Using single-cell sequencing to refine the search for disease culprits

web graphic nextseq with flowcell insets
Image credit: Illumina
[S]cientists, using a powerful technology called single-cell sequencing, have begun to peel apart the precise mechanisms of how individual cells operate. By quickly analyzing thousands — even millions — of cells in a single experiment, it’s now possible to visualize the specific cellular culprits for any given disease, how they might interact with their microscopic peers, and what molecules are involved in the process.

Here’s how single-cell sequencing works: A cancer biopsy is teased apart, and each of the thousands of cells is locked into its own tiny test tube on a microfluidic chip, and then treated with a series of enzymes and chemicals to coax the necessary genetic material out.

The cells are then probed for a predetermined set of variables: Scientists can check whether they carry a certain set of genes, or express specific molecules involved in disease pathogenesis.

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The data are aggregated, and through the magic of machine learning scientists can use that data to sort cells by their function and characteristics. Instead of averaging the genetic profile of the tissue sample, this analysis quantifies the prevalence of each different cell type — and can isolate the outliers.

Single-cell sequencing might ultimately help clinicians know whether a therapy is tailored to target the specific cell types that have gone rogue.

Read full, original post: ‘A new instruction manual for life’: Single-cell sequencing is opening up new avenues for potential treatments

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