Application of metabolite, transcriptional gene or microorganism as marker for sophora flavescens alkalosis of bees

Abstract

The invention relates to the technical field of bee breeding, in particular to application of a metabolite, a transcriptional gene or a microorganism as a marker for sophora flavescens alkalosis of bees. According to the invention, a plurality of markers related to the sophora flavescens alkalosis of bees are obtained through analysis of microorganisms, transcriptomes and metabolites, including a plurality of differentially expressed metabolites, transcriptional genes or microorganisms, and can be used for detecting the sophora flavescens alkalosis of bees, and the markers, especially metabolites of arginine succinic acid, spermidine or arachidonic acid, can be used for detecting the sophora flavescens alkalosis of bees. The transcription gene LOC107998471 and the microorganisms such as Gilliamella, Dorea and Lactobacillus plantarum are most remarkable, and the transcription gene LOC107998471 and the microorganisms such as Gilliamella, Dorea and Lactobacillus plantarum are most remarkable. In addition, the sophocarpidine poisoning of the bees can be relieved by feeding spermidine, and the method has important application value in the field of bee breeding.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bee breeding, and particularly relates to application of metabolites, transcription genes or microorganisms as markers for poisoning of bees by matrine. BACKGROUND

[0002] Bees are an important agricultural pollination medium, which plays an important role in ensuring food safety and promoting crop yield. In addition, bees play an important ecological role in maintaining and promoting biodiversity, protecting rare plants and ecosystem restoration. The health and survival of bees are threatened by a variety of factors, including diseases, parasites, environmental changes and the use of pesticides. Among them, the use of pesticides is considered to be the main factor.

[0003] Biological pesticides are biological products that use organisms or their metabolites to poison, trap or inhibit the normal growth and development of pests, and are an ecological pest control method with high efficiency, low toxicity, good environmental compatibility and strong safety. Matrine is a quinoline alkaloid derived from Sophora flavescens, such as Sophora alopecuroides. It can interfere with acetylcholine receptors (AChR) and acetylcholinesterase (AChE), and is widely used to prevent and control various pests, including white flies, pest mites, aphids and cotton pests, as well as diseases affecting fruits such as apple anthracnose, apple tree rot and grape downy mildew, affecting vegetables, tea trees, Chinese herbal medicines and forest trees.

[0004] Intestinal microbes of bees play an important role in food digestion, immune system regulation and pathogen resistance, thereby maintaining the health and survival of bees. New nicotine and organophosphorus pesticides, including nitenpyram, imidacloprid, thiacloprid, thiamethoxam, phoxim and fipronil, can disturb the abundance of Paenibacillus, Chelidonium majus, Bifidobacterium and Lactobacillus in the intestines of bees. Common pesticides such as glyphosate, imidacloprid, thiamethoxam and thiacloprid have a significant impact on gene expression in bees. These pesticides can down-regulate the expression of genes related to immunity, learning and movement, while up-regulating the expression of detoxification genes. In addition, other pesticides such as cypermethrin, thiophanate-methyl, dimethyldithiocarbamate, phenoxy carboxylic acid, cypermethrin, fluroxypyr and chloropyridine can also affect the immunity, growth and development and learning behavior of bees.

[0005] Although biological pesticides have a significant negative impact on the health of bees, there is little research on their mechanism of action on bees. SUMMARY

[0006] In order to solve the problems existing in the prior art, the present application provides application of metabolites, transcription genes or microorganisms as markers for poisoning of bees by matrine.

[0007] In a first aspect, the present application provides use of a metabolite, a transcribed gene or a microorganism as a marker for poisoning of honeybee by matrine; The metabolite comprises one or more of spermine, spermidine or arachidonic acid; The transcribed gene is LOC107998471 ; The microorganism comprises one or more of Gilliamella , Dorea or Lachnoclostridium .

[0008] The present application finds that, under the stress of matrine at medium-high concentration and for a long time, the microorganisms LOC107998471 , Gilliamella , Dorea and Lachnoclostridium show significant differences, and are consistently correlated with the differential metabolites in correlation analysis. The metabolites of spermine, spermidine, arachidonic acid and the transcribed genes LOC107998471 show significant differences under the stress of matrine at medium-high concentration and for a long time. This indicates that these metabolites, transcribed genes and microorganisms show more significant differences between honeybees poisoned by matrine and honeybees not poisoned by matrine, and can be used as markers for poisoning of honeybee by matrine.

[0009] Further, the use comprises any one of the following: i) determining whether the honeybee to be tested is poisoned by matrine by detecting the level of spermine, spermidine or arachidonic acid in the metabolites of the honeybee to be tested; ii) determining whether the honeybee to be tested is poisoned by matrine by detecting the expression level of LOC107998471 in the genome of the honeybee to be tested; iii) determining whether the honeybee to be tested is poisoned by matrine by detecting the abundance of Gilliamella , Dorea or Lachnoclostridium in the intestinal microorganism of the honeybee to be tested; iv) preparing a kit for use of i), ii) or iii).

[0010] Further, when any one of the following results occurs, it is determined that the honeybee to be tested is poisoned by matrine: i) the level of spermine, spermidine or arachidonic acid in the metabolites of the honeybee to be tested is significantly abnormal compared with the standard metabolite level; ii) the level of LOC107998471 in the genome of the honeybee to be tested is significantly abnormal compared with the standard expression level; iii) the abundance of Gilliamella , Dorea orLachnoclostridium abnormal compared with the standard microbial abundance.

[0011] In a second aspect, the present application provides use of the aforementioned metabolite, transcript or microbial detection reagent in the preparation of a kit for detecting whether the to-be-tested honeybee is matrine-poisoned.

[0012] In a third aspect, the present application provides use of spermidine in the preparation of a medicine for relieving matrine poisoning of a honeybee.

[0013] Further, the use comprises: improving the survival rate of the honeybee by feeding the honeybee poisoned by matrine with spermidine.

[0014] In a fourth aspect, the present application provides a kit for detecting matrine poisoning of a honeybee, which is used for detecting LOC107998471 a detection reagent.

[0015] Further, the detection reagent is a primer pair, which comprises: LOC107998471-F: 5'-CTACTAGACCAGAGCCAGAAAG-3', LOC107998471-R: 5'-CTCGTTGAGAAGCATCCATA-3'.

[0016] In a fifth aspect, the present application provides a medicine for relieving matrine poisoning of a honeybee, which comprises: spermidine.

[0017] The present application has the following beneficial effects: The present application screens the markers (various metabolites, transcript genes and microorganisms) related to matrine poisoning of a honeybee through microbial, transcriptome and metabolite research. Among them, the metabolites spermine, spermidine or arachidonic acid, the transcript genes LOC107998471 and the microorganisms Gilliamella , Dorea and Lachnoclostridium show significant differences in honeybees with or without matrine poisoning, and can be used to detect whether the honeybee is poisoned by matrine, and then applied to detection of diseases of the honeybee, thereby improving the survival rate of the honeybee. In addition, spermidine can also relieve matrine poisoning of the honeybee, and has important value in the field of honeybee breeding. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0019] Figure 1 is the comparison of the control group and the treatment group of the bees provided in Example 1 of the present application; wherein A is the mortality rate, B is the sucrose solution intake level, and C is the body weight.

[0020] Figure 2 is the gene expression profile difference of the control group and the treatment group provided in Example 1 of the present application.

[0021] Figure 3 is the GO function entry involved by the differentially expressed genes compared with the control group and the treatment group provided in Example 1 of the present application.

[0022] Figure 4 is the KEGG pathway involved by the differentially expressed genes compared with the control group and the treatment group provided in Example 1 of the present application.

[0023] Figure 5 is the analysis result of the detoxification factor related differentially expressed genes compared with the control group and the treatment group provided in Example 1 of the present application.

[0024] Figure 6 is the analysis of the significantly different metabolites compared with the control group and the treatment group (D15) provided in Example 1 of the present application.

[0025] Figure 7 is the analysis of the significantly different metabolites compared with the control group and the treatment group (D22) provided in Example 1 of the present application.

[0026] Figure 8 is the Real-time qPCR analysis result provided in Example 1 of the present application. DETAILED DESCRIPTION

[0027] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0028] The experimental methods involved in the following embodiments are all the conventional methods in the art if not specifically mentioned, for example, the experimental manuals in the art can be referred to, or the conditions suggested in the manufacturer's instructions can be followed.

[0029] The experimental materials and reagents involved in the following embodiments can be obtained from commercial channels if not specifically mentioned, for example: Example 1 The present application provides a bee 1. Experimental materials The bees used in the application are from Guizhou Provincial Academy of Agricultural Sciences, the bee colonies are checked every week, healthy bees are used, sucrose solution is provided to the bees, the sucrose solution is replaced daily and dead worker bees are removed, for 7 consecutive days. Then pollen is provided to the bees for 7 consecutive days. The mortality rate of worker bees is calculated, and the mortality rate of the bee colony is less than 10%, which is used for subsequent experiments.

[0030] 2. Experimental method 2.1 Treatment of each experimental group Sucrose solutions containing different concentrations of matrine are provided to the bees in different cages (the concentration of the sucrose solution is 50 w / v%), and the control group (CK) has 6 cages (30 bees per cage, the same below), and the bees are fed with sucrose solution without matrine; the treatment 1 group (T1) has 7 cages, and the bees are fed with sucrose solution containing 1.2 mg / L matrine, the treatment 2 group (T2) has 7 cages, and the bees are fed with sucrose solution containing 10 mg / L matrine, and the treatment 3 group (T3) has 13 cages, and the bees are fed with sucrose solution containing 40 mg / L. Because the higher the concentration of matrine, the more bees lost, therefore, the number of the treatment 3 group is increased more. When feeding, the sucrose solution containing different concentrations of matrine fed in each cage is replaced once a day (no pollen is provided). The culture temperature and humidity are 25°C and 60% respectively, the mortality rate of bees, the sucrose consumption of each bee, and the average weight of bees are calculated every day, and multi-omics analysis is carried out.

[0031] (1) Bee mortality rate = number of bees died on the day / total number of bees.

[0032] (2) Sucrose consumption of each bee = total daily sucrose consumption / (number of bees survived the previous day - number of bees died on the day / 2).

[0033] (3) Average weight of bees = (weight of cage with bees - weight of empty cage) / (number of bees survived the previous day - number of bees died on the day / 2).

[0034] (4) Multi-omics analysis of bees, the control group collects samples on the 8th, 15th and 22nd day, and the three treatment groups collect samples on the 15th and 22nd day, 10 bees in each cage are mixed as one biological sample (bee intestinal sample). Randomly take 3 biological samples of cages (each cage is one repetition) from each group of the control group and the three treatment groups, all samples are inactivated RNA degradation enzyme in liquid nitrogen for at least 5 minutes, and then stored in a -80°C refrigerator for subsequent experimental steps.

[0035] 2.2 Microbial analysis DNA is extracted using a commercially available kit, and the V4 target region of bacterial 16S rRNA gene is amplified, and the primers used for amplification are: Forward primer: 5'-CCTACGGNGCWGCAG-3'; Reverse primer: 5'-GACTACHVGGTACTATCC-3'. Sequencing libraries were generated using the NEBNext® Ultra™ II DNA Library Prep Kit, quantitatively evaluated by Agilent 5400, and then sequenced on the NovaSeq 6000 platform. Species annotation was performed using QIIME2 software. Species cumulative boxplot analysis of 16S rRNA data was performed using the vegan package in R software, and the richness of the microbial community and sample size were visualized. Non-metric multidimensional scaling analysis (NMDS) was performed by the ade4 package and ggplot2 package in R software to reduce the dimensionality of the data and visualize complex and multi-dimensional data. ANOSIM and ADONIS analysis were performed using the vegan package and ggplot2 package in R to analyze the differences between high-dimensional data sets.

[0036] 2.3 Transcriptome DEG analysis (1) For the intestinal samples of the aforementioned control group and 3 treatment groups, mRNA was extracted using a commercially available kit, and in the M-MuLV reverse transcriptase system, mRNA fragments were used as templates and random oligonucleotides as primers to synthesize the first cDNA strand. Subsequently, RNA was degraded using RNase H, and dNTPs were used in the DNA polymerase I system to synthesize the second cDNA strand. Purified double-stranded cDNA was subjected to end repair and tailing treatment, followed by sequencing. Next, cDNA fragments with a length of about 250-300 bp were selected using AMPure XP magnetic beads, and PCR amplification was performed. Finally, the PCR products were purified using AMPure XP magnetic beads, and the library was prepared according to the protocol of the NEBNext® Ultra™ RNA Library Prep Kit (Illumina®), and sequenced on the Illumina NovaSeq 6000 platform.

[0037] (2) Image data measured using a high-throughput sequencer was processed into sequence data (reads) by CASAVA base recognition. The fastp 0.23.1 software was used to filter reads containing adapter sequences, unknown nucleotides (N), and reads with a low quality (q value ≤ 20) of more than 50%, obtaining high-quality reads.

[0038] (3) Differentially expressed genes (DEGs) were screened using edgeR software in CK15 and T15 (15-day samples from the control group and the three treatment groups) and CK22 and T22 (22-day samples from the control group and the three treatment groups) according to the p-value ≤ 0.05. Volcano plots of upregulated and downregulated genes in these control groups were generated and expression analysis was performed using the Novogene Cloud Platform. The DEGs were classified into gene ontology (GO) types using WEGO software. Pathway analysis was performed using the Blastall tool by comparing isoforms with the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. Subsequently, relevant tools from the Novogene Cloud Platform and OmicShare platform were used to create graphs.

[0039] (4) Based on previous studies on the immune response of bees under pesticide stress, cytochrome P450, glutathione S-transferase, UDP-glucuronyltransferase, acetylcholinesterase, and ABC transporter were selected for further research. The expression cluster analysis of the above DEGs was performed using the NovoCloud platform.

[0040] (5) 12 DEGs were selected ( LOC107993345 , LOC107994703 , LOC107998471 , LOC107999176 , LOC108000407 , LOC108001650 , LOC108001900 , LOC108002960 , LOC108002963 , LOC108002964 , LOC108002965 and LOC108003566 Real-time quantitative PCR (qPCR) was performed. Specific primers were designed using Primer 5 based on the corresponding nucleic acid sequences. The PCR cycling conditions were: 95℃ denaturation for 30 seconds; 95℃ denaturation for 10 seconds and annealing and extension at 60℃ for 30 seconds, for 40 cycles. Real-time gene expression levels were measured using 2... −ΔΔCt The transcription of the β-actin housekeeping gene was used as an internal control. The experiment was repeated three times, with three independent biological samples in each repetition.

[0041] Table 1 Primer pairs for qPCR detection

[0042] 2.4 Non-targeted metabolomics analysis of bee gut The honeybee intestinal samples were mixed with pre-cooled 80% methanol, vortexed and centrifuged at 15,000 x g for 20 min at 4 °C. Subsequently, the supernatant was injected into sample vials and analyzed using a Vanquish ultra-high performance liquid chromatography system (Thermo Fisher, Germany) coupled with an Orbitrap Q Exactive™ HF mass spectrometer (Thermo Fisher, Germany). The samples were separated by a Hypesil Gold column (100 x 2.1 mm, 1.9 pm i.d.) at a flow rate of 0.2 mL / min. The eluents were A (0.1% formic acid in water) and B (methanol) in positive mode and A (5 mM ammonium acetate, pH = 9.0) and B (methanol) in negative mode.

[0043] The elution gradient program was as follows: 0-1.5 min, 98% A; 1.5-3 min, A decreased from 98% to 15%; 3-10 min, A decreased from 15% to 0%; 10-10.1 min, A increased from 0% to 98%; 11 min, 98% A; 12 min, 98% A. The mass spectrometer was set to positive / negative ion mode, with a spray voltage of 3.5 kV, a capillary temperature of 320 °C, a sheath gas flow rate of 35 psi, an S-lens radio frequency level of 60, an auxiliary gas flow rate of 10 L / min, and an auxiliary gas heater temperature of 350 °C.

[0044] The raw data of UHPLC-MS / MS were processed by Compound Discoverer 3.1 (CD3.1, Thermo Fisher) to complete the peak alignment, peak extraction, and quantitative analysis of each metabolite. The accurate identification and relative quantification of metabolites were obtained by matching with mzCloud, mzVault, and MassList databases. Subsequently, the metabolites were annotated using KEGG database, HMDB database, and LIPIDMaps database. The significance of metabolites was calculated using t-test, and metabolites with a VIP value greater than 1, a p-value less than 0.05, and a fold change greater than 1.5 were identified as differentially expressed metabolites. Thereafter, the metabolic pathways involved in these differentially expressed metabolites were subjected to enrichment analysis. Among them, metabolic pathways with p < 0.05 were considered to be significantly enriched pathways. All statistical analyses were completed using R, Python, and CentOS software.

[0045] 2.5 Correlation analysis of intestinal microbiota, transcriptomics, and metabolomics Based on the p-value, the top 20 differentially expressed metabolites and the top 10 differentially expressed bacterial genera were selected for correlation analysis. Furthermore, based on transcriptomics and metabolomics results, differentially expressed genes and metabolites were selected from different comparison groups for correlation analysis and KEGG enrichment analysis of differentially expressed genes and metabolites.

[0046] 3. Experimental Results 3.1 Toxicity of matrine to bees like Figure 1 As shown, the survival rate of bees decreased significantly in all three treatment groups, with the largest decrease observed in treatment group 2 (T2). However, the bees' sucrose consumption and body weight did not change significantly.

[0047] 3.2 Effects of matrine treatment on the microbial community The results showed that at the genus level, Gilliamella , Snodgrassella and Pseudomonas It was the most abundant genus in both the control and treatment groups. On day 22, three core bacterial groups were identified in both the control and treatment groups. Gilliamella , Snodgrassella and Lactobacillus ), while compared with the control group, Dorea and Lachnoclosdium Significant differences were observed.

[0048] 3.3 Effects of matrine treatment on DEGs The quality control process resulted in 24 datasets, each containing between 40,710,464 and 50,635,176 reads. The proportion of bases with a quality value greater than or equal to 20 in the sequencing data ranged from 97.33% to 97.65%.

[0049] (1) Differences in gene expression profiles of honeybees under matrine treatment In the comparisons between CK_D15 and T1_D15, CK_D15 and T2_D15, CK_D15 and T3_D15, CK_D22 and T1_D22, CK_D22 and T2_D22, and CK_D22 and T3_D22 (CK represents the control group, T1-T3 represent treatment groups 1-3, D15 represents treatment day 15, and D22 represents treatment day 22), 196, 829, 295, 110, 145, and 189 differentially expressed genes (DEGs) were identified, respectively. The number of upregulated genes in these comparison groups were 48, 117, 55, 33, 36, and 49, respectively, and the number of downregulated genes were 148, 712, 240, 77, 109, and 140, respectively. Venn diagram analysis showed that in the three D15 comparison groups, there were 8 and 54 co-upregulated genes, respectively. Figure 2and b) in Table 2. In contrast, there were 2 and 4 commonly up- and down-regulated genes in the three D22 comparison groups, respectively (c and d in Table 2). Among them, the number of differentially expressed genes was the most abundant in T2 treatment (10 mg / L matrine), especially in D15. Figure 2

[0050] (2) Function and pathway annotation of DEGs In the comparisons of CK_D15 vs. T1_D15, CK_D15 vs. T2_D15, CK_D15 vs. T3_D15, CK_D22 vs. T1_D22, CK_D22 vs. T2_D22 and CK_D22 vs. T3_D22, the differentially expressed genes (DEGs) were involved in 225, 455, 259, 148, 304 and 275 GO functional terms, respectively (a-f in Table 3). In the three treatment groups (T1, T2, T3) at D15, catalytic activity, acting on proteins and transport items were significantly enriched (p<0.05). Figure 3

[0051] Among them, the functional terms related to phosphate or phosphoric compound metabolism were enriched in T2 and T3 groups at D15, the functional terms related to oxidation activity and oxidation-reduction were enriched in T1 and T2 groups at D22, and the functional terms related to pyrophosphatase activity and hydrolase activity acting on acid anhydrides were enriched in T3 group at D22.

[0052] In the comparisons of CK_D15 vs. T1_D15, CK_D15 vs. T2_D15, CK_D15 vs. T3_D15, CK_D22 vs. T1_D22, CK_D22 vs. T2_D22 and CK_D22 vs. T3_D22, the differentially expressed genes (DEGs) were associated with 47, 64, 39, 22, 38 and 35 KEGG pathways, respectively (a-f in Table 4). These pathways mainly involved in metabolism, organismal systems, environmental information processing, cellular processes and genetic information processing, etc. Among them, Wnt signaling pathway, FoxO signaling pathway, mTOR signaling pathway, Toll and Imd signaling pathway and oxidative phosphorylation pathway were the top five pathways with the most enriched genes. Figure 4

[0053] (3) Analysis of DEGs related to bee detoxification factors The present application further analyzes the DEGs related to detoxification factors in the comparison of each control and treatment group at D15 and D22, and obtains 95 DEGs. Among them, 13 genes are extremely significantly different, which include 8 cytochrome P450 protein coding genes, 1 glutathione S-transferase protein coding gene, 2 UDP-glucuronosyltransferase protein coding genes and 2 acetylcholinesterase protein coding genes (a-d in Table 5). Figure 5 ​​​). Matrine treatment induced the expression of most detoxification factor-encoding genes, while a few genes were inhibited.

[0054] 3.4 Effect of matrine treatment on metabolites Differentially expressed metabolites between the control and the three treatment groups were mainly enriched in ABC transporters, cysteine and methionine metabolism, purine metabolism, tyrosine metabolism, drug metabolism-cytochrome P450, cytochrome P45 metabolism of exogenous substances, and glutathione metabolism. As shown in Figure 6 and Figure 7 and as shown in the following table, glutathione and spermidine were the most common metabolites, while glutathione metabolism, ABC transporters, cysteine and methionine metabolism were the most common pathways.

[0055] Table 2 KEGG enrichment of differentially expressed metabolites between the control and the three treatment groups

[0056] 3.5 Metabolome and microbiome analysis The present application screened a number of relevant microorganisms and metabolite combinations that showed significant relevance in the comparison of T2_D22 and T3_D22 with CK_D22 simultaneously, the main metabolites involved in 15 pairs were 2-[(3S)-1-(2-chlorobenzyl)-3-pyrrolidinyl]-5-methyl-1,3,4-oxadiazole, gamma-glutamylleucine, argininosuccinic acid, 1,3-dimethyl-6-(trifluoromethyl)-1H-pyrazolo[3,4-b]pyridin-4-ol, 2-[5-(2-hydroxypropyl)oxolan-2-yl]propanoic acid, 5-(2,5-dihydroxyhexyl)oxolan-2-one, 6-pentyl-2H-pyran-2-one, N-(2-morpholinylphenyl)-2-furan carboxamide, and phosphatidylcholine. The intestinal flora involved was Dorea and Lachnoclostridium .

[0057] Table 3 Correlation of differential metabolites and microbiota

[0058] 3.6 Metabolome and transcriptome analysis The present application used KEGG pathways as analysis items to identify pathways that were commonly enriched in each comparison group (treatment group T vs. control group CK) in metabolomics and transcriptomics. Subsequently, items that were commonly enriched in multiple (≥2) comparison groups were further screened. In addition, correlation analysis between metabolomics and transcriptomics was performed.

[0059] The study identified seven co-enriched KEGG pathways. These pathways included: arginine and proline metabolism, β-alanine metabolism, cysteine ​​and methionine metabolism, phototransduction-Drosophila metabolism, purine metabolism, starch and sucrose metabolism, and valine, leucine, and isoleucine degradation. Spermidine showed significant co-enrichment in both metabolomics and transcriptomics analyses of the two comparison groups. Spermidine was significantly enriched in both the arginine and proline metabolic pathway and the β-alanine metabolic pathway. LOC107998471 ( Aldh Arachidonic acid was co-enriched with five transcription genes in the phototransduction-Drosophila pathway. LOC108004131 ( myosin-IIIb ), LOC107998381 、( inaE ) LOC107995353 ( trpl ), LOC108001544 ( Trpgamma )and LOC108003363 ( CaMKII (Common enrichment.) Moreover... myosin-IIIb , inaE and CaMKII It was correlated with arachidonic acid. Furthermore, in both treatment groups (T2_D15 vs. CK_D15, T3_D15 vs. CK_D15), inaE and CaMKII There is also a correlation between them.

[0060] Table 4. Metabolites and transcribed genes enriched in the same KEGG pathway

[0061] 3.6 qPCR experimental verification This invention further uses qPCR detection with three bees in the control group and three bees in the experimental group (T1) for verification. The following primer pairs were used for detection: LOC107998471-F:5'-CTACTAGACCAGAGCCAGAAAG-3', LOC107998471-R:5'-CTCGTTGAGAAGCATCCATA-3'.

[0062] The results are as follows Figure 8 As shown. CK is the average of 3 bees in the control group, and T1 is the average of 3 bees in the treatment group, as shown. Figure 8 The results show that group T1 LOC107998471 On day 15, the expression level was significantly lower than that in the CK group. This further proves... LOC107998471 It can be used to identify matrine poisoning in bees.

[0063] 3.7 The application further provides a method for verifying the alleviating effect of spermidine on matrine toxicity, which has the following procedures: 1. Preparation of experimental materials 1.1 Experimental bee colony: Healthy Apis cerana cerana bees are selected, and a normal oviposition season and a colony strength of 5-8 colonies are selected. The number of queen cells is predicted to be about 10, so as to ensure that about 1800 worker bees can leave the hive the next day. If the number of colonies is insufficient or oviposition is poor, appropriate measures such as limiting the number of queen cells for oviposition need to be taken.

[0064] 1.2 Constant temperature and humidity box (artificial climate box): Set conditions: 35°C, 60% humidity, no light or 25°C, 60% humidity, no light.

[0065] Pre-start and disinfection: one day before the experiment (DAY0), start the constant temperature and humidity box and run to ensure stable environment in the box. The inside of the box is thoroughly disinfected with 75% medical alcohol.

[0066] 1.3 Pollen and sugar Provide pollen and sugar solution (white sugar and water in a mass ratio of 1:1).

[0067] 2. Experimental operation 2.1 Queen cell extraction (DAY0) and honeybee sub-packaging (DAY1) 2.1.1 Queen cell extraction (DAY0): in the afternoon, queen cells are extracted from the colony, and the queen cell cover is covered with gauze to ensure that 1350-1800 worker bees leave the hive the next day. The queen cell is placed in the constant temperature and humidity box, which is set to 35°C, 60% humidity, and no light to promote the hatching of honeybees.

[0068] 2.1.2 Honeybee sub-packaging (DAY1): the next morning, the worker bees after leaving the hive are sub-packaged into culture boxes, 30 worker bees per box, and the genetic background of each box of honeybees is kept as consistent as possible.

[0069] 2.1.3 The incubator is divided into 6 groups, numbered in order, which are: blank control CK (5 boxes), spermine treatment group (5 boxes), spermine + matrine treatment group (in which the syringe of group 5 is spermine and matrine, and the syringe of group 5 is spermine + matrine mixed with sugar water), glutathione treatment group (5 boxes), glutathione + matrine (in which the syringe of group 5 is glutathione and matrine, and the syringe of group 5 is glutathione + matrine mixed with sugar water), matrine treatment group (in which the syringe of group 5 is sugar water and matrine, and the syringe of group 5 is matrine sugar water) 2.1.4 Feeding: The divided honey bees need to be fed with sugar water and pollen balls. Sugar water is fed through a syringe, about 1-2 ml per syringe. Pollen balls are placed at the bottom of the incubator, about 0.5 g per pollen ball.

[0070] 2.2. Early stage of honeybee culture (DAY1~DAY7) (incubator settings: 35℃, 60% humidity, no light) 2.2.1 Pollen, sugar water feeding: from (DAY1) to (DAY5); honey bees need to be continuously fed with sugar water and pollen balls, and sugar water and pollen balls need to be replaced daily, and dry and wet cotton balls are used to clean the bottom of the box to maintain a good feeding environment. Pollen balls fed from DAY1 to DAY5 are mixed with honeybee intestinal homogenate.

[0071] 2.2.2 Pollen ball configuration: take 15g pollen balls as an example, 10g pollen and 5ml honeybee intestinal homogenate are needed. Among them, 5ml honeybee intestinal homogenate is obtained by adding 5 honeybee intestines into 5ml buffer mixture (2.5ml 1×PBS + 2.5ml sugar water) and grinding, and the buffer mixture needs to be mixed first before adding the honeybee intestine for grinding.

[0072] Table 5 Treatment methods of different treatment groups (1-7Day)

[0073] 2.2.3 Pollen, sugar water feeding: from (DAY6) to (DAY7), ordinary pollen balls are fed, without mixing intestinal homogenate.

[0074] 2.3. Poisoning and detoxification treatment (DAY8~DAY22) (incubator conditions set to 25℃, 60% humidity) 2.3.1 Mixed pesticide and mixed antidote sugar water feeding: from (DAY 8), no longer fed pollen pellets, continuously fed different pesticides or antidotes, etc. This treatment lasts until (DAY 22). When the pesticide sugar water is replaced every day, record the death of the bees, and the weight of the sugar water.

[0075] From (DAY 8), feeding and injection color usage instructions: Table 6 Treatment method of different treatment groups (8-22Day)

[0076] 2.3.2 Sugar water weighing: When replacing sugar water, attention should be paid to that the sugar water is not spilled, and weighing is carried out, and the weight of the old sugar water replaced and the new sugar water added is recorded. When the sugar water mixture is weighed, the syringes of the same color in the same box can be weighed together, and the syringes of different colors need to be weighed individually.

[0077] 2.3.3 Pesticide concentration distribution: Blank control group CK: no pesticide needs to be mixed, only pure sugar water (sugar: water = 1:1 w / w) is used for feeding.

[0078] Spermine: concentration of 10 mg / L Spermine + Matrine mixed sugar water: Spermine concentration is 10 mg / L, and Matrine concentration is 40 mg / L.

[0079] Glutathione: concentration of 350 mg / L Glutathione + Matrine mixed sugar water: Glutathione concentration is 350 mg / L, and Matrine concentration is 40 mg / L.

[0080] Matrine: pesticide concentration is 40 mg / L.

[0081] 2.4. Dissection: on the 22nd day (DAY 22), the remaining bees are dissected, which is the 14th day after pesticide treatment, and partial dissection is carried out on the treatment group and the blank control group (treatment 14d) (30 bees are dissected in each group).

[0082] Finally, it should be pointed out that the above examples are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. The application of metabolites, transcribed genes, or microorganisms as biomarkers for matrine poisoning in bees; The metabolites include: One or more of argininosuccinic acid, spermine, or arachidonic acid; The transcription gene is LOC107998471 ; The microorganisms include: Gilliamella , Dorea or Lachnoclostridium One or more of them.

2. The application according to claim 1, characterized in that, The application includes any of the following: i) Determine whether the bees being tested are poisoned by matrine by detecting the levels of arginine succinic acid, spermine, or arachidonic acid in the metabolites of the bees being tested; ii) By detecting the genome of the bee being tested LOC107998471 The expression level was used to determine whether the bees being tested were poisoned by matrine. iii) By detecting the gut microbiota of the bees being tested Gilliamella , Dorea or Lachnoclostridium The abundance of matrine was used to determine whether the bees being tested were poisoned by matrine. iv) Prepare kits for use as in i), ii), or ii).

3. The application according to claim 2, characterized in that, The test case is determined to be poisoned by matrine in bees when any of the following results are observed: i) The levels of arginine succinic acid, spermine, or arachidonic acid in the bee metabolites being tested were significantly abnormal compared to the levels of standard metabolites; ii) In the genome of the bee to be tested LOC107998471 The levels were significantly abnormal compared to the standard expression levels; iii) In the gut microbiota of the bees being tested Gilliamella , Dorea or Lachnoclostridium The abundance of these microorganisms was significantly abnormal compared to the standard microbial abundance.

4. The use of the detection reagents for metabolites, transcription genes or microorganisms described in any one of claims 1-3 in the preparation of a kit for detecting whether a bee is poisoned by matrine.

5. Application of spermidine in the preparation of drugs for relieving matrine poisoning in bees.

6. The application according to claim 5, characterized in that, The application includes improving the survival rate of bees by feeding them spermidine when they are poisoned by matrine.

7. A kit for detecting matrine poisoning in bees, characterized in that, include: Used for detection LOC107998471 The testing reagents.

8. The reagent kit according to claim 7, characterized in that, The detection reagent is a primer pair, including: LOC107998471-F:5'-CTACTAGACCAGAGCCAGAAAG-3', LOC107998471-R:5'-CTCGTTGAGAAGCATCCATA-3'.

9. A drug for relieving matrine poisoning in bees, characterized in that, Including spermidine.

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