Auto-amplification and spatial propagation of neutrophil extracellular traps.

The release of cellular DNA as neutrophil extracellular traps (NETs) plays a pivotal role in the immune response to pathogens by physically entrapping and killing microbes. NET release occurs at a greater frequency within neutrophil clusters and swarms, indicating a potential for collective behavior. However, little is known about how dense clustering of cells influences the frequency of NET release. Using an image-based assay for NETosis in nanowells, we show that the frequency of NETosis increases with cell density. We then co-incubate NETotic neutrophils with naïve neutrophils and find that NETotic neutrophils can induce secondary NETosis in naïve neutrophils in a cell density-dependent manner. Further mechanistic studies show that secondary NETosis is caused by a combination of DNA and protein factors. Finally, we immobilize NETotic neutrophils in a plaque, and then place the plaque near naïve neutrophils to characterize the spatial propagation of secondary NETosis. We find that secondary NETosis from naïve neutrophils increases over time, but remains spatially restricted to the periphery of the plaque. Together, we show that NETosis is an auto-amplified process, but that the spatial propagation of NET release is strictly regulated.

Data for assessing red blood cell deformability from microscopy images using deep learning.

Red blood cell (RBC) deformability is a vital biophysical property that dictates the ability of these cells to repeatedly squeeze through small capillaries in the microvasculature. This capability is known to differ between individuals and degrades due to natural aging, pathology, and cold storage. There is great interest in measuring RBC deformability because this parameter is a potential biomarker of RBC quality for use in blood transfusions. Measuring this property from microscopy images would greatly reduce the effort required to acquire this information, as well as improve standardization across different centers. This dataset consists of live cell microscopy images of RBC samples from 10 healthy donors. Each RBC sample is sorted into fractions based on deformability using the microfluidic ratchet device. Each deformability fraction is imaged in microwell plates using a Nikon CFI S Plan Fluor ELWD 40 × objective and a Nikon DS-Qi2 CMOS camera on a Nikon Ti-2E inverted microscope. This data could be reused to develop deep learning algorithms to associate live cell images with cell deformability.

See-N-Seq: RNA sequencing of target single cells identified by microscopy via micropatterning of hydrogel porosity.

Single cell RNA sequencing has the potential to elucidate transcriptional programs underlying key cellular phenotypes and behaviors. However, many cell phenotypes are incompatible with indiscriminate single cell sequencing because they are rare, transient, or can only be identified by imaging. Existing methods for isolating cells based on imaging for single cell sequencing are technically challenging, time-consuming, and prone to loss because of the need to physically transport single cells. Here, we developed See-N-Seq, a method to rapidly screen cells in microwell plates in order to isolate RNA from specific single cells without needing to physically extract each cell. Our approach involves encapsulating the cell sample in a micropatterned hydrogel with spatially varying porosity to selectively expose specific cells for targeted RNA extraction. Extracted RNA can then be captured, barcoded, reverse transcribed, amplified, and sequenced at high-depth. We used See-N-Seq to isolate and sequence RNA from cell-cell conjugates forming an immunological synapse between T-cells and antigen presenting cells. In the hours after synapsing, we found time-dependent bifurcation of single cell transcriptomic profiles towards Type 1 and Type 2 helper T-cells lineages. Our results demonstrate how See-N-Seq can be used to associate transcriptomic data with specific functions and behaviors in single cells.

Degradation of red blood cell deformability during cold storage in blood bags.

Red blood cells (RBCs) stored in blood bags develop a storage lesion that include structural, metabolic, and morphologic transformations resulting in a progressive loss of RBC deformability. The speed of RBC deformability loss is donor-dependent, which if properly characterized, could be used as a biomarker to select high-quality RBC units for sensitive recipients or to provide customized storage timelines depending on the donor. We used the microfluidic ratchet device to measure the deformability of red blood cells stored in blood bags every 14 days over a span of 56 days. We observed that storage in blood bags generally prevented RBC deformability loss over the current standard 42-day storage window. However, between 42 and 56 days, the deformability loss profile varied dramatically between donors. In particular, we observed accelerated RBC deformability loss for a majority of male donors, but for none of the female donors. Together, our results suggest that RBC deformability loss could be used to screen for donors who can provide stable RBCs for sensitive transfusion recipients or to identify donors capable of providing RBCs that could be stored for longer than the current 42-day expiration window.

Automated rare sperm identification from low-magnification microscopy images of dissociated microsurgical testicular sperm extraction samples using deep learning.

OBJECTIVE: To develop a machine learning algorithm to detect rare human sperm in semen and microsurgical testicular sperm extraction (microTESE) samples using bright-field (BF) microscopy for nonobstructive azoospermia patients. DESIGN: Spermatozoa were collected from fertile men. Testis biopsies were collected from microTESE samples determined to be clinically negative for sperm. A convolutional neural network based on the U-Net architecture was trained using 35,761 BF image patches with fluorescent ground truth image pairs to segment sperm. The algorithm was validated using 7,663 image patches. The algorithm was tested using 7,663 image patches containing abundant sperm, as well as 7,985 image patches containing rare sperm. SETTING: In vitro fertilization center and university laboratories. PATIENT(S): Normospermic and nonobstructive azoospermia patients. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Precision (positive predictive value [PPV]), recall (sensitivity), and F1-score of detected sperm locations. RESULT(S): For sperm-only samples, our algorithm achieved 91% PPV, 95.8% sensitivity, and 93.3% F1-score at ×10 magnification. For dissociated microTESE samples doped with an abundant quantity of sperm, our algorithm achieved 84.0% PPV, 72.7% sensitivity, and 77.9% F1-score. For dissociated microTESE samples doped with rare sperm, our algorithm achieved 84.4% PPV, 86.1% sensitivity, and 85.2% F1-score. CONCLUSION(S): Rare sperm can be detected in patients' testis biopsy samples for potential subsequent use in in vitro fertilization-intracytoplasmic sperm injection. A machine learning algorithm can use BF images at ×10 magnification to accurately detect sperm locations using automated imaging.

Technologies for measuring red blood cell deformability.

Human red blood cells (RBCs) are approximately 8 µm in diameter, but must repeatedly deform through capillaries as small as 2 µm in order to deliver oxygen to all parts of the body. The loss of this capability is associated with the pathology of many diseases, and is therefore a potential biomarker for disease status and treatment efficacy. Measuring RBC deformability is a difficult problem because of the minute forces (∼pN) that must be exerted on these cells, as well as the requirements for throughput and multiplexing. The development of technologies for measuring RBC deformability date back to the 1960s with the development of micropipette aspiration, ektacytometry, and the cell transit analyzer. In the past 10 years, significant progress has been made using microfluidics by leveraging the ability to precisely control fluid flow through microstructures at the size scale of individual RBCs. These technologies have now surpassed traditional methods in terms of sensitivity, throughput, consistency, and ease of use. As a result, these efforts are beginning to move beyond feasibility studies and into applications to enable biomedical discoveries. In this review, we provide an overview of both traditional and microfluidic techniques for measuring RBC deformability. We discuss the capabilities of each technique and compare their sensitivity, throughput, and robustness in measuring bulk and single-cell RBC deformability. Finally, we discuss how these tools could be used to measure changes in RBC deformability in the context of various applications including pathologies caused by malaria and hemoglobinopathies, as well as degradation during storage in blood bags prior to blood transfusions.

Blood unit segments accurately represent the biophysical properties of red blood cells in blood bags but not hemolysis.

BACKGROUND: The biophysical properties of red blood cells (RBCs) provide potential biomarkers for the quality of donated blood. Blood unit segments provide a simple and nondestructive way to sample RBCs in clinical studies of transfusion efficacy, but it is not known whether RBCs sampled from segments accurately represent the biophysical properties of RBCs in blood bags. STUDY DESIGN AND METHODS: RBCs were sampled from blood bags and segments every two weeks during 8 weeks of storage at 4°C. RBC deformability was measured by deformability-based sorting using the microfluidic ratchet device in order to derive a rigidity score. Standard hematological parameters, including mean corpuscular volume (MCV), red cell distribution width (RDW), mean cell hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and hemolysis were measured at the same time points. RESULTS: Deformability of RBCs stored in blood bags was retained over 4 weeks storage, but a progressive loss of deformability was observed at weeks 6 and 8. This trend was mirrored in blood unit segments with a strong correlation to the blood bag data. Strong correlations were also observed between blood bag and segment for MCV, MCHC, and MCH but not for hemolysis. CONCLUSION: RBCs sampled from blood unit segments accurately represent the biophysical properties of RBCs in blood bags but not hemolysis. Blood unit segments provide a simple and nondestructive sample for measuring RBC biophysical properties in clinical studies.

Assessing red blood cell deformability from microscopy images using deep learning.

Red blood cells (RBCs) must be highly deformable to transit through the microvasculature to deliver oxygen to tissues. The loss of RBC deformability resulting from pathology, natural aging, or storage in blood bags can impede the proper function of these cells. A variety of methods have been developed to measure RBC deformability, but these methods require specialized equipment, long measurement time, and highly skilled personnel. To address this challenge, we investigated whether a machine learning approach could be used to predict donor RBC deformability based on morphological features from single cell microscope images. We used the microfluidic ratchet device to sort RBCs based on deformability. Sorted cells are then imaged and used to train a deep learning model to classify RBC based image features related to cell deformability. This model correctly predicted deformability of individual RBCs with 81 ± 11% accuracy averaged across ten donors. Using this model to score the deformability of RBC samples was accurate to within 10.4 ± 6.8% of the value obtained using the microfluidic ratchet device. While machine learning methods are frequently developed to automate human image analysis, our study is remarkable in showing that deep learning of single cell microscopy images could be used to assess RBC deformability, a property not normally measurable by imaging. Measuring RBC deformability by imaging is also desirable because it can be performed rapidly using a standard microscopy system, potentially enabling RBC deformability studies to be performed as part of routine clinical assessments.

Monolithic hydrogel nanowells-in-microwells enabling simultaneous single cell secretion and phenotype analysis.

Cytokine secretion is a form of cellular communication that regulates a wide range of biological processes. A common approach for measuring cytokine secretion from single cells is to confine individual cells in arrays of nanoliter wells (nanowells) fabricated using polydimethylsiloxane. However, this approach cannot be easily integrated in standard microwell plates in order to take advantage of high-throughput infrastructure for automated and multiplexed analysis. Here, we used laser micropatterning to fabricate monolithic hydrogel nanowells inside wells in a microwell plate (microwells) using polyethylene glycol diacrylate (PEGDA). This approach produces high-aspect ratio nanowells that retain cells and beads during reagent exchange, enabling simultaneous profiling of single cell secretion and phenotyping via immunostaining. To limit contamination between nanowells, we used methylcellulose as a media additive to reduce diffusion distance. Patterning nanowells monolithically in microwells also dramatically increases density, providing ∼1200 nanowells per microwell in a microwell plate. Using this approach, we profiled IL-8 secretion from single MDA-MB-231 cells, which showed significant heterogeneity. We further profiled the polarization of THP-1 cells into M1 and M2 macrophages, along with their associated IL-1ß and CCL-22 secretion profiles. These results demonstrate the potential to use this approach for high-throughput secretion and phenotype analysis on single cells.

Image-based phenotyping of disaggregated cells using deep learning.

The ability to phenotype cells is fundamentally important in biological research and medicine. Current methods rely primarily on fluorescence labeling of specific markers. However, there are many situations where this approach is unavailable or undesirable. Machine learning has been used for image cytometry but has been limited by cell agglomeration and it is currently unclear if this approach can reliably phenotype cells that are difficult to distinguish by the human eye. Here, we show disaggregated single cells can be phenotyped with a high degree of accuracy using low-resolution bright-field and non-specific fluorescence images of the nucleus, cytoplasm, and cytoskeleton. Specifically, we trained a convolutional neural network using automatically segmented images of cells from eight standard cancer cell-lines. These cells could be identified with an average F1-score of 95.3%, tested using separately acquired images. Our results demonstrate the potential to develop an "electronic eye" to phenotype cells directly from microscopy images.

Multiplexed end-point microfluidic chemotaxis assay using centrifugal alignment.

A fundamental challenge to multiplexing microfluidic chemotaxis assays at scale is the requirement for time-lapse imaging to continuously track migrating cells. Drug testing and drug screening applications require the ability to perform hundreds of experiments in parallel, which is not feasible for assays that require continuous imaging. To address this limitation, end-point chemotaxis assays have been developed using fluid flow to align cells in traps or sieves prior to cell migration. However, these methods require precisely controlled fluid flow to transport cells to the correct location without undesirable mechanical stress, which introduce significant set up time and design complexity. Here, we describe a microfluidic device that eliminates the need for precise flow control by using centrifugation to align cells at a common starting point. A chemoattractant gradient is then formed using passive diffusion prior to chemotaxis in an incubated environment. This approach provides a simple and scalable approach to multiplexed chemotaxis assays. Centrifugal alignment is also insensitive to cell geometry, enabling this approach to be compatible with primary cell samples that are often heterogeneous. We demonstrate the capability of this approach by assessing chemotaxis of primary neutrophils in response to an fMLP (N-formyl-met-leu-phe) gradient. Our results show that cell alignment by centrifugation offers a potential avenue to develop scalable end-point multiplexed microfluidic chemotaxis assays.

Selective cell propagation via micropatterning of a thermally-activated hydrogel.

The ability to selectively propagate specific cells is fundamentally important to the development of clonal cell populations. Current methods rely on techniques such as limiting dilution, colony picking, and flow cytometry to transfer single cells into single wells, resulting in workflows that are low-throughput, slowed by propagation kinetics, and susceptible to contamination. Here, we developed a method, called selective laser gelation (SLG), to micropattern hydrogels in cell culture media in order to encapsulate specific cells to selectively arrest their growth. This process relies on the inverse gelation of methylcellulose, which forms a hydrogel when heated rather than cooled. Local heating using an infrared laser enables hydrogel micropatterning, while phase transition hysteresis retains the hydrogel after laser excitation. As a demonstration, we used this approach to selectively propagate transgenic CHO cells with increased antibody productivity. More generally, hydrogel micropatterning provides a simple and non-contact method for selective propagation of cells based on features identified by imaging.

Lossless immunocytochemistry using photo-polymerized hydrogel thin-films.

Immunocytochemistry (ICC), or immunofluorescence microscopy, is an essential biological technique for phenotyping cells in both research and diagnostic applications. Standard ICC methods often do not work well when the cell sample contains a small number of cells (<10 000) because of the significant cell loss that occurs during washing, staining, and centrifugation steps. Cell loss is particularly relevant when working with rare cells, such as circulating tumor cells, where such losses could significantly bias experimental outcomes. In order to eliminate cell loss in ICC protocols, we present a method to encapsulate the cell sample in a photo-polymerized hydrogel thin-film. The hydrogel thin-film is permeable to antibodies and other ICC reagents, thereby allowing the use of standard ICC protocols without modification. The cell sample is physically constrained by the hydrogel at the bottom surface of a standard (unmodified) imaging microtiter plate, thereby enabling the acquisition of high-quality micrographs regardless of the properties of the cell sample or staining reagents. Furthermore, while standard ICC requires several centrifugation steps during staining and washing, our hydrogel encapsulation method requires only a single centrifugation step. This property greatly reduces the time required to perform ICC protocols and is more compatible with robotic platforms. In this study, we show that standard ICC and Cytospin protocols are extremely lossy (>70% loss) when the sample contains less than 10 000 cells, while encapsulating the cells using a permeable hydrogel thin-film results in a lossless ICC process.

Deformability based sorting of stored red blood cells reveals donor-dependent aging curves.

A fundamental challenge in the transfusion of red blood cells (RBCs) is that a subset of donated RBC units may not provide optimal benefit to transfusion recipients. This variability stems from the inherent ability of donor RBCs to withstand the physical and chemical insults of cold storage, which ultimately dictate their survival in circulation. The loss of RBC deformability during cold storage is well-established and has been identified as a potential biomarker for the quality of donated RBCs. While RBC deformability has traditionally been indirectly inferred from rheological characteristics of the bulk suspension, there has been considerable interest in directly measuring the deformation of RBCs. Microfluidic technologies have enabled single cell measurement of RBC deformation but have not been able to consistently distinguish differences between RBCs between healthy donors. Using the microfluidic ratchet mechanism, we developed a method to sensitively and consistently analyze RBC deformability. We found that the aging curve of RBC deformability varies significantly across donors, but is consistent for each donor over multiple donations. Specifically, certain donors seem capable of providing RBCs that maintain their deformability during two weeks of cold storage in standard test tubes. The ability to distinguish between RBC units with different storage potential could provide a valuable opportunity to identify donors capable of providing RBCs that maintain their integrity, in order to reserve these units for sensitive transfusion recipients.

Isolation and genome sequencing of individual circulating tumor cells using hydrogel encapsulation and laser capture microdissection.

Circulating tumor cells (CTCs) are malignant cells released into the bloodstream with the potential to form metastases in secondary sites. These cells, acquired non-invasively, represent a sample of highly relevant tumor tissue that is an alternative to difficult and low-yield tumor biopsies. In recent years, there has been growing interest in genomic profiling of CTCs to enable longitudinal monitoring of the tumor's adaptive response to therapy. However, due to their extreme rarity, genotyping CTCs has proved challenging. Relevant mutations can be masked by leukocyte contamination in isolates. Heterogeneity between subpopulations of tumor cells poses an additional obstacle. Recent advances in single-cell sequencing can overcome these limitations but isolation of single CTCs is prone to cell loss and is prohibitively difficult and time consuming. To address these limitations, we developed a single cell sample preparation and genome sequencing pipeline that combines biophysical enrichment and single cell isolation using laser capture microdissection (LCM). A key component of this process is the encapsulation of enriched CTC sample in a hydrogel matrix, which enhances the efficiency of single-cell isolation by LCM, and is compatible with downstream sequencing. We validated this process by sequencing of single CTCs and cell free DNA (cfDNA) from a single patient with castration resistant prostate cancer. Identical mutations were observed in prostate cancer driver genes (TP53, PTEN, FOXA1) in both single CTCs and cfDNA. However, two independently isolated CTCs also had identical missense mutations in the genes for ATR serine/threonine kinase, KMT2C histone methyltransferase, and FANCC DNA damage repair gene. These mutations may be missed by bulk sequencing libraries, whereas single cell sequencing could potentially enable the characterization of key CTC subpopulations that arise during metastasis.

Microfluidic Separation of Circulating Tumor Cells Based on Size and Deformability.

Circulating tumor cells (CTCs) have been implicated as the seeds of cancer metastasis and therefore have the potential to provide significant prognostic and diagnostic values. Here, we describe a procedure for separating CTCs from whole blood based on size and deformability using the microfluidic ratchet device. This device leverages the ratcheting motion of single cells created as they are deformed through funnel-shaped constrictions using oscillatory flow in order to divert cells based on differences in size and deformability. Subsequent methods for CTC identification and enumeration using immunofluorescence after separation are also described.

Deformability based Cell Sorting using Microfluidic Ratchets Enabling Phenotypic Separation of Leukocytes Directly from Whole Blood.

The separation of leukocytes from whole blood is a prerequisite for many biological assays. Traditional methods require significant sample volumes and are often undesirable because they expose leukocytes to harsh physical or chemical treatment. Existing microfluidic approaches can work with smaller volumes, but lack selectivity. In particular, the selectivity of microfluidic systems based on microfiltration is limited by fouling due to clogging. Here, we developed a method to separate leukocytes from whole blood using the microfluidic ratchet mechanism, which filters the blood sample using a matrix of micrometer-scale tapered constrictions. Deforming single cells through such constrictions requires directionally asymmetrical forces, which enables oscillatory flow to create a ratcheting transport that depends on cell size and deformability. Simultaneously, oscillatory flow continuously agitates the cells to limit the contact time with the filter microstructure to prevent adsorption and clogging. We show this device is capable of isolating leukocytes from whole blood with 100% purity (i.e. no contaminant erythrocytes) and <2% leukocytes loss. We further demonstrate the potential to phenotypically sort leukocytes to enrich for granulocytes and lymphocytes subpopulations. Together, this process provides a sensitive method to isolate and sort leukocytes directly from whole blood based on their biophysical properties.

Microfluidic analysis of red blood cell deformability as a means to assess hemin-induced oxidative stress resulting from Plasmodium falciparum intraerythrocytic parasitism.

Hemolytic anemia is one of the hallmarks of malaria and leads to an increase in oxidized heme (hemin) within the plasma of infected individuals. While scavenger proteins sequester much of the circulating heme, it has been hypothesized that extracellular heme may play a central role in malaria pathogenesis. We have previously developed the multiplex fluidic plunger (MFP) device for the measurement of red blood cell (RBC) deformability. Here, we demonstrate that the measurement of changes in RBC deformability is a sensitive method for inferring heme-induced oxidative stress. We further show that extracellular hemin concentration correlates closely with changes in RBC deformability and we confirm that this biophysical change correlates with other indicators of cell stress. Finally, we show that reduced erythrocyte deformability corresponds with both erythrophagocytosis and RBC osmotic fragility. The MFP microfluidic device presents a simple and potentially inexpensive alternative to existing methods for measuring hemolytic cell stress that could ultimately be used to perform clinical assessment of disease progression in severe malaria.

Continuous Flow Deformability-Based Separation of Circulating Tumor Cells Using Microfluidic Ratchets.

Circulating tumor cells (CTCs) offer tremendous potential for the detection and characterization of cancer. A key challenge for their isolation and subsequent analysis is the extreme rarity of these cells in circulation. Here, a novel label-free method is described to enrich viable CTCs directly from whole blood based on their distinct deformability relative to hematological cells. This mechanism leverages the deformation of single cells through tapered micrometer scale constrictions using oscillatory flow in order to generate a ratcheting effect that produces distinct flow paths for CTCs, leukocytes, and erythrocytes. A label-free separation of circulating tumor cells from whole blood is demonstrated, where target cells can be separated from background cells based on deformability despite their nearly identical size. In doping experiments, this microfluidic device is able to capture >90% of cancer cells from unprocessed whole blood to achieve 10(4) -fold enrichment of target cells relative to leukocytes. In patients with metastatic castration-resistant prostate cancer, where CTCs are not significantly larger than leukocytes, CTCs can be captured based on deformability at 25× greater yield than with the conventional CellSearch system. Finally, the CTCs separated using this approach are collected in suspension and are available for downstream molecular characterization.

Deformability based sorting of red blood cells improves diagnostic sensitivity for malaria caused by Plasmodium falciparum.

The loss of red blood cell (RBC) deformability is part of the pathology of many diseases. In malaria caused by Plasmodium falciparum infection, metabolism of hemoglobin by the parasite results in progressive reduction in RBC deformability that is directly correlated with the growth and development of the parasite. The ability to sort RBCs based on deformability therefore provides a means to isolate pathological cells and to study biochemical events associated with disease progression. Existing methods have not been able to sort RBCs based on deformability or to effectively enrich for P. falciparum infected RBCs at clinically relevant concentrations. Here, we develop a method to sort RBCs based on deformability and demonstrate the ability to enrich the concentration of ring-stage P. falciparum infected RBCs (Pf-iRBCs) by >100× from clinically relevant parasitemia (<0.01%). Deformability based sorting of RBCs is accomplished using ratchet transport through asymmetrical constrictions using oscillatory flow. This mechanism provides dramatically improved selectivity over previous biophysical methods by preventing the accumulation of cells in the filter microstructure to ensure that consistent filtration forces are applied to each cell. We show that our approach dramatically improves the sensitivity of malaria diagnosis performed using both microscopy and rapid diagnostic test by converting samples with difficult-to-detect parasitemia (<0.01%) into samples with easily detectable parasitemia (>0.1%).