Virtual-freezing fluorescence imaging flow cytometry.

By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s-1 without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.

High-speed microparticle isolation unlimited by Poisson statistics.

High-speed isolation of microparticles (e.g., microplastics, heavy metal particles, microbes, cells) from heterogeneous populations is the key element of high-throughput sorting instruments for chemical, biological, industrial and medical applications. Unfortunately, the performance of continuous microparticle isolation or so-called sorting is fundamentally limited by the trade-off between throughput, purity, and yield. For example, at a given throughput, high-purity sorting needs to sacrifice yield, or vice versa. This is due to Poisson statistics of events (i.e., microparticles, microparticle clusters, microparticle debris) in which the interval between successive events is stochastic and can be very short. Here we demonstrate an on-chip microparticle sorter with an ultrashort switching window in both time (10 µs) and space (10 µm) at a high flow speed of 1 m s-1, thereby overcoming the Poisson trade-off. This is made possible by using femtosecond laser pulses that can produce highly localized transient cavitation bubbles in a microchannel to kick target microparticles from an acoustically focused, densely aligned, bumper-to-bumper stream of microparticles. Our method is important for rare-microparticle sorting applications where both high purity and high yield are required to avoid missing rare microparticles.

Intelligent Image-Activated Cell Sorting.

A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.

Targeted delivery of fluorogenic peptide aptamers into live microalgae by femtosecond laser photoporation at single-cell resolution.

Microalgae-based metabolic engineering has been proven effective for producing valuable substances such as food supplements, pharmaceutical drugs, biodegradable plastics, and biofuels in the past decade. The ability to accurately visualize and quantify intracellular metabolites in live microalgae is essential for efficient metabolic engineering, but remains a major challenge due to the lack of characterization methods. Here we demonstrate it by synthesizing fluorogenic peptide aptamers with specific binding affinity to a target metabolite and delivering them into live microalgae by femtosecond laser photoporation at single-cell resolution. As a proof-of-principle demonstration of our method, we use it to characterize Euglena gracilis, a photosynthetic unicellular motile microalgal species, which is capable of producing paramylon (a carbohydrate granule similar to starch). Specifically, we synthesize a peptide aptamer containing a paramylon-binding fluorescent probe, 7-nitrobenzofurazan, and introduce it into E. gracilis cells one-by-one by suppressing their mobility with mannitol and transiently perforating them with femtosecond laser pulses at 800 nm for photoporation. To demonstrate the method's practical utility in metabolic engineering, we perform spatially and temporally resolved fluorescence microscopy of single live photoporated E. gracilis cells under different culture conditions. Our method holds great promise for highly efficient microalgae-based metabolic engineering.