Application and method of protein biomarker in saliva in early pregnancy diagnosis of sow

Abstract

The invention belongs to the technical field of pig breeding, and particularly relates to application and a method of protein biomarkers in saliva in early pregnancy diagnosis of sows. According to the invention, the fact that A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3 and A0A287BQU9 proteins in saliva of the sow can be used as the protein biomarkers for early pregnancy diagnosis of the sow is found for the first time, the expression level of the proteins can be used as an important reference for identifying whether the sow is pregnant or not, and good accuracy, relatively high sensitivity, relatively high specificity and relatively low false alarm rate are achieved in early pregnancy diagnosis; a non-invasive and rapid sow early pregnancy diagnosis scheme is provided for a large-scale pig farm, and an innovative technical path is provided for improving the breeding efficiency in pig breeding.

Description

Technical Field

[0001] This invention relates to the field of pig farming technology, and in particular to the application and method of saliva protein biomarkers in early pregnancy diagnosis of sows. Background Technology

[0002] The parity of a sow per year is one of the core indicators determining the number of weaned piglets (PSY) produced annually. Current pregnancy diagnosis techniques have limitations, typically requiring artificial insemination 25 days after the initial insemination. This prevents sows with failed pregnancies from undergoing re-insemination within their first estrous cycle. This directly leads to prolonged non-productive days (NPD) and reduced parity per year, severely hindering sow reproductive performance and the economic benefits of pig farming. Therefore, improving existing pregnancy diagnosis methods is crucial for the development of the pig farming industry. Developing accurate, convenient, and efficient early pregnancy diagnosis techniques has become a key breakthrough for cost reduction and efficiency improvement in the pig farming industry.

[0003] Traditional methods for diagnosing sow pregnancy have several drawbacks. Ultrasound results are significantly affected by the operator's experience; diagnosing through observation of external features such as abdominal distension and mammary gland development suffers from time lag; hormone testing may lead to misidentification due to false estrus in some sows; and using boars to identify sows returning to estrus significantly increases the risk of malignant disease transmission. Currently, ultrasound remains a commonly used technique for diagnosing sow pregnancy both domestically and internationally. However, this technique cannot complete pregnancy diagnosis within the first estrous cycle (21 days) after artificial insemination. Sows that have not been inseminated must wait until the second estrous cycle, which increases the average NPD (pregnancy probability) by 10-15 days and raises breeding costs by 15%-20%. Furthermore, small and medium-sized pig farms, lacking specialized equipment and testing technologies such as ultrasound machines, often rely on behavioral patterns of sows for pregnancy assessment. This method has low diagnostic accuracy and is insufficient to effectively improve sow reproductive efficiency.

[0004] With the development and application of non-invasive pregnancy diagnostic technologies, some researchers have begun to utilize molecular diagnostic techniques to rapidly and specifically detect specific biomarkers in pregnant sows in order to achieve early pregnancy diagnosis. However, studies have found that the concentrations of existing biomarkers (such as estradiol and progesterone) fluctuate greatly, leading to inaccurate results and a high likelihood of false positives. Furthermore, the detection methods are highly invasive, typically requiring blood samples, which necessitates restraining the sow and can cause stress, potentially affecting embryo implantation. Additionally, the cost of a single blood sample is high, making it unsuitable for large-scale testing in pig farms. Therefore, developing new and effective early (within 21 days post-mating) pregnancy diagnostic biomarkers is of great significance. Summary of the Invention

[0005] To address the aforementioned technical problems in existing technologies, this invention provides several protein biomarkers (A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9) for early pregnancy diagnosis in sows. The expression levels of these proteins can serve as an important reference for identifying whether a sow is pregnant. They exhibit good accuracy, high sensitivity, specificity, and a low false alarm rate in early pregnancy diagnosis, providing a non-invasive and rapid early pregnancy diagnosis solution for large-scale pig farms and offering an innovative technical path to improve reproductive efficiency in pig farming.

[0006] The first aspect of this invention provides the application of protein biomarkers or their specific peptides in the preparation of a diagnostic kit for early pregnancy in sows, wherein the protein biomarker is at least one selected from A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9; wherein: the amino acid sequences of A0A480KE10 and its specific peptide are shown in SEQ ID NO.1 and SEQ ID NO.6, respectively; the amino acid sequences of A0A286ZUJ1 and its specific peptide are shown in SEQ ID NO.2 and SEQ ID NO.7, respectively; the amino acid sequences of D0G0C7 and its specific peptide are shown in SEQ ID NO.3 and SEQ ID NO.8, respectively; the amino acid sequences of A0A287BAB3 and its specific peptide are shown in SEQ ID NO.4 and SEQ ID NO.9, respectively; and the amino acid sequences of A0A287BQU9 and its specific peptide are shown in SEQ ID NO.5 and SEQ ID NO.10, respectively.

[0007] The second aspect of this invention provides the application of reagents for detecting protein biomarkers or their specific peptides in the preparation of a diagnostic kit for early pregnancy in sows, wherein the protein biomarker is at least one selected from A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9; wherein: the amino acid sequences of A0A480KE10 and its specific peptide are shown in SEQ ID NO.1 and SEQ ID NO.6, respectively; the amino acid sequences of A0A286ZUJ1 and its specific peptide are shown in SEQ ID NO.2 and SEQ ID NO.7, respectively; the amino acid sequences of D0G0C7 and its specific peptide are shown in SEQ ID NO.3 and SEQ ID NO.8, respectively; the amino acid sequences of A0A287BAB3 and its specific peptide are shown in SEQ ID NO.4 and SEQ ID NO.9, respectively; and the amino acid sequences of A0A287BQU9 and its specific peptide are shown in SEQ ID NO.5 and SEQ ID NO.10, respectively.

[0008] Furthermore, the kit is a gas chromatography-mass spectrometry (LC-MS / MS) kit.

[0009] Furthermore, the protein biomarker is a protein found in sow saliva samples.

[0010] Furthermore, the sow is a crossbred sow.

[0011] Furthermore, the protein biomarker is A0A480KE10.

[0012] A third aspect of the present invention provides a method for diagnosing early pregnancy in sows for non-diagnostic purposes, comprising the following steps:

[0013] Saliva samples were collected from sows after mating, and the expression levels of protein biomarkers or their specific peptides in the saliva samples were detected. The expression levels of the protein biomarkers or their specific peptides were used to determine whether the sows were pregnant.

[0014] The protein biomarker is at least one of A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9; wherein: the amino acid sequences of A0A480KE10 and its specific peptide are shown in SEQ ID NO.1 and SEQ ID NO.6, respectively; the amino acid sequences of A0A286ZUJ1 and its specific peptide are shown in SEQ ID NO.2 and SEQ ID NO.7, respectively; the amino acid sequences of D0G0C7 and its specific peptide are shown in SEQ ID NO.3 and SEQ ID NO.8, respectively; the amino acid sequences of A0A287BAB3 and its specific peptide are shown in SEQ ID NO.4 and SEQ ID NO.9, respectively; and the amino acid sequences of A0A287BQU9 and its specific peptide are shown in SEQ ID NO.5 and SEQ ID NO.10, respectively.

[0015] Furthermore, the expression levels of protein biomarkers or their specific peptides were detected using PRM-based LC-MS / MS targeted quantification technology. If the expression levels of A0A480KE10 or its specific peptides, A0A286ZUJ1 or its specific peptides, A0A287BAB3 or its specific peptides, and A0A287BQU9 or their specific peptides in the saliva samples of the tested sows were significantly lower than those in non-pregnant sows, the sows were determined to be pregnant; otherwise, they were determined to be non-pregnant. Alternatively, if the expression level of D0G0C7 or its specific peptides in the saliva samples of the tested sows was significantly higher than that in non-pregnant sows, the sows were determined to be pregnant; otherwise, they were determined to be non-pregnant.

[0016] Furthermore, the peak area integral value of protein biomarkers was detected by LC-MS / MS targeted quantitative technology based on PRM. When the peak area of ​​A0A480KE10 or its specific peptide in the saliva sample of the sow was ≥811309.39, or when the peak area of ​​A0A286ZUJ1 or its specific peptide in the saliva sample of the sow was ≥10038425, or when the peak area of ​​A0A287BAB3 or its specific peptide in the saliva sample of the sow was ≥1434147.47, or when the peak area of ​​A0A287BQU9 or its specific peptide in the saliva sample of the sow was ≥16114232.69, the sow was judged to be in a non-pregnant state, otherwise it was judged to be in a pregnant state; or when the peak area of ​​D0G0C7 or its specific peptide in the saliva sample of the sow was ≥2230957.10, the sow was judged to be in a pregnant state, otherwise it was judged to be in a non-pregnant state.

[0017] Optionally, the early pregnancy diagnosis is performed on the 15th day after mating of the sow.

[0018] Optionally, the sow is a crossbred sow.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The protein biomarkers (A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3 and A0A287BQU9) provided by this invention can be used to diagnose pregnancy in non-pregnant sows before their first estrus (day 15). They have good accuracy, high sensitivity, specificity and low false alarm rate. They can be used 10 days earlier than ultrasound diagnosis, which helps to identify non-pregnant sows that have been bred, reduce non-productive days and increase the number of litters per sow per year.

[0021] 2. Non-invasive, efficient and low cost: The test sample comes from sow saliva, which eliminates the need to restrain the sow and effectively reduces stress response in sows. It is suitable for batch testing in large-scale pig farms.

[0022] 3. High diagnostic accuracy: The core biomarker A0A480KE10 has an AUC of 1, achieving a "zero false positive" diagnosis, which is significantly more accurate than traditional hormone assays (accuracy rate 70%-80%). Biomarkers such as A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9 also have high accuracy, and the accuracy is even higher when used in combination.

[0023] 4. Great industrialization potential: Based on this, portable test kits can be developed with a short testing cycle. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a verification diagram of the quantitative analysis results of D-DIA proteomics and the detection results of ELISA in Example 4 of the present invention;

[0026] Figure 2 This is a heatmap showing the association between differentially expressed proteins and differentially expressed metabolites in metabolic pathways according to embodiments of the present invention.

[0027] Figure 3 This is a heatmap of differential protein clustering in an embodiment of the present invention;

[0028] Figure 4 This is a differential protein clustering volcano diagram from an embodiment of the present invention;

[0029] Figure 5 This is a graph showing the quantitative results of differentially expressed proteins A0A480KE10, A0A286ZUJ1, A0A287A042, A0A287AC34, A0A287AP73, D0G0C7, A0A287BAB3, and A0A287BQU9 in the saliva of pregnant and non-pregnant sows in an embodiment of the present invention.

[0030] Figure 6 The ROC curves for biomarkers A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9 in embodiments of the present invention are shown. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. The embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0032] Based on the information contained herein, various changes to the precise description of the invention can be readily made by those skilled in the art without departing from the spirit and scope of the appended claims. It should be understood that the scope of the invention is not limited to the defined processes, properties, or components, as these embodiments and other descriptions are merely illustrative of specific aspects of the invention. In fact, various modifications to embodiments of the invention that will be apparent to those skilled in the art or related fields are covered within the scope of the appended claims.

[0033] To better understand the invention and not to limit its scope, all figures and other numerical values ​​used in this invention to indicate amounts, percentages, or other quantities should, in all cases, be understood to be modified by the word "approximately." Therefore, unless specifically stated otherwise, the numerical parameters listed in the specification and appended claims are approximate values ​​and may vary depending on the desired properties being sought. Each numerical parameter should at least be considered as obtained based on reported significant figures and through conventional rounding methods.

[0034] Additionally, it should be noted that, unless otherwise defined, the scientific and technical terms used in the context of this invention should have the meanings commonly understood by those skilled in the art.

[0035] The terms “including,” “contains,” “includes,” “has,” and similar words are non-restrictive and can include other steps and other components that do not affect the result.

[0036] The term “and / or” should be considered as a specific disclosure of each of the two specified features or components, with or without the other. For example, “A and / or B” is considered to include (i) A, (ii) B, and (iii) A and B.

[0037] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0038] This invention collected saliva from pregnant and non-pregnant sows on day 15 post-mating, isolated proteins, and screened differentially expressed proteins using 4D-DIA non-targeted quantitative proteomics analysis dependent on LC-MS / MS. Differentially expressed metabolites were screened using LC-MS non-targeted metabolomics. Correlation analysis of differentially expressed proteins and metabolites revealed candidate differentially expressed proteins with high energy priority in the key metabolic regulatory network of early pregnancy: A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9. Except for D0G0C7, which was upregulated in the pregnant group, A0A480KE10, A0A286ZUJ1, A0A287BAB3, and A0A287BQU9 were all downregulated in the pregnant group.

[0039] Parallel reaction monitoring (PRM) targeted quantification technology using LC-MS / MS was used to quantify specific peptides of candidate differentially expressed proteins in the pregnant and non-pregnant groups. The results showed that the levels of A0A480KE10 (EGFLLALTQGR), A0A286ZUJ1 (KSDLFQEDLYPPTAGPDAALTAEEWLGGR), A0A287BAB3 (GLEWLAGIYSSGSSTYYADSVK), and A0A287BQU9 (NQVALNPQNTVFDAK) in the non-pregnant group were more than twice that in the pregnant group, and the level of D0G0C7 (LGGVQFDIDLPNK) in the non-pregnant group was 0.138 times that in the pregnant group. These results validated the above results and suggested that the expression levels of these proteins can serve as an important reference for identifying whether sows are pregnant, and have value as biomarkers for early pregnancy diagnosis in sows.

[0040] Receiver operating characteristic (ROC) analysis was used to analyze the predictive accuracy of the aforementioned protein biomarkers in determining the pregnancy status of sows. The areas under the curve (AUC) for A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9 were 1, 0.88, 0.85, 0.95, and 0.86, respectively, indicating high diagnostic value. Further comparison of PRM quantitative results with ultrasound pregnancy diagnosis results showed a true positive rate of over 75% and a true negative rate of over 80%. Specifically, the true positive rates for A0A480KE10, A0A287BAB3, and A0A287BQU9 were as high as 100%, and the true negative rates for A0A480KE10 and D0G0C7 were as high as 100%. This demonstrates that the protein biomarkers provided by this invention have good accuracy, high sensitivity, specificity, and a low false alarm rate in early pregnancy diagnosis.

[0041] Based on this, one embodiment of the present invention provides the application of protein biomarkers or their specific peptides in the preparation of a diagnostic kit for early pregnancy in sows, wherein the protein biomarker is at least one of A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9; wherein: the amino acid sequences of A0A480KE10 and its specific peptide are shown in SEQ ID NO.1 and SEQ ID NO.6, respectively; the amino acid sequences of A0A286ZUJ1 and its specific peptide are shown in SEQ ID NO.2 and SEQ ID NO.7, respectively; the amino acid sequences of D0G0C7 and its specific peptide are shown in SEQ ID NO.3 and SEQ ID NO.8, respectively; the amino acid sequences of A0A287BAB3 and its specific peptide are shown in SEQ ID NO.4 and SEQ ID NO.9, respectively; and the amino acid sequences of A0A287BQU9 and its specific peptide are shown in SEQ ID NO.5 and SEQ ID NO.10, respectively.

[0042] Preferably, the protein biomarker is A0A480KE10.

[0043] Saliva samples were collected from sows during their first estrus cycle (day 15) after mating, and the expression levels of protein biomarkers were detected. If low expression of A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, or A0A287BQU9 was detected, or high expression of D0G0C7 was detected, the sow was identified as pregnant. Using the protein biomarkers of this invention, the pregnancy status of sows can be rapidly and accurately determined early in the mating season, providing a non-invasive and rapid early pregnancy diagnosis solution for large-scale pig farms. It is expected that the development of portable testing kits will promote industrial application and provide an innovative technological path to improve reproductive efficiency in pig farming.

[0044] It should be noted that the expression levels of proteins A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9 are based on the general expression levels of these proteins in pigs in this field. The terms "high" and "low" are relative. Based on whether the expression level is higher or lower than this general level, for example, if A0A480KE10, A0A286ZUJ1, A0A287BAB3, and A0A287BQU9 are lower than the general expression level of these proteins in the non-pregnant group, then pregnancy is determined; if D0G0C7 is higher than the general expression level, then pregnancy is determined. Alternatively, if the expression level is within this general expression level relative to the general expression level of these proteins in the pregnant group, then pregnancy is determined.

[0045] In practice, the relative expression levels of the above-mentioned protein biomarkers were detected using PRM-based LC-MS / MS targeted quantification technology. When the levels of A0A480KE10 (EGFLLALTQGR), A0A286ZUJ1 (KSDLFQEDLYPPTAGPDAALTAEEWLGGR), A0A287BAB3 (GLEWLAGIYSSGSSTYYADSVK), and A0A287BQU9 (NQVALNPQNTVFDAK) in the saliva sample of the sow under test were significantly lower than those in non-pregnant sows (specifically, more than 2 times lower), the sow under test was determined to be pregnant; otherwise, it was determined to be non-pregnant. When the level of D0G0C7 (LGGVQFDIDLPNK) in the saliva sample of the sow under test was significantly higher than that in non-pregnant sows (specifically, more than 5 times higher), the sow under test was determined to be pregnant; otherwise, it was determined to be non-pregnant.

[0046] Alternatively, in practice, the peak area integral value of the above-mentioned protein biomarkers can be detected using PRM-based LC-MS / MS targeted quantification technology. When the peak area of ​​A0A480KE10 (EGFLLALTQGR) in the sow saliva sample is ≥811309.39, it is determined to be non-pregnant; otherwise, it is determined to be pregnant. When the peak area of ​​A0A286ZUJ1 (KSDLFQEDLYPPTAGPDAALTAEEWLGGR) in the sow saliva sample is ≥10038425, it is determined to be non-pregnant; otherwise, it is determined to be pregnant. A peak area ≥ 2230957.10 for D0G0C7 (LGGVQFDIDLPNK) in the sow's saliva sample indicates pregnancy, while a peak area ≥ 1434147.47 indicates pregnancy. Similarly, a peak area ≥ 16114232.69 for A0A287BQU9 (NQVALNPQNTVFDAK) in the sow's saliva sample indicates pregnancy.

[0047] Optionally, the kit is a gas chromatography-mass spectrometry (LC-MS / MS) kit.

[0048] Optionally, the protein biomarker is a protein in a sow's saliva sample.

[0049] Based on the same inventive concept described above, another embodiment of the present invention provides the application of reagents for detecting protein biomarkers or their specific peptides as described above in the preparation of diagnostic kits for early pregnancy in sows.

[0050] Optionally, the kit is a gas chromatography-mass spectrometry (LC-MS / MS) kit.

[0051] Optionally, the protein biomarker is a protein in a sow's saliva sample.

[0052] Based on the same inventive concept described above, this invention also provides a method for diagnosing early pregnancy in sows for non-diagnostic purposes, comprising the following steps:

[0053] Saliva samples were collected from sows after mating, and the expression levels of protein biomarkers or their specific peptides in the saliva samples were detected. The protein biomarkers were at least one of A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9.

[0054] Whether the sow to be tested is pregnant is determined based on the expression level of the protein biomarker or its specific peptide.

[0055] Optionally, the expression levels of protein biomarkers or their specific peptides are detected using PRM-based LC-MS / MS targeted quantification technology. If the expression level of A0A480KE10 or its specific peptide in the saliva sample of the sow is significantly lower than that in non-pregnant sows, the sow is determined to be pregnant; otherwise, it is determined to be non-pregnant. Alternatively, if the expression level of A0A286ZUJ1 or its specific peptide in the saliva sample of the sow is significantly lower than that in non-pregnant sows, the sow is determined to be pregnant; otherwise, it is determined to be non-pregnant. If the expression level of A287BAB3 or its specific peptide is significantly lower than that of non-pregnant sows, the sow is considered pregnant; otherwise, it is considered non-pregnant. Alternatively, if the expression level of A0A287BQU9 or its specific peptide in the saliva sample of the sow is significantly lower than that of non-pregnant sows, the sow is considered pregnant; otherwise, it is considered non-pregnant. Or, if the expression level of D0G0C7 or its specific peptide in the saliva sample of the sow is significantly higher than that of non-pregnant sows, the sow is considered pregnant; otherwise, it is considered non-pregnant.

[0056] Optionally, the peak area integral value of protein biomarkers is detected by PRM-based LC-MS / MS targeted quantification technology. If the peak area of ​​A0A480KE10 or its specific peptide in the sow's saliva sample is ≥811309.39, the sow is considered non-pregnant; otherwise, it is considered pregnant. Alternatively, if the peak area of ​​A0A286ZUJ1 or its specific peptide in the sow's saliva sample is ≥10038425, the sow is considered non-pregnant; otherwise, it is considered pregnant. A peak area of ​​A0A287BAB3 or its specific peptide ≥ 1,434,147.47 is considered a non-pregnant state, otherwise a pregnant state; or a peak area of ​​A0A287BQU9 or its specific peptide ≥ 16,114,232.69 in the saliva sample of the sow is considered a non-pregnant state, otherwise a pregnant state; or a peak area of ​​D0G0C7 or its specific peptide ≥ 2,230,957.10 in the saliva sample of the sow is considered a pregnant state, otherwise a non-pregnant state.

[0057] Optionally, the early pregnancy diagnosis is performed on the 15th day after mating of the sow.

[0058] Optionally, the sow is a crossbred sow.

[0059] Optionally, the detection method is PRM-based LC-MS / MS targeted quantification technology.

[0060] Optionally, the collected saliva is centrifuged at 3000 r / min for 10 min, and the supernatant is used to extract proteins by precipitation with organic solvents (e.g., Tris-saturated phenol, methanol, acetone). The extracted proteins are dissolved and ultrafiltered in a 10 kDa ultrafiltration tube. The ultrafiltration concentrate is collected and subjected to trypsin enzymatic hydrolysis. The hydrolysate is desalted, and the desalted eluent is fractionated. The fractions are combined and loaded onto LC-MS / MS to detect the expression level of protein biomarkers.

[0061] The present invention will be further illustrated below with reference to specific embodiments. Experimental methods in the following embodiments that do not specify specific conditions are generally performed under conventional conditions, such as those described in *Molecular Cloning: A Laboratory Manual (Fourth Edition)* published by Cold Spring Harbor Laboratory, or conditions recommended by the manufacturer. Furthermore, unless otherwise specified, all materials and reagents used in the following embodiments are commercially available.

[0062] Sow herd: The two-breed sows are sourced from the pig breeding base of Xinjiang Tiankang Animal Husbandry Technology Co., Ltd.

[0063] Biomarkers: The protein numbers are referenced from the UniProt database, and the specific protein sequences are shown in Table 1.

[0064] Table 1. Amino acid (AA) sequence information of protein biomarkers in the embodiments of the present invention.

[0065]

[0066]

[0067] The annotation information for biomarkers and the specific peptide information for detection are as follows:

[0068] A0A480KE10 (formerly known as A0A286ZMD1): Gene name: NAGK, Protein function: N-acetyl-D-glucosamine kinase, MW [KDa]: 37.33661; Specific peptide sequence: EGFLLALTQGR (see SEQ ID NO. 6).

[0069] A0A286ZUJ1: Gene name: CORO1A, Protein function: Coronin, MW[KDa]: 54.15172; Specific peptide sequence: KSDLFQEDLYPPTAGPDAALTAEEWLGGR (see SEQ ID NO.7).

[0070] D0G0C7 (formerly known as A0A287B262): Gene name: ATOX1, Protein function: HMA domain-containing protein, Antioxidant 1-copper chaperone, Antioxidant 1-copper chaperone, HMA domain-containing protein, Antioxidant protein 1-homolog (Yeast), Copper transport protein ATOX1, MW [KDa]: 6.29526; Specific peptide sequence: LGGVQFDIDLPNK (see SEQ ID NO. 8).

[0071] A0A287BAB3: Protein function: Ig-like domain-containing protein, MW[KDa]: 18.0091; Specific peptide sequence: GLEWLAGIYSSGSSTYYADSVK (see SEQ ID NO.9).

[0072] A0A287BQU9: Gene name: HSP70.2, Protein function: Heat shock protein 70.2, MW [KDa]: 100.85928; Specific peptide sequence: NQVALNPQNTVFDAK (see SEQ ID NO.10).

[0073] Example 1: Multi-omics screening of biomarkers

[0074] In this embodiment, saliva samples were collected from pregnant and non-pregnant sows on day 15 post-mating. Proteins were isolated, and proteins differentially expressed in early pregnancy were analyzed and screened using 4D-DIA technology and liquid chromatography-mass spectrometry (LC-MS) non-targeted metabolic multi-omics technology and bioinformatics methods.

[0075] 1.1 Test Samples

[0076] Eight crossbred sows of similar age, parity, body condition, and farrowing history were selected as experimental subjects. All sows were healthy, free of reproductive system diseases, and without genetic defects. Using a random number table, the eight sows were randomly divided into an experimental group and a control group (n=4). The experimental group received fresh semen with a sperm motility ≥0.7, while the control group received semen that had been treated in a 60℃ water bath for 15 minutes and confirmed by microscopic examination to be completely inactivated. The insemination volume for both groups was 80 mL per sow. The experimental procedure strictly followed production standards, and estrus was determined using boar estrus detection and the standing reflex under pressure.

[0077] Saliva was collected from sows on day 15 post-mating, before morning feeding, while the sows were standing. Before collection, the sows' mouths were cleaned with water to remove any feed residue. After the mouths had been chewing for 10-20 minutes, the sows were attracted to chew the gauze using a defatted sterile gauze. After the gauze had been chewed thoroughly, the saliva was squeezed into a centrifuge tube that had been treated with high temperature and high pressure using a self-sealing bag. The tubes were centrifuged at 3000 rpm for 10 minutes. The supernatant was then transferred to a 5 mL cryovial and stored in liquid nitrogen at -80°C for later use.

[0078] 1.24D-DIA proteomics analysis for screening differentially expressed proteins

[0079] 4D-DIA quantitative proteomics combines Data Independent Acquisition (DIA) and high-dimensional (4D) mass spectrometry analysis, improving the accuracy of protein identification and the depth of quantitative analysis. DIA does not rely on pre-selected peptide masses for MS analysis; instead, it systematically acquires all ion fragments across the entire mass range, dividing the full scan range of the mass spectrometer into several windows. It then cyclically selects, fragments, and detects all ions within each window, integrating multiple dimensions of information such as mass-to-charge ratio (m / z), retention time (RT), ionic intensity, and ionic mobility, thereby improving the precision and sensitivity of identification and quantification. 4D-DIA is based on the tims-TOF Pro mass spectrometry platform, using a dual-trapping ion mobility (TIMS) structure and a simultaneous cumulative continuous fragmentation (PASEF) scanning mode for qualitative and quantitative analysis of differential proteins. Its analytical workflow is as follows:

[0080] Salivary protein extraction: The frozen sample was removed, lyophilized, and 800 μL of extraction buffer (containing 8 M urea + 1% SDS + 1 mM PMSF) was added and mixed thoroughly. Then, an equal volume of saturated phenol-Tris-HCl solution (pH 7.8) was added, and the mixture was incubated at 4°C for 30 min, shaking frequently during incubation. The mixture was centrifuged at 7100 rpm for 10 min at 4°C, and the phenol supernatant was collected. Five volumes of pre-cooled methanol solution containing 0.1 M ammonium acetate were added, and the mixture was incubated overnight at -20°C. The mixture was centrifuged at 12000 rpm for 10 min at 4°C, and the precipitate was collected. Five volumes of pre-cooled methanol were added, the mixture was gently mixed, and the mixture was centrifuged at 12000 rpm for 10 min at 4°C, and the precipitate was collected. This process was repeated once. The above steps were repeated twice with acetone instead of methanol to thoroughly remove methanol. The mixture was centrifuged at 12000 rpm for 10 min at 4°C, and the precipitate was collected. After drying at room temperature (generally about 5 minutes), dissolve in sample lysis buffer (containing: 8M urea + 50mM Tris-HCl (pH 8.0) + 1mM DTT) and dissolve at room temperature for 3-5 minutes. Centrifuge the solution at 12000 rpm for 10 minutes at room temperature, collect the supernatant, and centrifuge again to collect the supernatant.

[0081] Trypsin digestion: Based on the determined protein concentration, take 50 μg of protein from each sample and dilute different groups of samples with lysis buffer to adjust to the same concentration and volume. Add 5 mM DTT to the protein solution, mix well, and incubate at 55 °C for 30 min. Then cool on ice to room temperature. Add 10 mM iodoacetamide (IAM) to the solution, mix thoroughly, and incubate at room temperature in the dark for 15 min. Next, add 6 volumes of acetone to the solution to precipitate the protein, and incubate at -20 °C for at least 4 h or overnight. Centrifuge at 8000 g for 10 min at 4 °C to collect the precipitate, and evaporate the acetone for 2-3 min. Redissolve the precipitate with 100 μL of 50 mM NH4HCO3 solution, add 1 mg / mL trypsin (Trypsin-TPCK) at 1 / 50 sample mass, and digest overnight at 37 °C. Adjust the pH to approximately 3 with phosphate to terminate the enzymatic digestion reaction.

[0082] Peptide desalting: The enzymatically hydrolyzed peptides are desalted using SOLA. TM Solid-phase extraction (SPE) 96-well plate and column desalting includes the following steps: (1) Activation: Activate the column with 200 μL of methanol, repeat twice; (2) Equilibration: Equilibrate the column with 200 μL of aqueous solution containing 0.1% (v / v) formic acid, repeat twice; (3) Sample loading: Take 50-500 μL of sample, adjust the vacuum, keep the droplet speed at 1 mL / min (about 1 drop / s), load the sample onto the column, and repeat the loading once after flow-through; (4) Washing: Wash with 200 μL of aqueous solution containing 0.1% formic acid, repeat twice; (5) Elution: Elute the peptide with 150 μL of aqueous solution containing 0.1% formic acid and 50% (v / v) acetonitrile, repeat twice, for a total of 3 times, to obtain 450 μL of eluent, which is then evaporated under vacuum.

[0083] High-resolution protein LC-MS / MS detection: First, prepare the internal standard. Mix each sample with the iRT (indexed retention time) at a volume ratio of 1:20. The iRT standard (Biognosys, ThermoFisher) contains 11 synthetically specific peptides and can be used for chromatographic system calibration and quantitative quality control. Peptides are separated using an EASY-nLC 1200 nano-scale liquid chromatography system. A C18 reversed-phase column (25cm × 75μm ID, 1.6μm C18, purchased from Ionopticks) is used. Mobile phase A is a 0.1% formic acid (FA) aqueous solution, and mobile phase B is a 0.1% FA and 80% acetonitrile (CAN) aqueous solution. The elution is initiated at 5% B at a flow rate of 300 nL / min, increased to 27% B at 45 min, 46% B at 50 min, and 100% B at 55 min, held for 60 min to complete the gradient elution. The separated peptides were directly injected into a Bruker TimsTOF Pro mass spectrometer. The ion source was set to a capillary voltage of 1.4 kV, a drying gas temperature of 180 °C, and a drying gas flow rate of 3.0 L / min. The mass scan range was 100–1700 m / z, and the ion mobility dimension was 0.7–1.3 Vs / cm. 2 The collision energy is 20-59 eV.

[0084] Salivary samples from early pregnancy sows were analyzed using 4D-DIA proteomics technology. Differentially expressed proteins (DEPs) were selected based on a fold change (FC) ≥ 1.2 or ≤ 1 / 1.2 and a p-value < 0.05. p < 0.05 indicated a significant difference, and p < 0.01 indicated a highly significant difference. FC = 0 and FC = inf both represented 'presence / absence' differences. A total of 491 differentially expressed proteins were identified. Compared with the non-pregnant control group, 172 proteins were upregulated and 319 proteins were downregulated in the pregnant group.

[0085] Four reproduction-related functional proteins (TINAGL1, PRCP, PGRMC1, and MESD) were further selected, and their levels were detected using enzyme-linked immunosorbent assay (ELISA) kits to verify the accuracy of the 4D-DIA analysis. The Porcine TINAGL1 ELISA kit (HB665-Pg), Porcine PRCP ELISA kit (HB659-Pg), Porcine PGRMC1 ELISA kit (HB661-Pg), and Porcine MESD ELISA kit (HB663-Pg) were all purchased from Shanghai Hengyuan Biotechnology Co., Ltd.

[0086] Relevant results are as follows Figure 1As shown, from left to right, the data represent the quantitative protein levels in the pregnant and non-pregnant groups. The horizontal axis represents the protein types, and the vertical axis represents the standardized values ​​of the test results. ELISA results showed that TINAGL1, PRCP, and PGRMC1 proteins were upregulated in the pregnant group, while MESD protein was downregulated, consistent with the 4D-DIA quantitative data, confirming the reliability of the 4D-DIA proteomics analysis results.

[0087] 1.3 LC-MS non-targeted metabolomics analysis for screening differentially expressed metabolites

[0088] The same batch of saliva samples was analyzed using LC-MS non-targeted metabolomics technology. The analysis procedure is as follows:

[0089] Sample pretreatment: Pass 1 mL of sample through an SPE solid-phase column, collect 3 mL of methanol eluent, dry the methanol with nitrogen evaporator, then add 300 μL of methanol-water solution containing 4 μg / mL L-2-chlorophenylalanine (methanol:water = 4:1, v / v) to reconstitute the sample, vortex for 1 min, sonicate in an ice-water bath for 10 min, then incubate at -40℃ for 30 min, centrifuge at 4℃ and 13000 rpm for 10 min, aspirate 150 μL of supernatant with a syringe, filter through a 0.22 μm organic phase pinhole filter, transfer to an LC vial, and store at -80℃ until LC-MS analysis.

[0090] Quality control (QC) samples were prepared by mixing equal volumes of extracts from all samples. All extraction reagents were pre-cooled at -20°C before use.

[0091] Liquid chromatography-mass spectrometry (LC-MS) analysis conditions: The analytical instrument was an ACQUITY UPLC I-Class plus ultra-high performance liquid chromatography-tandem QE plus high-resolution mass spectrometer system. Chromatographic conditions: Column: ACQUITY UPLC HSS T3 (100 mm × 2.1 mm, 1.8 μm); Column temperature: 45℃; Mobile phase A was an aqueous solution containing 0.1% formic acid, and mobile phase B was acetonitrile; Flow rate: 0.35 mL / min; Injection volume: 2 μL. Mass spectrometry conditions: Ion source: ESI; Sample mass spectrometry signals were acquired using both positive and negative ion scanning modes.

[0092] Data sample preprocessing: Before pattern recognition, the raw data were preprocessed using the metabolomics software Progenesis QI v3.0 (onlinear Dynamics, Newcastle, UKN) for baseline filtering, peak identification, integration, retention time correction, peak alignment, and normalization. The main parameters were: predictor tolerance: 5ppm / 10ppm (self-built library + METLIN), product tolerance: 10ppm / 20ppm (self-built library + METLIN).

[0093] Product qualitative and quantitative analysis: Compound identification was based on precise mass numbers, secondary fragments, and isotopic distributions. The Human Metabolome Database (HMDB), Lipidmaps (v2.3), the METLIN database, and EMDB 2.0 were used for qualitative analysis. For the extracted data, ion peaks with more than 50% of missing values ​​(0 values) within a group were removed, and 0 values ​​were replaced with half the minimum value. The qualitatively identified compounds were then screened based on a score of 36 (out of 80). Scores below 36 were considered inaccurate and deleted.

[0094] The screening of differentially expressed metabolic biomarkers between pregnant and non-pregnant groups employed a combination of unidimensional and multidimensional analyses. Unsupervised principal component analysis (PCA) was used to observe the overall distribution and data stability of samples between the pregnant and non-pregnant groups. Supervised partial least squares analysis (PLS-DA) and orthogonal partial least squares analysis (OPLS-DA) were used to distinguish metabolite differences between the pregnant and non-pregnant groups and to screen candidate biomarkers. In OPLS-DA analysis, variable weight values ​​(VIPs) were used to measure the expression patterns and reliability of screened metabolites, selecting differentially expressed metabolites suitable for pathway and signal analysis. The t-test was used to verify the differences between groups. A VIP value > 1 for the first principal component of the OPLS-DA model was used as the differential screening criterion. A total of 286 differentially expressed metabolites (DMs) were identified. Among them, 152 metabolites showed an upregulation trend in the pregnant group compared to the control group, while 134 metabolites showed a downregulation trend. These results reveal significant changes in the salivary metabolic profile of sows during early pregnancy.

[0095] 1.4 Combined analysis of proteome and metabolomics

[0096] 1.4.1 Expression Correlation Analysis

[0097] The top 20 differentially expressed proteins and metabolites (TOP20, sorted by p-value) were selected. Based on their relative abundance, Pearson correlation analysis was performed. The Pearson correlation coefficient was used to measure the linear correlation between the relative abundance of proteins and metabolites. The significance of the correlation coefficient was calculated using a t-test, with a threshold of p < 0.05. A correlation heatmap was then plotted based on the correlation analysis results of differentially expressed proteins and metabolites. Figure 2 As shown in the figure, red indicates high expression and blue indicates low expression.

[0098] 1.4.2 Analysis of differentially expressed proteins and metabolites via metabolic pathways

[0099] The 491 differentially expressed proteins screened by 4D-DIA and the 286 differentially expressed metabolites identified by LC-MS were uniformly mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database using UniprotID or KEGG ID. KEGG pathway enrichment analysis (hypergeometric test / Fisher exact test) was performed on the proteome and metabolome respectively. The p-value and false discovery rate (FDR) correction value were calculated, and pathways that were significantly enriched in both omics were extracted (p<0.05). The number of differentially expressed molecules in each pathway was counted, and pathways that appeared more than 3 times in the proteome and more than 1 time in the metabolome were screened. Finally, a total of 23 common pathways were obtained, of which 17 were in the proteome and 3 were in the metabolome. The pathways with the most enriched information in the proteome were purine metabolism and pyrimidine metabolism, and the pathway with the most enriched information in the metabolome was the sphingolipid signaling pathway, as shown in Table 1 below, where n represents the number of common pathways. Metabolic pathway analysis revealed a key metabolic regulatory network in early pregnancy and provided functional priorities for screening candidate biomarkers.

[0100] Table 1. Information on common pathways of differentially expressed proteins and metabolites.

[0101]

[0102]

[0103] 1.4.3 Screening and Analysis of Candidate Protein Biomarkers

[0104] By combining 4D-DIA proteomics and non-targeted metabolomics techniques, differentially expressed proteins were screened based on current research progress and the presence of unique peptides (screened according to a peptide protein library). Finally, 50 candidate proteins, including Q29058, P12069, and A0A287A8E1, were selected for preliminary validation analysis. The specific data are shown in Table 2. In the table below, +57 indicates that the 10th cysteine ​​(Cys, C) in the peptide has a fixed mass modification of +57 Da.

[0105] Table 2 Candidate differentially expressed proteins and their specific peptides

[0106]

[0107]

[0108] Example 2: Quantification of candidate biomarkers using parallel reaction monitoring (PRM) mass spectrometry scanning mode

[0109] Parallel reaction monitoring (PRM) is a high-resolution, high-precision ion monitoring technique based on LC-MS / MS. It selectively acquires the precursor ion of a target peptide during primary mass spectrometry, which then fragments into fragment ions in a collision cell. All fragment ions of the selected target peptide are detected during secondary mass spectrometry, enabling specific analysis of target proteins / peptides in complex samples. In this example, saliva samples were collected from 18 binary sows (n=13) on day 15 post-mating and from non-pregnant sows (n=5). Proteins were isolated, and candidate biomarkers were quantitatively analyzed using PRM scanning and data acquisition.

[0110] 2.1 Protein Extraction and Quantification

[0111] 1000 μL of sample was ultrafiltered using a 10 kDa ultrafiltration tube. The components on the filter membrane were collected, and ddH2O was added to bring the volume to an equal volume. 10 μL of the sample was reserved for quantification, and the remaining sample was stored at -80℃. The extracted protein concentration was determined using the Coomassie Brilliant Blue method (Bradford). 10 μL of BSA standard protein solutions at different concentration gradients and test sample solutions at different dilutions were added to 96-well plates, followed by the rapid addition of 300 μL of G250 staining solution. The plates were incubated at room temperature for 5 min, and the absorbance at 595 nm was measured. Each gradient was repeated three times. A standard curve was plotted using the absorbance of the standard protein solutions, and the protein concentration of the test samples was calculated. The results are shown in Table 3 below, where NP represents the non-pregnant group and P represents the pregnant group.

[0112] Table 3. Protein sample concentrations in the pregnant and non-pregnant groups to be tested.

[0113]

[0114] 2.2 Proteolysis and Desalting

[0115] Take the protein sample concentrated by ultrafiltration (concentration ≥1 μg / μL) and process it according to the trypsin digestion method (DTT reduction, iodoacetamide alkylation, trypsin digestion overnight). The digestion product is desalted using the same SPE steps (methanol activation, pure water equilibration, sample loading, washing, acetonitrile elution). The eluent is freeze-dried to powder and stored at -80℃ for later use. Before use, reconstitute with 100 μL of mobile phase A (0.1% formic acid aqueous solution). For detailed operation, see Example 1.

[0116] 2.3 Fraction Separation

[0117] Prepare mobile phase A (an aqueous solution containing 0.1% (v / v) formic acid) and mobile phase B (an aqueous solution containing 80% (v / v) acetonitrile and 0.1% (v / v) formic acid). Dissolve the lyophilized powder in 100 μL of mobile phase A, centrifuge at 14000 g for 20 min, and add 10 μL of the supernatant to a high-performance liquid chromatograph (HPLC) for separation at a flow rate of 0.7 mL / min. The separation gradient is set as shown in Table 4. Combine the fractions collected from 0 to 72 min into three fractions, lyophilize them, and prepare for HPLC.

[0118] Table 4 Elution gradient for peptide fraction separation

[0119]

[0120] 2.4 Spectral Library Construction – DDA Mode Liquid Chromatography-Mass Analytical Processing

[0121] To ensure the accuracy of PRM targeted quantification, a high-coverage scan of the mixed saliva sample was first performed using data-dependent acquisition (DDA) mode liquid chromatography-mass spectrometry analysis to establish a spectral library of the target peptides for subsequent PRM method parameter optimization.

[0122] Prepare mobile phase A (an aqueous solution containing 0.1% (wt) formic acid) and mobile phase B (an aqueous solution containing 80% (v / v) acetonitrile and 0.1% (v / v) formic acid). Dissolve the lyophilized fraction powder prepared above in 10 μL of mobile phase A, centrifuge at 14000g for 20 min at 4℃, and inject 1 μg of the supernatant sample for liquid chromatography-mass spectrometry (LC-MS) analysis. The elution conditions for LC-MS are shown in Table 5 below.

[0123] Using a Q Exactive HF-X mass spectrometer and Nanospray Flex... TMThe NSI ion source was set to 2.1 kV, the ion spray voltage to 320 °C, and the mass spectrometry was performed in data-dependent acquisition (DDA) mode. The full scan range was m / z 350-1500, the first-order mass spectrometry resolution was set to 120,000 (200 m / z), and the AGC was 3 × 10⁻⁶. 6 The maximum C-trap injection time was 80 ms. The top 40 precursor ions by ion intensity in the full scan were fragmented using high-energy collisional fragmentation (HCD) and detected by secondary mass spectrometry. The resolution of the secondary mass spectrometry was set to 15000 (200 m / z), and the AGC was 5 × 10⁻⁶. 4 The maximum injection time is 45ms, the peptide fragmentation collision energy is set to 27%, and raw mass spectrometry detection data (.raw) is generated.

[0124] Table 5 Elution gradient for liquid chromatography

[0125]

[0126] 2.5 DDA Search Parameters

[0127] The raw mass spectrometry data were processed using Skyline software. The search parameters are shown in Table 6 below.

[0128] Table 6 DDA Search Parameters

[0129]

[0130] 2.6 PRM mass spectrometry acquisition of ion pairs

[0131] PRM mass spectrometry was used to collect ion pairs for quantitative analysis, and the results are shown in Table 7.

[0132] Table 7 Ion pairs acquired by PRM mass spectrometry

[0133]

[0134]

[0135] 2.7 Quantitative Results

[0136] The expression levels of the candidate proteins were differentially analyzed, and the results are shown in Table 8.

[0137] Table 8. Results of PRM quantification and intergroup difference analysis of candidate proteins.

[0138]

[0139]

[0140] 2.8 Clustering heatmap analysis of candidate differentially expressed proteins

[0141] Cluster heatmaps, based on PRM targeting quantification results, analyzed the expression patterns of candidate proteins in saliva of the pregnant (P) and non-pregnant (NP) groups. Figure 3 A clustering heatmap of differentially expressed proteins across different groups is shown. The horizontal axis represents the sample groups (NP group and P group), and the vertical axis represents candidate differentially expressed proteins. Color intensity represents the relative expression levels of the proteins; red indicates high expression, and blue indicates low expression. In the clustering results, proteins marked with a significance level of "1" (e.g., EGFLLALTQGR, FC = 3.26, p = 9.49 × 10⁻⁶) are considered significant. -7 It forms an independent high-expression cluster in group P, and metabolic pathway analysis suggests that it is involved in key pregnancy processes such as embryo implantation and hormone regulation.

[0142] 2.9 Volcano Plot Analysis of Candidate Differential Protein Clustering

[0143] The volcano plot uses log2(FC) as the horizontal axis (reflecting the fold change in protein expression (FC, FC = NP / P) and -log10(p-value) as the vertical axis (reflecting statistical significance). Each point represents a candidate protein. The threshold is set at FC ≥ 1.2 and p < 0.05. Red points represent upregulated proteins in the NP group, green points represent downregulated proteins in the NP group, and gray points represent proteins with no significant difference (Not Significant). The results are as follows: Figure 4 As shown. It can be seen that A0A480KE10 (peptide modification sequence: EGFLLALTQGR, gene name: NAGK), A0A286ZUJ1 (peptide modification sequence: KSDLFQEDLYPPTAGPDAALTAEEWLGGR, gene name: CORO1A), A0A287A042 (peptide modification sequence: ILGTQEPSNVIVK, gene name: MGAM), A0A287AC34 (peptide modification sequence: VLVQNAAGSQEK, ... Genes TLN1, A0A287AP73 (peptide modification sequence: EVSFDVELPK), ITIH3, D0G0C7 (peptide modification sequence: LGGVQFDIDLPNK), A0A287BAB3 (peptide modification sequence: GLEWLAGIYSSGSSTYYADSVK), and A0A287BQU9 (peptide modification sequence: NQVALNPQNTVFDAK) showed significant differences between the pregnant and non-pregnant groups (p<0.05).

[0144] The quantitative results of differentially expressed proteins A0A480KE10, A0A287BAB3, A0A286ZUJ1, A0A287BQU9, D0G0C7, and A0A287A042, A0A287AC34, and A0A287AP73 in the PRM of saliva from pregnant and non-pregnant sows are shown in the table below. Figure 5The x-axis represents the sample grouping (NP group and P group), and the y-axis represents log10 (abuandance), where abuandance is the peak area value of PRM quantification. The relevant results are summarized in Table 9. It can be seen that proteins such as A0A480KE10, A0A287BAB3, A0A286ZUJ1, and A0A287BQU9 are highly expressed in the non-pregnant (NP) group, indicating downregulation in the pregnant (P) group. The D0G0C7 protein is lowly expressed in the NP group, indicating upregulation in the P group.

[0145] Table 9. Results of PRM quantification and intergroup difference analysis of candidate protein biomarkers.

[0146]

[0147] Example 3: Analysis of the Diagnostic Effect of Biomarkers on Pregnancy

[0148] Based on multi-omics joint analysis, PRM targeted quantitative validation, and existing research, the biomarkers of this invention, A0A480KE10, A0A287BAB3, A0A286ZUJ1, D0G0C7, and A0A287BQU9, were screened. ROC curve and AUC data analysis were performed on the aforementioned biomarkers. The receiver operating characteristic (ROC) curve is a line graph constructed with 1-specificity (also known as false positive rate or misreporting rate) as the X-axis and the true positive rate as the Y-axis. It is a comprehensive indicator reflecting the continuous variables of sensitivity and specificity. The true positive rate (TPR) refers to the proportion of all actually positive samples correctly identified as positive; TPR is also known as sensitivity. The false positive rate (FPR) refers to the proportion of all actually negative samples incorrectly identified as positive; FPR equals 1-specificity; it is also known as the misreporting rate. Specificity refers to the proportion of all samples that are actually negative that are correctly predicted as negative.

[0149] ROC analysis showed that A0A480KE10, A0A287BAB3, A0A286ZUJ1, D0G0C7, and A0A287BQU9 had higher diagnostic value on day 15 post-gestation in sows (see [link to analysis]). Figure 6The AUC (Area Under Curve) values ​​were 1, 0.95, 0.88, 0.85, and 0.86, respectively, indicating that the aforementioned biomarkers have high predictive diagnostic value. The optimal thresholds were 811309.39, 1434147.47, 1008424.52, 2230957.10, and 16114232.69 (see Table 10), which correspond to the peak area of ​​PRM quantitative detection when the Youden index is at its maximum value (Youden index = sensitivity + specificity – 1).

[0150] Table 10. Results of Diagnostic Value Analysis of Protein Biomarkers Based on ROC Curves

[0151]

[0152] In production applications, PRM technology is used to quantitatively detect specific peptides of protein biomarkers in the saliva of sows on day 15 of gestation. Based on the peak area integral value, a sample is considered non-pregnant if the peak area of ​​A0A480KE10 (EGFLLALTQGR) is ≥811309.39, otherwise pregnant; similarly, a sample is considered pregnant if the peak area of ​​A0A286ZUJ1 (KSDLFQEDLYPPTAGPDAALTAEEWLGGR) is ≥10038425, otherwise pregnant; and so on. A peak area ≥ 2230957.10 for 0G0C7 (LGGVQFDIDLPNK) indicates pregnancy, otherwise it indicates non-pregnancy. A peak area ≥ 1434147.47 for A0A287BAB3 (GLEWLAGIYSSGSSTYYADSVK) indicates non-pregnancy, otherwise it indicates pregnancy. A peak area ≥ 16114232.69 for A0A287BQU9 (NQVALNPQNTVFDAK) indicates non-pregnancy, otherwise it indicates pregnancy.

[0153] Based on the detection method and the obtained protein biomarker peak area in Example 2, and according to the above judgment rules, the pregnancy judgment results of this invention using protein biomarkers were compared and analyzed with the ultrasound pregnancy diagnosis results (13 pregnant cases, 5 non-pregnant cases). The ultrasound pregnancy diagnosis was initially performed on day 25 after mating and re-examined on day 35 after mating. The results are shown in Tables 11-15, where the true positive rate is the percentage of actually pregnant sows that were detected as pregnant, the false positive rate is the percentage of actually non-pregnant sows that were detected as pregnant, the true negative rate is the percentage of actually non-pregnant sows that were detected as non-pregnant, and the false negative rate is the percentage of actually pregnant sows that were detected as non-pregnant.

[0154] Table 11 Diagnostic Results of Biomarker A0A480KE10

[0155]

[0156] Table 12 Diagnostic Results of Biomarker A0A287BAB3

[0157]

[0158]

[0159] Table 14 Diagnostic Results of Biomarker D0G0C7

[0160]

[0161] Table 15 Diagnostic Results of Biomarker A0A287BQU9

[0162]

[0163] As can be seen from the table above, the protein biomarkers provided by this invention have good accuracy, high sensitivity, specificity, and low false alarm rate in early pregnancy diagnosis. The true positive rate is above 75%, and the true negative rate is above 80%. The true positive rate of A0A480KE10, A0A287BAB3, and A0A287BQU9 is as high as 100%, and the true negative rate of A0A480KE10 and D0G0C7 is as high as 100%, making them suitable as biomarkers for early pregnancy diagnosis in sows.

[0164] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. The application of protein biomarkers or their specific peptides in the preparation of diagnostic kits for early pregnancy in sows, characterized in that, The protein biomarker is at least one of A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9; wherein: The amino acid sequences of A0A480KE10 and its specific peptides are shown in SEQ ID NO.1 and SEQ ID NO.6, respectively; The amino acid sequences of A0A286ZUJ1 and its specific peptides are shown in SEQ ID NO.2 and SEQ ID NO.7, respectively; The amino acid sequences of D0G0C7 and its specific peptides are shown in SEQ ID NO.3 and SEQ ID NO.8, respectively; The amino acid sequences of A0A287BAB3 and its specific peptides are shown in SEQ ID NO.4 and SEQ ID NO.9, respectively; The amino acid sequences of A0A287BQU9 and its specific peptides are shown in SEQ ID NO.5 and SEQ ID NO.10, respectively.

2. The application of reagents for detecting protein biomarkers or their specific peptides in the preparation of diagnostic kits for early pregnancy in sows, characterized in that, The protein biomarker is at least one of A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9; wherein: The amino acid sequences of A0A480KE10 and its specific peptides are shown in SEQ ID NO.1 and SEQ ID NO.6, respectively; The amino acid sequences of A0A286ZUJ1 and its specific peptides are shown in SEQ ID NO.2 and SEQ ID NO.7, respectively; The amino acid sequences of D0G0C7 and its specific peptides are shown in SEQ ID NO.3 and SEQ ID NO.8, respectively; The amino acid sequences of A0A287BAB3 and its specific peptides are shown in SEQ ID NO.4 and SEQ ID NO.9, respectively; The amino acid sequences of A0A287BQU9 and its specific peptides are shown in SEQ ID NO.5 and SEQ ID NO.10, respectively.

3. The application of the reagent for detecting protein biomarkers or their specific peptides according to claim 2 in the preparation of a diagnostic kit for early pregnancy in sows, characterized in that, The protein biomarker is A0A480KE10.

4. The application of the reagent for detecting protein biomarkers or their specific peptides according to claim 2 in the preparation of a diagnostic kit for early pregnancy in sows, characterized in that, The kit is a gas chromatography-mass spectrometry (GC-MS) kit.

5. The application of the reagent for detecting protein biomarkers or their specific peptides according to claim 2 in the preparation of a diagnostic kit for early pregnancy in sows, characterized in that, The protein biomarker is a protein found in sow saliva samples.

6. The application of the reagent for detecting protein biomarkers or their specific peptides according to claim 1 in the preparation of a diagnostic kit for early pregnancy in sows, characterized in that, The sow in question is a crossbred sow.

7. A method for diagnosing early pregnancy in sows for non-diagnostic purposes, characterized in that, Includes the following steps: Saliva samples were collected from sows after mating, and the expression levels of protein biomarkers or their specific peptides in the saliva samples were detected. The expression levels of the protein biomarkers or their specific peptides were used to determine whether the sows were pregnant. The protein biomarker is at least one of A0A480KE10, A0A286ZUJ1, D0G0C7, A0A287BAB3, and A0A287BQU9; wherein: The amino acid sequences of A0A480KE10 and its specific peptides are shown in SEQ ID NO.1 and SEQ ID NO.6, respectively; The amino acid sequences of A0A286ZUJ1 and its specific peptides are shown in SEQ ID NO.2 and SEQ ID NO.7, respectively; The amino acid sequences of D0G0C7 and its specific peptides are shown in SEQ ID NO.3 and SEQ ID NO.8, respectively; The amino acid sequences of A0A287BAB3 and its specific peptides are shown in SEQ ID NO.4 and SEQ ID NO.9, respectively; The amino acid sequences of A0A287BQU9 and its specific peptides are shown in SEQ ID NO.5 and SEQ ID NO.10, respectively.

8. The method for diagnosing early pregnancy in sows for non-diagnostic purposes according to claim 7, characterized in that, The expression levels of protein biomarkers or their specific peptides were detected using PRM-based LC-MS / MS targeted quantification technology. If the expression levels of A0A480KE10 or its specific peptides, A0A286ZUJ1 or its specific peptides, A0A287BAB3 or its specific peptides, and A0A287BQU9 or their specific peptides in the saliva samples of the tested sows were significantly lower than those in non-pregnant sows, the sows were determined to be pregnant; otherwise, they were determined to be non-pregnant. Alternatively, if the expression level of D0G0C7 or its specific peptides in the saliva samples of the tested sows was significantly higher than that in non-pregnant sows, the sows were determined to be pregnant; otherwise, they were determined to be non-pregnant.

9. The method for diagnosing early pregnancy in sows for non-diagnostic purposes according to claim 7, characterized in that, The peak area integral value of protein biomarkers was detected by LC-MS / MS targeted quantitative technology based on PRM. When the peak area of ​​A0A480KE10 or its specific peptide in the saliva sample of the sow was ≥811309.39, or when the peak area of ​​A0A286ZUJ1 or its specific peptide in the saliva sample of the sow was ≥10038425, or when the peak area of ​​A0A287BAB3 or its specific peptide in the saliva sample of the sow was ≥1434147.47, or when the peak area of ​​A0A287BQU9 or its specific peptide in the saliva sample of the sow was ≥16114232.69, the sow was considered non-pregnant; otherwise, the sow was considered pregnant. Alternatively, when the peak area of ​​D0G0C7 or its specific peptide in the saliva sample of the sow was ≥2230957.10, the sow was considered pregnant; otherwise, the sow was considered non-pregnant.

10. The method for diagnosing early pregnancy in sows for non-diagnostic purposes according to claim 7, characterized in that, The early pregnancy diagnosis was made on the 15th day after mating of the sow, which was a crossbred sow.

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