Biomarker for related state of early pregnancy of dairy cow and application of biomarker

Abstract

The invention discloses a biomarker for related states of early pregnancy of dairy cows and application of the biomarker. Biological samples of a pregnancy group and a non-pregnancy group of the dairy cows after insemination are analyzed, and significantly different metabolites of the dairy cows in the non-pregnancy group and the pregnancy group are determined by utilizing a metabonomics technology; the method can be used for rapidly, simply, economically, effectively and accurately detecting and / or evaluating and / or identifying the related state of the early pregnancy of the dairy cow, provides a new means for improving the breeding efficiency of the dairy cow, optimizes the feeding management of the pregnant dairy cow, and has important economic value.

Description

Technical Field

[0001] The invention relates to the field of biotechnology, and in particular to biomarkers of early pregnancy-related states of dairy cows and applications thereof. Background Art

[0002] Embryonic and fetal loss in dairy cows is the main cause of reproductive failure. Losses associated with pregnancy failure during maternal pregnancy recognition may be as high as 30%. The establishment of pregnancy depends on the delicate balance between the endometrial intrinsic luteolytic and anti-luteolytic mechanisms, and is closely related to interferon-tau (IFN-tau) produced by the embryo in ruminants. IFN-tau can regulate the coordinated changes in the expression of transporters that increase the number of neutral and acidic amino acids in the uterine cavity to support the growth, development and survival of the embryo. Sheikh et al. found that the plasma IFN-tau concentration in the early embryonic death group of dairy cows was significantly lower than that in the pregnant group of cows. IFN-tau can stimulate the expression of genes such as ISG15, CCL8 and CXCL10 in peripheral blood leukocytes, and the expression of these genes can determine pregnancy, pregnancy failure and late embryonic death around 18 days. The study found that the pregnancy-associated glycoprotein (PAG) in the plasma of goats in early and mid-pregnancy gradually increased from the 26th day to the 51st day of artificial insemination, and the PAG concentration gradually increased until it was relatively stable at 114 days. Galdos et al. used metabolomics to identify important amino acid metabolites throughout the pregnancy stage of cattle and found that the embryonic development of dairy cows was related to related metabolites; Nicola performed LC-MS analysis on the milk of pregnant and non-pregnant buffaloes 17 days after artificial insemination. There were significant differences in the metabolite products and their expression between pregnant and non-pregnant buffaloes, and acetylcarnitine dominated the milk samples of non-pregnant buffaloes. Metabolome characterization can represent a new method to identify pregnancy. The use of metabolomics technology to detect changes in early pregnancy metabolites and detection technology that matches modern large-scale and industrialized breeding technology will attract more and more attention. However, there are currently few studies on the detection of metabolite indicators in early pregnancy in dairy cows, and there are still problems such as insufficient accuracy. Summary of the invention

[0003] In order to overcome the problems existing in the prior art, after research, the technical solution provided by the present invention is as follows:

[0004] In a first aspect, the present invention provides a biomarker for early pregnancy-related status in dairy cows, comprising a first biomarker and / or a second biomarker;

[0005] The first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prusin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid;

[0006] The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group;

[0007] The second biomarker comprises at least one of histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid;

[0008] The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group.

[0009] In the present invention, the terms "significantly differential metabolites" and "biomarkers" can be used interchangeably.

[0010] In the present invention, the early pregnancy-related state of dairy cows refers to the non-pregnant state or pregnant state of dairy cows 26-30 days after insemination.

[0011] In some embodiments, the present invention provides a biomarker for early pregnancy-related states in dairy cows, comprising a first biomarker and / or a second biomarker; the first biomarker comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, or at least 11 of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prunin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid; the measured value of the first biomarker in a biological sample from an early pregnancy group is statistically significantly lower than the measured value in a biological sample from a non-pregnant group;

[0012] The second biomarker comprises histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamic acid, proline, 7,8-dihydro-α-ionone , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24 of the group consisting of: 1.

[0013] The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group.

[0014] In some preferred embodiments, the present invention provides a biomarker for early pregnancy-related status in dairy cows, comprising a first biomarker and / or a second biomarker;

[0015] The first biomarker comprises at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, or at least 11 of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prunin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid;

[0016] The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group;

[0017] The second biomarker comprises histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxyfumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-purpurogenous at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24 of the group consisting of rolandraconazole, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid;

[0018] The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group.

[0019] In some preferred embodiments, the biological sample comprises cow plasma.

[0020] In the present invention, the criteria for statistical significance include:

[0021] (1) variable projection importance VIP; and

[0022] (2) t-test; and

[0023] (3) Univariate statistical analysis of the difference in FC.

[0024] In some embodiments, the statistically significant screening criteria include at least one of the following (a1)-(a3):

[0025] (a1) variable projection importance VIP>1; and

[0026] (a2) P < 0.05; and

[0027] (a3) FC>1.3 or FC<0.77.

[0028] It should be understood that when multiple biomarkers are used together, the AUC value is higher than when used alone, and the detection accuracy is higher.

[0029] Furthermore, in some preferred embodiments, the statistically significant screening criteria also include an AUC value greater than 0.7.

[0030] In some more preferred embodiments, the first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prunus glycosides, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, and myristic acid, and the AUC value of each of the above first biomarkers is greater than 0.7.

[0031] In some further more preferred embodiments, the first biomarker comprises taurodeoxycholic acid and / or dodecanoic acid, and the AUC value of each of the above first biomarkers is greater than 0.8.

[0032] In the present invention, "serial number", "number" and similar words are only used for distinction and cannot be understood as expressing or implying the relative importance or the number of technical features. For example, the terms "first" and "second" are only used for distinction and cannot be understood as expressing or implying the relative importance or the number of technical features.

[0033] In the present invention, the early pregnancy is 26-30 days after fertilization. More preferably, the early pregnancy is 28 days after fertilization.

[0034] In the present invention, insemination includes artificial insemination and natural insemination. In some preferred embodiments, the insemination is artificial insemination.

[0035] In a second aspect, the present invention provides a test paper, a reagent or a kit for detecting the above-mentioned biomarkers of early pregnancy-related states in dairy cows.

[0036] In a third aspect, the present invention provides a method for detecting early pregnancy-related states in dairy cows, the method comprising:

[0037] A) obtaining a biological sample containing biomarkers from a cow to be tested;

[0038] B) detecting a measurement value of a biomarker in the biological sample, wherein the biomarker comprises a first biomarker and / or a second biomarker;

[0039] The first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prusin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid;

[0040] The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group;

[0041] The second biomarker comprises at least one of histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid;

[0042] The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group; and

[0043] C) Processing the measured values ​​of the biomarkers by computer, thereby indicating that the tested dairy cow is in an early pregnancy state or a non-pregnant state.

[0044] In a fourth aspect, the present invention provides a device for detecting early pregnancy-related states in dairy cows, the device comprising:

[0045] 1) A data acquisition device for acquiring information of biological samples containing biomarkers obtained from the tested dairy cows and acquiring measurement values ​​of the biomarkers in the detected biological samples;

[0046] 2) a data processing device for processing the measured values ​​of the biomarkers detected in the biological sample, wherein the biomarkers include a first biomarker and / or a second biomarker;

[0047] The first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prusin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid;

[0048] The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group;

[0049] The second biomarker comprises at least one of histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid;

[0050] The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group; and

[0051] 3) An output device for outputting the result of computer processing of the measurement value of the biomarker, thereby indicating whether the tested dairy cow is in an early pregnancy state or a non-pregnant state.

[0052] In a fifth aspect, the present invention provides the biomarkers of early pregnancy-related states in dairy cows as described above, test strips, reagents or kits for detecting the biomarkers of early pregnancy-related states in dairy cows as described above, a method for detecting early pregnancy-related states in dairy cows as described above, and the use of the device for detecting early pregnancy-related states in dairy cows as described above in detecting and / or evaluating and / or identifying early pregnancy-related states in dairy cows.

[0053] The beneficial effects of the present invention include at least the following:

[0054] Since the metabolites of dairy cows change during early pregnancy after insemination, the present invention uses metabolomics technology to analyze biological samples of pregnant and non-pregnant groups of dairy cows after insemination, determines the significantly different metabolites in the biological samples of pregnant and non-pregnant groups of dairy cows, provides biomarkers for early pregnancy-related states in dairy cows and applications thereof, and provides for the first time a plurality of metabolite indicators for detecting early pregnancy-related states in dairy cows. The present invention can quickly, simply, economically, effectively and accurately detect and / or evaluate and / or identify early pregnancy-related states in dairy cows, provides a new means for improving the reproductive efficiency of dairy cows, and optimizes the feeding and management of pregnant dairy cows. The present invention has important economic value. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A graph showing the experimental stability evaluation of an embodiment of the present invention, wherein Figure 1 A is the total ion chromatogram of the QC sample detected by UHPLC-QTOF-MS in positive and negative ion modes; Figure 1B is the positive and negative ion TIC graphs of all QC samples; Figure 1 C is the one-dimensional distribution diagram of PCA-X of QC samples in positive and negative ion modes; Figure 1 D is the correlation analysis of positive and negative ion QC samples.

[0056] Figure 2 The PCA score graph of cows in group B and group C 28 days after artificial insemination in the embodiment of the present invention is shown, wherein: Figure 2 A is the PCA score graph under positive ion mode; Figure 2 B is the PCA score graph under negative ion mode.

[0057] Figure 3 The OPLS-DA score graph and permutation test graph of dairy cows in group B and group C on day 28 after artificial insemination in the embodiment of the present invention are shown, Figure 3 A and Figure 3 B are the OPLS-DA score graph and permutation test graph under the positive ion mode for 28 days; Figure 3 C and Figure 3 D are the OPLS-DA score graph and permutation test graph under the 28-day negative ion mode.

[0058] Figure 4 The heat map of the clustering of significantly different metabolites between group B and group C samples on the 28th day after artificial insemination in the embodiment of the present invention is shown, wherein red indicates upregulation and blue indicates downregulation.

[0059] Figure 5 The metabolic pathway analysis of significantly different metabolites between Group B and Group C on the 28th day after artificial insemination in the embodiment of the present invention is shown, wherein the horizontal axis is the pathway influence, the vertical axis is -log (P value), the darker the circle, the more significant the metabolite change in the metabolite pathway, and the larger the circle, the greater the pathway influence, wherein 1 represents the metabolism of linoleic acid, 2 represents the metabolism of arginine and proline, and 3 represents the metabolism of vitamin B6.

[0060] Figure 6 The ROC curve of the significantly differential metabolites with AUC values ​​greater than 0.7 on the 28th day after artificial insemination in the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical scheme and beneficial effects of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Examples of the embodiments are shown in the accompanying drawings. It should be understood that the specific embodiments described in the following embodiments of the present invention are only exemplary descriptions of the specific embodiments of the present invention, and are intended to be used to explain the present invention, but do not constitute a limitation of the present invention.

[0062] The endpoints of the scope disclosed in the present invention and any value are not limited to this accurate scope or value, and these scopes or values ​​should be understood as comprising values ​​close to these scopes or values. For numerical range, between the endpoint values ​​of each scope, between the endpoint values ​​of each scope and a separate point value, and between separate point values, can be combined with each other to obtain one or more new numerical ranges, and these numerical ranges should be considered as specifically disclosed in this article. In the description of the application, unless otherwise stated, the meaning of similar words such as "multiple / multiple" is two / kinds or more than two / kinds. In addition, the terms "include", "comprise" and any distortion thereof are intended to cover non-exclusive inclusions.

[0063] The present invention is further described in detail below in conjunction with the examples. It should be understood that if the experimental methods in the following examples are not specified with specific conditions, they are usually implemented according to conventional conditions or according to the conditions adopted by the partners.

[0064] Example 1

[0065] 1 Materials and methods

[0066] 1.1 Sample animals and groups

[0067] The Holstein cow blood samples used in the experiment of this embodiment were from a large dairy farm in Ningxia, and 63 healthy Holstein cows with 2-3 litters, similar age and body condition (body condition score BCS2.75 or so) were selected. Blood samples of cows without estrus were collected from the tail vein on the 28th day after artificial insemination, and B-ultrasound was used for pregnancy diagnosis examination at 32±3d. According to the pregnancy diagnosis results, they were divided into a pregnancy group (Group B, n=24) and a non-pregnant group (Group C, n=19). Twelve cows were randomly selected from each group, and the plasma of Group B and Group C of cows was analyzed respectively by UHPLC-Q / TOF-MS non-targeted metabolomics technology.

[0068] 1.2 Test methods

[0069] 1.2.1 Blood collection and storage

[0070] Blood was collected from the tail vein of dairy cows before morning feeding 28 days after artificial insemination. The upper plasma was collected after heparin sodium anticoagulation and centrifugation and stored in a -80℃ refrigerator for subsequent analysis.

[0071] 1.2.2 Sample testing method

[0072] Metabolite extraction methods include:

[0073] 100 μL of each sample was added with 400 μL of extracting solution (methanol and acetonitrile volume ratio = 1:1, internal standard concentration 5 μg / mL), vortexed for 30 seconds; sonicated for 5 minutes (ice-water bath); allowed to stand at -20°C for 1 hour; centrifuged the sample at 4°C, 12000 r / min for 15 minutes; took 425 μL of supernatant in an EP tube; dried the extract in a vacuum concentrator; added 100 μL of extracting solution (acetonitrile and water volume ratio = 1:1) to the dried metabolites for re-dissolution; vortexed for 30 seconds, sonicated in an ice-water bath for 10 minutes; centrifuged the sample at 4°C, 12000 r / min for 15 minutes; took 60 μL of supernatant and tested the metabolites on the machine.

[0074] The target compounds were separated by chromatography on a Waters ACQUITY UPLC BEH Amide (2.1*100mm, 1.7μm) liquid chromatography column using an Agilent 1290 (Agilent Technologies) ultra-high performance liquid chromatography-mass spectrometer. Phase A of the liquid chromatography was aqueous phase, containing 25mmol / L ammonium acetate and 25mmol / L ammonia water, and phase B was acetonitrile. Gradient elution was used: 0-0.5min, 95% B; 0.5-7min, 95%-65% B; 7-8min, 65%-40% B; 8-9min, 40% B; 9-9.1min, 40%-95% B; 9.1-12min, 95% B. Mobile phase flow rate: 0.5mL / min, column temperature: 25℃, sample plate temperature: 4℃, injection volume: 2μL for positive ions; 2μL for negative ions.

[0075] 1.3 Data processing and statistical analysis

[0076] The obtained raw mass spectrometry data were processed by ProteoWizard software and converted into mzXML format. The converted data were processed by XCMS program according to peak alignment, peak area extraction and peak integration. Data integrity and missing values ​​were checked, and data within the group with extreme values ​​or missing values ​​greater than 50% were deleted. After standardization and normalization of the data, parallel comparisons between metabolites and samples were performed.

[0077] After preprocessing the data using SIMCA-P software and Pareto-scaling, principal component analysis (PCA) was first used. For better visualization and subsequent analysis, orthogonal partial least squares discriminant analysis (OPLS-DA) was used to obtain more reliable information on the degree of correlation between the differences between metabolite groups and the experimental groups. After the expression model was established, the OPLS-DA model was permuted and the variable projection importance (VIP) was calculated, and the original data were subjected to univariate statistical analysis of the fold variation (FC) and t-test.

[0078] 1.4 Identification of significantly differentially expressed metabolites and bioinformatics analysis

[0079] The significantly different metabolites were screened based on the criteria of multidimensional statistical analysis VIP>1, univariate statistical analysis P<0.05 and FC>1.3 or FC<0.77. After screening, the MetaboAnalyst online analysis platform (https: / / www.metaboanalyst.ca / ) was used for poly ROC curve analysis and metabolic pathway analysis, and Origin 8.0 was used to analyze the significantly different metabolites.

[0080] 2 Results

[0081] 2.1 Experimental stability evaluation

[0082] The total ion currents of the QC samples in the positive and negative ion modes of UHPLC-QTOF-MS were compared to determine the spectral overlap. The BPC chromatographic peaks, signal intensities, and retention times of the QC samples all had good overlap in the spectra (e.g. Figure 1 A), indicating that the variation caused by instrument error in the entire experimental process is small; the TIC retention time and peak area of ​​the QC samples overlap well (as shown in Figure 1 B), indicating that the instrument has good stability; PCA-X one-dimensional distribution diagram of QC samples in positive and negative ion modes shows that all QC samples are distributed within 3STD (such as Figure 1 C); QC value approaches 1 (as shown in Figure 1 D), indicating that the QC samples have a high correlation and the experimental data in this embodiment are of high quality.

[0083] 2.2 Multivariate statistical analysis

[0084] 2.2.1 Principal Component Analysis (PCA) Analysis

[0085] PCA analysis is used to observe the overall distribution trend among all samples and find possible discrete points. PCA model parameter R 2 X represents the model's explanation rate for the X variable, and the PCA model parameter Q 2 It indicates the model's prediction ability for the X variable. 2 X is greater than 0.5 (R 2 X≥0.5) indicates that the model is stable and reliable. The PCA model spectrum obtained after cyclic interaction verification is as follows Figure 2 The results show that at 28 days, the R 2 X was 0.615 and 0.601 respectively, indicating that the expression model established above was stable and reliable.

[0086] 2.2.2 Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) Analysis

[0087] The OPLS-DA model was established, such as Figure 3 and as shown in Table 1. The model evaluation parameter R obtained after cyclic interaction verification 2 Y and Q 2 , R 2 Y≥0.5 and Q 2 When ≥0.5, the expression model is stable and reliable. 2 The closer Y is to 1, the more stable and reliable the expression model is, and the higher its predictive ability is. 2 The intercepts are all less than 0 (Q 2 The intercept <0) indicates that the OPLS-DA model established for the positive and negative ion mode data is not overfitted, and R 2 Y, Q 2 , Q 2 The intercepts all met the conditions, indicating that the established expression model was reliable and effective.

[0088] Table 1 Evaluation parameters of OPLS-DA model and permutation test

[0089]

[0090] 2.3 Screening of significantly different metabolites

[0091] According to the VIP value calculated by the OPLS-DA model, VIP>1, P<0.05, FC>1.3 or FC<0.77 were used to screen significantly different metabolites. In the present embodiment, a total of 35 significantly different metabolites were screened out in the experimental groups B and C in the positive and negative ion modes, of which 11 metabolites in group B (taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prunin, dodecanoic acid, histidine-methionine, 3-butyric acid, trans-aconitic acid, myristic acid and indoleacetic acid) were significantly lower than those in group C; 24 metabolites in group B (histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1- The metabolites of palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxyfumarate, threonine-threonine, proline-glutamic acid, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid were significantly higher in group A than in group C. The significantly differential metabolites identified in positive and negative ion modes are shown in Table 2.

[0092] Table 2 Significantly different metabolites in positive and negative ion modes in groups B and C on day 28 of artificial insemination

[0093]

[0094]

[0095]

[0096] 2.4 Cluster analysis of significantly different metabolites

[0097] The MetaboAnalyst analysis platform was used to perform cluster analysis on the significantly different metabolites. Figure 4 As shown, it was found that the samples in the same group could be well clustered in the same cluster, and the metabolites in the same cluster had similar expression patterns, indicating that the screened significant difference metabolites were reasonable and accurate.

[0098] 2.5 Metabolic pathway analysis

[0099] KEGG metabolic pathway analysis of significantly different metabolites screened between different groups, with influence > 0.2 as the screening standard. The 35 significantly different metabolites screened on the 28th day after artificial insemination were mainly enriched in 3 metabolic pathways, such as Figure 5 As shown, 1 represents the metabolism of linoleic acid, 2 represents the metabolism of arginine and proline, and 3 represents the metabolism of vitamin B6.

[0100] 3 Conclusion

[0101] In order to explore the change pattern of plasma metabolites of non-pregnant cows and pregnant cows that did not return to estrus on the 26th to 30th day (such as the 28th day) after artificial insemination of dairy cows, in order to determine the metabolic pathways that affect pregnancy. In an embodiment of the present invention, 63 healthy Holstein cows with similar parity, age and body condition were selected, artificial insemination was performed after estrus at the same time, and tail vein blood was collected before morning feeding on the 28th day after artificial insemination. Cows that returned to estrus within 28 days were eliminated, and B-ultrasound was used for pregnancy diagnosis examination at 32±3d. According to the test results, they were divided into a pregnant group (Group B) and a non-pregnant group (Group C), and 12 were randomly selected from each group. The plasma of dairy cows in the pregnant group and the non-pregnant group was detected by UHPLC-Q / TOF-MS non-targeted metabolomics technology.

[0102] The results showed that significant metabolites were screened with VIP>1, P<0.05, FC>1.3 or FC<0.77. A total of 35 significant metabolites were screened on the 28th day after artificial insemination, of which 24 metabolites in the pregnancy group were significantly higher than those in the non-pregnancy group, and 11 metabolites were significantly lower than those in the non-pregnancy group.

[0103] KEGG metabolic pathway analysis was performed on the significantly different metabolites. On the 28th day after artificial insemination, the pregnant group of dairy cows mainly included metabolites of metabolic pathways such as linoleic acid metabolism, arginine and proline metabolism, and vitamin B6 metabolism, such as linoleic acid, Nω-hydroxyarginine, proline, and pyridoxine. These metabolites, as biomarkers, were significantly higher than those in the non-pregnant group, which can provide nutrition for embryonic development and maintain the pregnancy of dairy cows. Specifically:

[0104] Linoleic acid is an essential fatty acid and a precursor of arachidonic acid. Linoleic acid has a good promoting effect on the synthesis of fat and protein. In the present invention, it is found that the linoleic acid in the plasma of the pregnant group of dairy cows on the 28th day after artificial insemination is significantly higher than that of the non-pregnant group of dairy cows, indicating that the linoleic acid level in the body of the pregnant dairy cow is increased. The increased linoleic acid inhibits the synthesis of PGF2α, which is beneficial to the maintenance of the corpus luteum, thereby leading to the maintenance of the pregnancy of the dairy cow.

[0105] Nω-hydroxyarginine (NOHA) is a natural and powerful arginase inhibitor. It competes with arginase and inhibits its activity, inhibiting the hydrolysis of L-arginine to L-ornithine. The present invention found that NOHA in the plasma of pregnant cows on the 28th day after artificial insemination was significantly higher than that of non-pregnant cows. The increased NOHA may inhibit arginase, leading to an increase in arginine, which is beneficial to the pregnancy of cows.

[0106] Proline is the main substrate for the synthesis of polyamines by proline oxidase, ornithine aminotransferase and ornithine decarboxylase in the placenta. The present invention found that proline is mainly involved in the metabolism of arginine and proline on the day after artificial insemination, and the proline in the plasma of the pregnant group of cows is significantly higher than that of the non-pregnant group of cows. The increased proline in early pregnancy may be used to support cell proliferation and differentiation, which is beneficial to the formation and development of the embryonic disc and provides energy for the embryonic development of pregnant cows.

[0107] Pyridoxine is a water-soluble vitamin and a metabolite of VB6. It exists independently in the animal body in a phosphorylated state or in combination with proteins. As a cofactor, pyridoxine 5-phosphate is mainly involved in many enzyme pathways of amino acid metabolism. Pyridoxine plays a vital role in the metabolic process of animals and contributes to the development of the nervous system. The present invention found that the pyridoxine in the plasma of the pregnant group of cows on the 28th day after artificial insemination was significantly higher than that of the non-pregnant group of cows, and the increased pyridoxine is conducive to maintaining early embryonic development.

[0108] Further, in some preferred embodiments, through AUC value screening, it is found that the individual AUC values ​​of the 10 significantly different metabolites of the present invention are greater than 0.7, especially the significantly different metabolites in the pregnancy group that are significantly lower than those in the non-pregnancy group generally have higher AUC values ​​(such as Figure 6 Moreover, when multiple proteins are used together, the AUC is higher than that when they are used alone, and the detection accuracy is higher.

[0109] The present invention analyzes biological samples of pregnant and non-pregnant groups of dairy cows after insemination, and uses metabolomics technology to determine the significantly different metabolites between the non-pregnant and pregnant groups of dairy cows. The present invention can quickly, simply, economically, effectively and accurately detect and / or evaluate and / or identify early pregnancy-related states of dairy cows, provide a new means for improving the reproductive efficiency of dairy cows, optimize the feeding and management of pregnant dairy cows, and has important economic value.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and do not constitute a limitation on the content of the present invention. Within the technical concept of the present invention, the technical solution of the present invention can be subjected to a variety of simple modifications, including the combination of various technical features in any other suitable manner, and these simple modifications and combinations should also be regarded as the contents disclosed by the present invention and belong to the protection scope of the present invention.

Claims

1. A biomarker for early pregnancy-related status in dairy cows, characterized in that: comprising a first biomarker and / or a second biomarker; The first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prusin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid; The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group; The second biomarker comprises at least one of histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid; The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group.

2. The biomarker of early pregnancy-related status in dairy cows according to claim 1, characterized in that: comprising a first biomarker and / or a second biomarker; The first biomarker comprises at least two of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prusin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid; The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group; The second biomarker comprises at least two of histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid; The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group.

3. The biomarker of early pregnancy-related status in dairy cows according to claim 1, characterized in that: The first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prunin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, and myristic acid.

4. The biomarker of early pregnancy-related status in dairy cows according to claim 3, characterized in that: The first biomarker comprises taurodeoxycholic acid and / or dodecanoic acid.

5. The biomarker of early pregnancy-related status in dairy cows according to claim 1, characterized in that: The biological sample includes cow plasma.

6. The biomarker of early pregnancy-related status in dairy cows according to claim 1, characterized in that: The time of the early pregnancy-related state of the dairy cow is 26-30 days after insemination.

7. A test paper, reagent or kit for detecting a biomarker of an early pregnancy-related state in a dairy cow according to any one of claims 1 to 6.

8. A method for detecting early pregnancy-related conditions in dairy cows, characterized in that: The method comprises: A) obtaining a biological sample containing biomarkers from a cow to be tested; B) detecting a measurement value of a biomarker in the biological sample, wherein the biomarker comprises a first biomarker and / or a second biomarker; The first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prusin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid; The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group; The second biomarker comprises at least one of histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid; The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group; and C) Processing the measured values ​​of the biomarkers by computer, thereby indicating whether the tested dairy cow is in an early pregnancy state or a non-pregnant state.

9. A device for detecting early pregnancy-related conditions in dairy cows, characterized in that: The device comprises: 1) A data acquisition device for acquiring information of biological samples containing biomarkers obtained from the tested dairy cows and acquiring measurement values ​​of the biomarkers in the detected biological samples; 2) a data processing device for processing the measured values ​​of the biomarkers detected in the biological sample, wherein the biomarkers include a first biomarker and / or a second biomarker; The first biomarker comprises at least one of taurodeoxycholic acid, triethanolamine, dimethylglycine, 1-methylguanosine, prusin, dodecanoic acid, histidine-methionine, 3-butyric acid, transaconitic acid, myristic acid, and indoleacetic acid; The measured value of the first biomarker in the biological sample from the early pregnancy group is statistically significantly lower than the measured value in the biological sample from the non-pregnancy group; The second biomarker comprises at least one of histidine-alanine, trans-taurine, 5'-deoxyadenosine, D-erythro-sphingosine-1-phosphate, leucine-histidine, 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine, N-(ω)-hydroxyarginine, D-gluconate, pyrrole-2-carboxylic acid, histidine-proline, glycolipid cholic acid, linoleic acid, threonine-alanine, dihydroxy fumarate, threonine-threonine, proline-glutamate, proline, 7,8-dihydro-α-ionone, pyridoxine, chenodeoxycholate, deoxycholic acid, N-acetyl-L-tyrosine, valine-methionine, and phosphoglycolic acid; The measured value of the second biomarker in the biological samples from the early pregnancy group is statistically significantly higher than the measured value in the biological samples from the non-pregnant group; and 3) An output device for outputting the result of computer processing of the measurement value of the biomarker, thereby indicating whether the tested dairy cow is in an early pregnancy state or a non-pregnant state.

10. The biomarker of early pregnancy-related status in dairy cows according to any one of claims 1-6, the test paper, reagent or kit for detecting the biomarker of early pregnancy-related status in dairy cows according to any one of claims 1-6 according to claim 7, the method for detecting early pregnancy-related status in dairy cows according to claim 8, and the use of the device for detecting early pregnancy-related status in dairy cows according to claim 9 in detecting and / or evaluating and / or identifying early pregnancy-related status in dairy cows.

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