CN116497135A - Microbial marker for predicting or diagnosing risk of non-alcoholic steatohepatitis - Google Patents
Microbial marker for predicting or diagnosing risk of non-alcoholic steatohepatitis Download PDFInfo
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Abstract
The application provides a microbial marker, belongs to the technical field of biology, and particularly relates to a liver disease biomarker and application thereof. The invention discovers that microorganisms such as Staphylococcus, clostridium, blautia in intestinal flora are closely related to nonalcoholic steatohepatitis for the first time, and early diagnosis of liver diseases is carried out through the marker of the invention, and the invention has the advantages of high specificity, strong sensitivity, simple collection and treatment of detection objects, no invasiveness, low cost and the like. The discovery of the marker provides a reference for diagnosing and treating liver diseases.
Description
Technical Field
The application relates to the field of disease diagnosis, in particular to a microbial marker for predicting or diagnosing non-alcoholic fatty liver disease risk.
Background
Nonalcoholic fatty liver disease (NAFLD) is broadly divided into two types. The first type is the most common type, including nonalcoholic fatty liver (NAFL) disease, which is common fatty liver disease. The second type is a severe disease, including nonalcoholic steatohepatitis (NASH), which is a disease that causes inflammation of hepatocytes by fatty liver.
Nonalcoholic steatohepatitis (NASH) is a common, often "silent," liver disease. It is histologically similar to alcoholic liver disease, but occurs in people with little or no alcohol consumption. NASH has the following three main features, and these three main features distinguish it from liver diseases of other metabolic origin: abnormal fat accumulation or deposition in the liver (liver steatosis), liver inflammation, and liver injury or liver tissue injury (liver fibrosis).
Most people with NASH are physically healthy and are unaware that they have liver problems. NASH, however, can be severe and can lead to cirrhosis, where the liver is permanently damaged, scarred, and no longer able to function properly. Cirrhosis can progress even further to hepatocellular carcinoma. About 10% to 15% of patients with histologically confirmed NASH develop cirrhosis and its sequelae, such as liver failure and hepatocellular carcinoma (HCC).
In general, NASH is first suspected in persons found to have increased results in liver tests included in the conventional blood test group, and is suspected when further evaluation shows no obvious cause (e.g. drug therapy, viral hepatitis or excessive alcohol use) to cause liver disease, and when X-ray or imaging studies of the liver show fat. However, in practice the only method that can diagnose NASH and distinguish between non-alcoholic fatty liver and NASH is liver biopsy. In liver biopsy, a needle is passed through the skin to remove a small piece of liver. NASH is diagnosed when the results of histological examination using a microscope confirm that there is inflammation in fat and damage or fibrosis in hepatocytes. An important piece of information obtained from biopsies is whether scar tissue (fibrotic tissue) has formed in the liver. Currently, diagnosis of NASH and confirmation of NASH treatment effect are mainly performed by a histopathological method in which liver tissue is taken out and examined by a microscope.
The lack of a microbial marker suitable for a method for rapidly identifying NASH in the art prevents accurate prevention, early diagnosis and treatment of non-alcoholic steatohepatitis.
Disclosure of Invention
The inventors have found by chance that there is a strong correlation between microorganisms and non-alcoholic steatohepatitis and that this correlation is verified by a verification test. The purpose of the application is to provide a marker capable of detecting diseases so as to solve the problems of early diagnosis and treatment of non-alcoholic steatohepatitis.
In order to achieve the above purpose, the present application specifically provides the following technical solutions:
in one aspect, the invention provides a biomarker for detectable disease, the biomarker comprising at least the following microorganisms: staphylococcus, clostridium, blautia.
In another aspect the present application also provides the use of a microbial marker in the detection of a non-alcoholic steatohepatitis agent, said non-alcoholic steatohepatitis detection being a disease risk prediction, disease diagnosis, monitoring or treatment.
The microorganism is from an animal waste sample;
preferably, the excrement is feces or urine.
The microorganism is derived from human feces and urine samples.
Predicting liver disease risk or disease diagnosis by measuring the abundance of microorganisms in a sample to be measured;
preferably, predicting liver disease risk or disease diagnosis by measuring the abundance of Staphylococcus in the test sample;
preferably, predicting liver disease risk or disease diagnosis by measuring Clostridium abundance in the test sample;
preferably, the risk of liver disease or disease diagnosis is predicted by measuring Blautha abundance in the sample to be tested.
The detection of the microorganism comprises the following detection steps:
a. separating a nucleic acid sample of the microorganism from the object to be measured using a nucleic acid sample separation apparatus;
b. sequencing the nucleic acid sample by using a gene sequencing device to obtain a sequencing result;
c. the sequencing results are compared to known normal levels of gene signature using a comparison device, while the obtained relative abundance values are compared to a predetermined threshold (cutoff) to predict risk of disease or disease diagnosis.
The microorganism further comprises one or more of Corynebacterium, bifidobacterium, allobaculum, bacteroides, psychrobacter, jeotgalicoccus, erysipelotrichaceae p-75-a5, coprobacillus, phascolarctobacterium, coriobacteriaceae, desulfovibrionaceae, clostridiales, saccharibacteria (TM 7).
When the abundance of one or more of Staphylococcus, blautia, corynebacterium, bacteroides, jeotgalicoccus, desulfovibrionaceae, erysipelotrichaceae p-75-a5, coprobacillus, phascolarctobacterium in the sample to be tested is above a threshold, the risk of the subject being ill increases;
the risk of developing a disease in the test subject increases when the abundance of one or more of Clostridium, bifidobacterium, clostridiales, allobaculum, psychrobacter, coriobacteriaceae, saccharibacteria (TM 7) in the test sample is below a threshold.
The abundance of the microorganism is provided based on the calculation of its gene sequence.
Compared with the prior art, the beneficial effects of this application include:
in one aspect, the present application finds and provides a biomarker for a microorganism that is significantly associated with symptoms of non-alcoholic steatohepatitis, which microorganism can be used for early diagnosis of non-alcoholic steatohepatitis. On the other hand, compared with other detection schemes, the method has the advantages of improved judgment accuracy, high specificity, strong sensitivity, simple detection object acquisition and processing, no invasiveness, low cost and the like. In addition, the microbial markers disclosed in the application can provide reference materials for developing microbial preparations for improving the non-alcoholic steatohepatitis, and can also be used for treating the microecological preparations of the non-alcoholic steatohepatitis.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate certain embodiments of the present application and therefore should not be considered as limiting the scope of the present application.
FIG. 1 is a 100-fold (left) and 400-fold (right) magnified image of a group M hepatocyte after staining;
FIG. 2 is a 100-fold (left) and 400-fold (right) magnified image of a group C hepatocyte after staining.
Detailed Description
The term as used herein:
"prepared from … …" is synonymous with "comprising". The terms "comprising," "including," "having," "containing," or any other variation thereof, as used herein, are intended to cover a non-exclusive inclusion. For example, a composition, step, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such composition, step, method, article, or apparatus.
The conjunction "consisting of … …" excludes any unspecified element, step or component. If used in a claim, such phrase will cause the claim to be closed, such that it does not include materials other than those described, except for conventional impurities associated therewith. When the phrase "consisting of … …" appears in a clause of the claim body, rather than immediately following the subject, it is limited to only the elements described in that clause; other elements are not excluded from the stated claims as a whole.
"and/or" is used to indicate that one or both of the illustrated cases may occur, e.g., a and/or B include (a and B) and (a or B).
AUC is the area under the estimated curve, specific meaning is described in Michael J.Pencina Ralph, B.D 'Agrotino Sr, ralph B.D' Agrotino Jr et al Evaluating Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond,2008, 27 (2): 157-172, incorporated herein by reference. The greater the AUC, the greater the diagnostic capacity. For each species, a diagnostic threshold (cutoff) is determined such that the sum of sensitivity and specificity of the diagnosis is highest at this threshold. The detailed determination method of the critical value is as follows: sequencing the relative abundance of the species from small to large, sequentially taking a value as a candidate critical value, calculating the sensitivity and the specificity under the candidate critical value, and taking the candidate critical value with the maximum sum of the sensitivity and the specificity as the final optimal critical value.
Sensitivity is called true positive rate, which is the probability that an actual patient is diagnosed as a patient by an index, i.e., the probability that a patient is diagnosed as positive. The specificity refers to true negative rate, which refers to the probability that an actual non-diseased patient is diagnosed as non-patient by an index, i.e., the probability that a non-patient is diagnosed as negative.
The terms used herein have meanings commonly understood by one of ordinary skill in the art to which the invention pertains. Terms such as "a," "an," and "the" are not intended to refer to only a singular entity, but rather include the general class of entities that can be used to describe a particular embodiment. The terminology herein is used to describe specific embodiments of the invention but their use does not limit the invention unless otherwise indicated in the claims.
In one aspect, the invention relates to a set of micro-biomarkers for predicting a subject's risk of developing non-alcoholic steatohepatitis, said set of micro-biomarkers consisting of one or more of Staphylococcus, clostridium, blautia together with other microorganisms.
In another aspect, the detection of a microorganism described herein comprises:
a. separating a nucleic acid sample of the microorganism from a measurement object using a nucleic acid sample separation apparatus;
b. sequencing the nucleic acid sample by using a gene sequencing device to obtain a sequencing result;
c. the sequencing results are compared to known normal levels of gene signature using a comparison device, while the obtained relative abundance values are compared to a predetermined threshold (cutoff) to predict risk of disease or disease diagnosis.
When the Staphylococcus, clostridium, blautia abundance value is greater than the threshold value, an increased risk of the subject having non-alcoholic steatohepatitis is indicated.
Embodiments of the present application will be described in detail below with reference to specific examples, but it will be understood by those skilled in the art that the following examples are only for illustration of the present application and should not be construed as limiting the scope of the present application. The specific conditions are not noted in the examples and are carried out according to conventional conditions or conditions recommended by the manufacturer. The reagents or apparatus used were conventional products commercially available without the manufacturer's attention.
To verify the findings of the inventors, the inventors constructed NASH models based on mice, and analyzed microorganisms in the mice on the basis of the models, verifying various NASH diagnostic markers.
Example 1NASH modeling and model validation
1.1 rat feeding management
SFP-class male SD rats (3 weeks old) 32 are routinely bred in an environment with constant temperature of 23-25 ℃ and humidity kept at 55%, and ultraviolet irradiation, timed ventilation and illumination and free ingestion are carried out in a breeding room. Water and feed were added daily and the litter was replaced every 2-3 days.
1.2NASH moulding
After 1 week of adaptive feeding, rats were randomly divided into 2 groups: one group is a conventional feed feeding group (control group, abbreviated as C group); the other group is a high-fat feed feeding group (model group, M group for short).
After 4 weeks of high fat diet feeding, rats in the high fat diet feeding group were intraperitoneally injected with 30mg/kg of STZ (30 mg/ml prepared in advance with citric acid buffer, and after 3 days of injection, fasting blood glucose levels were measured). After 5 weeks of high fat feed feeding, all the rat blood was taken into a sterile centrifuge tube, placed at room temperature for 2 hours, centrifuged at 3000rpm for 15min at 4 ℃, and the supernatant was taken to immediately detect blood lipids (HDL-C, TC, TG, LDL). The rats of the conventional feed group and the rats of the high-fat feed group are sacrificed, livers are taken, 4% paraformaldehyde solution is used for fixation, paraffin embedding, slicing and HE staining are carried out, and pathological conditions are observed.
The detection result shows that the blood lipid level of the rats in the M group is obviously higher than that of the rats in the C group. HE staining results are shown in the drawings of the application, wherein fig. 1 is an image magnified 100-fold and 400-fold after staining of group M hepatocytes, and fig. 2 is an image magnified 100-fold and 400-fold after staining of group C hepatocytes. From the HE staining pattern, the M groups of rats developed hepatic cell steatosis and cell balloon-like expansion.
EXAMPLE 2DNA extraction and amplification
2.1 microbiome Total DNA extraction
For various microbiome samples from different sources, according to past project experience, the most suitable total DNA extraction method is selected, simultaneously Nanodrop is adopted to quantify DNA, and the DNA extraction quality is detected by 1.2% agarose gel electrophoresis.
2.2 PCR amplification of target fragments
The PCR amplification is usually performed on variable regions (single or continuous multiple) of rRNA genes or specific gene fragments by taking target sequences such as microbial ribosomal RNA or specific gene fragments capable of reflecting flora composition and diversity as targets, designing corresponding primers according to conserved regions in the sequences, adding sample-specific Barcode sequences.
The PCR amplification adopts Pfu high-fidelity DNA polymerase of the full gold company, and strictly controls the amplification cycle number, so that the amplification conditions of the same batch of samples are consistent while the cycle number is as low as possible. Meanwhile, negative control is arranged, the negative control can detect microbial contamination such as environment, reagent and the like, and any sample group with the strip amplified by the negative control can not be used for subsequent experiments.
2.3 magnetic bead purification recovery of amplified products
1. Adding magnetic Beads (Vazyme VAHTSTM DNA Clean Beads) with the volume of 0.8 times into 25 μl of the PCR product, shaking and fully suspending, adsorbing on a magnetic rack for 5min, carefully sucking out the supernatant with a pipette;
2. adding 20 μl of 0.8 times magnetic bead washing liquid, shaking, suspending, placing on a magnetic rack, adsorbing for 5min, and carefully sucking out supernatant;
3. 200 μl of 80% ethanol is added, and the mixture is reversely placed on a magnetic rack, and is adsorbed to the other surface of the PCR tube by using magnetic beads, and the supernatant is sucked out after full adsorption;
4. standing at room temperature for 5min until alcohol volatilizes completely and magnetic beads crack;
5. adding 25 μl of the solution Buffer for Elution;
6. the PCR tube was placed on an adsorption rack for 5min, fully adsorbed, and the supernatant was removed to a clean 1.5ml centrifuge tube for storage.
2.4 fluorescent quantitation of amplified products
The PCR amplification recovery product was subjected to fluorescent quantitation with a quantitive reagent Quant-iT PicoGreen dsDNA Assay Kit and a quantitation instrument Microplate reader (BioTek, FLx 800). According to the fluorescence quantitative result, mixing the samples according to the sequencing quantity requirement of each sample.
Example 3DNA sequencing
3.1 sequencing library preparation
Sequencing libraries were prepared using TruSeq Nano DNA LT Library Prep Kit from Illumina corporation.
1) Firstly, repairing the sequence End of the amplification product, cutting off a protruding base at the 5 'End of a DNA sequence through an End Repair Mix 2 in a kit, and simultaneously adding a phosphate group and supplementing a missing base at the 3' End;
2) Adding an A base at the 3 'end of the DNA sequence to prevent the DNA fragment from self-ligating, and simultaneously ensuring that the target sequence can be connected with a sequencing joint (the 3' end of the sequencing joint is provided with a protruding T base);
3) Adding a sequencing linker containing a library-specific tag (i.e., index sequence) at the 5' end of the sequence to allow the DNA molecule to be immobilized on the Flow Cell;
4) Adopting BECKMAN AMPure XP Beads, removing the self-connecting segment of the joint through magnetic bead screening, and purifying the library system added with the joint;
5) Carrying out PCR amplification on the DNA fragments connected with the connectors so as to enrich the template of the sequencing library, and purifying the enriched product of the library again by adopting BECKMAN AMPure XP Beads;
6) The final fragment selection and purification was performed on the library by 2% agarose gel electrophoresis.
3.2 high throughput sequencing on-machine
1) Before sequencing on the machine, the library needs to be subjected to quality inspection on Agilent Bioanalyzer, and Agilent High Sensitivity DNA Kit is adopted. The qualified library had and only a single peak and was linker-free.
2) The library was then quantitated using Quant-iT PicoGreen dsDNA Assay Kit on a Promega QuantiFluor fluorescent quantitation system, and the qualified library concentration should be above 2 nM.
3) After the qualified sequencing libraries (Index sequence is not repeatable) are subjected to gradient dilution, mixing according to the required sequencing amount and performing sequencing on the machine after being denatured into single strands by NaOH;
4) If a Miseq sequencer is used for double-ended sequencing, the corresponding reagent is MiSeq Reagent Kit V3 (600 cycles); if Novaseq sequencer was used for double-ended sequencing, the corresponding Reagent was Novaseq 6000SP Reagent Kit (500 cycles).
Due to the characteristic of short MiSeq sequencing read length, and also to ensure sequencing quality, the optimal sequencing length of the target fragment is recommended to be 200-450bp.
Ribosomal RNAs contain multiple conserved regions and highly variable regions, and typically we use the conserved region design primers to amplify single or multiple variable regions of the rRNA gene, followed by sequencing to analyze microbial diversity. Due to the limitation of Miseq sequencing read length, and also to ensure sequencing quality, the optimally sequenced insert ranges from 200-450bp.
Example 4 sequence analysis
1) Firstly, carrying out primary screening on original off-machine data of high-throughput sequencing according to sequence quality; and retesting are carried out on the problem sample.
2) And (3) carrying out library and sample division on the original sequence which is subjected to quality primary screening according to index and Barcode information, and removing the Barcode sequence.
3) And performing sequence denoising or OTU clustering according to the QIIME2 dada2 analysis flow or the Vsearch software analysis flow.
4) The specific composition of each sample (group) at the taxonomic level of different species is presented, knowing the overall profile.
5) According to the distribution of ASV/OTU in different samples, the Alpha diversity level of each sample is evaluated, and whether the sequencing depth is proper or not is reflected by a sparse curve.
6) At the ASV/OTU level, the distance matrix of each sample is calculated, and the beta diversity difference and the difference significance among different samples (groups) are measured by combining a plurality of non-supervision sequencing and clustering means and a corresponding statistical test method.
7) At the species taxonomic composition level, the species abundance composition difference between different samples (groups) is further measured by various unsupervised and supervised sequencing, clustering and modeling means in combination with corresponding statistical inspection methods, and an attempt is made to find marker species.
8) Based on the composition distribution of species in each sample, a correlation network is constructed, a topology index is calculated, and an attempt is made to find key species.
9) Based on the 16S rRNA sequencing results, the flora metabolism function of the sample can be predicted, differential pathways can be found, and the species composition of a specific pathway can be obtained.
Data results
Based on the results of the above examples, statistical test analysis was performed.
Analysis of the alpha diversity of the intestinal flora shows that the difference between the group C and the group M is remarkable, and the diversity of the group M is remarkably reduced. In combination with other findings, intestinal microorganisms have been shown to affect the digestion and absorption of vitamins and the regulation of lipolysis in adipocytes in animals, and differential bacteria such as Coriobacteriaceae, erysipelotrichaceae are associated with the COX2/PGE2 metabolic pathway in group C and M abundances. The correlation data between related microbial markers and non-alcoholic steatohepatitis are shown in the following table:
note that: the mean and 95% ci are both abundance in%.
Based on the analysis of a rat model, the inventor detects and analyzes the abundance of the microorganisms serving as the markers in stool samples of healthy human bodies and non-alcoholic steatohepatitis patients, and verifies that the microbial markers are suitable to be used as markers for disease risk prediction, disease diagnosis or monitoring.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the present application and form different embodiments. For example, in the claims below, any of the claimed embodiments may be used in any combination. The information disclosed in this background section is only for enhancement of understanding of the general background of the application and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Claims (10)
1. Use of a microbial marker in a non-alcoholic steatohepatitis detection reagent, wherein the reagent is suitable for detecting a microorganism comprising: staphylococcus, clostridium, blautia.
2. Use of a microbial marker according to claim 1 in the detection of non-alcoholic steatohepatitis reagents, wherein the detection of non-alcoholic steatohepatitis is a disease risk prediction, disease diagnosis or monitoring.
3. Use of a microbial marker according to any one of claims 1 in the detection of non-alcoholic steatohepatitis reagents, wherein the microorganism is from an animal faecal sample;
preferably, the excrement is feces or urine.
4. Use of a microbial marker according to any one of claims 1 in the detection of non-alcoholic steatohepatitis reagents, wherein the microorganism is derived from human faeces, urine samples.
5. Use of a microbial marker according to claim 1 for the detection of non-alcoholic steatohepatitis agents, characterized in that the risk of liver disease or disease diagnosis is predicted by measuring the abundance of a microorganism in a sample to be tested;
preferably, predicting liver disease risk or disease diagnosis by measuring the abundance of Staphylococcus in the test sample;
preferably, predicting liver disease risk or disease diagnosis by measuring Clostridium abundance in the test sample;
preferably, the risk of liver disease or disease diagnosis is predicted by measuring Blautha abundance in the sample to be tested.
6. Use of a microbial marker according to claims 1-5 in the detection of non-alcoholic steatohepatitis reagents, characterized in that the detection of said microorganism comprises:
a. separating a nucleic acid sample of the microorganism from a measurement object using a nucleic acid sample separation apparatus;
b. sequencing the nucleic acid sample by using a gene sequencing device to obtain a sequencing result;
c. the sequencing results are compared to known normal levels of gene signature using a comparison device, while the obtained relative abundance values are compared to a predetermined threshold (cutoff) to predict risk of disease or disease diagnosis.
7. The use of a microbial marker according to any one of claims 1 to 5 in the detection of non-alcoholic steatohepatitis agents, wherein the microorganism further comprises one or more of Corynebacterium, bifidobacterium, allobaculum, bacteroides, psychrobacter, jeotgalicoccus, erysipelotrichaceae p-75-a5, coprobacillus, phascolarctobacterium, coriobacteriaceae, desulfovibrionaceae, clostridiales, saccharibacteria (TM 7).
8. The use of a microbial marker according to any one of claims 1 to 5 for the detection of non-alcoholic steatohepatitis, wherein the risk of developing a disease in a test subject is increased when the abundance of one or more of Staphylococcus, blautia, corynebacterium, bacteroides, jeotgalicoccus, desulfovibrionaceae, erysipelotrichaceae p-75-a5, coprobacillus, phascolarctobacterium in the test sample is above a threshold value.
9. The use of a microbial marker according to any one of claims 1 to 5 for the detection of non-alcoholic steatohepatitis agents, wherein the risk of developing a disease in a test subject is increased when the abundance of one or more of Clostridium, bifidobacterium, clostridiales, allobaculum, psychrobacter, coriobacteriaceae, saccharibacteria (TM 7) in the test sample is below a threshold value.
10. Use of a microbial marker according to any one of claims 1-5 in the detection of non-alcoholic steatohepatitis agents, wherein the abundance of the microorganism is provided based on the calculation of its gene sequence.
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