CN113862382B - Application of biomarker of intestinal flora in preparation of product for diagnosing adult immune thrombocytopenia - Google Patents
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Abstract
The invention discloses application of a biomarker of intestinal flora in preparing a product for diagnosing adult immune thrombocytopenia. According to the invention, by performing shotgun metagenome sequencing on an adult immune thrombocytopenia patient, a flora with abundance difference from that of a normal person in the intestinal tract of the immune thrombocytopenia patient is discovered for the first time. Further screening and analysis of the differential flora, the differential flora is found to have higher sensitivity and specificity for diagnosing diseases, which suggests that early detection and auxiliary diagnosis of adult immune thrombocytopenia can be realized by detecting the relative abundance of the flora.
Description
Technical Field
The invention belongs to the technical field of biological medicines, and particularly relates to application of a biomarker of intestinal flora in preparation of a product for diagnosing adult immune thrombocytopenia.
Background
Adult immune thrombocytopenia (Immune thrombocytopenia, ITP) is an autoimmune hemorrhagic disease characterized by isolated thrombocytopenia, the pathogenesis of which is primarily increased antibody-mediated platelet destruction and reduced thrombopoiesis. Adult immune thrombocytopenia often manifests itself as skin mucosal bleeding, menorrhagia, and even life threatening visceral or intracranial bleeding.
The pathogenesis of immune thrombocytopenia is complex, variable and highly heterogeneous, and new pathogenesis is continuously revealed in recent years, thus providing a new target for disease treatment. Previous studies have shown that an adult immune platelet patient has platelets recovered progressively and maintained for years following a fecal transplant. In studies of fecal transplantation for the treatment of clostridium difficile infection, fecal transplantation was found to induce the development of new diseases such as rheumatoid arthritis, xerosis and immune thrombocytopenia. These suggest that the intestinal flora has an important intrinsic link with the occurrence of immune thrombocytopenia.
Given the important role of intestinal flora in a variety of autoimmune diseases, it is speculated that intestinal flora may also play a critical role in the occurrence of immune thrombocytopenia. However, there is no research on the composition structure of intestinal flora of immune thrombocytopenia, and no reliable biomarker exists.
Disclosure of Invention
The invention aims to provide a group of biomarkers of intestinal flora and application thereof in preparing a product for diagnosing or assisting in diagnosing adult immune thrombocytopenia.
In order to achieve the above object, the present invention provides a novel use for understanding the biological markers of the sugar prasugrel bacteria Prevotella saccharolytica, the blackfungus Prevotella nigrescens, the zebra prasugrel bacteria Prevotella maculosa, the Prevotella sp.c561, the Bifidobacterium sp.12_1_47BFAA, the Bifidobacterium longum Bifidobacterium longum, the Clostridium sp.dl-VIII, the enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, the myxosporean fibrous bacteria Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and the clara paratyphi Paraprevotella clara.
The present invention provides the use of a biological marker known as septoria saccharoply Prevotella saccharolytica, septoria melanosis Prevotella nigrescens, septoria zebra Prevotella maculosa, prevotella sp.c561, bifidobacterium sp.12_1_47bfaa, bifidobacterium longum Bifidobacterium longum, clostridium sp.dl-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, myxosporean fibers Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and clayey eplery Paraprevotella clara in any of the following A1) -A3):
a1 Preparing a product for diagnosing or aiding in diagnosing immune thrombocytopenia;
a2 Preparing a product for predicting or aiding in predicting the risk of immune thrombocytopenia;
a3 A product for distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia.
In the application, each biomarker can be used as a marker for diagnosing immune thrombocytopenia, and whether the person to be tested has immune thrombocytopenia or has the risk of immune thrombocytopenia or is distinguished from non-immune thrombocytopenia can be judged by detecting whether one or two or more of the biomarkers exist in the fecal sample of the person to be tested or detecting the relative abundance value of the biomarkers in the fecal sample of the person to be tested. Further, these biomarkers can also be used to screen for drugs to treat immune thrombocytopenia or monitor the therapeutic effect of patients with immune thrombocytopenia.
In order to achieve the above object, the present invention further provides a method for detecting the following biomarkers: novel applications of substances of Prevotella saccharolytica Prevotella saccharolytica, prevotella melanogaster Prevotella nigrescens, prevotella sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, cellophaga Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and Clara-p Paraprevotella clara.
The present invention provides methods for detecting biomarkers as follows: use of a substance of prasugrel-degrading bacterium Prevotella saccharolytica, prasugrel melanosis Prevotella nigrescens, prasugrel-producing bacterium Prevotella maculosa, prevotella sp.c561, bifidobacterium sp.12_1_47bfaa, bifidobacterium longum Bifidobacterium longum, clostridium sp.dl-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, myxosporidia Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata, and clara paratyphi Paraprevotella clara in any of the following A1) -A3):
a1 Preparing a product for diagnosing or aiding in diagnosing immune thrombocytopenia;
a2 Preparing a product for predicting or aiding in predicting the risk of immune thrombocytopenia;
a3 A product for distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia.
The invention also provides methods for detecting biomarkers as follows: use of substances and readable vectors of prasugrel saccharolytica Prevotella saccharolytica, prasugrel melanosis Prevotella nigrescens, prasugrel zebra Prevotella maculosa, prevotella sp.c561, bifidobacterium sp.12_1_47bfaa, bifidobacterium longum Bifidobacterium longum, clostridium sp.dl-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, myxosporean fibrous bacteria Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and clayey eplerian Paraprevotella clara in any of the following A1) -A3):
a1 Preparing a product for diagnosing or aiding in diagnosing immune thrombocytopenia;
a2 Preparing a product for predicting or aiding in predicting the risk of immune thrombocytopenia;
a3 Preparing a product for distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia;
the readable carrier is described as follows: DNA sequencing is carried out on the fecal sample of the person to be tested, and the sequencing result is compared with a reference gene set to obtain the relative abundance values of the following biomarkers in the person to be tested: prevotella saccharolytica Prevotella saccharolytica, prevotella melanogaster Prevotella nigrescens, prevotella sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, cellophaga viscosa Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and Clavipita Paraprevotella clara, and then comparing the relative abundance values with the relative abundance values of the biomarkers in the reference data set, obtaining the disease probability of the to-be-tested person through random forest model calculation, if the disease probability of the to-be-tested person is greater than or equal to a threshold value, the to-be-tested person suffers from or candidates for suffering from immune thrombocytopenia, and if the disease probability of the to-be-tested person is less than the threshold value, the to-be-tested person does not suffer from or candidates for not suffering from immune thrombocytopenia. The greater the probability value of the disease in the subject, the greater the risk of the subject having immune thrombocytopenia. In one embodiment of the invention, the threshold is 0.5.
In order to achieve the above object, the present invention also provides a kit;
the function of the kit is any one of the following B1) -B3):
b1 Diagnosis or auxiliary diagnosis of immune thrombocytopenia;
b2 Predicting or aiding in predicting the risk of immune thrombocytopenia;
b3 Distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia;
the kit provided by the invention contains the following biomarkers for detection: substances of Prevotella saccharolytica Prevotella saccharolytica, prevotella melanogaster Prevotella nigrescens, prevotella sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, cellophaga viscosa Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and Clara-p Paraprevotella clara.
Furthermore, the kit also comprises the readable carrier.
Still further, the method is used for detecting the following biomarkers: substances of Prevotella saccharolytica Prevotella saccharolytica, prevotella melanogaster Prevotella nigrescens, prevotella sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, cellophaga-myxospora Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and Clavipita Paraprevotella clara are reagents and/or instruments for detecting relative abundance values of the biomarkers.
In order to achieve the above object, the present invention finally provides a system;
the function of the system is any one of the following B1) -B3):
b1 Diagnosis or auxiliary diagnosis of immune thrombocytopenia;
b2 Predicting or aiding in predicting the risk of immune thrombocytopenia;
b3 Distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia;
the system comprises:
1) Means for collecting a fecal sample from a subject;
2) For detecting the following biomarkers in the fecal sample: reagents and/or instruments for the relative abundance values of Prevotella saccharolytica Prevotella saccharolytica, prevotella melanogaster Prevotella nigrescens, prevotella sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, cellophaga Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and Claviper's Pu's bacteria Paraprevotella clara;
3) An apparatus for diagnosing or aiding in diagnosing immune thrombocytopenia comprising a data input module, a data storage module, a data calculation module, a data comparison module and a conclusion output module;
the data input module is used for inputting the relative abundance value of the biomarker in the fecal sample of the tested person detected in the step 2);
the data storage module is used for receiving and storing the relative abundance value of the biomarker in the fecal sample of the person to be tested, which is output from the data input module;
the data calculation module is used for retrieving and storing the relative abundance value of the biomarker in the fecal sample of the person to be tested in the data storage module, comparing the relative abundance value of each biomarker with the relative abundance value of each biomarker in the reference data set, and calculating to obtain the illness probability of the person to be tested through a random forest model;
the data comparison module is used for receiving the illness probability of the to-be-detected person output from the data calculation module and comparing the illness probability with a threshold value;
the conclusion output module is used for receiving the comparison result output by the data comparison module and outputting a conclusion according to the comparison result: if the disease probability of the to-be-tested person is more than or equal to a threshold value, the to-be-tested person suffers from or candidates for suffering from the immune thrombocytopenia, and if the disease probability of the to-be-tested person is less than the threshold value, the to-be-tested person does not suffer from or candidates for not suffering from the immune thrombocytopenia. In a specific embodiment of the present invention, the threshold is 0.5. The greater the probability value of the disease, the greater the risk of the subject having immune thrombocytopenia.
The use of Prevotella catarrhalis Prevotella saccharolytica, prevotella melanogaster Prevotella nigrescens, prevotela Prevotella maculosa, prevotela sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, sporobiophaga rhodosporidium, frankia symbiont of Datisca glomerata and Clara-Praeparata Paraprevotella clara as markers or targets for the preparation or screening of products for the treatment or co-treatment of immune thrombocytopenia is also within the scope of the invention.
In practical applications, the biomarkers can be used as markers or targets for screening drugs for treating or assisting in treating immune thrombocytopenia, for example, whether the candidate drugs can be used as drugs for treating or assisting in treating immune thrombocytopenia can be determined by detecting whether the relative abundance value of one or two or more of the biomarkers changes before and after the candidate drugs are contacted.
In any of the above applications or kits or systems, each biomarker further comprises a microorganism having 75% or more identity to its genomic sequence. The term "identity" as used herein refers to sequence similarity to a native nucleic acid sequence. "identity" includes nucleotide sequences having 75% or more, or 80% or more, or 85% or more, or 90% or more, or 95% or more identity with the genomic sequence of Prevotella sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, myxosphaera-phaga fibers Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata, or Clavipita Paraprevotella clara of the present invention (genomic sequence information for each biomarker is shown in Table 3). Identity can be assessed visually or by computer software. Using computer software, the identity between two or more sequences can be expressed in percent (%), which can be used to evaluate the identity between related sequences.
In any of the above applications or kits or systems, the reagents and/or instruments for detecting the relative abundance of each biomarker in the fecal sample of the subject may comprise reagents and/or instruments for extracting genomic DNA from the fecal sample of the subject, and reagents and/or instruments for sequencing genomic DNA from the fecal sample of the subject.
Further, the reagent and/or the apparatus for extracting genomic DNA from the fecal sample of the subject may be reagents and/or apparatuses required for the genomic DNA extraction methods commonly used in the prior art, or may be commercially available DNA extraction kits. In one embodiment of the invention, the reagent and/or the instrument for extracting genomic DNA from a fecal sample of a subject is the reagent and/or the instrument required for extracting genomic DNA by phenol/chloroform method.
The reagents and/or instruments for sequencing genomic DNA in a fecal sample of a subject may be reagents and/or instruments required for genomic DNA sequencing methods commonly used in the art, including first generation sequencing methods, second generation sequencing methods, and third generation sequencing methods. In one embodiment of the invention, the reagents and/or instruments used to sequence genomic DNA in a fecal sample of a subject are those required to sequence using an Illumina sequencing platform.
In any of the above applications or kits or systems, detecting the following biomarkers in the fecal sample: the method for obtaining the relative abundance values of Prevotella saccharolytica Prevotella saccharolytica, prevotella melanogaster Prevotella nigrescens, prevotella sp.C561, bifidobacterium sp.12_1_47BFAA, bifidobacterium longum Bifidobacterium longum, clostridium sp.DL-VIII, enterobacter aerogenes Enterobacter aerogenes, butyricimonas synergistica, cellophaga sp Sporocytophaga myxococcoides, frankia symbiont of Datisca glomerata and Clara-P.sp Paraprevotella clara comprises the following steps:
1) Extracting genomic DNA in a stool sample of a person to be detected, and constructing a sequencing library based on the genomic DNA;
2) Performing metagenome sequencing on the sequencing library, and performing sequence assembly on a sequencing result;
3) Comparing the assembled sequence with a reference gene set, and referencing the literature 'Qin J, li Y, cai Z, et al A metanome-wide association study of gut microbiota in type 2 diabetes.Nature.2012' according to the comparison result and the gene length; 490 (7418) the relative abundance values of each biomarker in the fecal sample of the subject were calculated as described in 55-60. Doi:10.1038/aperture 11450 ".
In any of the above applications or kits or systems, the reference gene set may be a newly constructed gene set or a database of any known sequences. The construction method of the reference gene set can comprise the following steps: sequencing the genomic DNA of the samples of the individuals with ITP diseases and the healthy individuals, and assembling the sequence of the sequencing result; the open reading frames were predicted in the assembly results using MetaGeneMark and the predicted open reading frames from different individuals were pooled together and clustered using CD-Hit (sequence similarity above 95% and alignment region greater than 90% of sequence length to remove redundant sequences) to give a reference gene set. In one embodiment of the invention, the reference gene set is a gene set constructed based on 35 samples of individuals diagnosed with ITP and 35 healthy individuals. By comparing the sequencing sequence with the reference gene set, a corresponding relation can be established between the sequencing sequence and the genes in the reference gene set, so that the number of the sequencing sequences corresponding to the specific genes in the sample can effectively reflect the relative abundance of the genes, and then the abundance of the genes annotated by the same species is accumulated, so that the relative abundance value of the species in the sample can be obtained.
In any of the above applications or kits or systems, the reference dataset is a dataset consisting of relative abundance values for each biomarker in samples of individuals diagnosed with ITP disease and healthy individuals, used as a reference for the relative abundance of each biomarker. In a specific embodiment of the invention, the reference dataset is a dataset consisting of relative abundance values for each biomarker in 35 samples of individuals diagnosed with ITP and 35 healthy individuals. The reference data set may be attached to a physical carrier, for example an optical disc, such as a CD-ROM or the like.
In any of the above applications or kits or systems, the immune thrombocytopenia is adult immune thrombocytopenia. The age of the tester is greater than or equal to 18 years old.
The invention provides a group of intestinal flora biomarkers and application thereof in diagnosis of adult immune thrombocytopenia, and the intestinal flora biomarkers can effectively solve the key problem of early diagnosis of immune thrombocytopenia, effectively distinguish or distinguish immune thrombocytopenia and non-immune thrombocytopenia, and provide ideas for pathogenesis research, drug action target research and accurate treatment.
Drawings
Figure 1 is a view of the beta diversity of immune thrombocytopenia patients and healthy controls at the species level. The graphical representation shows that there is a significant difference between immune thrombocytopenia patients and healthy controls.
Fig. 2 is a graph of error rate distribution for 10-fold cross-validation in a random forest classifier.
Figure 3 is a graph of receiver operating characteristics (Receiver Operating Characteristic, ROC) Curve and Area Under Curve (AUC) of a training set consisting of immune thrombocytopenia patients and healthy controls based on a random forest model (12 gut flora biomarkers).
Figure 4 is ROC curve and AUC results for a validation set consisting of immune thrombocytopenia patients and healthy controls based on a random forest model (12 gut flora biomarkers).
Detailed Description
The following examples facilitate a better understanding of the present invention, but are not intended to limit the same. The experimental methods in the following examples are conventional methods unless otherwise specified. The test materials used in the examples described below, unless otherwise specified, were purchased from conventional biochemical reagent stores. The quantitative tests in the following examples were all set up in triplicate and the results averaged.
Prevotella saccharolytica Prevotella saccharolytica is described in the literature "Down J, tanner ACR, dewhisst FE, wade WG. Prevoltella saccharolytica sp. Nov., isolated from the human oral cage. Int J Syst Evol Microbiol.2010;60 (Pt 10): 2458-2461.Doi:10.1099/ijs.0.014720-0.
Protopanax melanosis Prevotella nigrescens is described in the literature "Shah HN, gharcia SE.biochemical and chemical studies on strains designated Prevotella intermedia and proposal of a new pigmented species, prevotella nigrescens sp.nov.int J System bacteriol 1992;42 542-546.doi:10.1099/00207713-42-4-542 ".
Prevotella zebra Prevotella maculosa is described in the literature "Down J, sutcliffe IC, booth V, wade WG.Prevoltella maculosa sp.nov., isolated from the human oral capacitance.int J Syst Evol Microbiol.2007;57 (Pt 12): 2936-2939.Doi:10.1099/ijs.0.65281-0.
Prevoltella sp.C561 is described in the literature "Wen C, zheng Z, shao T, et al Quantitative metagenomics reveals unique gut microbiome biomarkers in ankylosing spondylitis [ published correction appears in Genome biol.2017Nov 8;18 214]. Genome biol.2017;18 (1) 142.Published 2017Jul 27.doi:10.1186/s13059-017-1271-6.
Bifidobacterium sp.12_1_47BFAA is described in the literature "Krumbeck JA, rasmussen HE, hutkins RW, et al Probiotics Bifidobacterium strains and galactooligosaccharides improve intestinal barrier function in obese adults but show no synergism when used together as synbiotics. Microbiol.2018; 6 (1): 121.Published 2018Jun 28.doi:10.1186/s40168-018-0494-4.
Bifidobacterium longum Bifidobacterium longum is described in the literature "Miller LG, finegold sm.antibacterial sensitivity of Bifidobacterium (Lactobacillus bifidus). J bacteriol.1967;93 (1) 125-130.
Clostridium sp.DL-VIII is described in the literature "Taghavi S, izquierdo JA, van der Lelie D.Complete Genome Sequence of Clostridium sp.Strain DL-VIII, a Novel Solventogenic Clostridium Species Isolated from Anaerobic Slude.genome Announc.2013;1 (4): e00605-13.Published 2013Aug 8.doi:10.1128/genome A.00605-13'.
Enterobacter aerogenes Enterobacter aerogenes is described in the literature "Aleo JJ, smith RF, ellen RP. Growth of Enterobacter aerogenes in a lathyrogen-containing medium. Can J Microbiol 1970;16 (5) 398-400.Doi:10.1139/m70-068.
Butyricimonas synergistica is described in the literature "Sakamoto M, takagaki A, matsumoto K, kato Y, goto K, benno Y.Butyricimonas syngerisica gen.nov., sp.nov.and Butyricimonas virosa sp.nov., butyl acid-producing bacteria in the family 'Porphyromonadaceae' isolated from rat pieces.int J Syst Evol Microbiol 2009;59 (Pt 7) 1748-1753. Doi:10.1099/ijs.0.007574-0.
Myxosporean fibrous phage Sporocytophaga myxococcoides is described in the literature "SIJPESTEIJN AK, FAHRAEUS G.adaptation of Sporocytophaga myxococcoides to degares.J Gen Microbiol.1949;3 (2): 224-235.Doi:10.1099/00221287-3-2-224 ".
Frankia symbiont of Datisca glomerata is described in the literature "Richau KH, kudahittige RL, pujic P, kudahittige NP, sellstedt A.structural and gene expression analyses of uptake hydrogenases and other proteins involved in nitrogenase protection in Frankia J biosci.2013;38 (4) 703-712.Doi:10.1007/s12038-013-9372-1.
Clara Paraprevotella clara is described in the literature "Morotomi M, nagai F, sakon H, tanaka R.Paraprefotella clara gen.nov., sp.nov.and Paraprevotella xylaniphila sp.nov., members of the family 'Prevoltellaceae' isolated from human pieces.int J Syst Evol Microbiol.2009;59 (Pt 8): 1895-1900.doi:10.1099/ijs.0.008169-0.
Example 1 screening of diagnostic biomarkers for adult immune thrombocytopenia
1. Subject information and sample collection thereof
1. Subject information
Subjects consisted of 49 Immune Thrombocytopenia (ITP) patients and 52 healthy volunteers from the clinical visit of the university of beijing people in the hospital of the blood department from 2 nd 2018 to 4 th 2019, each signed an informed consent.
Subject entry criteria: (1) patients all meet ITP diagnostic criteria; (2) patients with primary ITP are not treated with any drug prior to their visit. (3) healthy volunteers: age is greater than or equal to 18 years old, and no complicated diseases.
Subject exclusion criteria: (1) Other secondary thrombocytopenia including autoimmune diseases, thyroid diseases, lymphoproliferative diseases, myelodysplastic disorders (aplastic anemia and myelodysplastic syndrome), hematological malignancies, chronic liver diseases, splenic hyperfunction, immunodeficiency and infections (including helicobacter pylori, hepatitis b virus, hepatitis c virus, human immunodeficiency virus, etc.), etc., secondary thrombocytopenia, thrombocytopenia induced by drugs, thrombocytopenia of the same type of immunity, pseudo thrombocytopenia, congenital thrombocytopenia, etc.; (2) a history of antibiotics used in approximately 3 months; (3) extreme diets (parenteral nutrition or vegetarian diet); (4) a history of inflammatory bowel disease; (5) administering a microbial agent such as a triple viable bacteria capsule; (6) a history of gastrointestinal surgery; (7) malignancy; (8) severe liver and kidney peptic ulcer disease; (9) A history of heart disease and cerebrovascular disease or events that incorporates clinical significance; (10) gestation.
2. Sample collection
Collecting fecal samples of all subjects for metagenome sequencing, and collecting contemporaneous clinical detection indexes of patients and healthy volunteers. The collection of the fecal sample adopts a fecal sample collector, a proper amount of fecal sample (more than or equal to 1 g/sample) is collected and placed in the environment of 4 ℃, DNA is extracted within 24 hours, and the sample of which DNA cannot be immediately extracted is transported by dry ice and stored at the temperature of minus 80 ℃. The phenol/chloroform method is used to extract DNA. Qubit Fluorometer detecting the DNA concentration of the sample, detecting the DNA integrity of the sample by agarose gel electrophoresis (gel concentration: 1%; voltage: 150V; electrophoresis time: 40 min), and removing unqualified samples with insufficient total DNA or degradation. Qualified samples were used for sequencing library construction and Illumina sequencing.
2. Construction of sequencing library and metagenomic sequencing and assembly
1. Construction of sequencing library
Sequencing libraries were constructed by entrusted with the medical examination of martial arts, and all companies. The method comprises the following specific steps: 1) Breaking the qualified DNA sample by adopting a Covaris focusing ultrasonic instrument. 2) End Repair Mix was added and the End Repair was performed at 20℃for 30min, after which the DNA fragment was purified using QIA quick PCR Purification Kit (Qiagen, america). 3) A-tagging Mix was used to add an A base at the 3' end at 37℃for 30min, and then a sequencing adapter was ligated to both ends of the DNA fragment. 4) Fragment selection was performed using 2% agarose gel and QIA quick Gel Extraction kit (Qiagen, america) and several cycles of PCR amplification were performed to obtain PCR products. 5) The PCR product was purified using a 2% agarose gel and the target fragment was recovered using QIA quick Gel Extraction kit. 6) Sample libraries were quality controlled and quantified using an Agilent2100Bioanalyzer and ABI Step One Plus Real-Time PCR System.
2. Metagenomic sequencing and assembly
And (3) sequencing the qualified library obtained in the step (1) by using an Illumina sequencing platform. For each sample, high quality sequencing data (reads) were obtained after quality control of the raw data. De novo assembly was performed on the samples using the assembly software MEGAHIT. And simultaneously carrying out a plurality of assemblies on each sample by using a series of different k-mer parameters, then respectively comparing reads back to each assembly result by using SOAP2 to evaluate the assembly effect, and finally comprehensively considering the N50 and comparison rate condition, and selecting an optimal k-mer and the corresponding assembly result. Only contigs greater than 500bp will be retained during assembly for subsequent analysis.
3. Genome alignment and relative abundance calculation
1. The open reading frames (Open Reading Frames, ORFs) were predicted in the assembled result obtained in step 2, using MetaGeneMark (software version 2.10. Default parameters, the web address is http:// exon. Gatech. Edu/GeneMark/Metagenome/Prediction /).
2. The genes predicted from the different samples were pooled together and clustered using CD-Hit (sequence similarity above 95% and alignment region greater than 90% of the sequence length to remove redundant sequences) to give a gene set.
3. The sequence and alignment quality of each sequenced fragment was checked using the pathrope software for reassignment. The high quality reads of different samples were aligned with the established gene set using Bowtie2, respectively, with the following main alignment parameters: bowtie2parameters for PE reads- -p8- -ver-active-local-k 100- -score-minL,0,1.2. Since there is a one-to-many alignment in the alignment, the software Pathoscope (v 1.0) was used to reassign reads to the "most likely source" gene. The software uses a bayesian framework to examine the sequence and alignment quality of each read for reassignment.
4. According to the comparison result and the gene length, reference is made to the literature "Qin J, li Y, cai Z, et al A metaname-wide association study of gut microbiota in type 2diabetes, nature 2012;490 (7418) the method of 55-60. Doi:10.1038/aperture 11450", calculating the relative abundance of a species in a sample. The method comprises the following specific steps: for sample S, the relative abundance of a gene in the sample was calculated according to the following formula: a, a i ＝(X i /L i )/(∑ j X j /L j )。a i Represents the relative abundance of gene i in sample S, L i Represents the length of gene i, x i Represents the number of times gene i was detected in sample S (i.e., the number of reads over the alignment). NR comparison results were processed using MEGAN (version 4). MEGAN re-clusters BLAST alignment results according to NCBI species classification trees according to an algorithm named LCA, thereby obtaining species annotation information for each sequence. Summing up the annotated gene abundance of the same species to obtain the relative abundance value of the species in the sample.
5. Calculating species beta diversity (beta diversity), namely Bray-Curtis distance, by utilizing evolutionary relation and abundance information among various sample sequences so as to judge whether a remarkable microbial community difference exists among groups, wherein the calculating method refers to the literature Liu R, hong J, xu X, et al Gut microbiome and serum metabolome alterations in obesity and after weight-loss interaction. Nat Med.2017;23 (7) 859-868. Doi:10.1038/nm.4358'. Figure 1 shows the case of beta diversity at the species level for the immune thrombocytopenia patient group and the healthy control group. The figures show that there is a significant difference in the intestinal flora composition between the immune thrombocytopenia patient group and the healthy control group.
4. Random forest model screening potential biomarker
1. Experimental method
70% of immunocompromised patients and healthy subjects were randomly selected from the sample set as training sets, including 35 immunocompromised patients and 35 healthy subjects (tables 1, 2). Inputting the relative abundance of the species in each sample in the training set into a random forest classifier, carrying out 10 times of 10-fold cross validation on the classifier, calculating the immune thrombocytopenia risk of each individual by using the relative abundance of the species screened by the random forest model, drawing an ROC curve, and calculating the AUC as a judging model efficiency evaluation parameter. The combination number of the biomarker is less than 30, and the combination with the optimal discrimination performance is selected, the importance index of each species is output in the model, and the higher the importance index is, the higher the importance of the biomarker for discriminating immune thrombocytopenia and non-immune thrombocytopenia is represented.
2. Experimental results
Taking a training set as a sample, setting a 10-time 10-fold cross validation method, and screening by using a random forest classifier to obtain a combination (intestinal flora biomarker combination) with optimal discrimination efficiency, wherein the combination comprises the following 12 biomarkers: biomarker 1: prevotella saccharolytica Prevotella saccharolytica; biomarker 2: praecox melanosis Prevotella nigrescens; biomarker 3: prevotella zebra Prevotella maculosa; biomarker 4: prevotella sp.c561; biomarker 5: bifidobacterium sp.12_1_47bfaa; biomarker 6: bifidobacterium longum Bifidobacterium longum; biomarker 7: clostridium sp.dl-VIII; biomarker 8: enterobacter aerogenes Enterobacter aerogenes; biomarker 9: butyricimonas synergistica; biomarker 10: myxosphaericus sporozoites Sporocytophaga myxococcoides; biomarker 11: frankia symbiont of Datisca glomerata; biomarker 12: clara Paraprevotella clara.
Figure 2 shows the error rate distribution of 10-fold cross-validation in a random forest classifier. The model is trained with the relative abundance of species meeting the target obtained by MWAS procedure treatment on training set samples, with the bold black solid curve representing the average of 10 trials (the thin black curve representing 10 trials), and the red vertical line representing the number of species in the selected optimal combination. The importance index indicates the importance of each biomarker for discriminating between immune thrombocytopenia and non-immune thrombocytopenia, with a larger value indicating a greater importance of the biomarker (table 3). The results of the immune thrombocytopenia risk (probability of developing) for each individual calculated using the relative abundance values of the biomarkers screened by the random forest model are shown in table 4. Fig. 3 is ROC curve and AUC for the discrimination of ITP patients and healthy controls of the training set based on 12 biomarkers of random forest model, the discrimination efficacy of the training set samples is: auc= 92.29%,95% confidence interval ci= 85.88-98.69%. The intestinal flora biomarker combination obtained by the model can be used as a potential biomarker for distinguishing ITP from non-ITP.
5. Verifying the screened biomarkers using the verification set data
The model was validated using a validation set comprising 14 patients with immune thrombocytopenia and 17 healthy subjects, the relative abundance of 12 biomarkers in the validation set was calculated according to the method in step four, the results can be seen in tables 5 and 6, which were then input into a random forest classifier, and the risk of developing immune thrombocytopenia (probability of developing disease) was calculated for each individual using a combination of 12 markers. Table 7 is the probability of illness results for each individual in the validation set based on the 12 biomarker combinations prediction. Fig. 4 is ROC curve and AUC for the discrimination of ITP patients and healthy controls in the validation set based on 12 biomarkers of random forest model, which model discriminatory efficacy in the validation set: auc= 83.61% (95% ci= 67.69% -99.54%). It is demonstrated that the intestinal flora marker combination obtained by the model can be used as a potential biomarker for distinguishing ITP from non-ITP.
Therefore, in practical applications, the above-mentioned intestinal flora biomarker combination can be used to determine whether the subject has immune thrombocytopenia or risk of immune thrombocytopenia or distinguish ITP from non-ITP according to the following method:
1) Collecting a fecal sample from a subject;
2) Determining the relative abundance value of each biomarker in the sample obtained in step 1);
3) Comparing the relative abundance value of each biomarker in the sample obtained in the step 2) with the relative abundance value of each biomarker in the reference data set, calculating the illness probability of a testee through a random forest model, if the illness probability of the testee is more than or equal to 0.5, the testee suffers from or is candidate to suffer from immune thrombocytopenia, if the illness probability of the testee is less than 0.5, the testee does not suffer from or is candidate to suffer from immune thrombocytopenia, and the larger the illness probability value is, the greater the risk of the testee suffering from immune thrombocytopenia is.
TABLE 1 random forest model training set intestinal flora biomarker relative abundance information (1 st-6 th intestinal flora markers)
* HC: healthy controls; ITP: patients with immune thrombocytopenia
TABLE 2 random forest model training set intestinal flora biomarker relative abundance information (7 th-12 th intestinal flora markers)
TABLE 3 random forest model screening of 12 intestinal flora biomarker information
TABLE 4 probability of disease in training set based on 12 intestinal flora biomarker combinations
Table 5, random forest model verification of intestinal flora biomarker relative abundance information (1 st-6 th intestinal flora markers)
Table 6, random forest model verification of intestinal flora biomarker relative abundance information (7 th-12 th intestinal flora markers)
TABLE 7 probability of disease of the validated set based on 12 intestinal flora biomarker combinations
| Sample numbering | Probability of illness | Sample numbering | Probability of illness |
| HC02 | 0.300 | ITP02 | 0.724 |
| HC08 | 0.174 | ITP03 | 0.754 |
| HC12 | 0.308 | ITP06 | 0.502 |
| HC14 | 0.032 | ITP09 | 0.812 |
| HC16 | 0.188 | ITP21 | 0.532 |
| HC21 | 0.848 | ITP29 | 0.362 |
| HC22 | 0.350 | ITP31 | 0.794 |
| HC23 | 0.182 | ITP33 | 0.738 |
| HC24 | 0.090 | ITP36 | 0.484 |
| HC27 | 0.488 | ITP37 | 0.566 |
| HC31 | 0.482 | ITP39 | 0.490 |
| HC32 | 0.206 | ITP43 | 0.756 |
| HC33 | 0.072 | ITP46 | 0.414 |
| HC42 | 0.386 | ITP48 | 0.160 |
| HC45 | 0.200 | ||
| HC46 | 0.550 | ||
| HC48 | 0.286 |
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the scope of the invention.
Claims (7)
1. Prevotella saccharolyticaPrevotella saccharolyticaProteus nigrus (L.) BresPrevotella nigrescensPrevotella zebraPrevotella maculosa、Prevotella sp. C561、Bifidobacterium sp. 12_1_ 47BFAABifidobacterium longumBifidobacterium longum、Clostridium sp. DL-VIIIEnterobacter aerogenesEnterobacter aerogenes、Butyricimonas synergisticaCellophaga viscosaSporocytophaga myxococcoides、Frankia symbiont of Datisca glomerataAnd Clara ParamygdalinaParaprevotella claraUse as a biomarker in any one of the following A1) -A3):
a1 Preparing a product for diagnosing or aiding in diagnosing immune thrombocytopenia;
a2 Preparing a product for predicting or aiding in predicting the risk of immune thrombocytopenia;
a3 A product for distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia.
2. For detection of the following biomarkers: prevotella saccharolyticaPrevotella saccharolyticaProteus nigrus (L.) BresPrevotella nigrescensPrevotella zebraPrevotella maculosa、Prevotella sp. C561、Bifidobacterium sp. 12_1_47BFAABifidobacterium longumBifidobacterium longum、Clostridium sp. DL-VIIIEnterobacter aerogenesEnterobacter aerogenes、Butyricimonas synergisticaCellophaga viscosaSporocytophaga myxococcoides、Frankia symbiont of Datisca glomerataAnd Clara ParamygdalinaParaprevotella claraThe use of a substance according to any one of the following A1) to A3):
a1 Preparing a product for diagnosing or aiding in diagnosing immune thrombocytopenia;
a2 Preparing a product for predicting or aiding in predicting the risk of immune thrombocytopenia;
a3 A product for distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia.
3. For detection of the following biomarkers: prevotella saccharolyticaPrevotella saccharolyticaProteus nigrus (L.) BresPrevotella nigrescensPrevotella zebraPrevotella maculosa、Prevotella sp. C561、Bifidobacterium sp. 12_1_47BFAABifidobacterium longumBifidobacterium longum、Clostridium sp. DL-VIIIEnterobacter aerogenesEnterobacter aerogenes、Butyricimonas synergisticaCellophaga viscosaSporocytophaga myxococcoides、Frankia symbiont of Datisca glomerataAnd Clara ParamygdalinaParaprevotella claraThe use of a substance and a readable carrier according to any of the following A1) to A3):
a1 Preparing a product for diagnosing or aiding in diagnosing immune thrombocytopenia;
a2 Preparing a product for predicting or aiding in predicting the risk of immune thrombocytopenia;
a3 Preparing a product for distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia;
the readable carrier is described as follows: DNA sequencing is carried out on the fecal sample of the person to be tested, and the sequencing result is compared with a reference gene set to obtain the relative abundance value of each biomarker in the person to be tested: prevotella saccharolyticaPrevotella saccharolyticaProteus nigrus (L.) BresPrevotella nigrescensPrevotella zebraPrevotella maculosa、Prevotella sp. C561、Bifidobacterium sp. 12_1_47BFAABifidobacterium longumBifidobacterium longum、Clostridium sp. DL-VIIIEnterobacter aerogenesEnterobacter aerogenes、Butyricimonas synergisticaCellophaga viscosaSporocytophaga myxococcoides、Frankia symbiont of Datisca glomerataAnd Clara ParamygdalinaParaprevotella claraComparing the relative abundance value with the relative abundance value of each biomarker in the reference data set, and calculating to obtain the disease probability of the testee through a random forest model, wherein if the disease probability of the testee is more than or equal to a threshold value, the testee suffers from or is candidate to suffer from immune thrombocytopenia, and if the disease probability of the testee is less than the threshold value, the testee does not suffer from or is waiting for the patientNo immune thrombocytopenia is selected.
4. A use according to claim 3, characterized in that: the threshold is 0.5.
5. Use according to any one of claims 2-4, characterized in that: the method is used for detecting the following biomarkers: prevotella saccharolyticaPrevotella saccharolyticaProteus nigrus (L.) BresPrevotella nigrescensPrevotella zebraPrevotella maculosa、Prevotella sp. C561、Bifidobacterium sp. 12_1_47BFAABifidobacterium longumBifidobacterium longum、Clostridium sp. DL-VIIIEnterobacter aerogenesEnterobacter aerogenes、Butyricimonas synergisticaCellophaga viscosaSporocytophaga myxococcoides、Frankia symbiont of Datisca glomerataAnd Clara ParamygdalinaParaprevotella claraIs a reagent and/or instrument for detecting the relative abundance value of the biomarker.
6. A system, comprising:
1) Means for collecting a fecal sample from a subject;
2) For detecting the following biomarkers in the fecal sample: prevotella saccharolyticaPrevotella saccharolyticaProteus nigrus (L.) BresPrevotella nigrescensPrevotella zebraPrevotella maculosa、Prevotella sp. C561、Bifidobacterium sp. 12_1_47BFAABifidobacterium longumBifidobacterium longum、Clostridium sp. DL-VIIIEnterobacter aerogenesEnterobacter aerogenes、Butyricimonas synergisticaCellophaga viscosaSporocytophaga myxococcoides、Frankia symbiont of Datisca glomerataAnd Clara ParamygdalinaParaprevotella claraReagents and/or instrumentation for relative abundance values;
3) An apparatus for diagnosing or aiding in diagnosing immune thrombocytopenia comprising a data input module, a data storage module, a data calculation module, a data comparison module and a conclusion output module;
the data input module is used for inputting the relative abundance value of the biomarker in the fecal sample of the person to be detected, which is detected by the 2);
the data storage module is used for receiving and storing the relative abundance value of the biomarker in the fecal sample of the person to be tested, which is output from the data input module;
the data calculation module is used for retrieving and storing the relative abundance value of the biomarker in the fecal sample of the person to be tested in the data storage module, comparing the relative abundance value of each biomarker with the relative abundance value of each biomarker in the reference data set, and calculating to obtain the illness probability of the person to be tested through a random forest model;
the data comparison module is used for receiving the illness probability of the to-be-detected person output from the data calculation module and comparing the illness probability with a threshold value;
the conclusion output module is used for receiving the comparison result output by the data comparison module and outputting a conclusion according to the comparison result: if the disease probability of the to-be-detected person is more than or equal to a threshold value, the to-be-detected person suffers from or is candidate to suffer from immune thrombocytopenia, and if the disease probability of the to-be-detected person is less than the threshold value, the to-be-detected person does not suffer from or is candidate to suffer from immune thrombocytopenia;
the function of the system is any one of the following B1) -B3):
b1 Diagnosis or auxiliary diagnosis of immune thrombocytopenia;
b2 Predicting or aiding in predicting the risk of immune thrombocytopenia;
b3 Distinguishing or differentiating between immune thrombocytopenia and non-immune thrombocytopenia.
7. The system according to claim 6, wherein: the threshold is 0.5.
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