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Strain profiling and epidemiology of bacterial species from metagenomic sequencing
- Source :
- Nature Communications, Nature Communications, Vol 8, Iss 1, Pp 1-14 (2017)
- Publication Year :
- 2017
-
Abstract
- Microbial communities are often composed by complex mixtures of multiple strains of the same species, characterized by a wide genomic and phenotypic variability. Computational methods able to identify, quantify and classify the different strains present in a sample are essential to fully exploit the potential of metagenomic sequencing in microbial ecology, with applications that range from the epidemiology of infectious diseases to the characterization of the dynamics of microbial colonization. Here we present a computational approach that uses the available genomic data to reconstruct complex strain profiles from metagenomic sequencing, quantifying the abundances of the different strains and cataloging them according to the population structure of the species. We validate the method on synthetic data sets and apply it to the characterization of the strain distribution of several important bacterial species in real samples, showing how its application provides novel insights on the structure and complexity of the microbiota.<br />Microbiota is often a complex mixture of multiple coexisting species and strains with high level of phenotypic and genomic variability. Here, Albanese and Donati develop StrainEst for estimating the number and identity of coexisting strains and their relative abundances in mixed metagenomic samples.
- Subjects :
- 0301 basic medicine
Staphylococcus aureus
Genomic data
Science
030106 microbiology
Population structure
General Physics and Astronomy
Computational biology
Biology
Neisseria meningitidis
Polymorphism, Single Nucleotide
General Biochemistry, Genetics and Molecular Biology
Article
03 medical and health sciences
Microbial ecology
Databases, Genetic
Enterococcus faecalis
Escherichia coli
Staphylococcus epidermidis
Microbial colonization
Profiling (information science)
Humans
Propionibacterium acnes
lcsh:Science
Multidisciplinary
Bacteria
Microbiota
Computational Biology
High-Throughput Nucleotide Sequencing
General Chemistry
Bifidobacterium longum
Synthetic data sets
030104 developmental biology
Streptococcus pneumoniae
Strain distribution
Metagenomics
Metagenome
lcsh:Q
Settore BIO/19 - MICROBIOLOGIA GENERALE
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Nature Communications, Nature Communications, Vol 8, Iss 1, Pp 1-14 (2017)
- Accession number :
- edsair.doi.dedup.....01d4edeaff3a95acecda0fbccee4c7d8