Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems.

Since its establishment in 2009, single-cell RNA sequencing (RNA-seq) has been a major driver behind progress in biomedical research. In developmental biology and stem cell studies, the ability to profile single cells confers particular benefits. Although most studies still focus on individual tissues or organs, the recent development of ultra-high-throughput single-cell RNA-seq has demonstrated potential power in characterizing more complex systems or even the entire body. However, although multiple ultra-high-throughput single-cell RNA-seq systems have attracted attention, no systematic comparison of these systems has been performed. Here, with the same cell line and bioinformatics pipeline, we developed directly comparable datasets for each of three widely used droplet-based ultra-high-throughput single-cell RNA-seq systems, inDrop, Drop-seq, and 10X Genomics Chromium. Although each system is capable of profiling single-cell transcriptomes, their detailed comparison revealed the distinguishing features and suitable applications for each system.

Microarray Platforms Based on 3D Printing.

This paper introduces an innovative method for the fabrication and infusion of microwell arrays based on digital light processing (DLP) 3D printing. A low-cost DLP 3D printer is employed to fabricate microstructures rapidly with a broad dynamic range while maintaining high precision and fidelity. We constructed microwell arrays with varying diameters, from 200 to 2000 µm and multiple aspect ratios, in addition to microchannels with widths ranging from 45 to 1000 µm, proving the potential and flexibility of this fabrication method. The superimposition of parallel microchannels onto the microwell array, facilitated by positive or negative pressure, enabled the transfer of liquid to the microwells. Upon removal of the microchannel chip, a dispensed microdroplet array was obtained. This array can be modulated by adjusting the volume of the microwells and the inflow fluid. The filled microwell array allows chip-to-chip dispensing to the microreactor array through binding and centrifugation, facilitating multistep and multireagent assays. The 3D printing approach also enables the fabrication of intricate cavity designs, such as micropyramid arrays, which can be integrated with parallel microchannels to generate spheroid flowcells. This device demonstrated the ability to generate spheroids and manipulate their environment. We have successfully utilized precise modulation of spheroids size and performed parallel drug dose-response assays to evaluate its effectiveness. Furthermore, we managed to execute dynamic drug combinations based on a compact spheroids array, utilizing two orthogonal parallel microchannels. Our findings suggest that both the combination and temporal sequence of drug administration have a significant impact on therapeutic outcomes.

Integrating single-cell datasets with ambiguous batch information by incorporating molecular network features.

With the rapid development of single-cell sequencing techniques, several large-scale cell atlas projects have been launched across the world. However, it is still challenging to integrate single-cell RNA-seq (scRNA-seq) datasets with diverse tissue sources, developmental stages and/or few overlaps, due to the ambiguity in determining the batch information, which is particularly important for current batch-effect correction methods. Here, we present SCORE, a simple network-based integration methodology, which incorporates curated molecular network features to infer cellular states and generate a unified workflow for integrating scRNA-seq datasets. Validating on real single-cell datasets, we showed that regardless of batch information, SCORE outperforms existing methods in accuracy, robustness, scalability and data integration.

Chemoproteomics reveals baicalin activates hepatic CPT1 to ameliorate diet-induced obesity and hepatic steatosis.

Obesity and related metabolic diseases are becoming worldwide epidemics that lead to increased death rates and heavy health care costs. Effective treatment options have not been found yet. Here, based on the observation that baicalin, a flavonoid from the herbal medicine Scutellaria baicalensis, has unique antisteatosis activity, we performed quantitative chemoproteomic profiling and identified carnitine palmitoyltransferase 1 (CPT1), the controlling enzyme for fatty acid oxidation, as the key target of baicalin. The flavonoid directly activated hepatic CPT1 with isoform selectivity to accelerate the lipid influx into mitochondria for oxidation. Chronic treatment of baicalin ameliorated diet-induced obesity (DIO) and hepatic steatosis and led to systemic improvement of other metabolic disorders. Disruption of the predicted binding site of baicalin on CPT1 completely abolished the beneficial effect of the flavonoid. Our discovery of baicalin as an allosteric CPT1 activator opens new opportunities for pharmacological treatment of DIO and associated sequelae.

Microfluidic Device for Studying Controllable Hydrodynamic Flow Induced Cellular Responses.

Hydrodynamic flow is an essential stimulus in many cellular functions, regulating many mechanical sensitive pathways and closely associating with human health status and diseases. The flow pattern of blood in vessels is the key factor in causing atherosclerosis. Hemodynamics has great effect on endothelial cells' gene expression and biological functions. There are various tools that can be used for studying flow-induced cellular responses but most of them are either bulky or lack precise controllability. We develop an integrated microfluidic device that can precisely generate different flow patterns to human endothelial cells cultured on-chip. We monitored cell morphology and used small-input RNA-seq technology to depict the transcriptome profiles of human umbilical vein endothelial cells under uni- or bidirectional flow. Such integrated and miniatured device has greatly facilitated our understanding of endothelial functions with shear stimulus, not only providing new data on the transcriptomic scale but also building the connection between cell phenotypic changes and expression alternations.

Microfluidic single-cell whole-transcriptome sequencing.

Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole-transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2 M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis.

Large-Scale Integration of Single-Cell RNA-Seq Data Reveals Astrocyte Diversity and Transcriptomic Modules across Six Central Nervous System Disorders.

The dysfunction of astrocytes in response to environmental factors contributes to many neurological diseases by impacting neuroinflammation responses, glutamate and ion homeostasis, and cholesterol and sphingolipid metabolism, which calls for comprehensive and high-resolution analysis. However, single-cell transcriptome analyses of astrocytes have been hampered by the sparseness of human brain specimens. Here, we demonstrate how large-scale integration of multi-omics data, including single-cell and spatial transcriptomic and proteomic data, overcomes these limitations. We created a single-cell transcriptomic dataset of human brains by integration, consensus annotation, and analyzing 302 publicly available single-cell RNA-sequencing (scRNA-seq) datasets, highlighting the power to resolve previously unidentifiable astrocyte subpopulations. The resulting dataset includes nearly one million cells that span a wide variety of diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), multiple sclerosis (MS), epilepsy (Epi), and chronic traumatic encephalopathy (CTE). We profiled the astrocytes at three levels, subtype compositions, regulatory modules, and cell-cell communications, and comprehensively depicted the heterogeneity of pathological astrocytes. We constructed seven transcriptomic modules that are involved in the onset and progress of disease development, such as the M2 ECM and M4 stress modules. We validated that the M2 ECM module could furnish potential markers for AD early diagnosis at both the transcriptome and protein levels. In order to accomplish a high-resolution, local identification of astrocyte subtypes, we also carried out a spatial transcriptome analysis of mouse brains using the integrated dataset as a reference. We found that astrocyte subtypes are regionally heterogeneous. We identified dynamic cell-cell interactions in different disorders and found that astrocytes participate in key signaling pathways, such as NRG3-ERBB4, in epilepsy. Our work supports the utility of large-scale integration of single-cell transcriptomic data, which offers new insights into underlying multiple CNS disease mechanisms where astrocytes are involved.

FAM46C-mediated tumor heterogeneity predicts extramedullary metastasis and poorer survival in multiple myeloma.

Cancers originate from a single cell according to Nowell's theory of clonal evolution. The enrichment of the most aggressive clones has been developed and the heterogeneity arises for genomic instability and environmental selection. Multiple myeloma (MM) is a multiple relapse plasma cell cancer generated from bone marrow. Although there were accumulating researches in multiple myeloma pathogenesis, the heterogeneity remains poorly understood. The participants enrolled in this study were 4 EMP+ (EMP, Extramedullary plasmacytoma) and 2 EMP- primarily untreated MM patients. Single cell RNA sequencing and analysis were conducted for the single cell suspension, which was sorted by flow cytometry from peripheral blood mononuclear cells or bone marrow cells. In our research, the results of single cell RNA sequencing show that FAM46C determines MM tumor heterogeneity predicting extramedullary metastasis by influencing RNA stability. Further, we integrated and analyzed 2280 multiple myeloma samples from 7 independent datasets, which uncover that FAM46C mediated tumor heterogeneity predicts poorer survival in multiple myeloma.

Design and High-Resolution Analysis of an Efficient Periodic Split-and-Recombination Microfluidic Mixer.

We developed a highly efficient passive mixing device based on a split-and-recombine (SAR) configuration. This micromixer was constructed by simply bonding two identical microfluidic periodical open-trench patterns face to face. The structure parameters of periodical units were optimized through numerical simulation to facilitate the mixing efficiency. Despite the simplicity in design and fabrication, it provided rapid mixing performance in both experiment and simulation conditions. To better illustrate the mixing mechanism, we developed a novel scheme to achieve high-resolution confocal imaging of serial channel cross-sections to accurately characterize the mixing details and performance after each SAR cycle. Using fluorescent IgG as an indicator, nearly complete mixing was achieved using only four SAR cycles in an aqueous solution within a device's length of less than 10 mm for fluids with a Péclet number up to 8.7 × 104. Trajectory analysis revealed that each SAR cycle transforms the input fluids using three synergetic effects: rotation, combination, and stretching to increase the interfaces exponentially. Furthermore, we identified that the pressure gradients in the parallel plane of the curved channel induced vertical convection, which is believed to be the driving force underlying these effects to accelerate the mixing process.

Single-cell RNA-seq reveals early heterogeneity during aging in yeast.

The budding yeast Saccharomyces cerevisiae (S. cerevisiae) has relatively short lifespan and is genetically tractable, making it a widely used model organism in aging research. Here, we carried out a systematic and quantitative investigation of yeast aging with single-cell resolution through transcriptomic sequencing. We optimized a single-cell RNA sequencing (scRNA-seq) protocol to quantitatively study the whole transcriptome profiles of single yeast cells at different ages, finding increased cell-to-cell transcriptional variability during aging. The single-cell transcriptome analysis also highlighted key biological processes or cellular components, including oxidation-reduction process, oxidative stress response (OSR), translation, ribosome biogenesis and mitochondrion that underlie aging in yeast. We uncovered a molecular marker of FIT3, indicating the early heterogeneity during aging in yeast. We also analyzed the regulation of transcription factors and further characterized the distinctive temporal regulation of the OSR by YAP1 and proteasome activity by RPN4 during aging in yeast. Overall, our data profoundly reveal early heterogeneity during aging in yeast and shed light on the aging dynamics at the single cell level.

Establishment of intestinal organoid cultures modeling injury-associated epithelial regeneration.

The capacity of 3D organoids to mimic physiological tissue organization and functionality has provided an invaluable tool to model development and disease in vitro. However, conventional organoid cultures primarily represent the homeostasis of self-organizing stem cells and their derivatives. Here, we established a novel intestinal organoid culture system composed of 8 components, mainly including VPA, EPZ6438, LDN193189, and R-Spondin 1 conditioned medium, which mimics the gut epithelium regeneration that produces hyperplastic crypts following injury; therefore, these organoids were designated hyperplastic intestinal organoids (Hyper-organoids). Single-cell RNA sequencing identified different regenerative stem cell populations in our Hyper-organoids that shared molecular features with in vivo injury-responsive Lgr5+ stem cells or Clu+ revival stem cells. Further analysis revealed that VPA and EPZ6438 were indispensable for epigenome reprogramming and regeneration in Hyper-organoids, which functioned through epigenetically regulating YAP signaling. Furthermore, VPA and EPZ6438 synergistically promoted regenerative response in gut upon damage in vivo. In summary, our results demonstrated a new in vitro organoid model to study epithelial regeneration, highlighting the importance of epigenetic reprogramming that pioneers tissue repair.

Dissecting esophageal squamous-cell carcinoma ecosystem by single-cell transcriptomic analysis.

Esophageal squamous-cell carcinoma (ESCC), one of the most prevalent and lethal malignant disease, has a complex but unknown tumor ecosystem. Here, we investigate the composition of ESCC tumors based on 208,659 single-cell transcriptomes derived from 60 individuals. We identify 8 common expression programs from malignant epithelial cells and discover 42 cell types, including 26 immune cell and 16 nonimmune stromal cell subtypes in the tumor microenvironment (TME), and analyse the interactions between cancer cells and other cells and the interactions among different cell types in the TME. Moreover, we link the cancer cell transcriptomes to the somatic mutations and identify several markers significantly associated with patients' survival, which may be relevant to precision care of ESCC patients. These results reveal the immunosuppressive status in the ESCC TME and further our understanding of ESCC.

Single-cell RNA sequencing reveals chemokine self-feeding of myeloma cells promotes extramedullary metastasis.

In this study, we aimed to determine the mechanisms underlying the initial extramedullary translocation of myeloma cells from bone marrow into peripheral blood. We found that clonal circulating plasma cells (cPCs) are more frequently detected by flow cytometry in extramedullary plasmacytoma (EMP) patients and worsen their prognosis. It is technically much easier to collect single cPCs using FACS than it is to perform EMP biopsy. Therefore, combining EMP imaging with cPC detection may be a promising strategy for prognostic stratification. Here, using single-cell transcriptome analysis, we found that the chemokine CXCL12, a key molecule involved in CXCR4-dependent cell retention in the bone marrow, is abnormally upregulated in cPCs and might initially enable cPCs to evade bone marrow retention and translocate into the bloodstream.

Single-cell transcriptomic analysis in a mouse model deciphers cell transition states in the multistep development of esophageal cancer.

Esophageal squamous cell carcinoma (ESCC) is prevalent in some geographical regions of the world. ESCC development presents a multistep pathogenic process from inflammation to invasive cancer; however, what is critical in these processes and how they evolve is largely unknown, obstructing early diagnosis and effective treatment. Here, we create a mouse model mimicking human ESCC development and construct a single-cell ESCC developmental atlas. We identify a set of key transitional signatures associated with oncogenic evolution of epithelial cells and depict the landmark dynamic tumorigenic trajectories. An early downregulation of CD8+ response against the initial tissue damage accompanied by the transition of immune response from type 1 to type 3 results in accumulation and activation of macrophages and neutrophils, which may create a chronic inflammatory environment that promotes carcinogen-transformed epithelial cell survival and proliferation. These findings shed light on how ESCC is initiated and developed.

Heightened Innate Immune Responses in the Respiratory Tract of COVID-19 Patients.

The outbreaks of 2019 novel coronavirus disease (COVID-19) caused by SARS-CoV-2 infection have posed a severe threat to global public health. It is unclear how the human immune system responds to this infection. Here, we used metatranscriptomic sequencing to profile immune signatures in the bronchoalveolar lavage fluid of eight COVID-19 cases. The expression of proinflammatory genes, especially chemokines, was markedly elevated in COVID-19 cases compared to community-acquired pneumonia patients and healthy controls, suggesting that SARS-CoV-2 infection causes hypercytokinemia. Compared to SARS-CoV, which is thought to induce inadequate interferon (IFN) responses, SARS-CoV-2 robustly triggered expression of numerous IFN-stimulated genes (ISGs). These ISGs exhibit immunopathogenic potential, with overrepresentation of genes involved in inflammation. The transcriptome data was also used to estimate immune cell populations, revealing increases in activated dendritic cells and neutrophils. Collectively, these host responses to SARS-CoV-2 infection could further our understanding of disease pathogenesis and point toward antiviral strategies.

High-throughput single-cell whole-genome amplification through centrifugal emulsification and eMDA.

Single-cell whole-genome sequencing (scWGS) is mainly used to probe intercellular genomic variations, focusing on the copy number variations or alterations and the single-nucleotide variations (SNVs) occurring within single cells. Single-cell whole-genome amplification (scWGA) needs to be applied before scWGS but is challenging due to the low copy number of DNA. Besides, many genomic variations are rare within a population of cells, so the throughput of currently available scWGA methods is far from satisfactory. Here, we integrate a one-step micro-capillary array (MiCA)-based centrifugal droplet generation technique with emulsion multiple displacement amplification (eMDA) and demonstrate a high-throughput scWGA method, MiCA-eMDA. MiCA-eMDA increases the single-run throughput of scWGA to a few dozen, and enables the assessment of copy number variations and alterations at 50-kb resolution. Downstream target enrichment further enables the detection of SNVs with 20% allele drop-out.

Genomic Heterogeneity and Branched Evolution of Early Stage Primary Acral Melanoma Shown by Multiregional Microdissection Sequencing.

Acral melanoma (AM) is an extremely aggressive subtype of melanoma that is prevalent in eastern Asia. AM exhibits high intertumoral and intratumoral heterogeneities with poor prognosis. To associate the genomic heterogeneities with phenotypic traits and efficacy of treatments, a method is needed to recover genomic information from limited samples with high specificity and sensitivity from early stage AM specimens. We performed laser capture microdissection to isolate single micro-tumor nests, containing only dozens of cells, from stained tissue slices and then applied multiple annealing and looping-based amplification cycles, a highly efficient whole-genome amplification method originally developed for single cells, to amplify the whole genome of each tumor nest for sequencing. We were able to accurately profile the landscape of copy number alterations and single nucleotide variations of every single micro-tumor nest and to quantitatively characterize the heterogeneities at different levels, between tumor and nevi, among patients, among different phenotypes within a same tumor, and among adjacent tumor cell clusters with identical phenotypic appearance. We have found that genomic heterogeneity exists extensively and that branched evolution happens in the early stage of AM development. We are able to build the phylogenetic tree among these phenotypically addressable cell clusters.

A valve-less microfluidic peristaltic pumping method.

We demonstrate a valve-less microfluidic peristaltic pumping method which enables the delivery of continuous nanoliter-scale flow with high precision. The fluid is driven by squeezing the microchannels embedded in a poly(dimethylsiloxane) device with rolling cams or bearings. We achieve continuous and uniform flow with velocity range from 1 to 500 nl/s, with outflow volume error within 3 nl. The devices show enhanced backpressure resistance up to 340 kPa. This method also shows great flexibility. By altering the channels' layout, emulsions and plugs can be generated easily. These low-cost and easy-to-fabricate micro-pumps offer novel approaches for liquid actuation in various microfluidic applications.

Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos.

Circular RNAs (circRNAs) are a new class of non-polyadenylated non-coding RNAs that may play important roles in many biological processes. Here we develop a single-cell universal poly(A)-independent RNA sequencing (SUPeR-seq) method to sequence both polyadenylated and non-polyadenylated RNAs from individual cells. This method exhibits robust sensitivity, precision and accuracy. We discover 2891 circRNAs and 913 novel linear transcripts in mouse preimplantation embryos and further analyze the abundance of circRNAs along development, the function of enriched genes, and sequence features of circRNAs. Our work is key to deciphering regulation mechanisms of circRNAs during mammalian early embryonic development.