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Tambe, A.

Publications and source records attributed to Tambe, A..

2 recordsLinked to original sources

RNA binding and HEPN nuclease activation are decoupled in CRISPR-Cas13a

CRISPR-Cas13a enzymes are RNA-guided, RNA-activated ribonucleases. Their properties have been exploited as powerful tools for RNA detection, RNA imaging and RNA regulation. However, the relationship between target RNA binding and HEPN (higher-eukaryotes-and-prokaryotes nucleotide-binding)- domain nuclease activation is not well understood. Using sequencing experiments coupled with in vitro biochemistry, we find that Cas13as target RNA binding affinity and HEPN-nuclease activity are differentially affected by the number of and position of mismatches between the guide and target. We identify a central binding seed where perfect base pairing is absolutely required for target binding, and a separate nuclease switch where imperfect base-pairing results in tight binding but no HEPN-nuclease activation. These results demonstrate that the binding and cleavage activities of Cas13a are decoupled, highlighting a complex specificity landscape. Our findings underscore a need to consider the range of effects off-target recognition has on Cas13as RNA binding and cleavage behavior for RNA-targeting tool development.

biochemistry

Barcode identification for single cell genomics

Single-cell sequencing experiments use short DNA barcode tags to identify reads that originate from the same cell. In order to recover single-cell information from such experiments, reads must be grouped based on their barcode tag, a crucial processing step that precedes other computations. However, this step can be difficult due to high rates of mismatch and deletion errors that can afflict barcodes. Here we present an approach to identify and error-correct barcodes by traversing the de Bruijn graph of circularized barcode k-mers. This allows for assignment of reads to consensus fingerprints constructed from k-mers, and we show that for single-cell RNA-Seq this improves the recovery of accurate single-cell transcriptome estimates.

bioinformatics