SINC-seq: correlation of transient gene expressions between nucleus and cytoplasm reflects single-cell physiology

High-throughput mechanical phenotyping and transcriptomics of single cells

The molecular system regulating cellular mechanical properties remains unexplored at single-cell resolution mainly due to a limited ability to combine mechanophenotyping with unbiased transcriptional screening. Here, we describe an electroporation-based lipid-bilayer assay for cell surface tension and transcriptomics (ELASTomics), a method in which oligonucleotide-labelled macromolecules are imported into cells via nanopore electroporation to assess the mechanical state of the cell surface and are enumerated by sequencing. ELASTomics can be readily integrated with existing single-cell sequencing approaches and enables the joint study of cell surface mechanics and underlying transcriptional regulation at an unprecedented resolution. We validate ELASTomics via analysis of cancer cell lines from various malignancies and show that the method can accurately identify cell types and assess cell surface tension. ELASTomics enables exploration of the relationships between cell surface tension, surface proteins, and transcripts along cell lineages differentiating from the haematopoietic progenitor cells of mice. We study the surface mechanics of cellular senescence and demonstrate that RRAD regulates cell surface tension in senescent TIG-1 cells. ELASTomics provides a unique opportunity to profile the mechanical and molecular phenotypes of single cells and can dissect the interplay among these in a range of biological contexts.

Opto-combinatorial indexing enables high-content transcriptomics by linking cell images and transcriptomes

We introduce a simple integrated analysis method that links cellular phenotypic behaviour with single-cell RNA sequencing (scRNA-seq) by utilizing a combination of optical indices from cells and hydrogel beads. With our method, the combinations, referred to as joint colour codes, enable the link via matching the optical combinations measured by conventional epi-fluorescence microscopy with the concatenated DNA molecular barcodes created by cell-hydrogel bead pairs and sequenced by next-generation sequencing. We validated our approach by demonstrating an accurate link between the cell image and scRNA-seq with mixed species experiments, longitudinal cell tagging by electroporation and lipofection, and gene expression analysis. Furthermore, we extended our approach to multiplexed chemical transcriptomics, which enabled us to identify distinct phenotypic behaviours in HeLa cells treated with various concentrations of paclitaxel, and determine the corresponding gene regulation associated with the formation of a multipolar spindle.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

Studying relative RNA localization From nucleus to the cytosol

The precise coordination of important biological processes, such as differentiation and development, is highly dependent on the regulation of expression of the genetic information. The flow of the genetic information is tightly regulated on multiple levels. Among them, RNA export to cytosol is an essential step for the production of proteins in eukaryotic cells. Hence, estimating the relative concentration of RNA molecules of a given transcript species in the nucleus and in the cytosol is of major significance as it contributes to the understanding of the dynamics of RNA trafficking between the nucleus and the cytosol. The most efficient way to estimate the levels of RNA species genome-wide is through RNA sequencing (RNAseq). While RNAseq can be performed separately in the nucleus and in the cytosol, because measured transcript levels are relative to the total volume of RNA in these compartments, and because this volume is usually unknown, the transcript levels in the nucleus and in the cytosol cannot be directly compared. Here we show theoretically that if, in addition to nuclear and cytosolic RNA-seq, whole cell RNA-seq is also performed, then accurate estimations of the localization of transcripts can be obtained. Based on this, we designed a method that estimates, first the fraction of the total RNA volume in the cytosol (nucleus), and then, this fraction for every transcript. We evaluate our methodology on simulated data and nuclear and cytosolic single cell data available. Finally, we use our method to investigate the cellular localization of transcripts using bulk RNAseq data from the ENCODE project.

Fine-grained cell-type specific association studies with human bulk brain data using a large single-nucleus RNA sequencing based reference panel

Brain disorders are leading causes of disability worldwide. Gene expression studies provide promising opportunities to better understand their etiology but it is critical that expression is studied on a cell-type level. Cell-type specific association studies can be performed with bulk expression data using statistical methods that capitalize on cell-type proportions estimated with the help of a reference panel. To create a fine-grained reference panel for the human prefrontal cortex, we performed an integrated analysis of the seven largest single nucleus RNA-seq studies. Our panel included 17 cell-types that were robustly detected across all studies, subregions of the prefrontal cortex, and sex and age groups. To estimate the cell-type proportions, we used an empirical Bayes estimator that substantially outperformed three estimators recommended previously after a comprehensive evaluation of methods to estimate cell-type proportions from brain transcriptome data. This is important as being able to precisely estimate the cell-type proportions may avoid unreliable results in downstream analyses particularly for the multiple cell-types that had low abundances. Transcriptome-wide association studies performed with permuted bulk expression data showed that it is possible to perform transcriptome-wide association studies for even the rarest cell-types without an increased risk of false positives.

Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States

Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a singlecell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed singlecell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology.

Oligodendrocyte lineage cells: Advances in development, disease, and heterogeneity

Oligodendrocyte progenitor cells (OPCs) originate in the ventricular zone (VZ) of the brain and spinal cord, and their primary function is to differentiate into oligodendrocytes (OLs). Studies have shown that OPCs and OLs are pathologically and physiologically heterogeneous. Previous transcriptome analyses used Bulk RNA-seq, which compares average gene expression in cells and does not allow for heterogeneity. In recent years, the development of single-cell sequencing (scRNA-seq) and single-cell nuclear sequencing (snRNA-seq) has allowed us to study an individual cell. In this review, sc/snRNA-seq was used to study the different subpopulations of OL lineage cells, their developmental trajectories, and their applications in related diseases. These techniques can distinguish different subpopulations of cells, and identify differentially expressed genes in particular cell types under certain conditions, such as treatment or disease. It is of great significance to the study of the occurrence, prevention, and treatment of various diseases.

A SINC-Seq Protocol for the Analysis of Subcellular Gene Expression in Single Cells

Microfluidic devices offer precise control of single cells and molecules by liquid flows, downsizing tools to allow us to perform single-cell assays at unprecedented resolutions and minimizing contamination. In this chapter, we introduce an approach, called single-cell integrated nuclear and cytoplasmic RNA-sequencing (SINC-seq), which enables precise fractionation of cytoplasmic and nuclear RNA of single cells. This approach uses electric field control in microfluidics to manipulate single cells and RNA sequencing to dissect gene expression and RNA localization in subcellular compartments. The microfluidic system for SINC-seq exploits a hydrodynamic trap (a constriction in a microchannel) to isolate a single cell, selectively lyses its plasma membrane via a focused electric field, and retains the nucleus at the hydrodynamic trap during the electrophoretic extraction of cytoplasmic RNA. Here, we provide a step-by-step protocol from microfluidic RNA fractionation to off-chip preparation of RNA-sequencing libraries for full-length cDNA sequencing using both a short-read sequencer (Illumina) and a long-read sequencer (Oxford Nanopore Technologies).

Recent Advances in Microscale Electroporation

Electroporation (EP) is a commonly used strategy to increase cell permeability for intracellular cargo delivery or irreversible cell membrane disruption using electric fields. In recent years, EP performance has been improved by shrinking electrodes and device structures to the microscale. Integration with microfluidics has led to the design of devices performing static EP, where cells are fixed in a defined region, or continuous EP, where cells constantly pass through the device. Each device type performs superior to conventional, macroscale EP devices while providing additional advantages in precision manipulation (static EP) and increased throughput (continuous EP). Microscale EP is gentle on cells and has enabled more sensitive assaying of cells with novel applications. In this Review, we present the physical principles of microscale EP devices and examine design trends in recent years. In addition, we discuss the use of reversible and irreversible EP in the development of therapeutics and analysis of intracellular contents, among other noteworthy applications. This Review aims to inform and encourage scientists and engineers to expand the use of efficient and versatile microscale EP technologies.

Frontiers in single cell analysis: multimodal technologies and their clinical perspectives

Single cell multimodal analysis is at the frontier of single cell research: it defines the roles and functions of distinct cell types through simultaneous analysis to provide unprecedented insight into cellular processes. Current single cell approaches are rapidly moving toward multimodal characterizations. It replaces one-dimensional single cell analysis, for example by allowing for simultaneous measurement of transcription and post-transcriptional regulation, epigenetic modifications and/or surface protein expression. By providing deeper insights into single cell processes, multimodal single cell analyses paves the way to new understandings in various cellular processes such as cell fate decisions, physiological heterogeneity or genotype-phenotype linkages. At the forefront of this, microfluidics is key for high-throughput single cell analysis. Here, we present an overview of the recent multimodal microfluidic platforms having a potential in biomedical research, with a specific focus on their potential clinical applications.

Isotachophoresis: Theory and Microfluidic Applications

Isotachophoresis (ITP) is a versatile electrophoretic technique that can be used for sample preconcentration, separation, purification, and mixing, and to control and accelerate chemical reactions. Although the basic technique is nearly a century old and widely used, there is a persistent need for an easily approachable, succinct, and rigorous review of ITP theory and analysis. This is important because the interest and adoption of the technique has grown over the last two decades, especially with its implementation in microfluidics and integration with on-chip chemical and biochemical assays. We here provide a review of ITP theory starting from physicochemical first-principles, including conservation of species, conservation of current, approximation of charge neutrality, pH equilibrium of weak electrolytes, and so-called regulating functions that govern transport dynamics, with a strong emphasis on steady and unsteady transport. We combine these generally applicable (to all types of ITP) theoretical discussions with applications of ITP in the field of microfluidic systems, particularly on-chip biochemical analyses. Our discussion includes principles that govern the ITP focusing of weak and strong electrolytes; ITP dynamics in peak and plateau modes; a review of simulation tools, experimental tools, and detection methods; applications of ITP for on-chip separations and trace analyte manipulation; and design considerations and challenges for microfluidic ITP systems. We conclude with remarks on possible future research directions. The intent of this review is to help make ITP analysis and design principles more accessible to the scientific and engineering communities and to provide a rigorous basis for the increased adoption of ITP in microfluidics.

Gut mucosa dissociation protocols influence cell type proportions and single-cell gene expression levels

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of the cellular landscape of organs. Most single-cell protocols require fresh material, which limits sample size per experiment, and consequently, introduces batch effects. This is especially true for samples acquired through complex medical procedures, such as intestinal mucosal biopsies. Moreover, the tissue dissociation procedure required for obtaining single cells is a major source of noise; different dissociation procedures applied to different compartments of the tissue induce artificial gene expression differences between cell subsets. To overcome these challenges, we have developed a one-step dissociation protocol and demonstrated its use on cryopreserved gut mucosal biopsies. Using flow cytometry and scRNA-seq analysis, we compared this one-step dissociation protocol with the current gold standard, two-step collagenase digestion, and an adaptation of a recently published alternative, three-step cold-active Bacillus licheniformus protease digestion. Both cell viability and cell type composition were comparable between the one-step and two-step collagenase dissociation, with the former being more time-efficient. The cold protease digestion resulted in equal cell viability, but better preserves the epithelial cell types. Consequently, to analyze the rarer cell types, such as glial cells, larger total biopsy cell numbers are required as input material. The multi-step protocols affected cell types spanning multiple compartments differently. In summary, we show that cryopreserved gut mucosal biopsies can be used to overcome the logistical challenges and batch effects in large scRNA-seq studies. Furthermore, we demonstrate that using cryopreserved biopsies digested using a one-step collagenase protocol enables large-scale scRNA-seq, FACS, organoid generation and intraepithelial lymphocyte expansion.

Single-cell RNA-seq and its Applications in the Study of Psychiatric Disorders

Neuroscience is currently one of the most challenging research fields owing to the enormous complexity of the mammalian nervous system. We are yet to understand precise transcriptional programs that govern cell fate during neurodevelopment, resolve the connectome of the mammalian brain, and determine the etiology of various neurodegenerative and psychiatric disorders. Technological advances in the past decade, notably single-cell RNA sequencing, have enabled huge progress in our understanding of such features. Our current knowledge of the transcriptome is largely derived from bulk RNA sequencing, which reveals only the average gene expression of millions of cells, potentially missing out on minor transcriptome differences between cells detectable only at single-cell resolution. Since 2009, several single-cell RNA sequencing techniques have emerged that enable the accurate classification of neuronal and glial cell subtypes beyond classical molecular markers and electrophysiological features and allow the identification of previously unknown cell types. Furthermore, it enables the interrogation of molecular and disease-relevant mechanisms and offers further possibilities for the discovery of new drug targets and disease biomarkers. This review intends to familiarize the reader with the main single-cell RNA sequencing techniques developed throughout the past decade and discusses their application in the fields of brain cell taxonomy, neurodevelopment, and psychiatric disorders.

SUBCELLULAR TRANSCRIPTOMICS & PROTEOMICS: A COMPARATIVE METHODS REVIEW

The internal environment of cells is molecularly crowded, which requires spatial organization via subcellular compartmentalization. These compartments harbor specific conditions for molecules to perform their biological functions, such as coordination of the cell cycle, cell survival, and growth. This compartmentalization is also not static, with molecules trafficking between these subcellular neighborhoods to carry out their functions. For example, some biomolecules are multifunctional, requiring an environment with differing conditions or interacting partners, and others traffic to export such molecules. Aberrant localization of proteins or RNA species has been linked to many pathological conditions, such as neurological, cancer, and pulmonary diseases. Differential expression studies in transcriptomics and proteomics are relatively common, but the majority have overlooked the importance of subcellular information. In addition, subcellular transcriptomics and proteomics data do not always colocate because of the biochemical processes that occur during and after translation, highlighting the complementary nature of these fields. In this review, we discuss and directly compare the current methods in spatial proteomics and transcriptomics, which include sequencing- and imaging-based strategies, to give the reader an overview of the current tools available. We also discuss current limitations of these strategies as well as future developments in the field of spatial -omics.

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Subcellular information of protein and RNA give insights into molecular function.

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This review discusses strategies available to measure subcellular information.

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Hybridization of methods shows promise for exploring the composition of organelles.

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Advances are aiding understanding of the organisation and dynamics of cells.

Application of RNA subcellular fraction estimation method to explore RNA localization regulation

RNA localization is involved in multiple biological processes. Recent advances in subcellular fractionation based sequencing approaches uncovered localization pattern on a global scale. Most of existing methods adopt relative localization ratios (such as ratios of separately normalized TPMs of different subcellular fractions without considering the difference in total RNA abundances in different fractions), however, absolute ratios may yield different results on the preference to different cellular compartment. Experimentally, adding external Spike-in RNAs to different fractionation can be used to obtain absolute ratios. In addition, a spike-in independent computational approach based on multiple linear regression model can also be used. However, currently no custom tool is available. To solve this problem, we developed a method called Subcellular Fraction Abundance Estimator (SFAE) to correctly estimate relative RNA abundances of different subcellular fractionations. The ratios estimated by our method were consistent with existing reports. By applying the estimated ratios for different fractions, we explored the RNA localization pattern in cell lines and also predicted RBP motifs that were associated with different localization patterns. In addition, we showed that different isoforms of same genes could exhibit distinct localization patterns. To conclude, we believed our tool will facilitate future subcellular fractionation related sequencing study to explore the function of RNA localization in various biological problems.

Refining the Molecular Framework for Pancreatic Cancer with Single-cell and Spatial Technologies

Pancreatic ductal adenocarcinoma (PDAC) is a treatment-refractory malignancy in urgent need of a molecular framework for guiding therapeutic strategies. Bulk transcriptomic efforts over the past decade have yielded two broad consensus subtypes: classical pancreatic/epithelial versus basal-like/squamous/quasi-mesenchymal. Although this binary classification enables prognostic stratification, it does not currently inform the administration of treatments uniquely sensitive to either subtype. Furthermore, bulk mRNA studies are challenged by distinguishing contributions from the neoplastic compartment versus other cell types in the microenvironment, which is accentuated in PDAC given that neoplastic cellularity can be low. The application of single-cell transcriptomics to pancreatic tumors has generally lagged behind other cancer types due in part to the difficulty of extracting high-quality RNA from enzymatically degradative tissue, but emerging studies have and will continue to shed light on intratumoral heterogeneity, malignant-stromal interactions, and subtle transcriptional programs previously obscured at the bulk level. In conjunction with insights provided by single-cell/nucleus dissociative techniques, spatially resolved technologies should also facilitate the contextualization of gene programs and inferred cell-cell interactions within the tumor architecture. Finally, given that patients often receive neoadjuvant chemotherapy and/or chemoradiotherapy even in resectable disease, deciphering the gene programs enriched in or induced by cytotoxic therapy will be crucial for developing insights into complementary treatments aimed at eradicating residual cancer cells. Taken together, single-cell and spatial technologies provide an unprecedented opportunity to refine the foundations laid by prior bulk molecular studies and significantly augment precision oncology efforts in pancreatic cancer.

Single-nucleus RNA-seq2 reveals functional crosstalk between liver zonation and ploidy

Single-cell RNA-seq reveals the role of pathogenic cell populations in development and progression of chronic diseases. In order to expand our knowledge on cellular heterogeneity, we have developed a single-nucleus RNA-seq2 method tailored for the comprehensive analysis of the nuclear transcriptome from frozen tissues, allowing the dissection of all cell types present in the liver, regardless of cell size or cellular fragility. We use this approach to characterize the transcriptional profile of individual hepatocytes with different levels of ploidy, and have discovered that ploidy states are associated with different metabolic potential, and gene expression in tetraploid mononucleated hepatocytes is conditioned by their position within the hepatic lobule. Our work reveals a remarkable crosstalk between gene dosage and spatial distribution of hepatocytes.

Multimodal detection of protein isoforms and nucleic acids from low starting cell numbers

Protein isoforms play a key role in disease progression and arise from mechanisms involving multiple molecular subtypes, including DNA, mRNA and protein. Recently introduced multimodal assays successfully link genomes and transcriptomes to protein expression landscapes. However, the specificity of the protein measurement relies on antibodies alone, leading to major challenges when measuring different isoforms of the same protein. Here we utilize microfluidic design to perform same-cell profiling of DNA, mRNA and protein isoforms (triBlot) on low starting cell numbers (1-100 s of cells). After fractionation lysis, cytoplasmic proteins are resolved by molecular mass during polyacrylamide gel electrophoresis (PAGE), adding a degree of specificity to the protein measurement, while nuclei are excised from the device in sections termed "gel pallets" for subsequent off-chip nucleic acid analysis. By assaying TurboGFP-transduced glioblastoma cells, we observe a strong correlation between protein expression prior to lysis and immunoprobed protein. We measure both mRNA and DNA from retrieved nuclei, and find that mRNA levels correlate with protein abundance in TurboGFP-expressing cells. Furthermore, we detect the presence of TurboGFP isoforms differing by an estimated <1 kDa in molecular mass, demonstrating the ability to discern different proteoforms with the same antibody probe. By directly relating nucleic acid modifications to protein isoform expression in 1-100 s of cells, the triBlot assay holds potential as a screening tool for novel biomarkers in diseases driven by protein isoform expression.

Noncontact Multiphysics Probe for Spatiotemporal Resolved Single-Cell Manipulation and Analyses

Heterogeneity and spatial arrangement of individual cells within tissues are critical to the identity of the host multicellular organism. While current single-cell techniques are capable of resolving heterogeneity, they mostly rely on extracting target cells from their physiological environment and hence lose the spatiotemporal resolution required for understanding cellular networks. Here, a multifunctional noncontact scanning probe that can precisely perform multiple manipulation procedures on living single-cells, while within their physiological tissue environment, is demonstrated. The noncontact multiphysics probe (NMP) consists of fluidic apertures and "hump" shaped electrodes that simultaneously confine reagents and electric signals with a single-cell resolution. The NMP's unique electropermealization-based approach in transferring macromolecules through the cell membrane is presented. The technology's adjustable spatial ability is demonstrated by transfecting adjacent single-cells with different DNA plasmid vectors. The NMP technology also opens the door for controllable cytoplasm extraction from living single-cells. This powerful application is demonstrated by executing multiple time point biopsies on adherent cells without affecting the integrity of the extracted macromolecules or the viability of cells. Furthermore, the NMP's function as an electro-thermal based microfluidic whole-cell tweezer is reported. This work offers a multifunctional tool with unprecedented probing features for spatiotemporal single-cell analysis within tissue samples.

Tissue-specific transcriptome profiling of the Arabidopsis inflorescence stem reveals local cellular signatures

Genome-wide gene expression maps with a high spatial resolution have substantially accelerated plant molecular science. However, the number of characterized tissues and growth stages is still small due to the limited accessibility of most tissues for protoplast isolation. Here, we provide gene expression profiles of the mature inflorescence stem of Arabidopsis thaliana covering a comprehensive set of distinct tissues. By combining fluorescence-activated nucleus sorting and laser-capture microdissection with next-generation RNA sequencing, we characterized the transcriptomes of xylem vessels, fibers, the proximal and distal cambium, phloem, phloem cap, pith, starch sheath, and epidermis cells. Our analyses classified more than 15,000 genes as being differentially expressed among different stem tissues and revealed known and novel tissue-specific cellular signatures. By determining overrepresented transcription factor binding regions in the promoters of differentially expressed genes, we identified candidate tissue-specific transcriptional regulators. Our datasets predict the expression profiles of an exceptional number of genes and allow hypotheses to be generated about the spatial organization of physiological processes. Moreover, we demonstrate that information about gene expression in a broad range of mature plant tissues can be established at high spatial resolution by nuclear mRNA profiling. Tissue-specific gene expression values can be accessed online at https://arabidopsis-stem.cos.uni-heidelberg.de/.

NanoSINC-seq dissects the isoform diversity in subcellular compartments of single cells

Alternative mRNA isoforms play a key role in generating diverse protein isoforms. To dissect isoform usage in the subcellular compartments of single cells, we introduced an novel approach, nanopore sequencing coupled with single-cell integrated nuclear and cytoplasmic RNA sequencing, that couples microfluidic fractionation, which separates cytoplasmic RNA from nuclear RNA, with full-length complementary DNA (cDNA) sequencing using a nanopore sequencer. Leveraging full-length cDNA reads, we found that the nuclear transcripts are notably more diverse than cytoplasmic transcripts. Our findings also indicated that transcriptional noise emanating from the nucleus is regulated across the nuclear membrane and then either attenuated or amplified in the cytoplasm depending on the function involved. Overall, our results provide the landscape that shows how the transcriptional noise arising from the nucleus propagates to the cytoplasm.

Targeted permeabilization of the cell wall and extraction of charged molecules from single cells in intact plant clusters using a focused electric field

The extraction of cellular contents from plant cells covered with cell walls remains a challenge, as it is physically hindered by the cell wall. We present a new microfluidic approach that leverages an intense pulsed electric field for permeabilizing the cell wall and a focused DC electric field for extracting the cellular contents selectively from a few targeted cells in a cluster of intact plant cells. We coupled the approach with on-chip fluorescence quantification of extracted molecules leveraging isotachophoresis as well as off-chip reverse transcription-quantitative polymerase chain reaction detecting extracted mRNA molecules. Our approach offers a workflow of about 5 min, isolating a cluster of intact plant cells, permeabilizing the cell wall, selectively extracting cytosolic molecules from a few targeted cells in the cluster, and outputting them to off-chip analyses without any enzymatic reactions. We anticipate that this approach will create a new opportunity to explore plant biology through less biased data realized by the rapid extraction of molecules from intact plant clusters.

Nanoplasmon-enhanced drop-screen for high throughput single-cell nucleocytoplasmic miRNA profiling

Cell nucleocytoplasmic profiles of microRNAs (miRNAs) are critical to determining a single cell's essential functionalities, such as cellular transcription, nucleus export and degradation, which gives a comprehensive view of cellular processes. Despite the importance of addressing nucleocytoplasmic heterogeneity, the challenge of high-throughput screening remains. Although a droplet-based approach was developed for single-cell miRNA assays, the challenge of quantifying miRNA with high sensitivity to indicate nucleocytoplasmic heterogeneity remains. In this study, a nanoplasmon-enhanced droplet screening platform was developed to quantify single-cell nucleocytoplasmic heterogeneity with the high sensitivity of 0.1 nM. Droplet screening and multiplexed plasmonic assays are synergistic: droplet screening is used to isolate single cells for high-throughput screening, while enhanced nanoplasmonic assays are conducted to precisely determine different types of miRNAs, addressing the cell nucleocytoplasmic profile. Here, two nucleic acid-functionalized plasmonic nanosensors, silver nanoparticles functionalized with designed sequences to target miRNAs, are synthesized. After the targets are bound, competitive formation of sensor-target hybrids interferes with plasmonic coupling between the nanoparticles, decreasing a fluorescence signal and thus enabling high-sensitivity single-cell miRNA quantification. Using the fluorescence signal change as a readout allows continuous-flow measurement to provide a single-cell nucleocytoplasmic profile in a high-throughput manner (∼100 cells per minute) for effective quantitative cell biology.

Single cell transcriptome profiling of the human alcohol-dependent brain

Alcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain. We utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16 000 nuclei isolated from the prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes and microglia. To our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species and the first such analysis in humans for any addictive substance. These findings greatly advance the understanding of transcriptomic changes in the brain of alcohol-dependent individuals.

Assessing heterogeneity among single embryos and single blastomeres using open microfluidic design

The process by which a zygote develops from a single cell into a multicellular organism is poorly understood. Advances are hindered by detection specificity and sensitivity limitations of single-cell protein tools and by challenges in integrating multimodal data. We introduce an open microfluidic tool expressly designed for same-cell phenotypic, protein, and mRNA profiling. We examine difficult-to-study-yet critically important-murine preimplantation embryo stages. In blastomeres dissociated from less well-studied two-cell embryos, we observe no significant GADD45a protein expression heterogeneity, apparent at the four-cell stage. In oocytes, we detect differences in full-length versus truncated DICER-1 mRNA and protein, which are insignificant by the two-cell stage. Single-embryo analyses reveal intraembryonic heterogeneity, differences between embryos of the same fertilization event and between donors, and reductions in the burden of animal sacrifice. Open microfluidic design integrates with existing workflows and opens new avenues for assessing the cellular-to-molecular heterogeneity inherent to preimplantation embryo development.

Distinct Kinetics in Electrophoretic Extraction of Cytoplasmic RNA from Single Cells

The physical fractionation of cytoplasmic versus nuclear components of cells is a key step for studying the subcellular localization of molecules. The application of an electric field is an emerging method for subcellular fractionation of proteins and nucleic acids from single cells. However, the multibiophysical process that involves electrical lysis of cytoplasmic membranes, electrophoresis, and diffusion of charged molecules remains unclear. Here we study RNA dynamics in single cells during the electrophoretic extraction via a microfluidic system that enables stringent fractionation of the subcellular components leveraging a focused electric field. We identified two distinct kinetics in the extraction of RNA molecules, which were respectively associated with soluble RNA and mitochondrial RNA. We show that the extraction kinetics of soluble RNA is dominated by electrophoresis over diffusion and has a time constant of 0.15 s. Interestingly, the extraction of mitochondrial RNA showed unexpected heterogeneity in the extraction with slower kinetics (3.8 s), while reproducibly resulting in the extraction of 98.9% ± 2% after 40 s. Together, we uncover that the microfluidic system uniquely offers length bias-free fractionation of RNA molecules for quantitative analysis of correlations among subcellular compartments by exploiting the homogeneous electrophoretic properties of RNA.

Informing disease modelling with brain-relevant functional genomic annotations

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two.

Electric and Electrochemical Microfluidic Devices for Cell Analysis

Microfluidic devices are widely used for cell analysis, including applications for single-cell analysis, healthcare, environmental monitoring, and organs-on-a-chip that mimic organs in microfluidics. Moreover, to enable high-throughput cell analysis, real-time monitoring, and non-invasive cell assays, electric and electrochemical systems have been incorporated into microfluidic devices. In this mini-review, we summarize recent advances in these systems, with applications from single cells to three-dimensional cultured cells and organs-on-a-chip. First, we summarize microfluidic devices combined with dielectrophoresis, electrophoresis, and electrowetting-on-a-dielectric for cell manipulation. Next, we review electric and electrochemical assays of cells to determine chemical section activity, and oxygen and glucose consumption activity, among other applications. In addition, we discuss recent devices designed for the electric and electrochemical collection of cell components from cells. Finally, we highlight the future directions of research in this field and their application prospects.

Enabling cell-type-specific behavioral epigenetics in Drosophila: a modified high-yield INTACT method reveals the impact of social environment on the epigenetic landscape in dopaminergic neurons

BACKGROUND

Epigenetic mechanisms play fundamental roles in brain function and behavior and stressors such as social isolation can alter animal behavior via epigenetic mechanisms. However, due to cellular heterogeneity, identifying cell-type-specific epigenetic changes in the brain is challenging. Here, we report the first use of a modified isolation of nuclei tagged in specific cell type (INTACT) method in behavioral epigenetics of Drosophila melanogaster, a method we call mini-INTACT.

RESULTS

Using ChIP-seq on mini-INTACT purified dopaminergic nuclei, we identified epigenetic signatures in socially isolated and socially enriched Drosophila males. Social experience altered the epigenetic landscape in clusters of genes involved in transcription and neural function. Some of these alterations could be predicted by expression changes of four transcription factors and the prevalence of their binding sites in several clusters. These transcription factors were previously identified as activity-regulated genes, and their knockdown in dopaminergic neurons reduced the effects of social experience on sleep.

CONCLUSIONS

Our work enables the use of Drosophila as a model for cell-type-specific behavioral epigenetics and establishes that social environment shifts the epigenetic landscape in dopaminergic neurons. Four activity-related transcription factors are required in dopaminergic neurons for the effects of social environment on sleep.

Electrical Lysis and RNA Extraction from Single Cells Fixed by Dithiobis(succinimidyl propionate)

We present a microfluidic method for electrical lysis and RNA extraction from single fixed cells leveraging reversible cross-linker dithiobis(succinimidyl propionate) (DSP). Our microfluidic system captures a single DSP-fixed cell at a hydrodynamic trap, reverse-cross-links the DSP molecules on a chip with dithiothreitol, lyses the plasma membrane via electrical field, and extracts cytoplasmic RNA with isotachophoresis-aided nucleic acids extraction. All of the on-chip processes complete in less than 5 min. We demonstrated the method using K562 leukemia cells and benchmarked the performance of RNA extraction with reverse transcription quantitative polymerase chain reaction. We also demonstrated the integration of our method with single-cell RNA sequencing.

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.

Blood Relatives: Splicing Mechanisms underlying Erythropoiesis in Health and Disease

During erythropoiesis, hematopoietic stem and progenitor cells transition to erythroblasts en route to terminal differentiation into enucleated red blood cells. Transcriptome-wide changes underlie distinct morphological and functional characteristics at each cell division during this process. Many studies of gene expression have historically been carried out in erythroblasts, and the biogenesis of β-globin mRNA—the most highly expressed transcript in erythroblasts—was the focus of many seminal studies on the mechanisms of pre-mRNA splicing. We now understand that pre-mRNA splicing plays an important role in shaping the transcriptome of developing erythroblasts. Recent advances have provided insight into the role of alternative splicing and intron retention as important regulatory mechanisms of erythropoiesis. However, dysregulation of splicing during erythropoiesis is also a cause of several hematological diseases, including β-thalassemia and myelodysplastic syndromes. With a growing understanding of the role that splicing plays in these diseases, we are well poised to develop gene-editing treatments. In this review, we focus on changes in the developing erythroblast transcriptome caused by alternative splicing, the molecular basis of splicing-related blood diseases, and therapeutic advances in disease treatment using CRISPR/Cas9 gene editing.

Genetic identification of brain cell types underlying schizophrenia

With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.