Metagenomics technology bypasses the traditional method of microbial isolation and culture to extract total DNA directly from environmental samples, and obtains new functional genes and bioactive by constructing and screening metagenomic libraries, which include both culturable and unculturable microbial genetic information, thus increasing the chance of obtaining new bioactive.
Metagenomics is a new approach to microbial research in which the genomes of microbial populations in environmental samples are studied by functional gene screening and/or sequencing analysis, and can be used to analyze microbial diversity, population structure, evolutionary relationships, functional activity, and relationships with the environment.
Analysis of the role of the human microbiome in COVID-19 by metagenomics
In the article "Dissecting the role of the human microbiome in COVID-19 via metagenome-assembled genomes", published in Nature Communications in September, a total of 11,584 MAGs (metagenome-assembled genomes) and 5,403 non-redundant MAGs (nrMAGs) at the strain level were obtained from 514 nasal and fecal samples from COVID-19 patients, by metagenome assembly and binning techniques using published metagenome NGS data from six independent cohorts.
Reconstruction of MAGs from 514 COVID-19 related shotgun metagenomics sequencing data in the discovery cohorts (Ke S et al., 2022)
It was found that the strain abundance of many microbial species in the gut of COVID-19 patients was significantly reduced compared to normal subjects and that COVID-19 cases could be accurately distinguished from healthy controls based on gut microbiome characteristics and could predict the progression of COVID-19, along the lines shown below.
How to analyze metagenomic data?
1. metagenome assembly and binning
The authors used metaWRAP, an analysis process that integrates quality control, splicing, boxing, purification, evaluation, species annotation, abundance estimation, functional annotation and visualization, to process the raw sequencing data, incorporating over 140 tools. The detailed process is as follows.
a. QC and removal of host contamination of raw data
b. Assembly of the decontaminated data using the metaSPAdes tool in the metaWRAP
c. binning using MaxBin2, metaBAT2 and CONCOCT software, and purifying the binning results using the bin_refinement module, and finally assessing the contamination rate and completeness of the results using CheckM.
2. Clustering and dereplication of MAGs
The MAGs were clustered on species-level genome bins (SGBs) using the software dRep, and then the MAGs were taxonomically annotated based on the Genome Taxonomy database using the software GTDB-Tk.
3. Calculation of species abundance and phylogenetic tree
The abundance of each nrMAGs was calculated using the software Salmon, and evolutionary trees were constructed using PhyloPhlAn and embellished using iTOL.
4. Genome annotation of nrMAGs
The genomes obtained from bining were genetically predicted using Prokka software, and the genes were functionally annotated using MicrobeAnnotator and the completeness of each database annotation was assessed. Finally, functional analysis was performed using HUMANN3.
5. Statistical analysis
Alpha and Beta microbial diversity were calculated using the R's vegan package, and random forest regression analysis was performed using R' random Forest package.
Summary
Analysis of hundreds of WMS sequencing data revealed that COVID-19 patients lost many strains (nrMAGs) for certain microbial species compared to non-COVID-19 controls. Through machine learning, the authors demonstrated the feasibility of accurately detecting COVID-19 from healthy controls based on gut microbiome signatures at nrMAG levels. Further understanding of the interactions between the human microbiome (including bacteria, fungi, and viruses) and SARS-CoV-2 infection, or other viral infections, may be discovered in the future with continued optimization of technology and data analysis methods.
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CD Genomics provides Viral Metagenomic Sequencing and Metagenomic Shotgun Sequencing based on Illumina, Nanopore sequencing and PacBio SMRT sequencing platforms, helping you analyze various gut microbial samples, study the relationship between the microbiome and the host, and analyze the function of microorganisms at the genetic level.
Reference:
- Ke S, Weiss S T, Liu Y Y. Dissecting the role of the human microbiome in COVID-19 via metagenome-assembled genomes. Nature communications, 2022, 13(1): 1-15.
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