Single-cell barcoding and sequencing using droplet microfluidics

Intracellular delivery of mRNA to human primary T cells with microfluidic vortex shedding

Intracellular delivery of functional macromolecules, such as DNA and RNA, across the cell membrane and into the cytosol, is a critical process in both biology and medicine. Herein, we develop and use microfluidic chips containing post arrays to induce microfluidic vortex shedding, or μVS, for cell membrane poration that permits delivery of mRNA into primary human T lymphocytes. We demonstrate transfection with μVS by delivery of a 996-nucleotide mRNA construct encoding enhanced green fluorescent protein (EGFP) and assessed transfection efficiencies by quantifying levels of EGFP protein expression. We achieved high transfection efficiency (63.6 ± 3.44% EGFP + viable cells) with high cell viability (77.3 ± 0.58%) and recovery (88.7 ± 3.21%) in CD3 + T cells 19 hrs after μVS processing. Importantly, we show that processing cells via μVS does not negatively affect cell growth rates or alter cell states. We also demonstrate processing speeds of greater than 2.0 × 10⁶ cells s^-1 at volumes ranging from 0.1 to 1.5 milliliters. Altogether, these results highlight the use of μVS as a rapid and gentle delivery method with promising potential to engineer primary human cells for research and clinical applications.

Optimization of single-cell plate sorting for high throughput sequencing applications

Single cell sequencing has recently been applied to many immunological studies. Flow cytometric index sorting isolates cells for single cell sequencing with protein level data linked to sequences. However, successful sequencing of index sorted samples requires careful optimization of several sort parameters, including nozzle size, flow rate, threshold rate, and yield calculations. In this study, considerations and optimization data for each of these variables are presented. Our analysis focused on index sorting, but the findings can be applied to any plate sorting protocol. Minimization of flow rates and use of the 70 μm nozzle improved cell yields. Improvements in total read counts after sequencing were obtained by decreasing the threshold rate, or the number of cells processed per second. In addition, this technique provided linked protein and gene expression analysis of the cytokine interferon (IFN)γ, demonstrating that on a single cell basis IFNγ+ cells tend to express IFNG mRNA, and IFNγ- cells do not. Through rigorous optimization and quality control, we have identified parameters important to plate sorting and recommend the use of the 70 μm nozzle and low flow and threshold rates for analysis of rare populations of human lymphocytes.

Microfluidic Single-Cell Manipulation and Analysis: Methods and Applications

In a forest of a hundred thousand trees, no two leaves are alike. Similarly, no two cells in a genetically identical group are the same. This heterogeneity at the single-cell level has been recognized to be vital for the correct interpretation of diagnostic and therapeutic results of diseases, but has been masked for a long time by studying average responses from a population. To comprehensively understand cell heterogeneity, diverse manipulation and comprehensive analysis of cells at the single-cell level are demanded. However, using traditional biological tools, such as petri-dishes and well-plates, is technically challengeable for manipulating and analyzing single-cells with small size and low concentration of target biomolecules. With the development of microfluidics, which is a technology of manipulating and controlling fluids in the range of micro- to pico-liters in networks of channels with dimensions from tens to hundreds of microns, single-cell study has been blooming for almost two decades. Comparing to conventional petri-dish or well-plate experiments, microfluidic single-cell analysis offers advantages of higher throughput, smaller sample volume, automatic sample processing, and lower contamination risk, etc., which made microfluidics an ideal technology for conducting statically meaningful single-cell research. In this review, we will summarize the advances of microfluidics for single-cell manipulation and analysis from the aspects of methods and applications. First, various methods, such as hydrodynamic and electrical approaches, for microfluidic single-cell manipulation will be summarized. Second, single-cell analysis ranging from cellular to genetic level by using microfluidic technology is summarized. Last, we will also discuss the advantages and disadvantages of various microfluidic methods for single-cell manipulation, and then outlook the trend of microfluidic single-cell analysis.

Single-cell assay on microfluidic devices

Advances in microfluidic techniques have prompted researchers to study the inherent heterogeneity of single cells in cell populations.

Extensive exploration of T cell heterogeneity in cancers by single cell sequencing

Human T cells are a highly heterogeneous population and can recognize a wide variety of antigens by their T cell receptors (TCRs). Tumor cells display a large repertoire of antigens that serve as potential targets for recognition, thus making T cells in the tumor micro-environment more complicated. Making a connection between TCRs and the transcriptional information of individual T cells will be interesting for investigating clonal expansion within T cell populations under pathologic conditions. Advances in single cell RNA-sequencing (scRNA-seq) have allowed for comprehensive analysis of T cells. In this review, we briefly describe the research progress on tumor micro-environment T cells using single cell RNA sequencing, and then discuss how scRNA-seq can be used to resolve immune system heterogeneity in health and disease. Finally, we point out future directions in this field and potential for immunotherapy.

Coding of Experimental Conditions in Microfluidic Droplet Assays Using Colored Beads and Machine Learning Supported Image Analysis

To efficiently exploit the potential of several millions of droplets that can be considered as individual bioreactors in microfluidic experiments, methods to encode different experimental conditions in droplets are needed. The approach presented here is based on coencapsulation of colored polystyrene beads with biological samples. The decoding of the droplets, as well as content quantification, are performed by automated analysis of triggered images of individual droplets in-flow using bright-field microscopy. The decoding strategy combines bead classification using a random forest classifier and Bayesian inference to identify different codes and thus experimental conditions. Antibiotic susceptibility testing of nine different antibiotics and the determination of the minimal inhibitory concentration of a specific antibiotic against a laboratory strain of Escherichia coli are presented as a proof-of-principle. It is demonstrated that this method allows successful encoding and decoding of 20 different experimental conditions within a large droplet population of more than 10⁵ droplets per condition. The decoding strategy correctly assigns 99.6% of droplets to the correct condition and a method for the determination of minimal inhibitory concentration using droplet microfluidics is established. The current encoding and decoding pipeline can readily be extended to more codes by adding more bead colors or color combinations.

KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance

Members of the KDM5 histone H3 lysine 4 demethylase family are associated with therapeutic resistance, including endocrine resistance in breast cancer, but the underlying mechanism is poorly defined. Here we show that genetic deletion of KDM5A/B or inhibition of KDM5 activity increases sensitivity to anti-estrogens by modulating estrogen receptor (ER) signaling and by decreasing cellular transcriptomic heterogeneity. Higher KDM5B expression levels are associated with higher transcriptomic heterogeneity and poor prognosis in ER⁺ breast tumors. Single-cell RNA sequencing, cellular barcoding, and mathematical modeling demonstrate that endocrine resistance is due to selection for pre-existing genetically distinct cells, while KDM5 inhibitor resistance is acquired. Our findings highlight the importance of cellular phenotypic heterogeneity in therapeutic resistance and identify KDM5A/B as key regulators of this process.

Evaluating nanomedicine with microfluidics

Nanomedicines are engineered nanoscale structures that have an extensive range of application in the diagnosis and therapy of many diseases. Despite the rapid progress in and tremendous potential of nanomedicines, their clinical translational process is still slow, owing to the difficulty in understanding, evaluating, and predicting their behavior in complex living organisms. Microfluidic techniques offer a promising way to resolve these challenges. Carefully designed microfluidic chips enable in vivo microenvironment simulation and high-throughput analysis, thus providing robust platforms for nanomedicine evaluation. Here, we summarize the recent developments and achievements in microfluidic methods for nanomedicine evaluation, categorized into four sections based on their target systems: single cell, multicellular system, organ, and organism levels. Finally, we provide our perspectives on the challenges and future directions of microfluidics-based nanomedicine evaluation.

Technical Advances in Single-Cell RNA Sequencing and Applications in Normal and Malignant Hematopoiesis

Single-cell RNA sequencing (scRNA-seq) has been tremendously developed in the past decade owing to overcoming challenges associated with isolation of massive quantities of single cells. Previously, cell heterogeneity and low quantities of available biological material posed significant difficulties to scRNA-seq. Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of normal and malignant hematopoietic cells; this heterogeneity has often been ignored in omics studies. The application of scRNA-seq has profoundly changed our comprehension of many biological phenomena, including organ development and carcinogenesis. Hematopoiesis, is actually a maturation process for more than ten distinct blood and immune cells, and is thought to be critically involved in hematological homeostasis and in sustaining the physiological functions. However, aberrant hematopoiesis directly leads to hematological malignancy, and a deeper understanding of malignant hematopoiesis will provide deeper insights into diagnosis and prognosis for patients with hematological malignancies. Here, we aim to review the recent technical progress and future prospects for scRNA-seq, as applied in physiological and malignant hematopoiesis, in efforts to further understand the hematopoietic hierarchy and to illuminate personalized therapy and precision medicine approaches used in the clinical treatment of hematological malignancies.

Transcriptomic landscape of the blastema niche in regenerating adult axolotl limbs at single-cell resolution

Regeneration of complex multi-tissue structures, such as limbs, requires the coordinated effort of multiple cell types. In axolotl limb regeneration, the wound epidermis and blastema have been extensively studied via histology, grafting, and bulk-tissue RNA-sequencing. However, defining the contributions of these tissues is hindered due to limited information regarding the molecular identity of the cell types in regenerating limbs. Here we report unbiased single-cell RNA-sequencing on over 25,000 cells from axolotl limbs and identify a plethora of cellular diversity within epidermal, mesenchymal, and hematopoietic lineages in homeostatic and regenerating limbs. We identify regeneration-induced genes, develop putative trajectories for blastema cell differentiation, and propose the molecular identity of fibroblast-like blastema progenitor cells. This work will enable application of molecular techniques to assess the contribution of these populations to limb regeneration. Overall, these data allow for establishment of a putative framework for adult axolotl limb regeneration.

Limb regeneration requires a blastema with progenitor cells, immune cells, and an overlying wound epidermis, but molecular identities of these populations are unclear. Here, the authors use single-cell RNA-sequencing to identify transcriptionally distinct cell populations in adult axolotl limb blastemas.

Smart Hydrogel Microfluidics for Single-Cell Multiplexed Secretomic Analysis with High Sensitivity

Secreted proteins determine a range of cellular functionalities correlated with human health and disease progression. Because of cell heterogeneity, it is essential to measure low abundant protein secretions from individual cells to determine single-cell activities. In this study, an integrated platform consisting of smart hydrogel immunosensors for the sensitive detection of single-cell secretions is developed. A single cell and smart hydrogel microparticles are encapsulated within a droplet. After incubation, target secreted proteins from the cell are captured in the smart hydrogel particle for immunoassay. The temperature-induced volume phase transition of the hydrogel biosensor allows the concentration of analytes within the gel matrix to increase, enabling high-sensitivity measurements. Distinct heterogeneity for live cell secretions is determined from 6000 cells within 1 h. This method is tested for low abundant essential secretions, such as interleukin-6, interleukin-8, and monocyte chemoattractant protein-1 secretions of both suspended cells (HL60) and adherent cells (MCF7 and MDA-MB-231). This platform is highly flexible and can be used to simultaneously measure a wide range of clinically relevant cellular secretions; it thus represents a novel tool for precise biological assays.

Luminescent nanomaterials for droplet tracking in a microfluidic trapping array

The use of high-throughput multiplexed screening platforms has attracted significant interest in the field of on-site disease detection and diagnostics for their capability to simultaneously interrogate single-cell responses across different populations. However, many of the current approaches are limited by the spectral overlap between tracking materials (e.g., organic dyes) and commonly used fluorophores/biochemical stains, thus restraining their applications in multiplexed studies. This work demonstrates that the downconversion emission spectra offered by rare earth (RE)-doped β-hexagonal NaYF₄ nanoparticles (NPs) can be exploited to address this spectral overlap issue. Compared to organic dyes and other tracking materials where the excitation and emission is separated by tens of nanometers, RE elements have a large gap between excitation and emission which results in their spectral independence from the organic dyes. As a proof of concept, two differently doped NaYF₄ NPs (europium: Eu³⁺, and terbium: Tb³⁺) were employed on a fluorescent microscopy-based droplet microfluidic trapping array to test their feasibility as spectrally independent droplet trackers. The luminescence tracking properties of Eu³⁺-doped (red emission) and Tb³⁺-doped (green emission) NPs were successfully characterized by co-encapsulating with genetically modified cancer cell lines expressing green or red fluorescent proteins (GFP and RFP) in addition to a mixed population of live and dead cells stained with ethidium homodimer. Detailed quantification of the luminescent and fluorescent signals was performed to confirm no overlap between each of the NPs and between NPs and cells. Thus, the spectral independence of Eu³⁺-doped and Tb³⁺-doped NPs with each other and with common fluorophores highlights the potential application of this novel technique in multiplexed systems, where many such luminescent NPs (other doped and co-doped NPs) can be used to simultaneously track different input conditions on the same platform. Graphical abstract ᅟ.

Insulin mutations impair beta-cell development in a patient-derived iPSC model of neonatal diabetes

Insulin gene mutations are a leading cause of neonatal diabetes. They can lead to proinsulin misfolding and its retention in endoplasmic reticulum (ER). This results in increased ER-stress suggested to trigger beta-cell apoptosis. In humans, the mechanisms underlying beta-cell failure remain unclear. Here we show that misfolded proinsulin impairs developing beta-cell proliferation without increasing apoptosis. We generated induced pluripotent stem cells (iPSCs) from people carrying insulin (INS) mutations, engineered isogenic CRISPR-Cas9 mutation-corrected lines and differentiated them to beta-like cells. Single-cell RNA-sequencing analysis showed increased ER-stress and reduced proliferation in INS-mutant beta-like cells compared with corrected controls. Upon transplantation into mice, INS-mutant grafts presented reduced insulin secretion and aggravated ER-stress. Cell size, mTORC1 signaling, and respiratory chain subunits expression were all reduced in INS-mutant beta-like cells, yet apoptosis was not increased at any stage. Our results demonstrate that neonatal diabetes-associated INS-mutations lead to defective beta-cell mass expansion, contributing to diabetes development.

Microfluidic diamagnetic water-in-water droplets: a biocompatible cell encapsulation and manipulation platform

Droplet microfluidics enables cellular encapsulation for biomedical applications such as single-cell analysis, which is an important tool used by biologists to study cells on a single-cell level, and understand cellular heterogeneity in cell populations. However, most cell encapsulation strategies in microfluidics rely on random encapsulation processes, resulting in large numbers of empty droplets. Therefore, post-sorting of droplets is necessary to obtain samples of purely cell-encapsulating droplets. With the recent advent of aqueous two-phase systems (ATPS) as a biocompatible alternative of the conventional water-in-oil droplet systems for cellular encapsulation, there has also been a focus on integrating ATPS with droplet microfluidics. In this paper, we describe a new technique that combines ATPS-based water-in-water droplets with diamagnetic manipulation to isolate single-cell encapsulating water-in-water droplets, and achieve a purity of 100% in a single pass. We exploit the selective partitioning of ferrofluid in an ATPS of polyethylene glycol-polypropylene glycol-polyethylene glycol triblock copolymer (PEG-PPG-PEG) and dextran (DEX), to achieve diamagnetic manipulation of water-in-water droplets. A cell-triggered Rayleigh-Plateau instability in the dispersed phase thread results in a size distinction between the cell-encapsulating and empty droplets, enabling diamagnetic separation and sorting of the cell-encapsulating droplets from empty droplets. This is a simple and biocompatible all-aqueous platform for single-cell encapsulation and droplet manipulation, with applications in single-cell analysis.

Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT

Lineage relationships among the large number of heterogeneous cell types generated during development are difficult to reconstruct in a high-throughput manner. We recently established a method, scGESTALT, that combines cumulative editing of a lineage barcode array by CRISPR-Cas9 with large-scale transcriptional profiling using droplet-based single-cell RNA sequencing (scRNA-seq). The technique generates edits in the barcode array over multiple timepoints using Cas9 and pools of single-guide RNAs (sgRNAs) introduced during early and late zebrafish embryonic development, which distinguishes it from similar Cas9 lineage-tracing methods. The recorded lineages are captured, along with thousands of cellular transcriptomes, to build lineage trees with hundreds of branches representing relationships among profiled cell types. Here, we provide details for (i) generating transgenic zebrafish; (ii) performing multi-timepoint barcode editing; (iii) building scRNA-seq libraries from brain tissue; and (iv) concurrently amplifying lineage barcodes from captured single cells. Generating transgenic lines takes 6 months, and performing barcode editing and generating single-cell libraries involve 7 d of hands-on time. scGESTALT provides a scalable platform to map lineage relationships between cell types in any system that permits genome editing during development, regeneration, or disease.

Novel Variable Radius Spiral⁻Shaped Micromixer: From Numerical Analysis to Experimental Validation

A novel type of spiral micromixer with expansion and contraction parts is presented in order to enhance the mixing quality in the low Reynolds number regimes for point-of-care tests (POCT). Three classes of micromixers with different numbers of loops and modified geometries were studied. Numerical simulation was performed to study the flow behavior and mixing performance solving the steady-state Navier⁻Stokes and the convection-diffusion equations in the Reynolds range of 0.1⁻10.0. Comparisons between the mixers with and without expansion parts were made to illustrate the effect of disturbing the streamlines on the mixing performance. Image analysis of the mixing results from fabricated micromixers was used to verify the results of the simulations. Since the proposed mixer provides up to 92% of homogeneity at Re 1.0, generating 442 Pa of pressure drop, this mixer makes a suitable candidate for research in the POCT field.

Quantifying phenotypes in single cells using droplet microfluidics

This book chapter describes the use of droplet microfluidics to phenotype single cells. The basic process flow includes the encapsulation of single cells with a specific probe into aqueous micro-droplets suspended in a biocompatible oil. The probe is chosen to measure the phenotype of interest. After incubation, the encapsulated cell turns the probe fluorescent and renders the entire droplet fluorescent. Enumerating drops that are fluorescent quantifies the concentration of cells possessing the phenotype of interest. Examining the distribution of fluorescence further allows one to quantify the heterogeneity among the cell population.

Adult neurogenic deficits in HIV-1 Tg26 transgenic mice

Background

Even in the antiretroviral treatment (ART) era, HIV-1-infected patients suffer from milder forms of HIV-1-associated neurocognitive disorders (HAND). While the viral proteins Tat and gp120 have been shown to individually inhibit the proliferation and neural differentiation of neural stem cells (NSCs), no studies have characterized the effects of all the combined viral proteins on adult neurogenesis.

Methods

The HIV-1 Tg26 transgenic mouse model was used due to its clinical relevance to ART-controlled HIV-1-infected patients who lack active viral replication but suffer from continuous stress from the viral proteins. Quantitative RT-PCR analysis was performed to validate the expression of viral genes in the neurogenic zones. In vitro stemness and lineage differentiation assays were performed in cultured NSCs from HIV-1 Tg26 transgenic mice and their wild-type littermates. Hippocampal neurogenic lineage analysis was performed to determine potential changes in initial and late differentiation of NSCs in the subgranular zone (SGZ). Finally, fluorescent retroviral labeling of mature dentate granule neurons was performed to assess dendritic complexity and dendritic spine densities.

Results

Varying copy numbers of partial gag (p17), tat (unspliced and spliced variants), env (gp120), vpu, and nef transcripts were detected in the neurogenic zones of Tg26 mice. Significantly fewer primary neurospheres and a higher percentage of larger sized primary neurospheres were generated from Tg26 NSCs than from littermated wild-type mouse NSCs, implying that Tg26 mouse NSCs exhibit deficits in initial differentiation. In vitro differentiation assays revealed that Tg26 mouse NSCs have reduced neuronal differentiation and increased astrocytic differentiation. In the SGZs of Tg26 mice, significantly higher amounts of quiescent NSCs, as well as significantly lower levels of active NSCs, proliferating neural progenitor cells, and neuroblasts, were observed. Finally, newborn mature granule neurons in the dentate gyri of Tg26 mice had deficiencies in dendritic arborization, dendritic length, and dendritic spine density.

Conclusions

Both in vitro and in vivo studies demonstrate that HIV-1 Tg26 mice have early- and late-stage neurogenesis deficits, which could possibly contribute to the progression of HAND. Future therapies should be targeting this process to ameliorate, if not eliminate HAND-like symptoms in HIV-1-infected patients.

An efficient strategy for a controllable droplet merging system for digital analysis

Droplet merging is an important part of droplet manipulation approaches. Droplet merging methods with expansions inside channels can merge droplets in pairs through simple structures. However, they have a low success rate of merging under unstable fluidic conditions since the one-to-one pairing strategy is sensitive to fluctuation. This study presents a one-to-a-cluster pairing strategy to improve the success rate of merging under fluctuation. The one-to-a-cluster method was suitable for digital analysis and droplet MDA was performed in merged droplets successfully.

Efficient Production of On-Target Reads for Small RNA Sequencing of Single Cells Using Modified Adapters

Although single-cell mRNA sequencing has been a powerful tool to explore cellular heterogeneity, the sequencing of small RNA at the single-cell level (sc-sRNA-seq) remains a challenge, as these have no consensus sequence, are relatively low abundant, and are difficult to amplify in a bias-free fashion. We present two methods of single-cell-lysis that enable sc-sRNA-seq. The first method is a chemical-based technique with overnight freezing while the second method leverages on-chip electrical lysis of plasma membrane and physical extraction and separation of cytoplasmic RNA via isotachophoresis. We coupled these two methods with off-chip small RNA library preparation using CleanTag modified adapters to prevent the formation of adapter dimers. We then demonstrated sc-sRNA-seq with single K562 human leukemic cells. Our approaches offer a relatively short hands-on time of 6 h and efficient generation of on-target reads. The sc-sRNA-seq with our approaches showed detection of miRNA with various abundances ranging from 16 000 copies/cell to about 10 copies/cell. We anticipate this approach will create a new opportunity to explore cellular heterogeneity through small RNA expression.

Molecular diversification of regulatory T cells in nonlymphoid tissues

Foxp3+CD4+ regulatory T cells (Tregs) accumulate in certain nonlymphoid tissues, where they control diverse aspects of organ homeostasis. Populations of tissue Tregs, as they have been termed, have transcriptomes distinct from those of their counterparts in lymphoid organs and other nonlymphoid tissues. We examined the diversification of Tregs in visceral adipose tissue, skeletal muscle, and the colon vis-à-vis lymphoid organs from the same individuals. The unique transcriptomes of the various tissue Treg populations resulted from layering of tissue-restricted open chromatin regions over regions already open in the spleen, the latter tagged by super-enhancers and particular histone marks. The binding motifs for a small number of transcription factor (TF) families were repeatedly enriched within the accessible chromatin stretches of Tregs in the three nonlymphoid tissues. However, a bioinformatically and experimentally validated transcriptional network, constructed by integrating chromatin accessibility and single-cell transcriptomic data, predicted reliance on different TF family members in the different tissues. The network analysis also revealed that tissue-restricted and broadly acting TFs were integrated into feed-forward loops to enforce tissue-specific gene expression in nonlymphoid-tissue Tregs. Overall, this study provides a framework for understanding the epigenetic dynamics of T cells operating in nonlymphoid tissues, which should inform strategies for specifically targeting them.

A self-sufficient pressure pump using latex balloons for microfluidic applications

Here, we demonstrate a self-sufficient, inexpensive and disposable pressure pump using commercially available latex balloons. The versatility of the pump is demonstrated against various microfluidic structures, liquid viscosities, and ambient temperatures. The flow rate of the pump can be controlled by varying the size and thickness of the balloon. Importantly, the soft structure of the balloon allows for almost instantaneous change of the flow rate upon manual squeezing of the balloon. This feature has been used for dynamically changing the flow ratio of parallel streams in a T-shaped channel or varying the size of droplets in a droplet generation system. The self-sufficiency, simplicity of fabrication and operation, along with the low-cost of the balloon pump facilitate the widespread application of microfluidic technologies for various research, education, and in situ monitoring purposes.

Visual Experience-Dependent Expression of Fn14 Is Required for Retinogeniculate Refinement

Sensory experience influences the establishment of neural connectivity through molecular mechanisms that remain unclear. Here, we employ single-nucleus RNA sequencing to investigate the contribution of sensory-driven gene expression to synaptic refinement in the dorsal lateral geniculate nucleus of the thalamus, a region of the brain that processes visual information. We find that visual experience induces the expression of the cytokine receptor Fn14 in excitatory thalamocortical neurons. By combining electrophysiological and structural techniques, we show that Fn14 is dispensable for early phases of refinement mediated by spontaneous activity but that Fn14 is essential for refinement during a later, experience-dependent period of development. Refinement deficits in mice lacking Fn14 are associated with functionally weaker and structurally smaller retinogeniculate inputs, indicating that Fn14 mediates both functional and anatomical rearrangements in response to sensory experience. These findings identify Fn14 as a molecular link between sensory-driven gene expression and vision-sensitive refinement in the brain.

High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics

To enable the characterization of genetic heterogeneity in tumor cell populations, we developed a novel microfluidic approach that barcodes amplified genomic DNA from thousands of individual cancer cells confined to droplets. The barcodes are then used to reassemble the genetic profiles of cells from next-generation sequencing data. By using this approach, we sequenced longitudinally collected acute myeloid leukemia (AML) tumor populations from two patients and genotyped up to 62 disease relevant loci across more than 16,000 individual cells. Targeted single-cell sequencing was able to sensitively identify cells harboring pathogenic mutations during complete remission and uncovered complex clonal evolution within AML tumors that was not observable with bulk sequencing. We anticipate that this approach will make feasible the routine analysis of AML heterogeneity, leading to improved stratification and therapy selection for the disease.

Particle-Templated Emulsification for Microfluidics-Free Digital Biology

The compartmentalization of reactions in monodispersed droplets is valuable for applications across biology. However, the requirement of microfluidics to partition the sample into monodispersed droplets is a significant barrier that impedes implementation. Here, we introduce particle-templated emulsification, a method to encapsulate samples in monodispersed emulsions without microfluidics. By vortexing a mixture of hydrogel particles and sample solution, we encapsulate the sample in monodispersed emulsions that are useful for most droplet applications. We illustrate the method with ddPCR and single cell culture. The ability to encapsulate samples in monodispersed droplets without microfluidics should facilitate the implementation of compartmentalized reactions in biology.

Sixth European Seminar in Virology on Virus⁻Host Interaction at Single Cell and Organism Level

The 6th European Seminar in Virology (EuSeV) was held in Bertinoro, Italy, 22–24 June 2018, and brought together international scientists and young researchers working in the field of Virology. Sessions of the meeting included: virus–host-interactions at organism and cell level; virus evolution and dynamics; regulation; immunity/immune response; and disease and therapy. This report summarizes lectures by the invited speakers and highlights advances in the field.

Measurement of Cell-Matrix Adhesion at Single-Cell Resolution for Revealing the Functions of Biomaterials for Adherent Cell Culture

Cell adhesion is essential for a cell to maintain its functions, and biomaterials acting as the extracellular matrix (ECM) play a vital role. However, conventional methods for evaluating the functions of biomaterials become insufficient and sometimes incorrect when we give a deeper insight into single-cell research. In this work, we reported a novel methodology for the measurement of cell-matrix adhesion at single-cell resolution that could precisely evaluate the functions of biomaterials for adherent cell culture. A microfludic device, a live single-cell extractor (LSCE), was used for cell extraction. We applied this method to evaluate various modified biomaterials. The results indicated that poly(l-polylysine) (PLL)-coated glass and fibronection (FN)-coated glass slides showed the best biocompatibility for adherent cell culture following by the (3-aminopropyl)triethoxysilane (APTES)-coated glass, while piranha solution treated glass slide and octadecyltrichlorosilane (OTS)-coated glass showed weak biocompatibilities. Furthermore, APTES, PLL, and FN modifications enhanced the cell heterogeneity, while the OTS modification weakened the cell heterogeneity compare to the initial piranha solution treated glass. The method not only clarified the cell-matrix adhesion strength at single-cell resolution but also revealed the influences of biomaterials on cell-matrix adhesion and heterogeneity of cell-matrix adhesion for adherent cell culture. It might be a general strategy for precise evaluation of biomaterials.

Quantitative single-cell transcriptomics

Single-cell RNA sequencing (scRNA-seq) is currently transforming our understanding of biology, as it is a powerful tool to resolve cellular heterogeneity and molecular networks. Over 50 protocols have been developed in recent years and also data processing and analyzes tools are evolving fast. Here, we review the basic principles underlying the different experimental protocols and how to benchmark them. We also review and compare the essential methods to process scRNA-seq data from mapping, filtering, normalization and batch corrections to basic differential expression analysis. We hope that this helps to choose appropriate experimental and computational methods for the research question at hand.

Immersed AC electrospray (iACE) for monodispersed aqueous droplet generation

We report a new immersed alternating current (AC) electrospray droplet generation method that can generate monodispersed water-in-oil droplets, with diameters ranging from 5 μm to 150 μm, in a stationary oil phase. This method offers high through-put, easy size tuning, and droplets with a viscous aqueous phase at high ionic strengths (raw physiological samples). Yet, it does not require coordinated flows of the dispersed/continuous phases or even a microfluidic chip. The design relies on a small constant back pressure (less than 0.1 atm) to drive the water phase through a nozzle (glass micropipette) and a non-isotropic AC electric Maxwell pressure to eject it into the oil phase. Undesirable field-induced discharge and nanojet formation at the tip are suppressed with a biocompatible polymer, polyethylene oxide. Its viscoelastic property favors the monodispersed dripping mechanism, with a distinct neck forming at the capillary tip before pinch-off, such that the tip dimension is the only controlling length scale. Consecutive droplets are connected by a whipping filament that disperses the drops away from the high-field nozzle to prevent electro-coalescence. A scaling theory is developed to correlate the droplet size with the applied pressure, the most important tuning parameter, and to determine the optimum frequency. The potential applications of this technology to biological systems are demonstrated with a digital loop-mediated isothermal amplification experiment, with little damage to the nucleic acids and other biomolecules, but with easy adaptive tuning for the optimum droplet number for accurate quantification.

Mapping gene regulatory networks from single-cell omics data

Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future.

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment

Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We profiled 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph nodes, using single-cell RNA-seq. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer. Our results have important implications for characterizing tumor-infiltrating immune cells.

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion

Single-cell RNA sequencing technologies suffer from many sources of technical noise, including under-sampling of mRNA molecules, often termed "dropout," which can severely obscure important gene-gene relationships. To address this, we developed MAGIC (Markov affinity-based graph imputation of cells), a method that shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts. We validate MAGIC on several biological systems and find it effective at recovering gene-gene relationships and additional structures. Applied to the epithilial to mesenchymal transition, MAGIC reveals a phenotypic continuum, with the majority of cells residing in intermediate states that display stem-like signatures, and infers known and previously uncharacterized regulatory interactions, demonstrating that our approach can successfully uncover regulatory relations without perturbations.

Indel-correcting DNA barcodes for high-throughput sequencing

Modern high-throughput biological assays study pooled populations of individual members by labeling each member with a unique DNA sequence called a “barcode.” DNA barcodes are frequently corrupted by DNA synthesis and sequencing errors, leading to significant data loss and incorrect data interpretation. Here, we describe an error correction strategy to improve the efficiency and statistical power of DNA barcodes. Our strategy accurately handles insertions and deletions (indels) in DNA barcodes, the most common type of error encountered during DNA synthesis and sequencing, resulting in order-of-magnitude increases in accuracy, efficiency, and signal-to-noise ratio. The accompanying software package makes deployment of these barcodes straightforward for the broader experimental scientist community.

Many large-scale, high-throughput experiments use DNA barcodes, short DNA sequences prepended to DNA libraries, for identification of individuals in pooled biomolecule populations. However, DNA synthesis and sequencing errors confound the correct interpretation of observed barcodes and can lead to significant data loss or spurious results. Widely used error-correcting codes borrowed from computer science (e.g., Hamming, Levenshtein codes) do not properly account for insertions and deletions (indels) in DNA barcodes, even though deletions are the most common type of synthesis error. Here, we present and experimentally validate filled/truncated right end edit (FREE) barcodes, which correct substitution, insertion, and deletion errors, even when these errors alter the barcode length. FREE barcodes are designed with experimental considerations in mind, including balanced guanine-cytosine (GC) content, minimal homopolymer runs, and reduced internal hairpin propensity. We generate and include lists of barcodes with different lengths and error correction levels that may be useful in diverse high-throughput applications, including >10⁶ single-error–correcting 16-mers that strike a balance between decoding accuracy, barcode length, and library size. Moreover, concatenating two or more FREE codes into a single barcode increases the available barcode space combinatorially, generating lists with >10¹⁵ error-correcting barcodes. The included software for creating barcode libraries and decoding sequenced barcodes is efficient and designed to be user-friendly for the general biology community.

Out-of-equilibrium microcompartments for the bottom-up integration of metabolic functions

Self-sustained metabolic pathways in microcompartments are the corner-stone for living systems. From a technological viewpoint, such pathways are a mandatory prerequisite for the reliable design of artificial cells functioning out-of-equilibrium. Here we develop a microfluidic platform for the miniaturization and analysis of metabolic pathways in man-made microcompartments formed of water-in-oil droplets. In a modular approach, we integrate in the microcompartments a nicotinamide adenine dinucleotide (NAD)-dependent enzymatic reaction and a NAD-regeneration module as a minimal metabolism. We show that the microcompartments sustain a metabolically active state until the substrate is fully consumed. Reversibly, the external addition of the substrate reboots the metabolic activity of the microcompartments back to an active state. We therefore control the metabolic state of thousands of independent monodisperse microcompartments, a step of relevance for the construction of large populations of metabolically active artificial cells.

dropEst: pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments

Recent single-cell RNA-seq protocols based on droplet microfluidics use massively multiplexed barcoding to enable simultaneous measurements of transcriptomes for thousands of individual cells. The increasing complexity of such data creates challenges for subsequent computational processing and troubleshooting of these experiments, with few software options currently available. Here, we describe a flexible pipeline for processing droplet-based transcriptome data that implements barcode corrections, classification of cell quality, and diagnostic information about the droplet libraries. We introduce advanced methods for correcting composition bias and sequencing errors affecting cellular and molecular barcodes to provide more accurate estimates of molecular counts in individual cells.

New transcriptomic tools to understand testis development and functions

The testis plays a central role in the male reproductive system - secreting several hormones including male steroids and producing male gametes. A complex and coordinated molecular program is required for the proper differentiation of testicular cell types and maintenance of their functions in adulthood. The testicular transcriptome displays the highest levels of complexity and specificity across all tissues in a wide range of species. Many studies have used high-throughput sequencing technologies to define the molecular dynamics and regulatory networks in the testis as well as to identify novel genes or gene isoforms expressed in this organ. This review intends to highlight the complementarity of these transcriptomic studies and to show how the use of different sequencing protocols contribute to improve our global understanding of testicular biology.

TCR Transgenic Mice Reveal Stepwise, Multi-site Acquisition of the Distinctive Fat-Treg Phenotype

Visceral adipose tissue (VAT) hosts a population of regulatory T (Treg) cells, with a unique phenotype, that controls local and systemic inflammation and metabolism. Generation of a T cell receptor transgenic mouse line, wherein VAT Tregs are highly enriched, facilitated study of their provenance, dependencies, and activities. We definitively established a role for T cell receptor specificity, uncovered an unexpected function for the primordial Treg transcription-factor, Foxp3, evidenced a cell-intrinsic role for interleukin-33 receptor, and ordered these dependencies within a coherent scenario. Genesis of the VAT-Treg phenotype entailed a priming step in the spleen, permitting them to exit the lymphoid organs and surveil nonlymphoid tissues, and a final diversification process within VAT, in response to microenvironmental cues. Understanding the principles of tissue-Treg biology is a prerequisite for precision-targeting strategies.

zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs

Background

Single-cell RNA-sequencing (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific bar codes (BCs), and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus, the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI.

Findings

zUMIs is a pipeline that can handle both known and random BCs and also efficiently collapse UMIs, either just for exon mapping reads or for both exon and intron mapping reads. If BC annotation is missing, zUMIs can accurately detect intact cells from the distribution of sequencing reads. Another unique feature of zUMIs is the adaptive downsampling function that facilitates dealing with hugely varying library sizes but also allows the user to evaluate whether the library has been sequenced to saturation. To illustrate the utility of zUMIs, we analyzed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to introns. Also, we show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution.

Conclusions

zUMIs flexibility makes if possible to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs and is the most feature-rich, fast, and user-friendly pipeline to process such scRNA-seq data.

Integrating single-cell transcriptomic data across different conditions, technologies, and species

Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

Exclusive Liquid Repellency: An Open Multi-Liquid-Phase Technology for Rare Cell Culture and Single-Cell Processing

The concept of high liquid repellency in multi-liquid-phase systems (e.g., aqueous droplets in an oil background) has been applied to areas of biomedical research to realize intrinsic advantages not available in single-liquid-phase systems. Such advantages have included minimizing analyte loss, facile manipulation of single-cell samples, elimination of biofouling, and ease of use regarding loading and retrieving of the sample. In this paper, we present generalized design rules for predicting the wettability of solid-liquid-liquid systems (especially for discrimination between exclusive liquid repellency (ELR) and finite liquid repellency) to extend the applications of ELR. We then apply ELR to two model systems with open microfluidic design in cell biology: (1) in situ underoil culture and combinatorial coculture of mammalian cells in order to demonstrate directed single-cell multiencapsulation with minimal waste of samples as compared to stochastic cell seeding and (2) isolation of a pure population of circulating tumor cells, which is required for certain downstream analyses including sequencing and gene expression profiling.