PopMet · Investigating bacterial strain evolution through metagenomic genome assemblies
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2015-03-01 → 2017-02-28
- EU contribution
- €159,461
- Participants
- 1
- Scheme
- MSCA-IF-EF-ST
Lines connect the coordinator with its partners.
Results in brief
Investigating bacterial strain evolution through metagenomic genome assemblies
In microbial genomics classical reductionist approaches, focusing on single species, genes and genomes, are increasingly replaced by holistic “whole-community” metagenomic studies. In this approach, DNA of all genomes found in a given ecosystems is randomly sequenced, and the genomic content of the microorganisms within the environment are reconstructed, in order to enable quantification of the taxonomic and functional diversity within a given community. Earlier metagenomic studies relied mostly on identifying taxa at genus or broader taxonomic levels, typically using highly conserved genes found in all bacteria (marker genes). However, theoretical advances in using single nucleotide variants (SNVs) allow currently for the distinction of single bacterial species, or even strains. These advances are critically important, as pathogenicity and metabolism of bacteria are often strain specific. SNVs can also guide the reconstruction of the bacterial genomes, thus linking taxonomy to specific functions. In this project, we exploited the information in SNVs to get an understanding of the bacteria and their functional capacities in a diverse set of environments. This is different from classical metagenomics, in that we have a higher resolution to differentiate between single strains and in that we can recover part of the genomes and link this to the taxonomic identity of a bacterium, giving us more information about what who is doing at a given environment. This is important to understand how pathogenic bacteria are distributed in the environment, where they normally occur and when they turn from a “bystander” to an “aggressor” that is trying to damage the host. This kind of switch is known for many bacteria, e.g. E. coli is often found in the gut ecosystem, but is also often causing diarrhea, given opportunistic circumstances. Understanding the bacterial distribution and what can be considered as normal was thus an important scientific research goal in this project. A second part was to investigate how bacterial genomes evolve over time, as this is important to understand how the phenotype of a bacteria can change. Normally these changes in phenotype are not harmful to the host, but in some rare cases this can also lead to a switch from bystander to aggressor strain.
Data: CORDIS, © European Union
Project objective
Recent advances in metagenomics have revealed considerable genetic variation among the microbes that populate the human gut. It has been shown that multiple strains of a bacterial species can coexist in a microbial community. However, accurately differentiating strains in metagenomic samples is mostly not possible, even though pathogenicity is usually strain specific. Therefore, I propose to utilize single nucleotide variants (SNVs) to (i) identify and delineate bacterial strains and to (ii) reconstruct single strain genomes. As more than 1,000 metagenomic samples are available, a large database of bacterial genomes from natural environments will be built and made publicly available. This will give the opportunity to investigate the role of adaptive evolution, mutation rate variation between hosts and the colonization history of bacterial strains among humans, all with high confidence due to the sheer data volume. Further, I plan to explore rare SNVs (nucleotide variants segregating at very low frequencies) that many population genetic methods are reliant on. This will be of particular significance, as it will provide insights into growth dynamics of bacterial communities in natural environments, benefiting both evolutionary and clinical research.Thus, the PopMet project is the application of POPulation genetic analysis on large METagenomic datasets.
Original text from CORDIS.
Participants
- EUROPEAN MOLECULAR BIOLOGY LABORATORY · HeidelbergCoordinatorGermany
Links
Data: CORDIS, © European Union
