Method for identifying and classifying sample microorganisms
AssigneeChunlab, Inc.
InventorsMauricio Antonio Chalita Williams, Seok-Hwan YOON, Sung-Min HA
Life of this patent
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Abstract
The present invention relates to a method for identifying and classifying microorganisms included in a sample by using an exact k-mer matching algorithm and a bacterial core gene and, preferably, can more quickly and more accurately analyze the taxonomic composition of a metagenomic sample without bias.
Claims14
A method of identifying and classifying microorganisms in a sample, the method comprising the step of:
- providing microbial genome information obtained from the sample;
- obtaining a sample k-mer dataset using the microbial genome information;
- and
- comparing the sample k-mer dataset with a microbial taxon information-assigned reference k-mer database of reference microbial core genes to identify and classify microbes in the sample.
A method for obtaining abundance profiling information of microbial species in a sample, the method comprising the steps of:
- providing microbial genome information obtained from the sample;
- obtaining a sample k-mer dataset using the microbial genome information;
- and
- comparing the sample k-mer dataset with a microbial taxon information-assigned reference k-mer database of reference microbial core genes,
- wherein the microbial taxon information is classified by unique ID values and is assigned to individual k-mers in the reference k-mer database,
- wherein the sample microbial genome information includes sequencing reads obtained by next generation sequencing (NGS), and
- for individual sequencing reads of the sample microbial genome,
- (i) creating a k-mer dataset including one or more k-mers and comparing with the reference k-mer database of reference microbial core genes to select a k-mer whose nucleotide sequence is exactly matched, from the reference k-mer database,
- (ii) obtaining unique ID information assigned to the selected k-mer,
- (iii) selecting an ID as a unique ID for a sequencing read if a unique ID list includes one unique ID or all identical unique IDs, or selecting a unique ID corresponding to the least common ancestor (LCA) if a unique ID list includes two or more different unique IDs, using list information including one or more unique IDs obtained for the sequencing reads,
- (iv) combining taxon information of the unique IDs corresponding to the taxonomic levels assigned to individual sequencing reads, and
- generating an entire unique ID list with collecting the unique IDs corresponding to the taxonomic levels obtained for the individual sequencing reads for entire sequencing reads included in the sample microbial genome,
- obtaining the number of the classified reads by unique ID corresponding to the taxonomic level, from the full unique ID list for microbes in the sample, and
- obtaining an abundance in the sample for the microbial species or taxon information corresponding to the unique IDs by dividing the number of the classified reads by unique ID with a sum of the number of classified reads in the full unique ID list.
A system of identifying and classifying a microorganism in a sample, the system comprising:
- (a) a reference k-mer database of reference microbial core genes;
- and (b) a processor equipped with a k-mer extractor and a k-mer analyzer,
- wherein the reference k-mer database comprises at least one k-mer generated from DNA information of at least one reference microbial core gene, and the k-mer is assigned with microbial taxon information,
- wherein the k-mer extractor in the processor extracts at least one k-mer from metagenomic information obtained from the sample to generate k-mer database;
- and
- wherein the k-mer analyzer in the processor selects a k-mer exactly identical in nucleic acid sequence information from the k-mers contained in the reference k-mer database of reference core genes with respect to the k-mer contained in a sample k-mer dataset, lists unique IDs accounting for taxon information of the selected k-mer, and identifies and classifies the microbe in the sample, based on the taxonomic information about the selected k-mer.
Dependencies are inferred from the claim text.