Intelligent image-activated cell sorting 2.0.

The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of ∼2000 events per second and a high sensitivity of ∼50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology.

Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering.

Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.

Role of CC chemokine receptor 2 in bone marrow cells in the recruitment of macrophages into obese adipose tissue.

The MCP-1 (monocyte chemoattractant protein-1)/CCR2 (CC motif chemokine receptor-2) pathway may play a role in macrophage infiltration into obese adipose tissue. Here we investigated the role of CCR2 in the recruitment of bone marrow-derived macrophages into obese adipose tissue in vitro and in vivo. Using the TAXIScan device, which can measure quantitatively the directionality and velocity of cell migration at time lapse intervals in vitro, we demonstrated that bone marrow cells (BMCs) from wild type mice migrate directly toward MCP-1 or culture medium conditioned by adipose tissue explants of genetically obese ob/ob mice, which are efficiently suppressed by pharmacological blockade of CCR2 signaling. The number of F4/80-positive macrophages was reduced in the adipose tissue from high fat diet-fed obese KKAy or ob/ob mice treated with a CCR2 antagonist propagermanium relative to vehicle-treated groups. We also found that the number of macrophages is reduced in the adipose tissue from ob/ob mice reconstituted with CCR2(-/-) BMCs (ob/ob + CCR2(-/-) BMCs) relative to those with CCR2+/+ BMCs (ob/ob + CCR2+/+ BMCs). Expression of mRNAs for CD11c and TLR4 (Toll-like receptor 4) markers of proinflammatory M1 macrophages was also decreased in the adipose tissue from ob/ob + CCR2(-/-) BMCs relative to ob/ob + CCR2+/+ BMCs, whereas mannose receptor and CD163, markers of anti-inflammatory M2 macrophages, were unchanged. This study provides in vivo and in vitro evidence that CCR2 in bone marrow cells plays an important role in the recruitment of macrophages into obese adipose tissue.

Quantitative analysis of eosinophil chemotaxis tracked using a novel optical device -- TAXIScan.

We have reported previously the development of an optically accessible, horizontal chemotaxis apparatus, in which migration of cells in the channel from a start line can be traced with time-lapse intervals using a CCD camera (JIM 282, 1-11, 2003). To obtain statistical data of migrating cells, we have developed quantitative methods to calculate various parameters in the process of chemotaxis, employing human eosinophil and CXCL12 as a model cell and a model chemoattractant, respectively. Median values of velocity and directionality of each cell within an experimental period could be calculated from the migratory pathway data obtained from time-lapse images and the data were expressed as Velocity-Directionality (VD) plot. This plot is useful for quantitatively analyzing multiple migrating cells exposed to a certain chemoattractant, and can distinguish chemotaxis from random migration. Moreover precise observation of cell migration revealed that each cell had a different lag period before starting chemotaxis, indicating variation in cell sensitivity to the chemoattractant. Thus lag time of each cell before migration, and time course of increment of the migrating cell ratio at the early stages could be calculated. We also graphed decrement of still moving cell ratio at the later stages by calculating the duration time of cell migration of each cell. These graphs could distinguish different motion patterns of chemotaxis of eosinophils, in response to a range of chemoattractants; PGD(2), fMLP, CCL3, CCL5 and CXCL12. Finally, we compared parameters of eosinophils from normal volunteers, allergy patients and asthma patients and found significant difference in response to PGD(2). The quantitative methods described here could be applicable to image data obtained with any combination of cells and chemoattractants and useful not only for basic studies of chemotaxis but also for diagnosis and for drug screening.