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Science Papers on Approach to Quickly Sort Single Cells, Alternative Splicing in Cancer

A system for high-speed sorting of single cells based on fluorescence imaging is reported in Science this week. While flow cytometry allows for rapid cell sorting, it is limited to a low-dimensional parameter space and lacks subcellular resolution. Fluorescence microscopy, meanwhile, enables high-resolution readouts of cellular morphology and protein localization but lacks the ability to isolate cells with specific phenotypes at high speed. To address these limitations, a team led by scientists from the European Molecular Biology Laboratory developed high-speed image-enabled cell sorting (ICS), which combines fluorescence imaging using radiofrequency-tagged emission with a traditional cuvette-based droplet sorter and new low-latency signal processing and sorting electronics. ICS, the researchers say, sorts cells based on measurements from image data at speeds up to 15,000 events per second, and they show that it quantifies cell morphology and localization of labeled proteins and increases the resolution of cell cycle analyses by separating mitotic stages. They also demonstrated the combination of ICS with CRISPR-pooled screens to identify regulators of the nuclear factor pathway, enabling the completion of genome-wide image-based screens in about 9 hours of run time. "ICS substantially expands the phenotypic space accessible to cell-sorting applications and functional genomic screening," the authors write. "With the potential to include downstream multi-omics readouts, ICS provides a fundamentally new capability for probing deep into the molecular mechanisms underlying cell physiology and protein localization."

A new approach for studying isoform-level alternative splicing in cancer is presented in Science Advances this week. Tumors display widespread transcriptome alterations, and the effects of a handful of spliced isoforms in cancer have been investigated. Yet the clinical relevance of most isoform switches in tumors remains poorly characterized. Combining long-read sequencing and follow-on analysis with short-read RNA sequencing, a group of investigators from the Jackson Laboratory for Genomic Medicine developed platform that identifies and annotates full-length isoforms and infers tumor-specific splicing events. They apply the platform to breast cancer samples and identify thousands of previously unannotated isoforms, including ones associated with poor survival and specific breast cancer subtypes. The team also provides a library of novel breast tumor-specific isoforms as a resource for immuno-oncology therapeutic development.