Biology – Quantitative Biology – Genomics
Scientific paper
2010-07-20
Biology
Quantitative Biology
Genomics
28 pages, 12 figures
Scientific paper
Bacteria are the unseen majority on our planet, with millions of species and comprising most of the living protoplasm. While current methods enable in-depth study of a small number of communities, a simple tool for breadth studies of bacterial population composition in a large number of samples is lacking. We propose a novel approach for reconstruction of the composition of an unknown mixture of bacteria using a single Sanger-sequencing reaction of the mixture. This method is based on compressive sensing theory, which deals with reconstruction of a sparse signal using a small number of measurements. Utilizing the fact that in many cases each bacterial community is comprised of a small subset of the known bacterial species, we show the feasibility of this approach for determining the composition of a bacterial mixture. Using simulations, we show that sequencing a few hundred base-pairs of the 16S rRNA gene sequence may provide enough information for reconstruction of mixtures containing tens of species, out of tens of thousands, even in the presence of realistic measurement noise. Finally, we show initial promising results when applying our method for the reconstruction of a toy experimental mixture with five species. Our approach may have a potential for a practical and efficient way for identifying bacterial species compositions in biological samples.
Amir Amnon
Zuk Or
No associations
LandOfFree
Bacterial Community Reconstruction Using A Single Sequencing Reaction does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Bacterial Community Reconstruction Using A Single Sequencing Reaction, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Bacterial Community Reconstruction Using A Single Sequencing Reaction will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-125946