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WO2023080501A1 - Procédé de fourniture d'informations pour prévoir une réponse immunitaire à un vaccin contre le sars-cov-2 par l'intermédiaire d'un microbiote intestinal et de profils de biomarqueurs fonctionnels, et procédé de fourniture d'informations de vaccin personnalisées pour un sujet - Google Patents

Procédé de fourniture d'informations pour prévoir une réponse immunitaire à un vaccin contre le sars-cov-2 par l'intermédiaire d'un microbiote intestinal et de profils de biomarqueurs fonctionnels, et procédé de fourniture d'informations de vaccin personnalisées pour un sujet Download PDF

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WO2023080501A1
WO2023080501A1 PCT/KR2022/016100 KR2022016100W WO2023080501A1 WO 2023080501 A1 WO2023080501 A1 WO 2023080501A1 KR 2022016100 W KR2022016100 W KR 2022016100W WO 2023080501 A1 WO2023080501 A1 WO 2023080501A1
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ortholog
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kegg
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Korean (ko)
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성혜
송준영
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Korea University Research and Business Foundation
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    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23L—FOODS, FOODSTUFFS OR NON-ALCOHOLIC BEVERAGES, NOT OTHERWISE PROVIDED FOR; PREPARATION OR TREATMENT THEREOF
    • A23L33/00—Modifying nutritive qualities of foods; Dietetic products; Preparation or treatment thereof
    • A23L33/10—Modifying nutritive qualities of foods; Dietetic products; Preparation or treatment thereof using additives
    • A23L33/135—Bacteria or derivatives thereof, e.g. probiotics
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K39/00—Medicinal preparations containing antigens or antibodies
    • A61K39/12—Viral antigens
    • A61K39/215—Coronaviridae, e.g. avian infectious bronchitis virus
    • C—CHEMISTRY; METALLURGY
    • 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
    • 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
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • 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
    • 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
    • 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
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu

Definitions

  • the present invention relates to a method for providing information for predicting an immune response upon vaccination with SARS-CoV-2 and a method for providing customized vaccine information, and more specifically, to a taxonomic composition of the intestinal microflora and metabolites produced by microorganisms. And functional biomarkers including them are confirmed to have a significant correlation with the immune response after vaccination, and intestinal microbial biomarkers and functional markers showing good or bad immune responses are identified to determine the effect of SARS-CoV-2 after vaccination. It is to predict the immune response or to provide customized vaccine information for the subject.
  • Coronavirus disease 2019 (COVID-19) is a novel respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It spread from Wuhan, China in December 2019 and is now causing a pandemic and causing a serious health crisis worldwide. As of March 3, 2022, more than 442 million confirmed cases of COVID-19 and more than 5.9 million deaths have been recorded worldwide.
  • SARS-CoV-2 severe acute respiratory syndrome coronavirus 2
  • Vaccination is known to be the best means of overcoming the pandemic, but the immunogenicity of vaccines can vary from person to person.
  • the post-vaccination immune response depends on intrinsic factors (e.g. age, sex, genetics, comorbidity and pre-existing immunity), extrinsic factors (e.g. nutrition, environment, behavioral factors) and vaccine (e.g. vaccine type, adjuvant, route of administration). may be affected by a variety of factors, including those related to
  • the gut microbiome is an important determinant of the basic immune status and immune response to vaccines.
  • the gut microbiome consists of more than 100 trillion bacteria of more than 150 species, which play important roles in the development, direction, and priming of the immune system, influencing both innate and acquired immunity.
  • Enhancing the effectiveness of existing vaccines is as important as developing effective new vaccines to the success of global efforts against the COVID-19 pandemic.
  • Current vaccinations are non-individual and uniform, and do not consider individual variability in immunological responses. Accordingly, the present inventors have completed the invention of a method for providing information capable of increasing vaccine efficacy through the correlation between the above-described intestinal microbial community, their metabolites, and functional biomarkers and immune responses.
  • the technical problem to be achieved by the present invention is to provide an information providing method for predicting an immune response through the composition of the intestinal microflora of a subject before vaccination at the time of SARS-CoV-2 vaccination.
  • Another technical problem to be achieved by the present invention is to provide subject-specific vaccination information for determining a vaccine that can most efficiently induce an immune response in a subject through the composition of the subject's intestinal microflora.
  • Another technical problem to be achieved by the present invention is to provide probiotics for immunity enhancement and/or health functional food for immunity enhancement.
  • Another technical problem to be achieved by the present invention is to provide an information providing method for predicting an immune response through the intestinal metabolome and functional biomarkers of a subject before vaccination at the time of SARS-CoV-2 vaccination.
  • Another technical problem to be achieved by the present invention is to provide subject-specific vaccination information for determining a vaccine capable of inducing the most efficient immune response in a subject through the composition of the subject's intestinal metabolites and functional biomarkers.
  • the present invention is Parasutterella genus, Eubacterium_g23 PAC001034_s, Blautia_uc, Ruminococcaceae PAC000661_g genus, Eubacterium_g5 LT907848_s, Romboutsia genus, Roseburia triocola, Romboutsia timonensis, Clostridium PAC001136_s, La Genus chnospiraceae PAC001043_g and Lachnospiraceae PAC001043_g
  • Provided is a method for providing vaccination information tailored to a subject, comprising detecting any one or more microorganisms from the group consisting of PAC001449_s.
  • the Eubacterium_g23 PAC001034_s species has a 16s rRNA having 98% or more homology with the nucleotide of SEQ ID NO: 1
  • the Eubacterium_g5 LT907848_s species has a 16s rRNA having 98% or more homology with the nucleotide of SEQ ID NO: 2
  • the Roseburia cescola species has a 16s rRNA having 98% or more homology with the nucleotide of SEQ ID NO: 3
  • the Romboutsia timonensis species has a 16s rRNA having 98% or more homology with the nucleotide of SEQ ID NO: 4
  • the Clostridium PAC001136_s species has SEQ ID NO: 5 nucleotide and 16s rRNA having 98% or more homology
  • the Lachnospiraceae PAC001043_g PAC001449_s species may have 16s rRNA having 98% or more homology with nu
  • the vaccine may be a vaccine against corona virus.
  • the step of determining the subject as having a good immune response to the viral vector vaccine can include more.
  • the viral vector vaccine may be an adenovirus vector vaccine.
  • mRNA messenger ribonucleic acid
  • kits for providing vaccination information tailored to a subject, including the composition is provided.
  • genus Parasutterella Eubacterium_g23 PAC001034_s, Blautia_uc, genus Ruminococcaceae PAC000661_g, genus Eubacterium_g5 LT907848_s, genus Romboutsia, Roseburia triocola, Romboutsia timonensis, Clostridium PAC001136_s, Lachnospiraceae PAC00 1043_g, consisting of Lachnospiraceae PAC001043_g PAC001449_s and combinations thereof
  • Probiotics for immunity enhancement and/or health functional food for immunity enhancement comprising at least one selected from the group are provided.
  • the present invention relates to endoglucanase (KEGG ortholog K01179), fumarate hydratase class I (KEGG ortholog K01676), two-component regulatory system LytTR family sensor kinase (two -component regulatory system, LytTR family, sensor kinase, KEGG ortholog K02478), anthranilate synthase component I orthologs (KEGG ortholog K01657), butyryl-CoA dehydrogenase , KEGG ortholog K00248), two-component system, OmpR family, response regulator CpxR (two-component system, OmpR family, response regulator CpxR, KEGG ortholog K07662), peptide/nickel transport system permease protein protein, KEGG ortholog K02033), putative ABC transport system ATP-binding protein (KEGG ortholog K02003), aminocarboxymuconate-semialdehyde decarboxylase (KEGG ortholog K
  • the vaccine may be a vaccine against corona virus.
  • a step of determining a subject having a good immune response to the viral vector vaccine may be further included.
  • a step of determining the subject as having a poor immune response to the viral vector vaccine may be further included.
  • the viral vector vaccine may be an adenovirus vector vaccine.
  • aminocarboxymuconate-semialdehyde decarboxylase in the biological sample isolated from the subject, aminocarboxymuconate-semialdehyde decarboxylase, iron complex transport system ATP binding protein, aromatic-L-amino acid / L-tryptophan dicarboxyl lase, glycine cleavage system transcriptional repressor, cobalt/nickel transport system ATP-binding protein, RNA 2', 3'-cyclic 3'-phosphodiesterase, propionyl-CoA carboxylase beta chain, putative ABC transport system ATP-binding protein (KEGG ortholog K02021), ferredoxin hydrogenase subunit, betaine/cartinine transporter BCCT family, HlyD family secreted protein, thiosulfate/3-mercaptopyruvate sulfurtransferase, If at least one functional biomarker from the group consisting of serine palmitoyltransferase, CRP
  • mRNA messenger ribonucleic acid
  • endoglucanase fumarate hydratase class I
  • two-component regulatory system LytTR family sensor kinase anthranilate synthase component I ortholog
  • butyryl-CoA dehydrogenase two-component regulatory system OmpR family response regulator CpxR
  • peptide/nickel transport system fermease protein putative ABC transport system ATP binding protein (KEGG ortholog K02003), aminocarboxymuconate-semialdehyde decarboxylase, iron complex transport system ATP binding protein, aromatic-L-amino acid/L-tryptophan decarboxylase, glycine cleavage system transcriptional repressor, cobalt/nickel transport system ATP-binding protein, RNA 2', 3'-cyclic 3'- Phosphodiesterase, propionyl-CoA carboxylase beta chain, putative ABC transport system ATP-binding protein (KEGG ortholog K0202
  • a kit for providing vaccination information tailored to a subject including the composition is provided.
  • the composition of the intestinal microflora taxa of the subject before inoculation can be identified, and the degree of humoral immune response of the subject after inoculation can be predicted.
  • 1 is a schematic diagram of sample collection and survey of the present invention.
  • Figure 2 shows the change in alpha diversity (Shannon), beta diversity and ternary plot after administration of two different vaccine platforms.
  • 6 is a three-way plot (a: phylum, b: strong) according to the classification stage, showing changes in the microbiota for the ChAdOx1 vaccination group and the BNT162b2 vaccination group.
  • FIG. 7 is a three-way plot (c: neck, d: family) according to the classification stage, showing the changes in the microbiota for the ChAdOx1 vaccination group and the BNT162b2 vaccination group.
  • FIG. 8 is a three-way plot (e: species) according to the classification stage, showing the changes in the microbiota for the ChAdOx1 vaccination group and the BNT162b2 vaccination group.
  • Figure 9 shows baseline differences in microbiome species richness (ACE) and distance between sets with respect to immunogenicity of two different vaccine platforms.
  • ACE microbiome species richness
  • Figure 12 shows the change of the Simpson's and Phylogenetic Diversity alpha diversity indices by dividing the excellent immune response group and the poor immune response group after inoculation.
  • Figure 14 shows the results of linear discriminant analysis effect size (LEfSe) analysis for identifying functional biomarkers for metabolites with p ⁇ 0.05.
  • the present inventors found that the gut microbiome affects the immune response after SARS-CoV-2 vaccination, and that adenoviral vectors and vaccine components induce changes in the gut microbiome to affect the immune response after repeated vaccination. It was confirmed that the present invention was completed, and specific details for carrying out the present invention are as follows.
  • the present invention is Parasutterella genus, Eubacterium_g23 PAC001034_s, Blautia_uc, Ruminococcaceae PAC000661_g genus, Eubacterium_g5 LT907848_s, Romboutsia genus, Roseburia triocola, Romboutsia timonensis, Clostridium PAC001136_s, La Genus chnospiraceae PAC001043_g and Lachnospiraceae PAC001043_g
  • Provided is a method for providing vaccination information tailored to a subject, comprising the step of detecting any one or more microorganisms from the group consisting of PAC001449_s.
  • the biological sample may preferably be feces of a subject, but is not limited thereto.
  • the Eubacterium_g23 PAC001034_s species has a 16s rRNA having 98% or more homology with the nucleotide of SEQ ID NO: 1
  • the Eubacterium_g5 LT907848_s species has a 16s rRNA having 98% or more homology with the nucleotide of SEQ ID NO: 2, the Roseburia cescola
  • the species has 16s rRNA having 98% or more homology with the nucleotide of SEQ ID NO: 3
  • the Romboutsia timonensis species has 16s rRNA having 98% or more homology with nucleotide of SEQ ID NO: 4
  • the Clostridium PAC001136_s species has SEQ ID NO: 5 16s rRNA having 98% or more homology with the nucleotide
  • the Lachnospiraceae PAC001043_g PAC001449_s species may have 16s rRNA having 98% or more homology with the nucleo
  • the 16s rRNA is an rRNA constituting the 30S subunit of the prokaryotic ribosome, and most of the base sequences are significantly conserved, while high base sequence diversity is shown in some sections. In particular, since there is little diversity among homologous species, but there is diversity between different species, prokaryotes can be usefully identified by comparing 16S rRNA sequences.
  • the genus Parasutterella, the genus Blautia, the genus Ruminococcaceae PAC000661_g, the genus Romboutsia, and the genus Lachnospiraceae PAC001043_g may include all microorganisms of subclasses, and the 16s rRNA of each microbial species included therein is per Ezbiocloud, NCBI genbank, etc. It can be confirmed through methods known in the art.
  • Detection of the microorganisms may be achieved through a known detection method known in the art, preferably through a detection agent.
  • the detection agent is a primer or probe capable of specifically detecting organic biomolecules such as proteins, nucleic acids, lipids, glycolipids, glycoproteins, or sugars (monosaccharide, disaccharide, oligosaccharide, etc.) that are specifically present in the microorganism. , antisense oligonucleotides, LNA (Locked Nucleic Acids), aptamers or antibodies, and preferably fusion primers targeting a specific region of the 16S rRNA gene.
  • LNA Locked Nucleic Acids
  • provision of subject-specific vaccination information means that, based on the microbial taxa and functional marker information, it is possible to predict whether a subject will have an excellent or poor immune response to a specific vaccine and show the best immune response to the subject. It refers to the provision of vaccination information that is available.
  • the subject may be a mammal including a human.
  • the excellent immune response group and the poor immune response group can be classified by the anti-SARS-CoV-2-S IgG titer in the blood at 3 weeks after the completion of the second vaccine vaccination, preferably anti-SARS-CoV-2 If the -S IgG titer is 2500 U/mL or more, it can be classified as an excellent immune response group, and if it is 1000 U/mL or less, it can be classified as a poor immune response group.
  • an intestinal microbial profile that can serve as a biomarker of the immune response was secured, and accordingly, information capable of predicting the immune response of the subject Provides a method of delivery.
  • the vaccine may be a vaccine against corona virus.
  • the coronavirus vaccine may be either a viral vector vaccine or an mRNA vaccine, and more preferably, the viral vector vaccine may be ChAdOx1 and the mRNA vaccine may be BNT162b2.
  • the step of determining the subject as having a good immune response to the viral vector vaccine can include more.
  • the viral vector vaccine may be an adenovirus vector vaccine.
  • a subject with a good immune response refers to a subject with an excellent humoral immune response after vaccination, and preferably may be a subject whose blood concentration of anti-SARS-CoV-2 S IgG is 2500 U/mL or more.
  • mRNA messenger ribonucleic acid
  • a composition for providing vaccination information tailored to a subject, including an agent for detecting any one or more of the above, is provided. Description of the detection agent is as described above.
  • kits for providing vaccination information tailored to a subject, including the composition is provided.
  • the kit may include a detection agent as an essential component.
  • a detection agent as an essential component.
  • a test tube or other suitable container in addition to a fusion primer complementary to the specific nucleotide of each microorganism, a test tube or other suitable container, reaction buffer, deoxynucleotides (dNTPs), Taq-polymerase and reverse transcriptase, DNase, RNase inhibitors, DEPC-water, sterile water, and the like.
  • the kit may include various tools and reagents known in the art that facilitate the measurement of microbial levels, such as suitable carriers, labeling substances capable of generating a detectable signal, stabilizers, and the like.
  • the species diversity may preferably be alpha diversity, more preferably any one or more selected from the group consisting of ACE, Chao1, Jackknife, Shannon, NPShannon, Simpson and Phylogenetic diversity, most preferably ACE alpha diversity can be
  • ACE alpha diversity
  • Example 2 there was a significant correlation between the species diversity of the intestinal microflora before inoculation and the excellent immune response after inoculation.
  • an excellent immune response with an anti-S IgG titer of 2500 or more was observed after completion of vaccination.
  • the present inventors found that the following group 1 and group 2 gut microbial taxa had a significant correlation with the immune response after vaccination, respectively.
  • Group 1 Genus Parasutterella, Eubacterium_g23 PAC001034_s, Blautia_uc, Genus Ruminococcaceae PAC000661_g, Genus Eubacterium_g5 LT907848_s, Genus Romboutsia, Roseburia triocola, Romboutsia timonensis, Clostridium PAC001136_s, Lachnospiraceae PAC001043_ The group consisting of the genus g and Lachnospiraceae PAC001043_g PAC001449_s; and
  • Group 2 the group consisting of Anaerotignum PAC001031_s, Bifidobacterium animalis, Bacteroides dorei and Megasphaera indica;
  • the microorganisms belonging to the first group were a relatively dominant taxa of the intestinal microflora before inoculation of the group having an excellent immune response after inoculation.
  • Parasutterella genus, Eubacterium_g23 PAC001034_s and Blautia_uc were relatively dominant in the ChAdOx1 inoculated group with excellent immune response, and in the BNT162b2 inoculated group with excellent immune response, Ruminococcaceae PAC000661_g genus, Eubacterium_g5 LT907848_s, Romboutsia genus, Roseburia stiicola, Romboutsia ti monensis, Clostridium
  • the genera PAC001136_s, Lachnospiraceae PAC001043_g and Lachnospiraceae PAC001043_g PAC001449_s belonged to the relatively dominant taxa.
  • the microorganisms belonging to the second group were relatively dominant taxa of the intestinal microflora before inoculation of the group with poor immune response after inoculation.
  • Anaerotignum PAC001031_s and Bifidobacterium animalis were relatively dominant in the poor immune response group of the ChAdOx1 inoculated group, and Bacteroides dorei and Megasphaera indica belonged to relatively dominant taxa in the poor immune response group of the BNT162b2 inoculated group.
  • the present invention relates to genus Parasutterella, Eubacterium_g23 PAC001034_s, Blautia_uc, genus Ruminococcaceae PAC000661_g, genus Eubacterium_g5 LT907848_s, genus Romboutsia, Roseburia triocola, Romboutsia timonensis, Clostridium PAC001136_s, Lachnospiraceae PAC001043 Genus _g, selected from the group consisting of Lachnospiraceae PAC001043_g PAC001449_s and combinations thereof Provides probiotics for enhancing immunity comprising at least one.
  • the present invention is Parasutterella genus, Eubacterium_g23 PAC001034_s, Blautia_uc, Ruminococcaceae PAC000661_g genus, Eubacterium_g5 LT907848_s, Romboutsia genus, Roseburia triocola, Romboutsia timonensis, Clostridium PAC001136_s, Lachnospiraceae PAC001043_g At least one selected from the group consisting of the genus Lachnospiraceae PAC001043_g PAC001449_s and combinations thereof It provides a health functional food for enhancing immunity comprising a.
  • probiotics refers to microorganisms having antibacterial and enzymatic activities that help balance intestinal microorganisms and products produced by the microorganisms.
  • probiotics are defined as live bacteria in the form of single or complex strains that are supplied to humans or animals in the form of dry cells or fermentation products to improve the intestinal flora.
  • immuno enhancement means strengthening and/or improving the immunity of an organism. It includes those that enhance immunity against diseases or have good immune responses to vaccines.
  • the health functional food of the present invention can be used in various ways such as pharmaceuticals, foods, and beverages for improving the intestinal environment.
  • Functional foods of the present invention include, for example, various foods, candy, chocolate, beverages, gum, tea, vitamin complexes, health supplements, etc., and can be used in the form of powders, granules, tablets, capsules or beverages.
  • the health functional food of the present invention may be added to food or beverages for the purpose of improving the intestinal environment.
  • the amount of the extract in the food or beverage is generally 0.01 to 50% by weight, preferably 0.1 to 20% by weight of the total food weight of the health functional food composition of the present invention, and the health drink composition is 100 ml Based on 0.02 to 10 g, it may be added at a rate of preferably 0.3 to 1 g.
  • the health beverage composition of the present invention has no particular limitations on the liquid component except for containing the strain as an essential component in the indicated ratio, and may contain various flavors or natural carbohydrates as additional components like conventional beverages.
  • natural carbohydrates described above are monosaccharides such as glucose and fructose, disaccharides such as maltose, sucrose, and lactose, oligosaccharides, polysaccharides such as dextrins and cyclodextrins, and sugar alcohols such as xylitol, sorbitol, and erythritol. .
  • flavoring agents other than those described above, flavoring agents (stevia extract (eg rebaudioside A, glycyrrhizin, etc.) and synthetic sweeteners (saccharin, aspartame, etc.) can advantageously be used.
  • the proportion of is generally about 1 to 20 g, preferably about 5 to 12 g per 100 ml of the composition of the present invention.
  • the composition of the present invention includes various nutrients, vitamins, minerals (electrolytes), flavors such as synthetic flavors and natural flavors, colorants and enhancers (cheese, chocolate, etc.), pectic acid and its salts, alginic acid and its salts, It may contain organic acids, protective colloidal thickeners, pH adjusters, stabilizers, preservatives, glycerin, alcohol, carbonation agents used in carbonated beverages, and the like.
  • the compositions of the present invention may contain fruit flesh for preparing natural fruit juice, fruit juice beverages, and vegetable beverages. These components may be used independently or in combination. The proportion of these additives is not critical, but is generally selected from the range of 0 to about 50 parts by weight per 100 parts by weight of the composition of the present invention.
  • the present invention relates to endoglucanase (KEGG ortholog K01179), fumarate hydratase class I (KEGG ortholog K01676), two-component regulatory system LytTR family sensor kinase (two -component regulatory system, LytTR family, sensor kinase, KEGG ortholog K02478), anthranilate synthase component I orthologs (KEGG ortholog K01657), butyryl-CoA dehydrogenase , KEGG ortholog K00248), two-component system, OmpR family, response regulator CpxR (two-component system, OmpR family, response regulator CpxR, KEGG ortholog K07662), peptide/nickel transport system permease protein protein, KEGG ortholog K02033), putative ABC transport system ATP-binding protein (KEGG ortholog K02003), aminocarboxymuconate-semialdehyde decarboxylase (KEGG ortholog K
  • the KEGG ortholog used to define the functional biomarker refers to a group of homologous genes in the genome provided by the Kyoto Encyclopedia of Genes and Genomes.
  • the term "functional biomarker” is a biomarker selected to predict the immune response of a subject based on the function in the metabolic pathway of a metabolite, preferably the metabolic pathway and It may be a relevant metabolomic biomarker.
  • Detection of the functional biomarker may be performed using a method known in the art.
  • the component to be detected is an amino acid, it may be a primer, probe, aptamer, or antibody capable of complementary binding, and in the case of a protein, LC- It can be done through MS (liquid chromatography-mass spectrometry) technique or ELISA (enzyme-linked immunosorbent assay), and in other cases, it can be detected through reagents or chemicals that can quantify them.
  • a step of determining a subject having a good immune response to the viral vector vaccine may be further included.
  • a step of determining the subject as having a poor immune response to the viral vector vaccine may be further included.
  • a subject with a good immune response refers to a subject with an excellent humoral immune response at 3 weeks after completion of vaccination, preferably a subject whose blood concentration of anti-SARS-CoV-2 S IgG is 2500 U/mL or more can be
  • the subject with a poor immune response refers to a subject with a poor humoral immune response at 3 weeks after completion of vaccination, preferably a subject whose blood anti-SARS-CoV-2 S IgG concentration is 1000 U/mL or less can be
  • the viral vector vaccine may be an adenovirus vector vaccine.
  • aminocarboxymuconate-semialdehyde decarboxylase in the biological sample isolated from the subject, aminocarboxymuconate-semialdehyde decarboxylase, iron complex transport system ATP binding protein, aromatic-L-amino acid / L-tryptophan dicarboxyl lase, glycine cleavage system transcriptional repressor, cobalt/nickel transport system ATP-binding protein, RNA 2', 3'-cyclic 3'-phosphodiesterase, propionyl-CoA carboxylase beta chain, putative ABC transport system ATP-binding protein (KEGG ortholog K02021), ferredoxin hydrogenase subunit, betaine/cartinine transporter BCCT family, HlyD family secreted protein, thiosulfate/3-mercaptopyruvate sulfurtransferase, If at least one functional biomarker from the group consisting of serine palmitoyltransferase, CRP
  • mRNA messenger ribonucleic acid
  • functional biomarkers of lase, CRP/FNR family transcriptional regulator anaerobic regulatory protein, and pocalyxin-analog were detected before in
  • a subject with a good immune response refers to a subject with an excellent humoral immune response at 3 weeks after completion of vaccination, preferably a subject whose blood concentration of anti-SARS-CoV-2 S IgG is 2500 U/mL or more can be
  • the subject with a poor immune response refers to a subject with a poor humoral immune response at 3 weeks after completion of vaccination, preferably a subject whose blood anti-SARS-CoV-2 S IgG concentration is 1000 U/mL or less can be
  • endoglucanase fumarate hydratase class I
  • two-component regulatory system LytTR family sensor kinase anthranilate synthase component I ortholog
  • butyryl-CoA dehydrogenase two-component regulatory system OmpR family response regulator CpxR
  • peptide/nickel transport system fermease protein putative ABC transport system ATP binding protein (KEGG ortholog K02003), aminocarboxymuconate-semialdehyde decarboxylase, iron complex transport system ATP binding protein, aromatic-L-amino acid/L-tryptophan decarboxylase, glycine cleavage system transcriptional repressor, cobalt/nickel transport system ATP-binding protein, RNA 2', 3'-cyclic 3'- Phosphodiesterase, propionyl-CoA carboxylase beta chain, putative ABC transport system ATP-binding protein (KEGG ortholog K0202
  • a kit for providing vaccination information tailored to a subject including the composition is provided.
  • the kit may include a detection agent as an essential component.
  • a detection agent as an essential component.
  • a capture antibody, a detection antibody, a buffer, a test tube or other appropriate container, a reaction buffer, sterile water, and the like may be included.
  • the kit may include various tools and reagents known in the art that facilitate measurement of functional biomarkers, such as suitable carriers, labeling substances capable of generating detectable signals, stabilizers, and the like.
  • the present inventors found that the functional biomarker populations of group 1 and group 2 below each had a significant correlation with the immune response after vaccination.
  • Group 1 endoglucanases, fumarate hydratase class I, two-component regulatory system LytTR family sensor kinases, anthranilate synthase component I orthologs, aminocarboxymuconate-semialdehyde decarboxylase, iron complex transport system ATP-binding protein, aromatic-L-amino acid/L-tryptophan decarboxylase, glycine cleavage system transcriptional repressor, cobalt/nickel transport system ATP-binding protein, RNA 2', 3'-cyclic 3' -phosphodiesterase, propionyl-CoA carboxylase beta chain, putative ABC transport system ATP-binding protein (KEGG ortholog K02021), ferredoxin hydrogenase subunit, betaine/cartinine transporter BCCT family, HlyD family secreted proteins, thiosulfate/3-mercaptopyruvate sulfurtransferase, serine palmitoyltransfer
  • Group 2 butyryl-CoA dehydrogenase, two-component regulatory system OmpR family response regulator CpxR, peptide/nickel transport system permease protein, putative ABC transport system ATP binding protein (KEGG ortholog K02003), ribosomal protein L11 Methyltransferase, pyrroline-5-carboxylate reductase, 23S rRNA (guanosine 2251-2'-O)-methyltransferase, anaerobic ribonucleoside-triphosphate reductase active protein, epoxy quiosine reductase, putative sigma-54 regulatory protein, 2-iminobutanoate/2-iminopropanoate deaminase, rod-shaped determinant protein RodA, competence protein ComEA and acrylaminoacyl;
  • functional markers belonging to the first group were relatively dominant functional biomarkers of the intestinal microflora before inoculation of the group in which the immune response was excellent after completion of inoculation.
  • endoglucanase, fumarate hydratase class I, two-component regulatory system LytTR family sensor kinase, and anthranilate synthase component I orthologs were relatively dominant in the superior immunoreactive group of the ChAdOx1 inoculum, and BNT162b2 Aminocarboxymuconate-semialdehyde decarboxylase, iron complex transport system ATP binding protein, aromatic-L-amino acid/L-tryptophan decarboxylase, glycine cleavage system transcriptional repressor, Cobalt/nickel transport system ATP-binding protein, RNA 2', 3'-cyclic 3'-phosphodiesterase, propionyl-CoA carboxylase beta chain, putative ABC
  • the microorganisms belonging to the second group were relatively dominant functional biomarkers before inoculation of the group with poor immune response after inoculation.
  • butyryl-CoA dehydrogenase, two-component control system OmpR family response regulator CpxR, peptide / nickel transport system fermease protein and putative ABC transport system ATP binding protein ( KEGG ortholog K02003) was relatively dominant, and ribosomal protein L11 methyltransferase, pyrroline-5-carboxylate reductase, 23S rRNA (guanosine 2251-2'-O) -Methyltransferase, anaerobic ribonucleoside-triphosphate reductase activator protein, epoxyquiosine reductase, putative sigma-54 regulatory protein, 2-iminobutanoate/2-iminopropanoate diamina enzyme, rod-shaped crystal protein RodA, competence protein ComE
  • V1 first inoculation
  • V2 before the second inoculation
  • V3 3 weeks after the second inoculation
  • Anti-S antibody titers were measured using the anti-SARS-CoV-2 S assay kit (Roche, Switzerland) according to the protocol of Elecsys®. A titer below the lower limit of quantification was set at a value of 0.4. Based on data on immune correlation of protection and association between anti-S IgG and neutralizing antibody titers, participants with an IgG titer of 2500 or greater in V3 were labeled as good immune responders, and participants with titers less than 1000 were labeled as having poor immune responses. labeled as a group. In addition, participants with an IgG titer of 120 or more in V2 were labeled as the V2 excellent immune response group, and participants with a V2 titer of less than 40 were labeled as the V2 poor immune response group.
  • Total DNA from the microbiota was extracted using the FastDNA® SPIN Kit for Soil (MP Biomedicals, Southern California, USA) according to the manufacturer's instructions. PCR amplification was performed using fusion primers targeting the V3-V4 region of the 16S rRNA gene using the extracted DNA as a template. Primers of SEQ ID NOs: 7 and 8 in Table 1 were used for amplification. The highlighted part below is the target site.
  • the primer of SEQ ID NO: 7 was fused to the 3' end of 5'-AATGATACGGCGACCACCGAGATCTACAC-XXXXXXXTCGTCGGCAGCGTC-3' composed of P5 graft binding, i5 index, and NexTera consensus.
  • the primer of SEQ ID NO: 8 was fused to the 3' end of 5'-CAAGCAGAAGACGGCATACGAGAT-XXXXXXXGTCTCGTGGGCTCGG-3' composed of P7 graft binding, i7 index, and NexTera consensus.
  • the "X" represents the Illumina NexTera barcode region.
  • PCR amplification was performed under the following conditions: initial denaturation at 95 °C for 3 min, followed by 25 cycles of denaturation at 95 °C for 30 sec, primer binding at 55 °C for 30 sec, elongation at 72 °C for 30 sec. , and a final elongation step at 72 °C for 5 min.
  • PCR products were confirmed by electrophoresis using a 1% agarose gel and then visualized using the Gel Doc system (Bio-Rad, Hercules, CA, USA). Amplified products were purified using CleanPCR kit (CleanNA). Equal concentrations of purified products were pooled and short fragments (off-target products) were removed using the CleanPCR kit (CleanNA).
  • Raw readings were first quality checked and low quality ( ⁇ Q25) readings were filtered out using Trimmomatic (ver. 0.32). After QC processing, paired-end sequence data was merged with default parameters using the fastq_mergepairs command of VSEARCH ver.2.13.4. Next, the primers were trimmed using the Myers-Miller alignment algorithm at a similarity cutoff of 0.8 (Myers EW, Miller W. Optimal alignments in linear space. Comput Appl Biosci 1988; 4: 11-7.).
  • Non-specific amplicons i.e., those that do not encode 16S rRNA, were detected using the nhmmer algorithm of the HMMER software package version 3.2.1 with hmm profile (Wheeler TJ, Eddy SR. nhmmer: DNA homology search with profile HMMs. Bioinformatics 2013; 29: 2487-2489.).
  • Unique reads were extracted and redundant reads were clustered into unique reads using VSEARCH's deep-full-length command (Rognes T, Flouri T, Nichols B, et al. VSEARCH: a versatile open source tool for metagenomics. PeerJ 2016; 4: e2584.).
  • EzBioCloud 16S rRNA database (Yoon SH, Ha SM, Kwon S, et al. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol 2017; 67: 1613-1617.) It was used for taxonomic assignment using VSEARCH's usearch_global command, after which a more accurate pairwise alignment was performed. Chimeric reads were filtered to obtain reads of ⁇ 97% similarity by reference-based chimeric reads detection using the CHIME algorithm and EzBioCloud's non-chimeric 16S rRNA database.
  • ACE Cho A, Lee S-M. Estimating the Number of Classes via Sample Coverage. J Am Stat Assoc1992; 87: 210-217.
  • Chao1 Choao A. Estimating the population size for capture -recapture data with unequal catchability. Biometrics 1987; 43: 783-791.
  • Jackknife Jack KP, Overton WS. Robust Estimation of Population Size When Capture Probabilities Vary Among Animals. Ecology 1979; 60: 927-936.
  • Shannon Magnurran AE. Measuring biological diversity: John Wiley & Sons, 2013.
  • NPShannon Cho A, Shen T-J.
  • the biomarker uses a statistical comparison algorithm (linear discriminant analysis effect size, LEfSe] (Segata N, Izard J, Waldron L, et al. Metagenomic biomarker discovery and explanation. Genome Biol 2011; 12: R60.) Logarithmic scoring of the above linear discriminant analysis is presented as the LDA score All microbiome count data were normalized to the number of 1000 reads before further use All assays mentioned above were performed in ChunLab , Inc.'s bioinformatics cloud platform, EzBioCloud 16S-based MTP.
  • a total of 159 blood samples were collected from 53 fully vaccinated participants before the first dose (V1), before the second dose (V2) and 3 weeks after the second dose (V3) (Fig. 1). All 159 blood samples (81 from BNT162b2 inoculated subjects and 78 from ChAdOx1 inoculated subjects) were scored for anti-SARS-CoV-2 S IgG.
  • Tables 2 to 4 The baseline characteristics of the participants according to the type of vaccine inoculated and the antibody response are shown in Tables 2 to 4 below.
  • Table 2 shows blood test results of all of the ChAdOx1 and BNT162b2 inoculation groups
  • Tables 3 and 4 below show details of dividing the ChAdOx1 and BNT162b2 inoculation groups into excellent and poor immune response groups, respectively.
  • the geometric mean titer (GMT) of anti-SARS-CoV-2 S IgG at baseline (V1) was 0.4 U/mL in all participants. Regardless of vaccine type, higher antibody titers were observed in participants who received 2 doses than those who received 1 dose. It was confirmed that there was no significant difference in the GMT of anti-SARS-CoV-2 S IgG titers between the ChAdOx1 vaccinated group and the BNT162b2 vaccinated group in V1, V2 and V3.
  • MCHC mean corpuscular hemoglobin concentration
  • Stool samples were collected at three consecutive time points (V1, V2 and V3) from 53 participants to investigate changes in the gut microbiota in response to vaccination (Fig. 1). Of the 159 stool samples collected, 30 were excluded from analysis due to poor quality and 129 stool samples were used for sequencing (63 from ChAdOx1 inoculum and 66 from BNT162b2 inoculum). The humoral immune response was evaluated using corresponding blood samples.
  • the relative abundance of bacterial taxa was assessed to determine microbiological factors (taxonomic biomarkers in V1 based on antibody titers in V3) that influence antibody production to the COVID-19 vaccine.
  • LEfSe was used to differentiate the composition of the gut microbiome based on the immune response in both the ChAdOx1 and BNT162b2 groups (FIG. 13A, 13B).
  • the pre-vaccination intestinal microbiome of the excellent immune response group in the ChAdOx1 inoculation group was detected the Parasutterella genus, Eubacterium_g23 PAC001034_s and Blautia_uc, and the poor immune response group PAC001031_s and Bifidobacterium animalis group were detected.
  • the gut microbiome of the superior immune response group was Ruminococcaceae PAC000661_g, Eubacterium_g5 LT907848_s, Romboutsia, Roseburia triocola, Romboutsia timonensis, Clostridium PAC001136_s, Lachnospiraceae PAC001043_g, and Lachnospiraceae PAC00104.
  • 3_g PAC001449_s genus was detected, and Bacteroides dorei and Megasphaera were detected in the poor immune response group. indica was predominantly detected.
  • biomarkers of an excellent immune response after vaccination were analyzed for the time point before vaccination, and biomarkers were determined based on an LDA score of 2.5 or higher. showed up
  • ChAdOx1 (taxonomic markers V1 : V3) taxon name LDA score (log 10) p-value genus Parasutterella 3.55382 0.02402 Eubacterium_g23 PAC001034_s 2.95184 0.02381 Blautia_uc 2.72821 0.04829
  • BNT162b2 (taxonomic markers V1 : V3) taxon name LDA score (log 10) p-value Genus Ruminococcaceae PAC000661_g 3.72866 0.01823 Eubacterium_g5 LT907848_s 3.61881 0.02987 genus Romboutsia 3.58706 0.04067 Roseburia diarrhea 3.56697 0.04119 Romboutsia timonensis 3.55002 0.04067 Clostridium PAC001136_s 3.39063 0.01823 Genus Lachnospiraceae PAC001043_g 3.30157 0.04119 Lachnospiraceae PAC001043_g PAC001449_s 3.20569 0.01823
  • a marker having a positive LDA score is a marker that was dominant in the good immune response group
  • a marker having a negative LDA score is a marker that was dominant in the poor immune response group.
  • LEfSe, or LDA effect size is the absolute value of the LDA score.
  • a marker having a positive LDA score is a marker that was dominant in the good immune response group
  • a marker having a negative LDA score is a marker that was dominant in the poor immune response group.
  • LEfSe, or LDA effect size is the absolute value of the LDA score.
  • KEGG orthologs abundantly observed in the BNT162b2 inoculated group are shown in FIG. 14B and Table 8, and functional markers were selected based on the LDA effect size of 1.6.
  • iron complex transport system ATP binding protein (iron complex transport) system ATP-binding protein

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Abstract

La présente invention concerne un procédé de fourniture d'informations pour prévoir une réponse immunitaire à une vaccination contre le SARS-CoV-2 et un procédé de fourniture d'informations de vaccin personnalisées, et plus spécifiquement, la présente invention vérifie que la composition taxonomique d'un microbiote intestinal, les métabolites produits par celui-ci, et leurs profils fonctionnels sont significativement corrélés à la réponse immunitaire après vaccination, et peuvent ainsi être utilisés pour prévoir la réponse immunitaire à une vaccination contre le SARS-CoV-2 ou fournir des informations de vaccin personnalisées pour le sujet. Selon la présente invention, par identification de la composition taxonomique et de biomarqueurs fonctionnels du microbiote intestinal d'un sujet avant la vaccination, le niveau de réponse immunitaire humorale du sujet après vaccination peut être prévu et des informations peuvent être fournies pour une administration de vaccin qui devrait induire une réponse immunitaire efficace et moins d'effets secondaires chez le sujet.
PCT/KR2022/016100 2021-11-03 2022-10-21 Procédé de fourniture d'informations pour prévoir une réponse immunitaire à un vaccin contre le sars-cov-2 par l'intermédiaire d'un microbiote intestinal et de profils de biomarqueurs fonctionnels, et procédé de fourniture d'informations de vaccin personnalisées pour un sujet Ceased WO2023080501A1 (fr)

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KR1020220066976A KR102837385B1 (ko) 2021-11-03 2022-05-31 장내 기능적 바이오마커 프로파일을 통해 SARS-CoV-2 백신의 면역반응을 예측하기 위한 정보제공방법 및 대상체 맞춤형 백신정보제공방법
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KR1020220066986A KR102837389B1 (ko) 2021-11-03 2022-05-31 장내 미생물군집 프로파일을 통해 SARS-CoV-2 백신의 면역반응을 예측하기 위한 정보제공방법 및 대상체 맞춤형 백신정보제공방법

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