Early selection evaluation method for grass carp salt tolerance based on serum metabolic markers

Abstract

This invention relates to an early selection and evaluation method for salt tolerance in grass carp based on serum metabolic markers. The method includes: (1) calculating the salinity sensitivity coefficient based on the serum metabolic markers obtained through screening: SSC = (normal control group index value - salinity treatment group index value) / normal control group index value, the larger the value, the more sensitive the fish; (2) calculating the fuzzy membership index based on the SSC value; (3) calculating the weight coefficient of each serum metabolic marker based on principal component analysis. w =Contribution rate of a single indicator / Cumulative contribution rate of principal components; (4) Calculate the comprehensive evaluation value of grass carp's salinity sensitivity based on fuzzy membership index and serum metabolic marker weight coefficient; (5) Salt tolerance assessment: In the early salt tolerance assessment, the higher the comprehensive evaluation value of salinity sensitivity, the worse the salt tolerance. This method can achieve accurate assessment of grass carp's salinity sensitivity by detecting and analyzing the dynamic changes of specific serum metabolic markers.

Description

Technical Field

[0001] This invention relates to a method for early selection and evaluation of salt tolerance in grass carp based on serum metabolic markers. Background Technology

[0002] The information disclosed in this background section is intended only to enhance some understanding of the overall background of the invention and is not necessarily to be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art.

[0003] Soil salinization is a major environmental problem hindering the sustainable development of global agriculture. my country, as one of the countries most severely affected by salinization, possesses 1.487 billion mu (approximately 165 million hectares) of saline-alkali land and 690 million mu (approximately 46 million hectares) of saline-alkali water areas, widely distributed in Northeast, North, and Northwest China. These saline-alkali resources have long been idle, resulting in enormous resource waste and economic losses. In recent years, saline-alkali aquaculture, as an innovative resource utilization model, has received widespread attention both domestically and internationally. This model, through the ecological approach of "using fish to reduce salinity and improve alkali conditions," can not only effectively improve the saline-alkali soil and water environment but also create considerable economic benefits.

[0004] Grass carp (Ctenopharyngodon idellus) is one of my country's most important freshwater economic fish species, consistently ranking first in annual production. Traditionally, grass carp is considered a narrow-haline fish, but recent studies have revealed its tolerance to saline-alkali water environments, making it a potential candidate species for saline-alkali water aquaculture. However, water salinity is a key environmental factor affecting fish survival, growth, and physiological functions; changes in salinity can trigger a series of physiological stress responses in fish. Research shows that salinity stress can lead to metabolic disorders, liver lipid deposition, immunosuppression, and decreased muscle quality in grass carp, severely impacting their aquaculture profitability. Therefore, in-depth analysis of the salt tolerance mechanism of grass carp and the breeding of new salt-tolerant varieties are of great significance for promoting the sustainable development of grass carp aquaculture in saline-alkali lands.

[0005] Currently, the evaluation system for grass carp salinity sensitivity mainly relies on traditional indicators, including phenotypic parameters such as survival rate, growth performance, and behavioral observations. However, these evaluation indicators have significant limitations: firstly, their responses are significantly delayed, only manifesting as slow growth, abnormal behavior, or even death after the fish's physiological balance is significantly disrupted; secondly, these indicators cannot reflect the dynamic changes in the fish's internal physiological metabolism under salinity stress in real time. In contrast, blood metabolic indicators have higher sensitivity and timeliness, exhibiting characteristic changes in the early stages of physiological imbalance, thus more accurately reflecting the grass carp's tolerance to salinity stress. Therefore, establishing a salinity sensitivity evaluation method based on serum metabolic markers provides an early evaluation method for the breeding of salt-tolerant grass carp varieties. It can also be used for real-time monitoring of salinity adaptation during aquaculture, which has significant application value for promoting the development of the aquaculture industry in saline-alkali waters. Summary of the Invention

[0006] This invention addresses the shortcomings of existing methods for evaluating the salinity adaptability of grass carp, such as insufficient sensitivity and delayed timeliness, by innovatively proposing an evaluation method based on serum metabolic biomarkers. This method enables precise assessment of the salinity sensitivity of grass carp by detecting and analyzing the dynamic changes of specific serum metabolic biomarkers.

[0007] The technical solution adopted in this invention is as follows:

[0008] In a first aspect of the invention, a combination of biomarkers for evaluating the salt tolerance of grass carp is provided, the biomarker combination comprising the following substances: poly(2-methacryloyloxyethylphosphorylcholine) (PMPC), D-glutamine, acetylcholine, caproic acid, L-lysine, pantothenic acid, myo-inositol, glycerol, deoxyinosine, dethiobiotin, 1,2-dioleoyl-sn-glycerol-3-phosphate (DOPG), ketoleucine, N-α-acetyl-L-ornithine, 4-acetylbutyrate, and phosphatidylinositol 36:4 (PI 36:4, 36 carbon atoms and 4 double bonds).

[0009] In a second aspect of the invention, the application of the combination of markers in evaluating the salt tolerance of grass carp is provided.

[0010] Specific applications include: (1) comprehensive evaluation of the breeding of new salt-tolerant grass carp varieties; (2) evaluation of stress response under acute salinity stress; and (3) assessment of physiological regulation capacity during chronic salinity adaptation.

[0011] In a third aspect of the present invention, a method for early selective breeding evaluation of salt tolerance in grass carp based on serum metabolic markers is provided, the method comprising the following steps:

[0012] (1) Calculate the salinity sensitivity coefficient based on the serum metabolic markers obtained from screening: SSC = (indicator value of normal control group - indicator value of salinity treatment group) / indicator value of normal control group. The larger the value, the more sensitive the group.

[0013] (2) Calculate the fuzzy membership index based on the SSC value: Xi represents the detection value of the i-th comprehensive index, where Xmin and Xmax are the minimum and maximum values ​​of the index, respectively.

[0014] (3) Calculate the weight coefficient of each serum metabolic marker based on principal component analysis: wj = contribution rate of a single indicator / cumulative contribution rate of principal components;

[0015] (4) Calculate the comprehensive evaluation value of grass carp's salinity sensitivity based on fuzzy membership index and serum metabolic marker weighting coefficient:

[0016] (5) Salt tolerance assessment: In the early salt tolerance assessment, the higher the comprehensive evaluation value of salinity sensitivity, the worse the salt tolerance.

[0017] In step (1), the index value of the normal control group and the index value of the salinity treatment group refer to the content of serum metabolic markers in the normal control group and the salinity treatment group.

[0018] In step (1), the salinity in the normal control group was 0 ppt, and the salinity in the salinity treatment group was greater than 0 ppt.

[0019] In step (2), Xi represents the detection value of the i-th comprehensive index, which is the SSC value calculated for each serum metabolic marker.

[0020] Compared with the related technologies known to the inventors, one of the technical solutions of the present invention has the following beneficial effects:

[0021] This invention innovatively proposes an evaluation method based on serum metabolites. This method can accurately assess the salinity sensitivity of grass carp by detecting and analyzing the dynamic changes of specific serum metabolic markers. It is specifically applicable to the following scenarios: (1) comprehensive evaluation of the breeding of new salt-tolerant grass carp varieties; (2) evaluation of stress response under acute salinity stress; (3) assessment of physiological regulatory capacity during chronic salinity adaptation. The establishment of this technology provides new technical means and evaluation standards for the study of grass carp salt tolerance. Attached Figure Description

[0022] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0023] Figure 1 Principal component analysis of serum metabolic markers showing significant differences under different salinity levels. Detailed Implementation

[0024] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0025] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0026] To enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below with reference to specific embodiments.

[0027] Example 1: Screening of serum metabolic markers under salinity stress

[0028] Grass carp salinity stress experiment design: Grass carp from the Yangtze River system, with an initial weight of 100±2g, healthy, uninjured, and uniform in size, were selected. Three salinity gradient treatment groups were set up: 0ppt (control group), 4ppt, and 8ppt, with three replicates for each treatment group. Ten grass carp were stocked per tank for a 60-day rearing period. During the experiment, commercial formulated feed was provided twice daily at regular intervals, with the feed amount being 1-3% of the fish's body weight and dynamically adjusted according to feeding behavior. Simultaneously, 20% of the water was replaced daily to maintain water quality stability, and analytical grade NaCl was added to maintain the target salinity (controlling error ±0.1g / L).

[0029] Blood collection: Blood was collected at 30 and 60 days. Grass carp were anesthetized with 50 mg / L MS-222 for 1-2 minutes, and 200 μL of tail vein blood was rapidly collected within 1 minute to ensure sample quality. The fish were immediately returned to the rearing tank after blood collection to minimize stress. After the blood samples were allowed to stand at room temperature for 2 hours, the serum was separated by centrifugation at 3000 rpm for 10 minutes and stored at -80℃ for later use.

[0030] Serum metabolic marker detection: 80 μL of serum was collected from each sample, and pre-cooled methanol / acetonitrile mixture was added for protein precipitation. After standing at -20℃ for 30 minutes, the supernatant was collected by centrifugation. Serum metabolites were detected using high-resolution liquid chromatography-tandem mass spectrometry in both positive and negative ion modes. The raw data were converted to mzXML format using ProteoWizard software, and then processed for peak detection, extraction, retention time alignment, and peak area integration. Finally, metabolite annotation was completed using the MS2 database (BiotreeDB, V2.1).

[0031] Serum metabolic biomarker screening: Strict quality control was performed on the metabolite data obtained from annotation. Orthogonal partial least squares discriminant analysis (OPLS-DA) combined with t test (p<0.05) was used to identify metabolites with significant differences between groups (VIP>1). Biomarkers were screened from the metabolites with significant differences. The screening criteria were: (1) statistical significance (p<0.05); (2) trend of change: the content of metabolites showed a significant downward trend with increasing salinity, which was verified by linear regression analysis (p<0.05, R2>0.85); (3) biological relevance: the metabolites should be essential compounds or metabolic derivatives involved in the physiological activities of grass carp. Finally, a combination of salinity-responsive metabolites with potential diagnostic value was obtained.

[0032] Serum metabolic markers were screened using the methods described above (Table 1). A total of 15 serum metabolites with significant differences were identified, and compared with the control group (NC), the salinity treatment group showed a linear decreasing trend. Principal component analysis showed that the screened metabolites could significantly distinguish the metabolic characteristics of grass carp under different salinity treatments. Figure 1 This indicates that the screened metabolites are representative.

[0033] Table 1. Screening of serum metabolic markers in grass carp under different salinities (relative quantification; data standardized).

[0034]

[0035]

[0036] Example 2: Salt tolerance analysis of grass carp of different sizes

[0037] This study used grass carp of different sizes (100g, 200g, and 300g) as experimental subjects, dividing them into four groups: 100g group, 200g group, 300g group, and a control group. The fish were exposed to salinity levels of 4 ppt and 0 ppt (control group) for 30 days. Blood samples were collected, serum was separated, and serum metabolic markers were detected. Principal component analysis was used to determine the weight coefficients of each metabolic indicator, and the comprehensive salinity sensitivity index was calculated using membership functions (Table 6). The results showed that the salinity sensitivity indices for 100g, 200g, and 300g grass carp were 0.550, 0.514, and 0.467, respectively. The data indicate that the salinity sensitivity of grass carp exhibits a significant size dependence, with 100g individuals showing the highest salinity sensitivity, exceeding that of 200g and 300g individuals. This result suggests that smaller individuals (around 100g) are most susceptible to salinity effects during grass carp farming.

[0038] The specific steps include:

[0039] (1) Calculate the salinity sensitivity coefficient (Table 3) based on the serum metabolite content obtained from screening (Table 2): SSC = (index value of normal control group - index value of salinity treatment group) / index value of normal control group. The larger the value, the more sensitive the group. (2) Calculate the fuzzy membership index (Table 4) based on the SSC value: Xi represents the detection value of the i-th comprehensive index, where Xmin and Xmax are the minimum and maximum values ​​of the index, respectively; (3) Calculate the weight coefficient of each serum metabolic marker based on principal component analysis: wj = contribution rate of a single index / cumulative contribution rate of principal components, Table 5; (4) Calculate the comprehensive evaluation value of grass carp's salinity sensitivity based on fuzzy membership index and serum metabolic marker weight coefficients (Table 6): (5) Salt tolerance assessment: In the early salt tolerance assessment, the higher the comprehensive evaluation value of salinity sensitivity, the worse the salt tolerance.

[0040] Table 2. Serum metabolic markers after different salinity treatments.

[0041] Parameters Control group (0 ppt) 100 g (4 ppt) 200 g (4 ppt) 300 g (4 ppt) PMPC 5.23±0.18 4.14±0.21 4.28±0.18 4.41±0.28 D-glutamine 3.73±0.33 2.73±0.24 2.57±0.27 3.15±0.15 Acetylcholine 3.45±0.16 2.32±0.17 1.77±0.16 2.09±0.24 Caproic acid 2.94±0.26 1.27±0.20 1.26±0.23 1.11±0.18 L-Lysine 1.90±0.34 1.11±0.17 1.23±0.22 0.96±0.11 Pantothenic acid 1.65±0.05 0.79±0.05 0.73±0.04 1.18±0.13 Myo-inositol 1.08±0.07 0.46±0.02 0.56±0.05 0.60±0.09 Glycerol 0.91±0.06 0.51±0.11 0.64±0.01 0.65±0.10 Deoxyinosine 0.95±0.08 0.59±0.02 0.79±0.01 0.71±0.03 Dethiobiotin 0.86±0.04 0.59±0.03 0.63±0.03 0.66±0.04 DOPG 0.53±0.04 0.37±0.03 0.45±0.02 0.42±0.02 Ketoleucine 0.50±0.06 0.15±0.02 0.23±0.01 0.21±0.02 N-α-acetyl-l-ornithine 5.01±0.61 2.25±0.21 1.55±0.01 1.76±0.28 4-acetylbutyrate 3.32±0.45 2.49±0.14 2.06±0.19 1.76±0.07 Pi 36:4 7.19±0.51 5.73±0.26 5.17±0.23 5.05±0.08

[0042] Table 3. Salinity sensitivity coefficients for different groups

[0043] Parameters 100g 200g 300g PMPC 0.204±0.041 0.178±0.036 0.155±0.053 D-glutamine 0.263±0.065 0.307±0.073 0.148±0.040 Acetylcholine 0.327±0.050 0.486±0.047 0.395±0.071 Caproic acid 0.575±0.067 0.578±0.076 0.631±0.062 L-Lysine 0.408±0.090 0.345±0.117 0.492±0.058 Pantothenic acid 0.511±0.032 0.550±0.027 0.27±0.084 Myo-inositol 0.573±0.018 0.478±0.047 0.442±0.085 Glycerol 0.447±0.122 0.306±0.009 0.301±0.112 Deoxyinosine 0.355±0.025 0.136±0.009 0.221±0.03 Dethiobiotin 0.288±0.043 0.243±0.035 0.203±0.048 DOPG 0.355±0.05 0.225±0.046 0.2687±0.035 Ketoleucine 0.701±0.033 0.537±0.008 0.602±0.047 N-α-acetyl-l-ornithine 0.559±0.04 0.697±0.001 0.655±0.055 4-acetylbutyrate 0.266±0.042 0.392±0.056 0.482±0.022 Pi 36:4 0.206±0.036 0.284±0.032 0.301±0.011

[0044] Table 4. Membership index of serum metabolic markers after different salinity treatments.

[0045] Parameters 100g 200g 300g PMPC 0.496 0.423 0.361 D-glutamine 0.407 0.481 0.217 Acetylcholine 0.333 0.637 0.463 Caproic acid 0.399 0.403 0.494 L-Lysine 0.402 0.321 0.509 Pantothenic acid 0.844 0.913 0.418 Myo-inositol 0.785 0.628 0.571 Glycerol 0.575 0.372 0.365 Deoxyinosine 0.822 0.132 0.402 Dethiobiotin 0.647 0.539 0.441 DOPG 0.607 0.365 0.446 Ketoleucine 0.75 0.239 0.437 N-α-acetyl-l-ornithine 0.291 0.596 0.503 4-acetylbutyrate 0.287 0.591 0.805 Pi 36:4 0.432 0.652 0.699

[0046] Table 5. Principal component matrix, contribution rate, and weight of serum metabolic markers after different salinity treatments.

[0047]

[0048]

[0049] Table 6. Comprehensive evaluation values ​​of grass carp in different groups

[0050] Grouping 100g 200g 300g S value 0.550 0.514 0.467

[0051] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A combination of serum metabolic markers for evaluating salt tolerance in grass carp, characterized in that, This serum metabolic marker combination includes the following substances: poly[2-methacryloyloxyethylphosphocholine], D-glutamine, acetylcholine, hexanoic acid, L-lysine, pantothenic acid, inositol, glycerol, deoxyinosine, desulfobiotin, 1,2-dioleoyl-sn-glycerol-3-phosphate, ketoleucine, N-α-acetyl-L-ornithine, 4-acetylbutyrate, and phosphatidylinositol 36:

4.

2. The application of the serum metabolic marker combination in claim 1 in evaluating the salt tolerance of grass carp.

3. The application as described in claim 2, characterized in that, Specific applications include: (1) comprehensive evaluation of the breeding of new salt-tolerant grass carp varieties; (2) evaluation of stress response under acute salinity stress; and (3) assessment of physiological regulation capacity during chronic salinity adaptation.

4. A method for early selective breeding evaluation of salt tolerance in grass carp based on serum metabolic markers, characterized in that, The method includes the following steps: (1) Calculate the salinity sensitivity coefficient SSC for each serum metabolic marker in the serum metabolic marker combination obtained by screening according to claim 1: SSC = (normal control group index value - salinity treatment group index value) / normal control group index value. The larger the SSC value, the more sensitive it is. The normal control group index value and the salinity treatment group index value refer to the content of serum metabolic markers in the normal control group and the salinity treatment group. (2) Calculate the fuzzy membership index based on the SSC value: , Represents the detection value of the i-th comprehensive index, where and These are the minimum and maximum values ​​of the indicator, respectively. The detection value of the i-th comprehensive index refers to the SSC value calculated for each serum metabolic marker; (3) Calculate the weight coefficient of each serum metabolic marker based on principal component analysis: wj =Contribution rate of a single indicator / Cumulative contribution rate of principal components; (4) Calculate the comprehensive evaluation value of grass carp's salinity sensitivity based on fuzzy membership index and serum metabolic marker weighting coefficient: ; (5) Salt tolerance assessment: In the early salt tolerance assessment, the higher the comprehensive evaluation value of salinity sensitivity, the worse the salt tolerance.

5. The method for early selection and evaluation of salt tolerance in grass carp based on serum metabolic markers as described in claim 4, characterized in that, In step (1), the salinity in the normal control group was 0 ppt, and the salinity in the salinity treatment group was greater than 0 ppt.

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