Microfluidic Enrichment and Computational Analysis of Rare Sequences from Mixed Genomic Samples for Metagenomic Mining
Name
crispr.2022.0054.pdf
Description
Published version
Size
532.17 KB
Format
Adobe PDF
Checksum (MD5)
1eb881330833f43cc351185bd1de1f3a
Author(s)
Cui, Naiwen
Faure, Guihem
Singh, Ankita
Macrae, Rhiannon
Zhang, Feng
Date Issued
October 1, 2022
Journal
The CRISPR Journal
Publisher
Mary Ann Liebert Inc
Citation
Cui, Naiwen, Faure, Guihem, Singh, Ankita, Macrae, Rhiannon and Zhang, Feng. 2022. "Microfluidic Enrichment and Computational Analysis of Rare Sequences from Mixed Genomic Samples for Metagenomic Mining." The CRISPR Journal, 5 (5).
Version
Final published version
Abstract
Many powerful molecular biology tools have their origins in natural systems, including restriction modification enzymes and the CRISPR effectors, Cas9, Cas12, and Cas13. Heightened interest in these systems has led to mining of genomic and metagenomic data to identify new orthologs of these proteins, new types of CRISPR systems, and uncharacterized natural systems with novel mechanisms. To accelerate metagenomic mining, we developed a high-throughput, low-cost droplet microfluidic-based method for enrichment of rare sequences in a mixed starting population. Using a computational pipeline, we then searched in the enriched data for the presence of CRISPR-Cas systems, identifying a previously unknown CRISPR-Cas system. Our approach enables researchers to efficiently mine metagenomic samples for sequences of interest, greatly accelerating the search for nature's treasures.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1089/crispr.2022.0054
