Open Access
A technology of a different sort: microraft arrays
Author(s) -
Belén CortésLlanos,
Yuli Wang,
Christopher E. Sims,
Nancy L. Allbritton
Publication year - 2021
Publication title -
lab on a chip
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.064
H-Index - 210
eISSN - 1473-0197
pISSN - 1473-0189
DOI - 10.1039/d1lc00506e
Subject(s) - computer science , nanotechnology , isolation (microbiology) , sort , organoid , sorting , population , selection (genetic algorithm) , computational biology , artificial intelligence , biology , bioinformatics , materials science , neuroscience , demography , information retrieval , sociology , programming language
A common procedure performed throughout biomedical research is the selection and isolation of biological entities such as organelles, cells and organoids from a mixed population. In this review, we describe the development and application of microraft arrays, an analysis and isolation platform which enables a vast range of criteria and strategies to be used when separating biological entities. The microraft arrays are comprised of elastomeric microwells with detachable polymer bases (microrafts) that act as capture and culture sites as well as supporting carriers during cell isolation. The technology is elegant in its simplicity and can be implemented for samples possessing tens to millions of objects yielding a flexible platform for applications such as single-cell RNA sequencing, subcellular organelle capture and assay, high-throughput screening and development of CRISPR gene-edited cell lines, and organoid manipulation and selection. The transparent arrays are compatible with a multitude of imaging modalities enabling selection based on 2D or 3D spatial phenotypes or temporal properties. Each microraft can be individually isolated on demand with retention of high viability due to the near zero hydrodynamic stress imposed upon the cells during microraft release, capture and deposition. The platform has been utilized as a simple manual add-on to a standard microscope or incorporated into fully automated instruments that implement state-of-the-art imaging algorithms and machine learning. The vast array of selection criteria enables separations not possible with conventional sorting methods, thus garnering widespread interest in the biological and pharmaceutical sciences.