Innovative approach keeps cells alive during RNA extraction

By The Science Advisory Board staff writers

August 17, 2022 -- Scientists at the Swiss Federal Institute of Technology Lausanne (EPFL) and ETH Zurich have jointly developed an innovative single-cell transcriptome profiling approach, called Live-seq, that keeps cells alive during RNA extraction for further study while also being minimally invasive.

Their work, published August 17 in the journal Nature, is based on a technique called fluidic force microscopy (FluidFM) which leverages microscopic channels that are thinner than human hair in order to manipulate tiny volumes of fluids (femtoliters) in a sample under the microscope.

The authors note that single-cell RNA sequencing (scRNA-seq) has "greatly advanced our ability to characterize cellular heterogeneity" but scRNA-seq "requires lysing cells, which impedes further molecular or functional analyses on the same cells." They contend that Live-seq uses FluidFM "allowing to couple a cell's ground-state transcriptome to its downstream molecular or phenotypic behavior."

Researchers say they have shown that Live-seq can accurately stratify diverse cell types and states without introducing major cellular disturbances. In their proof-of-concept, they used the platform to directly map the "trajectory" of individual immune cells before and after they became active, as well as adipose stromal cells before and after they differentiated into fat cells. In addition, Live-seq was used as a "transcriptomic recorder" allowing researchers to predict how strongly -- or weakly -- an immune cell would react to an immunological challenge.

The authors said they "expect the next generation of the Live-seq approach to allow for sampling of many more cells, aiming to alleviate relevant statistical power and cellular resolution concerns." The researchers also "anticipate that Live-seq will transform single-cell transcriptomics, and possibly other omics technologies such as single-cell proteomics and metabolomics, from the current end-point type assay into a temporal analysis workflow."

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