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Volume 40 Issue 8, August 2022

Single-cell-type tissue proteomics

Artistic impression of the Deep Visual Proteomics method developed by Mund et al., which is based on a combination of imaging, deep learning and mass spectrometry. Single cells are segmented, cell-typed, excised from tissue and analyzed for their protein content.

See Mund et al.

Image: Juliet Percival, Illustrator. Cover Design: Erin Dewalt

Volume 40 Issue 8

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Editorial

  • The biotech sector must devote more resources to cybersecurity — especially those companies that are manufacturers of essential medical products.

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  • By quantifying thousands of proteins in tumor cells in an unbiased manner, Deep Visual Proteomics uncovers mechanisms that drive tumor evolution and reveals new therapeutic targets. The method incorporates advanced microscopy, artificial intelligence and ultra-high-sensitivity proteomics to characterize individual cell identities.

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  • We developed EasyFuse, a computational machine learning pipeline that detects cancer-specific gene fusions with superior performance over existing tools. Individual gene fusions exhibit a high frequency of pre-established CD4+ and CD8+ T-cell responses and thus represent a previously untapped source of neo-antigens that can be exploited for personalized immunotherapies.

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    • Hackathons not only advance science itself but also help to educate young biotechnologists and artificial intelligence enthusiasts and to build capacity in digital biotechnology in low-income settings.

      • Timothy P. Jenkins
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    • A quarterly snapshot of job expansions, reductions and availability in the biotech and pharma sectors.

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