectively; or If the level of SEQ ID NO: 81 or 134 in the second milk sample is higher than the level in the first milk sample or higher than the reference sample, the welfare of the one cow has improved.

3. A method for improving at least one of milk production, milk quality, meat production or meat quality of at least one cow, the method comprising i. determining the level of at least one miRNA that regulates the cell cycle in the first milk sample, wherein the miRNA is selected from SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112 and 111 or a functional variant thereof, wherein the functional variant is identical to SEQ ID NO: 94, 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112, and 111 have at least 60% sequence identity; ii. comparing the level of the at least one miRNA to a reference level, wherein if the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 85, 74, 83, 113, 1, and if the one or more miRNAs selected from SEQ ID NOs: 132, 112 and 111 are above the one or more reference levels, then at least one welfare parameter of the at least one cattle has been compromised or is compromised, or if the one or more miRNAs selected from SEQ ID NOs: 81 and 134 are below the one or more reference levels, then at least one welfare parameter of the at least one cattle has been compromised; iii. improving the welfare of the at least one cow; wherein improving the welfare of the at least one cow improves at least one of milk production, milk quality, meat production and meat quality.

4. A method for determining at least one welfare parameter of at least one cattle, the method comprising determining the level of at least one miRNA, wherein the miRNA is selected from the group consisting of SEQ ID NO: 94, 123, 93, 84, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 120, 48, 112, 111, 31, 87 and 55 or a functional variant thereof, wherein the functional variant has at least 60% overall sequence identity with SEQ ID NO: 94, 123, 93, 84, 2, 81, 134, 85, 52, 74, 83, 6, 113, 70, 1, 69, 132, 120, 48, 112, 111, 31, 87 and 55, respectively; When the level of 111, 31, 87 and 55 or a functional variant thereof is increased by 1 log2FC or more compared to the reference level, or wherein the level of SEQ ID NO: 2, 81 or 134 is decreased by -1 log2FC or more compared to the reference level, at least one welfare parameter of the at least one cow has been impaired or not impaired.

5. A method according to any preceding claim, wherein the cattle are dairy cattle, preferably bovines.

6. A method according to any preceding claim, wherein the cattle are of a breed selected from Holstein or Brown Swiss.

7. A method according to any preceding claim, wherein the milk sample is from a herd of cattle.

8. A method according to any preceding claim, wherein the welfare parameter of at least one cow can be or comprise at least one of heat stress, social stress, metabolic stress, disease stress or a combination thereof.

9. A method according to claim 8, wherein the welfare of at least one of the cattle has been compromised by heat stress or is compromised by heat stress.

10. The method of claim 1, wherein the method comprises determining the levels of all of SEQ ID NOs: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112, and 111, or functional variants thereof, wherein the functional variants are identical to those of SEQ ID NOs: 94, 123, 93, 84, 85, 74, 83, 113, 1, 132, 112, and 111, respectively. 123, 93, 84, 81, 134, 85, 74, 83, 113, 1, 132, 112 and 111 have at least 60% sequence identity.

11. The method according to any preceding claim, wherein the reference level is the level of one or more miRNAs in a milk sample from at least one cow, wherein the welfare of the cow is not or has not been compromised, or wherein the reference level is an average level from cows, wherein the welfare of the cows is not or has not been compromised.

12. The method of claim 2, wherein improving the welfare of the at least one cattle comprises one or more of altering heat exposure, improving access to additional water, altering feed, reducing animal density, and providing a cooling system.

13. Apparatus or system adapted to determine whether at least one welfare parameter of at least one cattle has been compromised or is compromised, the apparatus comprising: i. A unit capable of determining the level of one or more miRNAs according to claim 1 or 4; ii. A processor configured with a reference table corresponding to a reference level of one or more miRNAs according to Table 4; iii. wherein the device or system is suitable for iv. receiving milk samples; v. determining the level of said one or more miRNAs; vi. comparing the determined levels of the one or more miRNAs to the reference table; and vii. Determine whether the welfare of the at least one cattle has been or is being compromised.

14. A computer-implemented method for determining whether the welfare of at least one head of cattle has been compromised, the method comprising: i. providing the level of one or more miRNAs from a milk sample selected from Table 4; ii. providing a mathematical model comprising a reference level of one or more corresponding miRNAs selected from Table 4; iii. using the mathematical model to determine whether the provided level deviates significantly from the reference level; as well as iv. providing the system or user with a determination whether the welfare of the at least one cattle has been or is being compromised.

15. A kit for assessing at least one welfare parameter of at least one cattle, said kit comprising a device according to claim 15 and instructions for use.

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