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Singling out microbes in the mountains of metagenomic data from complex samples, such as soil or seawater, is computationally intensive. To address this challenge, a team of researchers from the ӳý, led by institute member and senior author Eric Alm, and graduate student and first author Brian Cleary, created a new method – latent strain analysis (LSA) – that separates sequencing reads into biologically informed partitions and enables assembly of individual genomes, including those of bacteria that are relatively low-abundance. The team also showed that LSA is sensitive enough to separate reads from several strains of the same species. can be found in Nature Biotechnology.

Working with the ӳý’s Proteomics Platform, a team led by Norbert Perrimon of Harvard Medical School and the ӳý built a novel proteomic mapping platform that they used in fruit flies. The approach uses a new protein labeling technique that is applied to live tissues, enabling the characterization of organelle proteomes. The team used the technique to map the mitochondrial matrix proteome in Drosophila muscle and then built , a database of Drosophila mitochondrial proteins with subcompartmental annotation. Read more in .