To uncover the heterogeneity of cellular populations and multicellular constructs we show on-demand isolation of single mammalian cells and 3D cell cultures by coupling bright-field microdroplet imaging with real-time classification and sorting using convolutional neural networks.
The encapsulation of cells together with micro‐objects in monodispersed water‐in‐oil microdroplets offers a powerful means to perform quantitative biological studies within large cell populations. In such applications, accurate object detection is crucial to ensure control over the content for every compartment. In particular, the ability to rapidly count and localize objects is key to future applications in single‐cell ‐omics, cellular aggregation, and cell‐to‐cell interactions. In this paper, the authors combine the Deep Learning object detector YOLOv4‐tiny with microfluidic Image‐Activated Droplet Sorting (DL‐IADS), to perform flexible, label‐free classification, counting, and localization of multiple micro‐objects simultaneously and at high‐throughput. They trained YOLOv4‐tiny to detect SH‐SY5Y cells, polyacrylamide beads, and cellular aggregates in a single model, with a precision of 92% for cells, 98% for beads, and 81% for aggregates. They exploit this accuracy and counting ability to implement a closed‐loop feedback that enables controlled loading of microbeads via the automated adjustment of flow rates. They subsequently demonstrate the combinatorial sorting of co‐encapsulated single cells and single beads based on real‐time classification at up to 111 Hz, with enrichment factors of up to 145. Finally, they demonstrate spatially‐resolved sorts by evaluating cell‐to‐cell distances in real‐time to isolate cell doublets with high purity.
The movement trajectories of organisms serve as dynamic read-outs of their behaviour and physiology. For microorganisms this can be difficult to resolve due to their small size and fast movement. Here, we devise a novel droplet microfluidics assay to encapsulate single micron-sized algae inside closed arenas, enabling ultralong high-speed tracking of the same cell. Comparing two model species - Chlamydomonas reinhardtii (freshwater, 2 cilia), and Pyramimonas octopus (marine, 8 cilia), we detail their highly-stereotyped yet contrasting swimming behaviours and environmental interactions. By measuring the rates and probabilities with which cells transition between a trio of motility states (smooth-forward swimming, quiescence, tumbling or excitable backward swimming), we reconstruct the control network that underlies this gait switching dynamics. A simplified model of cell-roaming in circular confinement reproduces the observed long-term behaviours and spatial fluxes, including novel boundary circulation behaviour. Finally, we establish an assay in which pairs of droplets are fused on demand, one containing a trapped cell with another containing a chemical that perturbs cellular excitability, to reveal how aneural microorganisms adapt their locomotor patterns in real-time.
At all scales, the movement patterns of organisms serve as dynamic read-outs of their behaviour and physiology. We devised a novel droplet microfluidics assay to encapsulate single algal microswimmers inside closed arenas, and comprehensively studied their roaming behaviour subject to a large number of environmental stimuli. We compared two model species, Chlamydomonas reinhardtii (freshwater alga, 2 cilia), and Pyramimonas octopus (marine alga, 8 cilia), and detailed their highly-stereotyped behaviours and the emergence of a trio of macroscopic swimming states (smooth-forward, quiescent, tumbling or excitable backward). Harnessing ultralong timeseries statistics, we reconstructed the species-dependent reaction network that underlies the choice of locomotor behaviour in these aneural organisms, and discovered the presence of macroscopic non-equilibrium probability fluxes in these active systems. We also revealed for the first time how microswimmer motility changes instantaneously when a chemical is added to their microhabitat, by inducing deterministic fusion between paired droplets - one containing a trapped cell, and the other, a pharmacological agent that perturbs cellular excitability. By coupling single-cell entrapment with unprecedented tracking resolution, speed and duration, our approach offers unique and potent opportunities for diagnostics, drug-screening, and for querying the genetic basis of micro-organismal behaviour.
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