
References:
1. Stepanauskas, R. et al. Improved genome recovery and integrated cell-size analyses of individual uncultured microbial cells and viral particles. Nat. Commun. 8, 84 (2017).
Single Amplified Genomes, SAGs, obtained through Singe-Cell Genomics (SCG) methods, contain the genomic information of a single cell. Considering no contamination from the methodology, if DNA from different species are found in a SAG it implies a possible interaction between two different organism. For example, in a SAG from a bacterivorous unicellular eukaryote it is possible to find also DNA from a green algae, suggesting that the former is a predator of the latter.
However, DNA from a second organism within a SAG has a low presence compared to the ‘host’ cell genome, making it hard to be amplified during the Multiple Displacement Amplification reaction (MDA). For Blanes Bay Microbial Observatory (BBMO) SAGs, a Low Coverage Sequencing (LoCoS) method is used to improve the recovering of these ‘foreign’ traces of DNA. Specifically, a superficial amplification (low sequencing depth) is done using an alternative reaction to MDA called WGA-X1, which improves the amplification quality and the posterior sequencing results.
This methodology aims to detect interactions of interest in SAGs, for which a deeper sequencing will be done and proper genomic analyses will follow. In total, for the winter season of 2016 there are a total number of 756 SAGs sequenced at Bigelow: one half for autotrophic organism and the other half for heterotrophic organisms. Samples for the summer of 2016 are being sequenced as well. Thus, we will be able to study different patterns of interactions in two different periods of time in which we know there are the highest differences in the microbial community structure within a year in the BBMO.
Overall, by analyzing SAGs from the Blanes Bay Microbial Observatory through different times of the year (i.e. winter and summer), we expect to discover interactions and their patterns through time, helping validating already existing interactions found in the literature and making possible the generation of networks with higher sensitivity.