A variety of sequencing strategies have been developed to identify the plethora of microorganisms present in metagenomic samples. The most commonly used approaches are (i) targeted, amplicon-based, short-read sequencing of the bacterial 16S ribosomal RNA (rRNA) gene or fungal internal transcribed spacer (ITS) region, or (ii) shotgun metagenomic short-read sequencing. Once data has been generated, the challenge is to identify the taxonomic origin of each sequencing read, and to reconstruct the genome of every member of the complex microbial population — even those present at a fraction of the total cellular abundance. Many computational methods for metagenomic deconvolution rely on alignment to reference genomes, binning and other methods that require a priori knowledge or statistical assumptions.

Our ProxiMeta^™ Platform takes the guesswork out of metagenomic deconvolution. Direct evidence of sequences that are co-located in cells (generated using our proximity ligation, or Hi-C kits) is used to assign shotgun sequencing reads with high confidence to the bacteria, fungi, algae, protozoans and viruses to which they belong. The proximity ligation data also provides the long-range information needed for genome scaffolding, and allows for the attribution of mobile elements to their hosts.

Learn how researchers have used the ProxiMeta Platform to assemble high-quality genomes from:

• a human fecal sample
• a cow rumen sample
• a wastewater sample
• a microbial community recovered from degraded polyurethane from a landfill
• a microbrew