CN115011706A - Application of fecal microorganism marker in noninvasive identification/early warning of perinatal fatty liver cows - Google Patents
Application of fecal microorganism marker in noninvasive identification/early warning of perinatal fatty liver cows Download PDFInfo
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- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
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- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
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- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
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- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
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- C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
- C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
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- C12R—INDEXING SCHEME ASSOCIATED WITH SUBCLASSES C12C - C12Q, RELATING TO MICROORGANISMS
- C12R2001/00—Microorganisms ; Processes using microorganisms
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Abstract
The invention discloses application of a fecal microbe marker in noninvasive identification/early warning of perinatal fatty liver cows, and belongs to the technical field of microbes and clinical medicine. The microorganism marker is one or more of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax) and Lacnospiraceae (Lachnospiraceae) in combination. The AUC value of the microbial marker of the invention accords with the diagnostic significance, and has higher clinical diagnosis application value; the application of the microbial marker of the invention can diagnose, identify and monitor the perinatal fatty liver dairy cows, has low cost and simple operation, is a non-invasive and non-invasive detection means, accords with the concepts of animal welfare and healthy breeding, and can be widely applied to the large-scale breeding of the dairy cows.
Description
Technical Field
The invention relates to the technical field of microorganisms and clinical medicine, in particular to application of a fecal microorganism marker in noninvasive identification/early warning of perinatal fatty liver cows.
Background
Fatty liver is a metabolic disorder disease of perinatal dairy cows, especially high-producing dairy cows. The period from 21 days prenatal to 21 days postpartum of the cow is perinatal (Drackley, 1999; Grummer, 1995). Perinatal cows have reduced energy intake and greatly reduced exercise capacity due to reduced feed intake, and production and lactation require a large amount of energy support, which results in the change of fat mobilization, the body consumes own fat, the concentration of free fatty acids (NEFA) in blood is increased, the rate of uptake of free fatty acids by the liver is increased, the NEFA enters the liver and is esterified to form Triglyceride (TG), and the TG can be secreted out of the liver in a hydrolysis mode or in a Very Low Density Lipoprotein (VLDL) mode; but the secretion into the blood in the form of VLDL is inefficient. When the synthesis rate of TG is higher than the transport rate, TG accumulation in the liver is caused, and fat is accumulated in the liver more than the normal content of the liver, which is called fatty liver. The fatty liver disease of the dairy cow is one of the metabolic disorder diseases frequently occurring in the perinatal period of the dairy cow, can seriously cause ketosis, postpartum paralysis and the like, and seriously influences the milk production performance, the reproductive performance and the service life of the dairy cow. The incidence of the disease is particularly frequent in the perinatal period of the dairy cows, the incidence rate is relatively high (5-10% of the dairy cows suffer from severe fatty liver, and 30-40% of the dairy cows suffer from moderate or mild fatty liver), and huge economic loss is caused to the dairy industry. Therefore, accurate diagnosis of perinatal fatty liver cows is beneficial to the health of the cows and can reduce economic loss of a pasture.
At present, the detection methods of fatty liver mainly include liver biopsy, serum physiology and biochemistry, proteomics and metabonomics, digital image technology and the like. Wherein, liver biopsy, namely taking liver tissues from a milk cow living body to measure fat content, is an important examination method for liver metabolism research; at present, the gold standard for diagnosing the fatty liver of the dairy cow is determined by detecting the proportion of hepatic triglyceride in the wet weight of the liver. Normal milk cow liver TG < 1%; mild fatty liver disease with TG < 1% < 5%; moderate fatty liver is obtained when TG is more than 5% and less than 10%; TG > 10% is severe fatty liver. However, the method is an invasive method, has the influence of frosting on the health of the dairy cows and is not beneficial to animal welfare; moreover, poor prognosis can also lead to concurrent infectious diseases. The fatty liver of the cow can be clinically diagnosed through physiological and biochemical serum, the current approved diagnosis method is a Y value method (3 serum biochemical indexes are used for calculation) proposed by Reid, but a relatively large error still exists through research, and the method is not suitable for large-scale pastures.
In the earlier research, the inventor finds that the small molecule metabolite in the excrement can be used as a marker to perform noninvasive diagnosis on the fatty liver dairy cow. However, the measurement process of the small molecule metabolites is relatively complicated, and the abundance and stability of the small molecule metabolites are relatively low. Therefore, the search for new fecal markers for noninvasive identification or early warning of fatty liver cows is still a bottleneck to be broken through in the urgent need of preventing and treating fatty liver diseases of perinatal cows.
Disclosure of Invention
Aiming at the prior art, the invention aims to provide a group of microbial markers and application thereof in noninvasive identification/early warning of perinatal fatty liver cows. The diagnosis capability verifies that the AUC value of the microbial marker of the invention accords with the diagnostic significance and has higher clinical diagnosis application value; the application of the microbial marker of the invention can diagnose, identify and monitor the perinatal fatty liver dairy cows, has low cost and simple operation, is a non-invasive and non-invasive detection means, accords with the concepts of animal welfare and healthy breeding, and can be widely applied to the large-scale breeding of the dairy cows.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect of the present invention, there is provided a use of a microorganism of at least one of the following 1) to 3) as a microbial marker in the preparation of a reagent or a kit for diagnosing fatty liver disease in a perinatal cow:
1) bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum);
2) prevotella saccharivorax (Prevotella multisaccharivorax);
3) bacteria of the family Lachnospiraceae (Lachnospiraceae).
The three microbial markers are separated from the cow dung, the fatty liver diseases of the cow can be accurately identified, the AUC value of each microbial marker accords with the diagnostic significance, and the clinical diagnosis application value is high; moreover, when a plurality of compounds are applied in combination, the AUC is closer to 1 than that of the single compound, and the diagnosis effect is better; when the three microbial markers are used in a combined manner, the identification effect on the fatty liver disease of the dairy cows in the perinatal period is the best.
Thus, preferably, the microbial marker is a combination of three species of Bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum), Prevotella saccharophila (Prevotella multisaccharivorax) and Lachnospiraceae (lactobacillus);
alternatively, the microbial marker is a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum) and a bacterium belonging to the family Lachnospiraceae (lactobacillus).
In a second aspect of the invention, there is provided the use of a reagent for detecting a microbial marker in a metabolite of a cow in the manufacture of a product for non-invasive identification of fatty liver disease in a perinatal cow;
the microorganism marker is one or more of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax) and Lacnospiraceae (Lachnospiraceae) in combination.
Preferably, the microbial marker is a combination of three species of Bifidobacterium pseudolongum (Bifidobacterium pseudolongum), Prevotella saccharivorans (Prevotella multisaccharivorax) and Lachnospiraceae (lactobacillus);
alternatively, the microbial marker is a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum) and a bacterium belonging to the family Lachnospiraceae (lactobacillus).
Further, the reagent is a reagent for detecting the relative abundance of the microbial markers in the dairy cow metabolites.
Preferably, the reagents are reagents for metagenomic sequencing, 16S sequencing or qPCR sequencing.
Preferably, the dairy metabolite is feces.
In the above applications, the method for non-invasively identifying fatty liver disease of perinatal cows comprises the following steps:
(1) collecting feces from the perinatal cows to be detected;
(2) detecting the relative abundance of the microbial markers in the dairy manure;
(3) and identifying whether the perinatal dairy cows to be detected have the fatty liver disease or not based on the relative abundance of the detected microbial markers.
The invention has the beneficial effects that:
(1) the invention provides a microbial marker for non-invasive identification and identification of fatty liver disease cows from the species level for the first time based on a macroproteomics technology. The diagnosis capability proves that the AUC of each microbial marker is higher, and the clinical diagnosis application value is higher.
(2) The microbial marker disclosed by the invention is used for identifying, identifying and monitoring the fatty liver dairy cow, is low in cost and simple to operate, is a non-invasive and non-invasive detection means, accords with the concepts of animal welfare and healthy breeding, can be widely applied to large-scale breeding of the dairy cow in the future, and promotes the healthy and efficient development of the dairy industry.
(3) The invention uses the fecal microorganism marker, and the feces are the terminal metabolites of the dairy cows and can reflect the metabolic condition of the organism; but also can diagnose/early warn the metabolic condition of the cow noninvasively. Secondary damage to the dairy cows caused by liver biopsy is avoided; and the complicated steps and inconvenience brought by binding the cattle during serum collection are also avoided. In addition, compared with the fecal small molecule metabolite discovered by the inventor in the earlier period, the fecal microbial marker has higher and more stable abundance than the small molecule metabolite, and is beneficial to ensuring the specificity and sensitivity of the marker; and the measuring process of the fecal microorganisms is simpler and more convenient than that of the micromolecular metabolites.
Drawings
FIG. 1: random forest analysis of the fecal microorganism, Bifidobacterium pseudoolongum, at MFLvsNorm.
FIG. 2: random forest analysis of the fecal microorganism, Bifidobacterium pseudoolongum, in SFLvsNorm.
FIG. 3: joint analysis in ROC using different species of fecal microorganisms and combinations thereof in the mflvs norm group; wherein B represents Bifidobacterium pseudolongum (Bifidobacterium pseudolongum), L represents Lachnospiraceae (Lachnospiraceae), and P represents Prevotella saccharivorans (Prevotella multisaccharivorax); b + L + P represents a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Lachnospiraceae (Lachnospiraceae) and Prevotella saccharivorans (Prevotella multisaccharivorax); b + L represents Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum) and Lachnospiraceae (Lachnospiraceae) in combination; b + P represents a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum) and Prevotella saccharivorax (Prevotella multisaccharivorax); p + L represents a combination of Prevotella saccharivorans (Prevotella multisaccharivorax) and Lachnospiraceae (Lachnospiraceae).
FIG. 4: joint analysis in ROC using different species of fecal microorganisms and combinations thereof in the sflvs norm group; wherein B represents Bifidobacterium pseudolongum (Bifidobacterium pseudolongum), L represents Lachnospiraceae (Lachnospiraceae), and P represents Prevotella saccharivorans (Prevotella multisaccharivorax); b + L + P represents a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Lachnospiraceae (Lachnospiraceae) and Prevotella saccharivorans (Prevotella multisaccharivorax); b + L represents Bifidobacterium pseudolongum (B.pseudolongum pseudoolongum) and Lachnospiraceae (Lachnospiraceae) in combination; b + P represents a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum) and Prevotella saccharivorax (Prevotella multi saccharorivorax); p + L represents a combination of Prevotella saccharivorans (Prevotella multisaccharivorax) and Lachospiraceae (Lachnospiraceae).
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, 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 application belongs.
As mentioned above, the fatty liver disease of the dairy cow is one of the frequent metabolic disorder diseases of the dairy cow in the perinatal period, and can also cause ketosis, postpartum paralysis and the like seriously affecting the milk production performance, reproductive performance and service life of the dairy cow. Causing huge economic loss to the milk industry. Such losses can be effectively avoided if early identification or corresponding warning measures are possible. The only reliable diagnosis method at present is liver biopsy, which is the measurement of fat content by taking liver tissue from a milk cow living body. However, the method is an invasive method, has the influence of frosting on the health of the dairy cows and is not beneficial to animal welfare; moreover, poor prognosis can also lead to concurrent infectious diseases; therefore, the noninvasive method for early diagnosis of the fatty liver cows has important significance and value.
The proteome covers a wide range, including food, sea, soil, and intestinal tract. With the recent advances and developments in sample processing and mass spectrometry, the use of macroproteins in conjunction with bioinformatics has matured. Metaproteomics also has a high change in analysis of intestinal changes caused by NAFLD. In particular, it may reveal changes in the classification, function and metabolic pathways of the intestinal microbiota.
(1) The invention adopts 4D proteomics technology to carry out macroproteomics analysis on the feces. The advantage of macroproteomics is the comprehensive analysis of the classification and function of microorganisms in the feces.
The method comprises the following specific steps:
extracting protein. Taking out the sample from-80 ℃, weighing a proper amount of tissue sample into a mortar precooled by liquid nitrogen, adding liquid nitrogen, and fully grinding the tissue sample into powder. The samples were sonicated by adding powdered 4 volumes phenol extraction buffer (containing 10mM dithiothreitol, 1% protease inhibitor) to each sample. Adding equal volume of Tris equilibrium phenol, centrifuging at 4 deg.C and 5500g for 10min, collecting supernatant, adding 5 times volume of 0.1M ammonium acetate/methanol to precipitate overnight, and washing protein precipitate with methanol and acetone respectively. And finally, re-dissolving the precipitate by using 8M urea, and determining the protein concentration by using a BCA kit.
② enzymolysis by pancreatin. Performing enzymolysis on each sample protein in equal amount, adding an appropriate amount of standard protein, adjusting the volume to be consistent with the lysate, slowly adding TCA with the final concentration of 20%, uniformly mixing by vortex, and precipitating for 2h at 4 ℃. 4500g, centrifuging for 5min, discarding the supernatant, and washing the precipitate with precooled acetone for 2-3 times. Air drying the precipitate, adding TEAB with final concentration of 200mM, ultrasonically breaking the precipitate, adding trypsin at a ratio of 1:50 (protease: protein, m/m), and performing enzymolysis overnight. Dithiothreitol (DTT) was added to give a final concentration of 5mM, and the mixture was reduced at 56 ℃ for 30 min. Iodoacetamide (IAA) was then added to give a final concentration of 11 mM.
And thirdly, liquid chromatography-mass spectrometry combined analysis. The peptide fragment was dissolved in mobile phase A (0.1% (v/v) formic acid aqueous solution) by liquid chromatography, and then separated by using EASY-nLC 1000 ultra performance liquid system. The mobile phase A is an aqueous solution containing 0.1 percent of formic acid and 2 percent of acetonitrile; mobile phase B was an aqueous solution containing 0.1% formic acid and 90% acetonitrile. Setting a liquid phase gradient: 0-40min, 5% -25% B; 40-52min, 25% -35% B; 52-56min, 35% -80% B; 56-60min, 80% B, the flow rate is maintained at 500 nL/min.
The peptide fragments are separated by an ultra-high performance liquid phase system, injected into an NSI ion source for ionization and then analyzed by Q ExactivetTM Plus mass spectrum. The ion source voltage was set at 2.1kV and both the peptide fragment parent ion and its secondary fragment were detected and analyzed using the high resolution Orbitrap. The scanning range of the primary mass spectrum is set to be 350-1800m/z, and the scanning resolution is set to be 70,000; the secondary mass spectral scan range was then fixed with a starting point of 100m/z and the secondary scan resolution was set to 17,500. The data acquisition mode uses a data-dependent scanning (DDA) program, i.e., after a primary scan, the first 10 peptide fragment parent ions with the highest signal intensity are selected to enter the HCD collision cell in sequence and are fragmented by 28% of fragmentation energy, and secondary mass spectrometry is also performed in sequence. To improve the effective utilization of the mass spectra, the Automatic Gain Control (AGC) was set to 5E4, the signal threshold was set to 20000ions/s, the maximum injection time was set to 100ms, and the dynamic exclusion time of the tandem mass spectrometry scan was set to 30 seconds to avoid repeated scans of the parent ions.
Fourthly, searching and comparing the database. Secondary mass spectral data were retrieved using Maxquant (v1.5.2.8). And (3) retrieval parameter setting: adding a reverse library into the database to calculate false positive rate (FDR) caused by random matching, and adding a common pollution library into the database to eliminate the influence of pollution protein in the identification result; the enzyme cutting mode is set as Trypsin/P; the number of missed cutting sites is set to 2; the First-level parent ion mass error tolerance of the First search and the Main search is respectively set to be 20ppm and 5ppm, and the mass error tolerance of the second-level fragment ions is 0.02 Da. Cysteine alkylation was set as a fixed modification, variable modifications were oxidation of methionine, acetylation of the N-terminus of the protein, deamidation (NQ). The FDR of protein identification and PSM identification is set to be 1%.
(2) Firstly, rejecting unqualified or unreasonable data by data repeatability detection and mass spectrum quality control detection of macro proteome data; the reliability of the screening model is verified by a Pearson correlation coefficient and an OPLS-DA method, and then differentially expressed proteins between a normal group and a diseased group are screened out. Species Annotation MaxQuant (v.1.5.2.8.8) was resolved using the software Unipept (v.2.0.0 https:// unipept.content. be/datasets) and mass spectral datahttp:// www.maxquant.org/)。
(3) The biomarkers of the invention are subjected to a stringent screening process.
(4) We performed analyses on 31 dairy individuals using macroproteomics. Compared with other methods for identifying fatty liver individuals by using fecal microorganism indexes, the method has good verification capability on microorganisms screened at the seed level.
The invention finally discovers 3 species level microbial markers with diagnostic value: bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax), and Lachnospiraceae (Lactobacillus).
The 3 microbial markers have higher identification capability in identifying NormvsMFL. It was also found that Bifidobacterium pseudolongum (Bifidobacterium pseudogonongum) in feces has a higher discriminating power in both NormvsMFL and NormvsSFL, and that Bifidobacterium pseudogonongum may be positively correlated with the thickness of the intestinal mucosa. Since the mucus layer plays a crucial role in intestinal protection, it is important to develop studies on mucus-degrading bacteria for understanding the underlying causes of diseases such as intestinal diseases and for implementing new therapeutic strategies.
3 microbial markers with diagnostic value, which are discovered by the invention, come from the excrement, and are identified by using microorganisms generated by normal metabolism of the dairy cows, so that the time and the convenience are saved, and the diagnostic cost is saved; the diagnosis does not need traditional blood sample collection or operation puncture, is a painless identification marker, and has important significance for the health and safety of the dairy cows and the welfare of animals; the marker provided by the invention is used for identifying and diagnosing the fatty liver disease of the dairy cow, so that the production of the dairy cow is not influenced, and the negative effects of reduction of the yield of the dairy cow, health stress, even concurrent infection and the like caused by blood sample collection, surgical puncture and the like are avoided. Saving diagnosis and treatment cost and promoting high yield and synergism.
The biomarker adopted by the invention is derived from excrement, is a microorganism in intestinal tracts of the dairy cow, can well indicate the metabolic condition of the dairy cow, and can accurately indicate the metabolic condition of the dairy cow through the change of relative abundance content of the microorganism in the excrement for fatty liver of the dairy cow.
In order to make the technical solutions of the present application more clearly understood by those skilled in the art, the technical solutions of the present application will be described in detail below with reference to specific embodiments.
The test materials used in the examples of the present invention, which were not specifically described, were all those conventional in the art and commercially available.
Example 1: screening and discovery of candidate markers-screening and discovery of metabolite differentiation markers for liver biopsy diagnostic populations
First, 31 cows were selected as Discovery sets and classified into normal group (Norm, n ═ 10) and medium fatty liver group (MFL, n ═ 9) severe fatty liver group (SFL, n ═ 12) by liver biopsy.
Collecting the feces of the cows, detecting the corresponding signal abundance of the protein in each sample by a mass spectrometry technology, obtaining the LFQ intensity of the protein in each sample by a non-standard quantitative calculation method, and obtaining a relative quantitative value of each sample according to the LFQ intensity of the protein among different samples.
The method comprises the following steps of firstly calculating the differential expression quantity of protein between two samples in a comparison group, firstly calculating the average value of quantitative values of each sample in multiple times of repetition, and then calculating the ratio of the average values between the two samples, wherein the ratio is used as the final differential expression quantity of the comparison group.
Second step to calculate the significance P-value of the protein in the differential expression between the two samples, the relative quantification of each sample was first log2 (to fit the data to a normal distribution), and then the P-value was calculated using the two-sample two-tailed T-test method. When p-value <0.05, the change in differential expression level exceeded 1.5 as a change threshold for significant upregulation and was less than 1/1.5 as a change threshold for significant downregulation.
The summary data for all differentially expressed proteins in this project is presented in table 1.
Table 1: differentially expressed protein statistics
Example 2: the most fold-changing proteins in the normal (Norm) and diseased groups are almost all derived from the microorganism, Bifidobacterium pseudoolongum.
The macro proteome was screened for 218 differentially expressed protein proteins in mflvs norm and the ten proteins with the greatest fold change were screened, with the fold change being the greatest for protein A0A7ICF4 reaching 70.48, and all of these proteins were from Bifidobacterium pseudoluogum (see table 2). Also we observed the most fold-changing protein F3BBL3 from Lachnospiraceae bacteria in the sflvs norm group in the first ten fold-changing proteins to a fold-changing of 48.37. Another protein is from Treponema paraluisticuli, and the remaining proteins are from Bifidobacterium pseudomonologum (Table 3).
Table 2: proteins with a fold-number top 10 in the MFLvsNorm group
Table 3: proteins with a variable number of top 10 rows in the SFLvsNorm group
Example 3: verification of identification ability of microorganisms-ROC curve and random forest analysis
First, forty microorganisms at species level were selected for random forest analysis, and we observed that the Bifidobacterium pseudoolongum scored the highest on the X-axis in FIG. 1, which also demonstrated that the Bifidobacterium pseudoolongum had a higher ability to differentiate between the MFL group and the Norm group, and we also observed that the Bifidobacterium pseudoolongum ranked higher in FIG. 2, at the fourth position.
We analyzed changes in the abundance of microorganisms using ROC analysis in SPSS and found species-level Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharophila (Prevotella multisaccharivorax) and Muricidae (Lachnospiraceae bacteria) in feces. It has higher verifying ability compared to other microorganisms, as shown in Table 4. Also Bifidobacterium pseudolongum (Bifidobacterium pseudolongum) performed well in SFLvsNorm, but the AUC values of the other two microorganisms were not ideal (table 5).
Table 4: accuracy validation of species level fecal microbiology diagnosis cow metabolic status (MFLvsNorm) 1
1 Note: the fecal microbial population of cows is the first 20 abundant microorganisms.
Table 5: seed of a plantAccuracy validation of microbial diagnosis of cow metabolic status in horizontal feces (SFLvsNorm) 1
1 Note: the fecal microbial population of cows is the first 20 abundant microorganisms.
We used ROC in SPSS for analysis and found that the microorganism bifidus pseudomonas gum in both groups MFLvs Norm and sflvs Norm at the species level, the area under the curve (AUC) was greater than 0.7 in both groups, and as high as 0.867 in MFLvs Norm (table 4), with higher validation ability. The area under the curve also reached 0.725 in SFLvsNorm (Table 5).
Example 4: abundance changes of microorganisms in the Norm-MFL-SFL three groups
The abundance of the microorganisms Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax) and Lachnospiraceae (Lachnospiraceae) in the ROC curve varied as shown in (Table 6), with the enrichment of Lachnospiraceae (Lachnospiraceae) being 3.55E +10 in Norm and increasing nearly twice in the MFL. Also Bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum) has an almost 10-fold increase in abundance in both MFL and SFL states, and in particular a greater increase in MFL.
Wherein the enrichment of Lachnospiraceae (Lachnospiraceae) is 55.78% in Norm and 66.00% in MFL. Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum) was found to be 0.73% abundant in Norm and 6% elevated in MFL and SFL (Table 7).
Table 6: the top 20 microorganisms are abundant at species level (mean. + -. standard deviation)
Table 7: variation of relative proportions of fecal microbial species levels abundance for different metabolic states of cows (mean ± sd) 1
1 Note: the proportion of microorganisms in the feces of the cow is 20% of the total abundance of these microorganisms in the normal state (Norm).
Example 5: joint analysis of microorganisms and microorganisms to improve validation ability
To improve the validation of the microorganisms among the groups, we performed a joint analysis of 3 microorganisms. And (3) performing different permutation and combination on the three microorganism variables by utilizing binary logistic regression in the SPSS, fitting a predicted value after combination, and performing ROC analysis.
Table 8: accuracy analysis for joint diagnosis of metabolic state (MFLvsNorm) of dairy cow by species-level different microorganisms
Table 9: accuracy analysis for joint diagnosis of metabolic state (SFLvsNorm) of dairy cow by species level different microorganisms
The results show (FIGS. 3-4, tables 8-9): the combination of two microorganisms, Bifidobacterium pseudogonorum + Lachnospiraceae, was the best combination in the MFLvsNorm group (Table 8). The combined diagnosis of two microorganisms, Bifidobacterium pseudogonocum + Lachnospiraceae, in the SFLvsNorm group is also one of the best diagnostic combinations (Table 9).
In conclusion, species-level microorganisms of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax) and Lachnospiraceae (Lachnospiraceae) in cow dung can be used as markers for noninvasive diagnosis of perinatal fatty liver cows.
In cow breeding applications, potentially fatty liver affected cows can be identified by detecting the relative abundance of these 3 or 2 (Bifidobacterium pseudoolongum + Lachnospiraceae) microorganisms in the cow feces. When the abundance of Bifidobacterium pseudolongum (Bifidobacterium pseudolongum) and the abundance of drospirenone (Lachnospiraceae) in fecal microorganisms both tend to increase, particularly when all three (plus Prevotella multisaccharivorax) increase, a warning is given that the perinatal cows may be at risk of suffering from fatty liver, and the feeding regimen should be adjusted or adjustments should be made in time to avoid losses. The biomarker provides a new technology and a new method for noninvasive detection and diagnosis of fatty liver diseases of cows in the future.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (8)
1. Use of at least one microorganism of the following 1) -3) as a microorganism marker in the preparation of a reagent or a kit for diagnosing fatty liver disease of a perinatal cow:
1) bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum);
2) prevotella saccharivorax (Prevotella multisaccharivorax);
3) bacteria of the family Lachnospiraceae (Lachnospiraceae).
2. The use according to claim 1, wherein the microbial marker is a combination of three species of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax) and Lachnospiraceae (Lactobacillus);
alternatively, the microbial marker is a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum) and a bacterium belonging to the family Lachnospiraceae (lactobacillus).
3. Use of a reagent for detecting a microbial marker in a metabolite of a cow in the preparation of a product for non-invasive identification of fatty liver disease in a perinatal cow;
the microorganism marker is one or more of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax) and Lacnospiraceae (Lachnospiraceae) in combination.
4. The use according to claim 3, wherein the microbial marker is a combination of three species of Bifidobacterium pseudolongum (Bifidobacterium pseudoolongum), Prevotella saccharivorax (Prevotella multisaccharivorax) and Lachnospiraceae (Lactobacillus);
alternatively, the microbial marker is a combination of Bifidobacterium pseudolongum (Bifidobacterium pseudolongum pseudoolongum) and a bacterium belonging to the family Lachnospiraceae (lactobacillus).
5. Use according to claim 3, wherein the reagent is a reagent for detecting the relative abundance of a microbial marker in a metabolite of a cow.
6. Use according to claim 3 or 5, wherein the reagents are reagents for metagenomic sequencing, 16S sequencing or qPCR sequencing.
7. Use according to claim 3 or 4, wherein the dairy metabolite is faeces.
8. The use according to claim 3 or 4, wherein the method for non-invasively identifying perinatal cow fatty liver disease comprises:
(1) collecting feces from the perinatal cows to be detected;
(2) detecting the relative abundance of the microbial markers in the dairy manure;
(3) diagnosing/or identifying whether the dairy cow to be tested is likely to suffer from the fatty liver disease based on the relative abundance of the detected microbial markers.
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