WO2016008081A1 - Biomarqueur pour la cirrhose du foie et ses utilisations - Google Patents

Biomarqueur pour la cirrhose du foie et ses utilisations Download PDF

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WO2016008081A1
WO2016008081A1 PCT/CN2014/082181 CN2014082181W WO2016008081A1 WO 2016008081 A1 WO2016008081 A1 WO 2016008081A1 CN 2014082181 W CN2014082181 W CN 2014082181W WO 2016008081 A1 WO2016008081 A1 WO 2016008081A1
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liver cirrhosis
genes
col7a
clostridiales
gut
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PCT/CN2014/082181
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English (en)
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Lanjuan LI
Nan Qin
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Zhejiang University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P1/00—Drugs for disorders of the alimentary tract or the digestive system
    • A61P1/16—Drugs for disorders of the alimentary tract or the digestive system for liver or gallbladder disorders, e.g. hepatoprotective agents, cholagogues, litholytics
    • 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
    • C12Q1/02—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving viable microorganisms
    • C12Q1/04—Determining presence or kind of microorganism; Use of selective media for testing antibiotics or bacteriocides; Compositions containing a chemical indicator therefor
    • 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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K35/00—Medicinal preparations containing materials or reaction products thereof with undetermined constitution
    • A61K35/66—Microorganisms or materials therefrom
    • A61K35/74—Bacteria

Definitions

  • the present invention relates to the field of biomedicine and biotech, specifically related to biomarker for liver cirrhosis and its applications.
  • Liver cirrhosis is an advanced liver disease resulting from acute or chronic liver injur ⁇ ' ' of any origin, including alcohol abuse, obesity and hepatitis virus infection.
  • the prognosis for patients with decompensated liver cirrhosis is poor, and they frequently require liver transplantation 1 .
  • the liver interacts directly with the gut through the hepatic portal and bile secretion 2 systems.
  • Enteric dysbiosis especially the translocation of bacteria 3 and their products 4,3 across the gut epithelial barrier, is involved in the progression of liver cirrhosis.
  • the phylogenetic and functional composition changes in the human gut microbiota that are related to this progression remain obscure 5 .
  • liver cirrhosis 6 such as spontaneous bacterial peritonitis'' and hepatic encephalopathy 8
  • early-stage liver disease 9 such as alcoholic liver disease 10 and non-alcoholic fatty liver disease 11
  • definitive associations between alterations in gut microbiota and liver pathology in humans are still lacking 12 .
  • Studies of liver cirrhosis patients 13 andof mouse models for alcoholic liver disease 10 have revealed a similar and substantial alteration in the gut microbiota, as measured by sequencing of 16S rRNA genes. How these phylogenetic alterations relate to changes in the functioning of the gut microbiota is unclear.
  • gut microbiota in human health and disease 14 has received unprecedented attention over the past few years with the rapid development of next-generation sequencing technologies.
  • Several complex chronic diseases, such as obesity 15-18 , inflammatory bowel disease 19 ' 20 , diabetes mellitus 21 , metabolic syndrome 22 , symptomatic atherosclerosis 23 and non-alcoholic fatty liver disease 10 have been associated to gut microbiota.
  • a metagenomic study of 345 Chinese individuals with type-2 diabetes (T2D) identified 60,000 T2D-associated genes 24.
  • T2D type-2 diabetes
  • HMP human microbiome gene resource 25 , which includes most of the genera, enzyme families and community configurations from the microbiota of healthy adults from Western countries 25 .
  • a quantitative metagenomics analysis "' ⁇ of stool samples from Chinese liver cirrhosis patients and their healthy counterparts with the objective of improving the understanding of gut microbiota changes associated with liver cirrhosis was carried out.
  • Our invention aims to provide additional knowledge of gut microbiota modifications in liver cirrhosis patients and to propose targeted biomarkers offering a non-invasive approach for early detection of the disease.
  • a biomarker for liver cirrhosis in a human comprising VeiUonelia atypica ACS- 134-V-Col7a over-represented in gut microbiota of LC affected subjects as compared to healthy subjects and at least one bacterial strain over-represented in gut microbiota of healthy subject as compared to LC affected subjects.
  • the strain over-represented in gut microbiota of healthy subject as compared to LC affected subjects comprises Bacleroides uniformis ATCC 8492, and Clostridiciles
  • a method of treating/preventing liver cirrhosis in a human comprising administering to the human a therapeutically effective amount of a probiotic composition comprising one or more bacterial strains, wherein the composition
  • a probiotic composition comprising one or more bacterial strains, wherein the composition
  • a kit for diagnosing of li ver cirrhosis comprising reagents for:
  • step (b) comparing the amount obtained in step (a) with a preset threshold.
  • a method for monitoring the efficacy of treatment of LC comprising the steps of:
  • step (b) comparing the amount obtained in step (a) with a preset threshold.
  • a method for identify ing microbiota affected by LC disease in a human comprising;
  • step c) selecting one or more bacterial strains to compensate the expression of one or more genes identified in step c).
  • Figure 1 Illustrates diagram of the data analysis pipeline
  • FIG. 1 illustrates taxonomic assignment of metagenomics species
  • MGS enriched in Chinese liver cirrhosis patients and healthy individuals.
  • Species-level assignment was deduced from the best BlastN hits of genes from a given MGS at thresholds of the average of >95% identity and >90% overlap with genes from a sequenced genome. For MGS where these thresholds were not reached, an assignment was attributed at the lowest taxonomy level where at least 80% of the genes had the same best hit BlastP taxonomy; in all cases this criteria held true at higher taxonomic levels.
  • Example 1 Construction of a liver cirrhosis gut microbial gene set and comparison with previous gene sets
  • the liver cirrhosis patients and healthy control adults were Han Chinese. In total, 123 liver cirrhosis patients and 114 healthy control adults were enrolled in our cohort. Our investigation included two phases. The first phase was a discovery phase in which 98 liver cirrhosis patients and 83 healthy controls were enrolled to characterize gut microbial compositional and functional changes between the two groups. The second phase was a validation phase, in which an additional 25 liver cirrhosis patients and 31 controls were enrolled to validate the accuracy of the discovery phase findings.
  • the reads were assembled into contigs for all samples using the assembly software SOAPdenovo 29 .Unassembled reads from 166 samples were pooled and the de novo assembly process was performed again for these reads (see Methods and Fig. 1 ).
  • the MetaGene program predicted 13,371,697 open reading frames (ORFs) using a 100-bp cut-off for prediction.
  • the total length of the predicted ORPs was 9,495,923,532 bp, representing 90.28% of the total length of the contigs.
  • 1,047,885 (54.6%) were complete genes, while 869,808 (45.4%) were incomplete.
  • a non-redundant "LC gene set" was established by removing redundant ORFs, defined as those sharing 95% identity over 90% of the shorter ORF length in pair-wise alignments.
  • the final non-redundant liver cirrhosis gut gene set contained 2,688,468 ORFs, with an average length of 750bp and 42% of reads could be aligned to the gene catalogue.
  • the MetaHIT catalogue contained 3,452,726 genes, HMP 4,768,112 genes, and T2D 2,148,029 genes. In total 674,131 genes were shared among all four catalogues.
  • the LC, MetaHIT, HMP and T2D gene sets contained 794,647, 1 ,419,517 2,620,096 and 623,570 unique genes, respectively.
  • the HMP gut gene set was not included, as it contained Sanger, 454 or Illumina based 16S sequences, in addition to whole metagenomic data andit was generated from exclusively healthy individuals rather than from a disease cohort with accompanying healthy controls.
  • the merged gene catalogue contained 5,382,817 genes, of which 797,690 were shared between all three catalogues. Of the genes in the LC gene set, 63.9% were also present in either one or both of the remaining two, whereas 37.1% were unique.
  • the MetaHIT and T2D sets contained 57.7% and 33.9% unique genes respectively. Large differences were also observed in the two gene sets derived from Chinese cohorts, the LC and T2D sets.
  • genes of a given species are expected to have closely similar abundances in an individual. Species abundances vary greatly ( 12 to > 1000-fold) across individuals in a cohort31, and so genes of a same species can be efficiently clustered by abundance co-variation. The resulting clusters are denoted metagenomic species (MGS) here. Similar approaches were previously used in other studies24,27,28,32.
  • Each cirrhotic patient and healthy control subject provided a fresh stool sample that was delivered immediately from our hospital to the lab on ice bag using insulating polystyrene foam containers. In the lab it was divided into 5 aliquots of 200mg and immediately stored at -80°C.A frozen aliquot (200 mg) of each faecal sample was processed by phenol Trichloromethane DNA extraction method 16 as previously described. DNA concentration was measured by nanodrop (Thermo Scientific) and its molecular size was estimated by agarose gel electrophoresis.
  • DNA libraries were constructed according to the manufacturer's instruction (Illumina). Same workflows from Illumina were used to perform cluster generation, template hybridization, isothermal amplification, linearization, blocking, denaturing and hybridization of the sequencing primers. Paired-end sequencing 2* 100bp was performed for all libraries.
  • Reads that mapped to human genome together with their mated/paired reads were removed from each sample using BWA with parameters -n 0.2. Then quality control was preceded with following criteria: a) Reads containing more than 3 N bases were removed, b) Reads containing more than 50 bases with low quality (Q2) were removed, c) No more than 10 bases with low quality (Q2) or assigned as N in the tail of reads were trimmed. Sequences that lost their mated reads were considered as single reads and were used in the assembly procedure. Resulting filtered reads were considered for next step analysis.
  • MetaGeneMark 33 (prokaryotic GeneMark.hmm version 2.8) was used to predict ORFs in scaffolds without ambiguous bases.
  • the non-redundant human gut gene set was built by pair-wise comparison of all the predicted ORFs using blat and the redundant ORFs were removed using a criterion of 95% identity over 90% of the shorter ORF length, which is consistent with the criterion used for the non-redundant European human gut gene set 31 and T2D study 24 .
  • MetaGeneMark to predict genes in assembled contigs originally from MetaHIT and T2D study and merged these three gene sets into a single one with the above method.
  • SOAPalign 2.21 was used to align paired-end clean reads against reference genomes with parameters -r 2 -m 200 -x 1000. Reads with alignments on same reference genomes might be assigned into two types:
  • U Unique reads
  • My Multiple reads
  • reads have alignments with more than one genome, if these genomes come from one species; we denote these reads as unique reads. If they are from more than one species, we denote these reads as multiple reads.
  • AbfU and Ab(M) are abundance of unique and multiple reads respectively, / is length of relative genome.
  • Co/let there is a species specific coefficient Co/let us suppose one read in ⁇ M ⁇ has alignments with /V different species then Co was calculated as follows.
  • AbfU and Ab(M) are abundance of unique and multiple reads respectively, / is length of gene G.
  • Co For each multiple reads we calculate a specific coefficient Co for this gene, let us suppose one read with multiple ⁇ M ⁇ alignments in TV different genes, then Co was calculated as follows.
  • MCS MetaGenomic Species
  • the remaining MGS were annotated using blastP analysis and assigned to a given taxonomical level from genus to superkingdom level if >80% of its 50 tracer genes had the same level of assignment". All 36 remaining species but one could thus be assigned to a given genus, family or order. The quality of the clustering was thus validated by the homogenous annotation of its marker genes, which also held true for the whole MGS genes (data not shown). Abundance of the 66 MGS in each individual was computed using the 50 tracer genes.
  • liver transplantation official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society 13, 1582-1588, doi : 10.1002/lt.21277 (2007).

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Abstract

Les communautés microbiennes fécales et leur composition fonctionnelle sont caractérisées par une étude d'associations de microbiome intestinal complet-sauvage d'échantillons de selles provenant de 98 patients atteints de cirrhose du foie et de 83 témoins en bonne santé. Veillonella atypique ACS-134-V-Col7a est enrichi chez les patients atteints de cirrhose du foie tandis que Bacteroides uniformis ATCC 8492 et Clostridiales sont enrichis chez les témoins. L'invention porte sur un biomarqueur pour la cirrhose du foie chez l'homme comprenand Veillonella atypique ACS-134-V-Col7a et au moins une souche bactérienne sur-représentée dans le microbiote intestinal d'un sujet en bonne santé par comparaison avec des sujets atteints de cirrhose du foie, qui comprend Bacteroides uniformis ATCC 8492 et Clostridiales. Veillonella atypique ACS-134-V-Col7a, Bacteroides uniformis ATCC 8492 et Clostridiales peuvent être utilisés pour le traitement/la prévention ou le diagnostic de la cirrhose du foie.
PCT/CN2014/082181 2014-07-15 2014-07-15 Biomarqueur pour la cirrhose du foie et ses utilisations WO2016008081A1 (fr)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021256618A1 (fr) * 2020-06-19 2021-12-23 한국식품연구원 Composition pour prédire ou diagnostiquer un risque de maladie à l'aide de microbes intestinaux, kit de diagnostic l'utilisant, procédé pour fournir des informations et procédé pour cribler un agent pour prévenir ou traiter le diabète
KR20210157234A (ko) * 2020-06-19 2021-12-28 한국식품연구원 장내 미생물을 이용한 간질환 위험도 예측 또는 진단용 조성물, 그를 이용한 진단키트, 정보제공방법 및 간질환 예방 또는 치료제 스크리닝 방법

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JPH04330016A (ja) * 1991-05-01 1992-11-18 Rikagaku Kenkyusho 過酸化脂質低下剤
US20130288261A1 (en) * 2011-05-31 2013-10-31 Jens Walter Probiotics and methods of obtaining same
CN104195146A (zh) * 2014-07-15 2014-12-10 浙江大学 肝硬化微生物标志物及应用

Patent Citations (3)

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Publication number Priority date Publication date Assignee Title
JPH04330016A (ja) * 1991-05-01 1992-11-18 Rikagaku Kenkyusho 過酸化脂質低下剤
US20130288261A1 (en) * 2011-05-31 2013-10-31 Jens Walter Probiotics and methods of obtaining same
CN104195146A (zh) * 2014-07-15 2014-12-10 浙江大学 肝硬化微生物标志物及应用

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Title
CHEN, Y. ET AL.: "Characterization of Fecal Microbial Communities in Patients with Liver Cirrhosis", HEPATOLOGY, vol. 54, 31 December 2011 (2011-12-31), pages 562 - 572, XP055159513, DOI: doi:10.1002/hep.24423 *
WEI, X. ET AL.: "Abnormal fecal microbiota community and functions in patients with hepatitis B liver cirrhosis as revealed by a metagenomic approach", BMC GASTROENTEROLOGY, vol. 13, 26 December 2013 (2013-12-26), XP021172118, DOI: doi:10.1186/1471-230X-13-175 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021256618A1 (fr) * 2020-06-19 2021-12-23 한국식품연구원 Composition pour prédire ou diagnostiquer un risque de maladie à l'aide de microbes intestinaux, kit de diagnostic l'utilisant, procédé pour fournir des informations et procédé pour cribler un agent pour prévenir ou traiter le diabète
KR20210157234A (ko) * 2020-06-19 2021-12-28 한국식품연구원 장내 미생물을 이용한 간질환 위험도 예측 또는 진단용 조성물, 그를 이용한 진단키트, 정보제공방법 및 간질환 예방 또는 치료제 스크리닝 방법
KR102363094B1 (ko) * 2020-06-19 2022-02-16 한국식품연구원 장내 미생물을 이용한 간질환 위험도 예측 또는 진단용 조성물, 그를 이용한 진단키트, 정보제공방법 및 간질환 예방 또는 치료제 스크리닝 방법
KR20220024324A (ko) * 2020-06-19 2022-03-03 한국식품연구원 장내 미생물을 이용한 간질환 위험도 예측 또는 진단용 조성물, 그를 이용한 진단키트, 정보제공방법 및 간질환 예방 또는 치료제 스크리닝 방법
KR102622107B1 (ko) * 2020-06-19 2024-01-08 한국식품연구원 장내 미생물을 이용한 간질환 위험도 예측 또는 진단용 조성물, 그를 이용한 진단키트, 정보제공방법 및 간질환 예방 또는 치료제 스크리닝 방법

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