Multi-ATOM: Ultrahigh-throughput single-cell quantitative phase imaging with subcellular resolution.
Kelvin C M LeeAndy K S LauAnson H L TangMaolin WangAaron T Y MokBob M F ChungWenwei YanHo C ShumKathryn S E CheahGodfrey C F ChanHayden K H SoKenneth Kin-Yip WongKevin K TsiaPublished in: Journal of biophotonics (2019)
A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assays, which provides useful insights into understanding the biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single-cell precision to define cell identities in a large and heterogeneous population of cells-hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multiplexed asymmetric-detection time-stretch optical microscopy (multi-ATOM) that captures and processes quantitative label-free single-cell images at ultrahigh throughput without compromising subcellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10 000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multivariate, cell-type classification (e.g. breast cancer subtypes, and leukemic cells vs peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.
Keyphrases
- label free
- single cell
- high throughput
- high resolution
- rna seq
- induced apoptosis
- molecular dynamics
- cell cycle arrest
- electron transfer
- single molecule
- deep learning
- endoplasmic reticulum stress
- machine learning
- acute myeloid leukemia
- optical coherence tomography
- mass spectrometry
- cell death
- high speed
- oxidative stress
- quality improvement
- fluorescence imaging
- photodynamic therapy