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MAC-Seq: Coupling Low-Cost, High-Throughput RNA-Seq with Image-Based Phenotypic Screening in 2D and 3D Cell Models

Part of the Methods in Molecular Biology book series (MIMB,volume 2691)

Abstract

Transcriptomic profiling has fundamentally influenced our understanding of cancer pathophysiology and response to therapeutic intervention and has become a relatively routine approach. However, standard protocols are usually low-throughput, single-plex assays and costs are still quite prohibitive. With the evolving complexity of in vitro cell model systems, there is a need for resource-efficient high-throughput approaches that can support detailed time-course analytics, accommodate limited sample availability, and provide the capacity to correlate phenotype to genotype at scale. MAC-seq (multiplexed analysis of cells) is a low-cost, ultrahigh-throughput RNA-seq workflow in plate format to measure cell perturbations and is compatible with high-throughput imaging. Here we describe the steps to perform MAC-seq in 384-well format and apply it to 2D and 3D cell cultures. On average, our experimental conditions identified over ten thousand expressed genes per well when sequenced to a depth of one million reads. We discuss technical aspects, make suggestions on experimental design, and document critical operational procedures. Our protocol highlights the potential to couple MAC-seq with high-throughput screening applications including cell phenotyping using high-content cell imaging.

Key words

  • RNA-seq
  • Multiplexing
  • High-throughput screening
  • 3D cell models
  • High-content imaging

Equal author contribution: Xiang Mark Li and David Yoannidis

Equal senior author contribution: Gisela Mir Arnau, Timothy Semple and Kaylene J. Simpson

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Acknowledgements

We thank members of the Molecular Genomics Core facility and Victorian Centre for Functional Genomics for their valuable input into the development of these methodologies. The Victorian Centre for Functional Genomics (KJS) is funded by the Australian Cancer Research Foundation (ACRF), Phenomics Australia, through funding from the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS) program and the Peter MacCallum Cancer Centre Foundation. This project has been supported by specific project funding through Phenomics Australia (KJS) and separate Peter MacCallum Foundation grants to GMA and SR.

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Correspondence to Xiang Mark Li .

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Li, X.M. et al. (2023). MAC-Seq: Coupling Low-Cost, High-Throughput RNA-Seq with Image-Based Phenotypic Screening in 2D and 3D Cell Models. In: Jenkins, B.J. (eds) Inflammation and Cancer. Methods in Molecular Biology, vol 2691. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3331-1_22

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  • DOI: https://doi.org/10.1007/978-1-0716-3331-1_22

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3330-4

  • Online ISBN: 978-1-0716-3331-1

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