Technologies for Single-Cell Isolation

A precise microdissection strategy enabled spatial heterogeneity analysis on the targeted region of formalin-fixed paraffin-embedded tissues

In recent years, the development of spatial transcriptomic technologies has enabled us to gain an in-depth understanding of the spatial heterogeneity of gene expression in biological tissues. However, a simple and efficient tool is required to analyze multiple spatial targets, such as mRNAs, miRNAs, or genetic mutations, at high resolution in formalin-fixed paraffin-embedded (FFPE) tissue sections. In this study, we developed hydrogel pathological sectioning coupled with the previously reported Sampling Junior instrument (HPSJ) to assess the spatial heterogeneity of multiple targets in FFPE sections at a scale of 180 μm. The HPSJ platform was used to demonstrate the spatial heterogeneity of 9 ferroptosis-related genes (TFRC, NCOA4, FTH1, ACSL4, LPCAT3, ALOX12, SLC7A11, GLS2, and GPX4) and 2 miRNAs (miR-185-5p and miR522) in FFPE tissue samples from patients with triple-negative breast cancer (TNBC). The results validated the significant heterogeneity of ferroptosis-related mRNAs and miRNAs. In addition, HPSJ confirmed the spatial heterogeneity of the L858R mutation in 7 operation-sourced and 4 needle-biopsy-sourced FFPE samples from patients with lung adenocarcinoma (LUAD). The successful detection of clinical FFPE samples indicates that HPSJ is a precise, high-throughput, cost-effective, and universal platform for analyzing spatial heterogeneity, which is beneficial for elucidating the mechanisms underlying drug resistance and guiding the prescription of mutant-targeted drugs in patients with tumors.

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

Starting with screening strains to construct synthetic microbial communities (SynComs) for traditional food fermentation

With the elucidation of community structures and assembly mechanisms in various fermented foods, core communities that significantly influence or guide fermentation have been pinpointed and used for exogenous restructuring into synthetic microbial communities (SynComs). These SynComs simulate ecological systems or function as adjuncts or substitutes in starters, and their efficacy has been widely verified. However, screening and assembly are still the main limiting factors for implementing theoretic SynComs, as desired strains cannot be effectively obtained and integrated. To expand strain screening methods suitable for SynComs in food fermentation, this review summarizes the recent research trends in using SynComs to study community evolution or interaction and improve the quality of food fermentation, as well as the specific process of constructing synthetic communities. The potential for novel screening modalities based on genes, enzymes and metabolites in food microbial screening is discussed, along with the emphasis on strategies to optimize assembly for facilitating the development of synthetic communities.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Single-cell somatic copy number alteration profiling of vitreous humor seeds in retinoblastoma

BACKGROUND

Heterogeneity can impact biomarker identification. Thus, we investigated the somatic copy number alterations (SCNAs) of individual tumor cells in the vitreous humor of a retinoblastoma patient using single-cell whole-genome profiling and explored the genomic concordance among vitreous and aqueous humor, vitreous seeds, and tumor.

METHODS

Aqueous humor (AH), vitreous humor (VH), and tumor biopsy were obtained from an enucleated globe with retinoblastoma and vitreous seeding. Micromanipulation was used to manually isolate 39 live single tumor cells from vitreous seeds harvested from the VH. The SCNA profiles of these individual cells were generated via whole-genome sequencing and analyzed alongside profiles from the tumor mass and cell-free DNA (cfDNA) from AH and VH.

RESULTS

Heatmap of VH single-cell SCNA profiles demonstrates heterogeneity among individual vitreous seeds with one clearly dominant subclone (23 of 37 cells). The SCNA profiles from the cells in this subclone demonstrate an average concordance of 98% with cfDNA profiles from acellular AH and VH and with the tumor profile.

CONCLUSIONS

Our findings reveal some heterogeneity among single-cell SCNA profiles in individual VH seeds. Despite this heterogeneity, the dominant vitreous subclone exhibits extremely (>98%) high concordance with the SCNA profile from tumor and AH, suggesting AH cfDNA is representative of the dominant genomic subclone. This may facilitate tumoral biomarker identification via the AH. This preliminary work supports the potential of applying single-cell technology to VH seeds in retinoblastoma as a platform to study tumor subclones, which may provide insight into the genomic complexity of disease.

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

CellMag-CARWash: A High Throughput Droplet Microfluidic Device for Live Cell Isolation and Single Cell Applications

The recent push toward understanding an individual cell's behavior and identifying cellular heterogeneity has created an unmet need for technologies that can probe live cells at the single-cell level. Cells within a population are known to exhibit heterogeneous responses to environmental cues. These differences can lead to varied cellular states, behavior, and responses to therapeutics. Techniques are needed that are not only capable of processing and analyzing cellular populations at the single cell level, but also have the ability to isolate specific cell populations from a complex sample at high throughputs. The new CellMag-Coalesce-Attract-Resegment Wash (CellMag-CARWash) system combines positive magnetic selection with droplet microfluidic devices to isolate cells of interest from a mixture with >93% purity and incorporate treatments within individual droplets to observe single cell biological responses. This workflow is shown to be capable of probing the single cell extracellular vesicle (EV) secretion of MCF7 GFP cells. This article reports the first measurement of β-Estradiol's effect on EV secretion from MCF7 cells at the single cell level. Single cell processing revealed that MCF7 GFP cells possess a heterogeneous response to β-Estradiol stimulation with a 1.8-fold increase relative to the control.

Single-Cell RNA Sequencing: Technological Progress and Biomedical Application in Cancer Research

Single-cell RNA-seq (scRNA-seq) is a revolutionary technology that allows for the genomic investigation of individual cells in a population, allowing for the discovery of unusual cells associated with cancer and metastasis. ScRNA-seq has been used to discover different types of cancers with poor prognosis and medication resistance such as lung cancer, breast cancer, ovarian cancer, and gastric cancer. Besides, scRNA-seq is a promising method that helps us comprehend the biological features and dynamics of cell development, as well as other disorders. This review gives a concise summary of current scRNA-seq technology. We also explain the main technological steps involved in implementing the technology. We highlight the present applications of scRNA-seq in cancer research, including tumor heterogeneity analysis in lung cancer, breast cancer, and ovarian cancer. In addition, this review elucidates potential applications of scRNA-seq in lineage tracing, personalized medicine, illness prediction, and disease diagnosis, which reveals that scRNA-seq facilitates these events by producing genetic variations on the single-cell level.

CRISPR-mediated editing of β-lactoglobulin (BLG) gene in buffalo

Milk is a good source of nutrition but is also a source of allergenic proteins such as α-lactalbumin, β-lactoglobulin (BLG), casein, and immunoglobulins. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas technology has the potential to edit any gene, including milk allergens. Previously, CRISPR/Cas has been successfully employed in dairy cows and goats, but buffaloes remain unexplored for any milk trait. In this study, we utilized the CRISPR/Cas9 system to edit the major milk allergen BLG gene in buffaloes. First, the editing efficiency of designed sgRNAs was tested in fibroblast cells using the T7E assay and Sanger sequencing. The most effective sgRNA was selected to generate clonal lines of BLG-edited cells. Analysis of 15 single-cell clones, through TA cloning and Sanger sequencing, revealed that 7 clones exhibited bi-allelic (-/-) heterozygous, bi-allelic (-/-) homozygous, and mono-allelic (-/+) disruptions in BLG. Bioinformatics prediction analysis confirmed that non-multiple-of-3 edited nucleotide cell clones have frame shifts and early truncation of BLG protein, while multiple-of-3 edited nucleotides resulted in slightly disoriented protein structures. Somatic cell nuclear transfer (SCNT) method was used to produce blastocyst-stage embryos that have similar developmental rates and quality with wild-type embryos. This study demonstrated the successful bi-allelic editing (-/-) of BLG in buffalo cells through CRISPR/Cas, followed by the production of BLG-edited blastocyst stage embryos using SCNT. With CRISPR and SCNT methods described herein, our long-term goal is to generate gene-edited buffaloes with BLG-free milk.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.

Time-resolved fluoroimmunoassay for Aspergillus detection based on anti-galactomannan monoclonal antibody from stable cell line

Invasive Aspergillosis is a high-risk illness with a high death rate in immunocompromised people due to a lack of early detection and timely treatment. Based on immunology study, we achieved an efficient production of anti-galactomannan antibody by Chinese hamster ovary (CHO) cells and applied it to time-resolved fluoroimmunoassay for Aspergillus galactomannan detection. We first introduced dual promoter expression vector into CHO host cells, and then applied a two-step screening strategy to screen the stable cell line by methionine sulfoximine pressurization. After amplification and fermentation, antibody yield reached 4500 mg/L. Then we conjugated the antibodies with fluorescent microspheres to establish a double antibody sandwich time-resolved fluoroimmunoassay, which was compared with the commercial Platelia™ Aspergillus Ag by clinical serum samples. The preformed assay could obtain the results in less than 25 min, with a limit of detection for galactomannan of approximately 1 ng/mL. Clinical results of the two methods showed that the overall percent agreement was 97.7% (95% CI: 96.6%-98.4%) and Cohen's kappa coefficient was 0.94. Overall, the assay is highly consistent with commercial detection, providing a more sensitive and effective method for the rapid diagnosis of invasive aspergillosis.

Atomic Force Microscopy for the Study of Cell Mechanics in Pharmaceutics

Cell mechanics is gaining attraction in drug screening, but the applicable methods have not yet become part of the standardized norm. This review presents the current state of the art for atomic force microscopy, which is the most widely available method. The field is first motivated as a new way of tracking pharmaceutical effects, followed by a basic introduction targeted at pharmacists on how to measure cellular stiffness. The review then moves on to the current state of the knowledge in terms of experimental results and supplementary methods such as fluorescence microscopy that can give relevant additional information. Finally, rheological approaches as well as the theoretical interpretations are presented before ending on additional methods and outlooks.

Live cell pool and rare cell isolation using Enrich TROVO system

Although several technologies have been developed to isolate cells of interest from a heterogenous sample, clogging and impaired cell viability limit such isolation. We have developed the Enrich TROVO system as a novel, nonfluidic technology to sort live cells. The TROVO system combines imaging-based cell selection and photo-crosslinking of (gelatin methacrylate) gelMA-hydrogel to capture cells. After capture, cells are released by enzymatic digestion of the hydrogel and then retrieved for downstream analysis or further cell culturing. The system can capture cells with a recovery rate of 48% while maintaining 90% viability. Moreover, TROVO can enrich rare cells 506-fold with 93% efficiency using single step isolation from a 1:104 cell mixture, and can also capture one target cell from 1 million cells, reaching an enrichment ratio of 9128. In addition, 100% purity and 49% recovery rate can be achieved by a following negative isolation process. Compared to existing technologies, the TROVO system is clog-resistant, highly biocompatible, and can process a wide range of sample sizes.

Advances in long-read single-cell transcriptomics

Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.

The isolation strategy and chemical analysis of oil cells from Asari Radix et Rhizoma

BACKGROUND

Single-cell analysis, a rapidly evolving field, encounters significant challenges in detecting individual cells within complex plant tissues, particularly oil cells (OCs). The intricate process of single-cell isolation, coupled with the inherent chemical volatility of oil cells, necessitates a comprehensive methodology.

RESULTS

This study presents a method for obtaining intact OC from Asari Radix et Rhizoma (ARR), a traditional herbal medicine. The developed approach facilitates both qualitative and quantitative analysis of diverse OCs. To determine the most reliable approach, four practical methods-laser capture microdissection, micromanipulation capturing, micromanipulation piping, and cell picking-were systematically compared and evaluated, unequivocally establishing cell picking as the most effective method for OC isolation and chemical analysis. Microscopic observations showed that OCs predominantly distribute in the cortex of adventitious and fibrous roots, as well as the pith and cortex of the rhizome, with distinct morphologies-oblong in roots and circular in rhizomes. Sixty-three volatile constituents were identified in OCs, with eighteen compounds exhibiting significant differences. Safrole, methyleugenol, and asaricin emerged as the most abundant constituents in OCs. Notably, cis-4-thujanol and tetramethylpyrazine were exclusive to rhizome OCs, while isoeugenol methyl ether was specific to fibrous root OCs based on the detections. ARR roots and rhizomes displayed marked disparities in OC distribution, morphology, and constituents.

CONCLUSION

The study highlights the efficacy of cell picking coupled with HS-SPME-GC-MS as a flexible, reliable, and sensitive method for OC isolation and chemical analysis, providing a robust methodology for future endeavors in single-cell analyses.

Heterogeneity and molecular landscape of melanoma: implications for targeted therapy

Uveal cancer (UM) offers a complex molecular landscape characterized by substantial heterogeneity, both on the genetic and epigenetic levels. This heterogeneity plays a critical position in shaping the behavior and response to therapy for this uncommon ocular malignancy. Targeted treatments with gene-specific therapeutic molecules may prove useful in overcoming radiation resistance, however, the diverse molecular makeups of UM call for a patient-specific approach in therapy procedures. We need to understand the intricate molecular landscape of UM to develop targeted treatments customized to each patient's specific genetic mutations. One of the promising approaches is using liquid biopsies, such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA), for detecting and monitoring the disease at the early stages. These non-invasive methods can help us identify the most effective treatment strategies for each patient. Single-cellular is a brand-new analysis platform that gives treasured insights into diagnosis, prognosis, and remedy. The incorporation of this data with known clinical and genomics information will give a better understanding of the complicated molecular mechanisms that UM diseases exploit. In this review, we focused on the heterogeneity and molecular panorama of UM, and to achieve this goal, the authors conducted an exhaustive literature evaluation spanning 1998 to 2023, using keywords like "uveal melanoma, "heterogeneity". "Targeted therapies"," "CTCs," and "single-cellular analysis".

DEPArray™ single-cell technology: A validation study for forensic applications

In forensics investigations, it is common to encounter biological mixtures consisting of homogeneous or heterogeneous components from multiple individuals and with different genetic contributions. One promising mixture deconvolution strategy is the DEPArray™ technology, which enables the separation of cell populations before genetic analysis. While technological advances are fundamental, their reliable validation is crucial for successful implementation and use for casework. Thus, this study aimed to 1) systematically validate the DEPArray™ system concerning specificity, sensitivity, repeatability, and contamination occurrences for blood, epithelial, and sperm cells, and 2) evaluate its potential for single-cell analysis in the field of forensic science. Our findings confirmed the effective identification of different cell types and the correct assignment of successfully genotyped single cells to their respective donor(s). Using the NGM Detect™ Amplification Kit, the average profile completeness for diploid cells was approximately 80%, with ∼ 290 RFUs. In contrast, haploid sperm analysis yielded an average completeness of 51% referring to the haploid reference profile, accompanied by mean peak heights of ∼ 176 RFUs. Although certain alleles of heterozygous loci in diploid cells showed strong imbalances, the overall peak balances yielded acceptable values above ≥ 60% with a mean value of 72% ± 0.21, a median of 77%, but with a maximum imbalance of 9% between heterozygous peaks. Locus dropouts were considered stochastic events, exhibiting variations among donors and cell types, with a notable failure incidence observed for TH01. Within the wet-lab experimentation with >500 single cells for the validation, profiling was performed using the consensus approach, where profiles were selected randomly from all data to better mirror real casework results. Nevertheless, complete profiles could be achieved with as few as three diploid cells, while the average success rate increased to 100% when using profiles of 6-10 cells. For sperms, however, a consensus profile with completeness >90% of the autosomal diploid genotype could be attained using ≥15 cells. In addition, the robustness of the consensus approach was evaluated in the absence of the respective reference profile without severe deterioration. Here, increased stutter peaks (≥ 15%) were found as the main artifact in single-cell profiles, while contamination and drop-ins were ascertained as rare events. Lastly, the technique's potential and limitations are discussed, and practical guidance is provided, particularly valuable for cold cases, multiple perpetrator rapes, and analyses of homogeneous mixed evidence.

Single-cell transcriptomics: background, technologies, applications, and challenges

Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.

Precision isolation and cultivation of single cells by vortex and flat-top laser ejection

Single-cell isolation stands as a critical step in single-cell studies, and single-cell ejection technology based on laser induced forward transfer technology (LIFT) is considered one of the most promising methods in this regard for its ability of visible isolating single cell from complex samples. In this study, we improve the LIFT technology and introduce optical vortex laser-induced forward transfer (OV-LIFT) and flat-top laser-induced forward transfer (FT-LIFT) by utilizing spatial light modulator (SLM), aiming to enhance the precision of single-cell sorting and the cell's viability after ejection. Experimental results demonstrate that applying vortex and flat-top beams during the sorting and collection process enables precise retrieval of single cells within diameter ranges of 50 μm and 100 μm, respectively. The recovery rates of Saccharomyces cerevisiae and Escherichia coli DH5α single cell ejected by vortex beam are 89 and 78%, by flat-top beam are 85 and 57%. When employing Gaussian beam sorting, the receiving range extends to 400 μm, with cultivation success rates of S. cerevisiae and E. coli DH5α single cell are 48 and 19%, respectively. This marks the first application of different mode beams in the ejection and cultivation of single cells, providing a novel and effective approach for the precise isolation and improving the viability of single cells.

An open-source FACS automation system for high-throughput cell biology

Recent advances in gene editing are enabling the engineering of cells with an unprecedented level of scale. To capitalize on this opportunity, new methods are needed to accelerate the different steps required to manufacture and handle engineered cells. Here, we describe the development of an integrated software and hardware platform to automate Fluorescence-Activated Cell Sorting (FACS), a central step for the selection of cells displaying desired molecular attributes. Sorting large numbers of samples is laborious, and, to date, no automated system exists to sequentially manage FACS samples, likely owing to the need to tailor sorting conditions ("gating") to each individual sample. Our platform is built around a commercial instrument and integrates the handling and transfer of samples to and from the instrument, autonomous control of the instrument's software, and the algorithmic generation of sorting gates, resulting in walkaway functionality. Automation eliminates operator errors, standardizes gating conditions by eliminating operator-to-operator variations, and reduces hands-on labor by 93%. Moreover, our strategy for automating the operation of a commercial instrument control software in the absence of an Application Program Interface (API) exemplifies a universal solution for other instruments that lack an API. Our software and hardware designs are fully open-source and include step-by-step build documentation to contribute to a growing open ecosystem of tools for high-throughput cell biology.

A single-cell genomic strategy for alternative transcript start sites identification

Alternative transcription start sites (TSSs) usage plays a critical role in gene transcription regulation in mammals. However, precisely identifying alternative TSSs remains challenging at the genome-wide level. We report a single-cell genomic technology for alternative TSSs annotation and cell heterogeneity detection. In the method, we utilize Fluidigm C1 system to capture individual cells of interest, SMARTer cDNA synthesis kit to recover full-length cDNAs, then dual priming oligonucleotide system to specifically enrich TSSs for genomic analysis. We apply this method to a genome-wide study of alternative TSSs identification in two different IFN-β stimulated mouse embryonic fibroblasts (MEFs). The data clearly discriminate two IFN-β stimulated MEFs. Moreover, our results indicate 81% expressed genes in these two cell types containing multiple TSSs, which is much higher than previous predictions based on Cap-Analysis Gene Expression (CAGE) (58%) or empirical determination (54%) in various cell types. This indicates that alternative TSSs are more pervasive than expected and implies our strategy could position them at an unprecedented sensitivity. It would be helpful for elucidating their biological insights in future.

Application of Single Cell Gene Expression Technologies to Neurotoxicology

Neurotoxicological research faces the challenge of linking biological changes resulting from exposures to neuronal function. An additional challenge is understanding cell-type specific differences and selective vulnerabilities of distinct neuronal populations to toxic insults. Single cell RNA-sequencing (scRNA-seq) allows for measurement of the transcriptome of individual cells. This makes it a valuable tool for validating and characterizing cell types present in multicell type samples in complex tissue or cell culture models, but also for understanding how different cell types respond to toxic insults. Pathway analysis of differentially expressed genes can provide in depth insights into underlying cell type-specific mechanisms of neurotoxicity. Toxicological data often has to be translated to outcomes for human health which requires an understanding of inter-species differences. Transcriptomic data aids in understanding these differences, including understanding developmental timelines of different species. We believe that scRNA-seq holds exciting promises for future neurotoxicological research.

Mild Quantitative One Step Removal of Macrophages from Cocultures with Human Umbilical Vein Endothelial Cells Using Thermoresponsive Poly(Di(Ethylene Glycol)Methyl Ether Methacrylate) Brushes

The authors report on a mild, label-free, and fast method for the separation of human umbilical vein endothelial cells (HUVEC), which are relevant cells, whose use is not limited to studies of endothelial dysfunction, from cocultures with macrophages to afford HUVEC in ≈100% purity. Poly(di(ethylene glycol)methyl ether methacrylate) (PDEGMA) brushes with a dry thickness of (5 ± 1) nm afford the highly effective one-step separation by selective HUVEC detachment, which is based on the brushes' thermoresponsive behavior. Below the thermal transition at 32 °C the brushes swells and desorbs attached proteins, resulting in markedly decreased cell adhesion. Specifically, HUVEC and macrophages, which are differentiated from THP-1 monocytes, are seeded and attached to PDEGMA brushes at 37°C. After decreasing the temperature to 22°C, HUVEC shows a decrease in their cell area, while the macrophages are not markedly affected by the temperature change. After mild flushing with a cell culture medium, the HUVEC can be released from the surface and reseeded again with ≈100% purity on a new surface. With this selective cell separation and removal method, it is possible to separate and thereby purify HUVEC from macrophages without the use of any releasing reagent or expensive labels, such as antibodies.

Advances in the Application of Single-Cell Transcriptomics in Plant Systems and Synthetic Biology

Plants are complex systems hierarchically organized and composed of various cell types. To understand the molecular underpinnings of complex plant systems, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for revealing high resolution of gene expression patterns at the cellular level and investigating the cell-type heterogeneity. Furthermore, scRNA-seq analysis of plant biosystems has great potential for generating new knowledge to inform plant biosystems design and synthetic biology, which aims to modify plants genetically/epigenetically through genome editing, engineering, or re-writing based on rational design for increasing crop yield and quality, promoting the bioeconomy and enhancing environmental sustainability. In particular, data from scRNA-seq studies can be utilized to facilitate the development of high-precision Build-Design-Test-Learn capabilities for maximizing the targeted performance of engineered plant biosystems while minimizing unintended side effects. To date, scRNA-seq has been demonstrated in a limited number of plant species, including model plants (e.g., Arabidopsis thaliana), agricultural crops (e.g., Oryza sativa), and bioenergy crops (e.g., Populus spp.). It is expected that future technical advancements will reduce the cost of scRNA-seq and consequently accelerate the application of this emerging technology in plants. In this review, we summarize current technical advancements in plant scRNA-seq, including sample preparation, sequencing, and data analysis, to provide guidance on how to choose the appropriate scRNA-seq methods for different types of plant samples. We then highlight various applications of scRNA-seq in both plant systems biology and plant synthetic biology research. Finally, we discuss the challenges and opportunities for the application of scRNA-seq in plants.

A bioorthogonal cell sorting strategy for isolation of desired cell phenotypes

Here we describe a cost-effective and simplified cell sorting method using tetrazine bioorthogonal chemistry. We successfully isolated SKOV3 cells from complex mixtures, demonstrating efficacy in separating mouse lymphocytes expressing interferon and HeLa cells expressing virally transduced green fluorescent protein post-infection.

Clonally derived chicken primordial germ cell lines maintain biological characteristics and proliferative potential in long-term culture

Chicken primordial germ cells (PGCs) are important cells with significant implications in preserving genetic resources, chicken breeding and production, and basic research on genetics and development. Currently, chicken PGCs can be cultured long-term in vitro to produce single-cell clones. However, systematic exploration of the cellular characteristics of these single-cell clonal lines has yet to be conducted. In this study, single-cell clonal lines were established from male and female PGCs of Rugao Yellow Chicken and Shouguang Black Chicken, respectively, using a micropipette-based method for single-cell isolation and culture. Analysis of glycogen granule staining, mRNA expression of pluripotency marker genes (POUV, SOX2, NANOG), germ cell marker genes (DAZL, CVH), and SSEA-1, EMA-1, SOX2, C-KIT, and CVH protein expression showed positive results, indicating that PGCs maintain normal cellular properties after single-cell cloning. Furthermore, tests on proliferation ability and gene expression levels in PGC single-cell clonal lines showed high expression of the pluripotency-related genes and TERT compared to control PGCs, and PGC single-cell clonal lines demonstrated higher proliferation ability. Finally, green fluorescent protein (GFP)-PGC single-cell clonal lines were established, and it was found that these single-cell clonal lines could still migrate into the gonads of recipients, suggesting their potential for germ-line transmission. This study systematically validated the normal cellular characteristics of PGC single-cell clonal lines, indicating that they could be applied in genetic modification research on chickens.

Digital PCR for Single-Cell Analysis

Single-cell analysis provides an overwhelming strategy for revealing cellular heterogeneity and new perspectives for understanding the biological function and disease mechanism. Moreover, it promotes the basic and clinical research in many fields at a single-cell resolution. A digital polymerase chain reaction (dPCR) is an absolute quantitative analysis technology with high sensitivity and precision for DNA/RNA or protein. With the development of microfluidic technology, digital PCR has been used to achieve absolute quantification of single-cell gene expression and single-cell proteins. For single-cell specific-gene or -protein detection, digital PCR has shown great advantages. So, this review will introduce the significance and process of single-cell analysis, including single-cell isolation, single-cell lysis, and single-cell detection methods, mainly focusing on the microfluidic single-cell digital PCR technology and its biological application at a single-cell level. The challenges and opportunities for the development of single-cell digital PCR are also discussed.

Haemato-Immunological Response of Immunized Atlantic Salmon (Salmo salar) to Moritella viscosa Challenge and Antigens

Winter ulcer disease is a health issue in the Atlantic salmonid aquaculture industry, mainly caused by Moritella viscosa. Although vaccination is one of the effective ways to prevent bacterial outbreaks in the salmon farming industry, ulcer disease related to bacterial infections is being reported on Canada's Atlantic coast. Here, we studied the immune response of farmed immunized Atlantic salmon to bath and intraperitoneal (ip) M. viscosa challenges and evaluated the immunogenicity of M. viscosa cell components. IgM titers were determined after infection, post boost immunization, and post challenge with M. viscosa. IgM+ (B cell) in the spleen and blood cell populations were also identified and quantified by 3,3 dihexyloxacarbocyanine (DiOC6) and IgM-Texas red using confocal microscopy and flow cytometry. At 14 days post challenge, IgM was detected in the serum and spleen. There was a significant increase in circulating neutrophils 3 days after ip and bath challenges in the M. viscosa outer membrane vesicles (OMVs) boosted group compared to non-boosted. Lymphocytes increased in the blood at 7 and 14 days after the ip and bath challenges, respectively, in OMVs boosted group. Furthermore, a rise in IgM titers was detected in the OMVs boosted group. We determined that a commercial vaccine is effective against M. viscosa strain, and OMVs are the most immunogenic component of M. viscosa cells.

Unravelling the enigma of the human microbiome: Evolution and selection of sequencing technologies

The human microbiome plays a crucial role in maintaining health, with advances in high-throughput sequencing technology and reduced sequencing costs triggering a surge in microbiome research. Microbiome studies generally incorporate five key phases: design, sampling, sequencing, analysis, and reporting, with sequencing strategy being a crucial step offering numerous options. Present mainstream sequencing strategies include Amplicon sequencing, Metagenomic Next-Generation Sequencing (mNGS), and Targeted Next-Generation Sequencing (tNGS). Two innovative technologies recently emerged, namely MobiMicrobe high-throughput microbial single-cell genome sequencing technology and 2bRAD-M simplified metagenomic sequencing technology, compensate for the limitations of mainstream technologies, each boasting unique core strengths. This paper reviews the basic principles and processes of these three mainstream and two novel microbiological technologies, aiding readers in understanding the benefits and drawbacks of different technologies, thereby guiding the selection of the most suitable method for their research endeavours.

Protocol for selecting single human pluripotent stem cells using a modified micropipetter

Single-cell clonal selection is a critical procedure for generating a homogeneous population of human pluripotent stem cells. Here, we present a protocol that repurposes the STRIPPER Micropipetter, normally used for in vitro fertilization, to pick single stem cells. We describe steps for tool and reagent preparation, single-cell picking, and colony passaging. We then detail procedures for amplification and analysis. Our protocol does not require cell sorting and produces homogenous clonal cultures with more than 50% survival rate. For complete details on the use and execution of this protocol, please refer to Deng et al.1.

Single-cell sequencing in pancreatic cancer research: A deeper understanding of heterogeneity and therapy

Pancreatic cancer, including pancreatic ductal adenocarcinomas (PDACs), is a malignant tumor with characteristics of tumor-stroma interactions. Patients often have a poor prognosis and a poor long-term survival rate. In recent years, rapidly-developing single-cell sequencing techniques have been used to analyze cell populations at a single-cell resolution, so that it is now possible to have a more in-depth and clearer understanding of the genetic composition of pancreatic cancer. In this review, we provide an overview of the current single-cell sequencing techniques and their applications in the exploration of intratumoral heterogeneity, the tumor microenvironment, therapy resistance, and novel treatments. Our hope is to provide new insight into the potential of precision therapy, which will perhaps one day lead to significant advances in PDAC treatment.

Microfluidic based single cell or droplet manipulation: Methods and applications

The isolation of single cell or droplet is first and crucial step to single-cell analysis, which is important for cancer research and diagnostic methods. This review provides an overview of technologies that are currently used or in development to realize the isolation. Microfluidic based manipulation is an emerging technology with the distinct advantages of miniaturization and low cost. Therefore, recent developments in microfluidic isolated methods have attracted extensive attention. We introduced herein five strategies based on microfluid: trap, microfluidic discrete manipulation, bioprinter, capillary and inertial force. For every technology, their basic principles and features were discussed firstly. Then some modified approaches and applications were listed as the extension. Finally, we compared the advantages and drawbacks of these methods, and analyzed the trend of the manipulation based on microfluidics.

Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

Single-cell analysis reveals the immune heterogeneity and interactions in lungs undergoing hepatic ischemia-reperfusion

Hepatic ischemia-reperfusion IR (HIR) is an unavoidable pathophysiological process during liver transplantation, resulting in systematic sterile inflammation and remote organ injury. Acute lung injury (ALI) is a serious complication after liver transplantation with high postoperative morbidity and mortality. However, the underlying mechanism is still unclear. To assess the phenotype and plasticity of various cell types in the lung tissue microenvironment after HIR at the single-cell level, single-cell RNA sequencing (scRNA-seq) was performed using the lungs from HIR-induced mice. In our results, we identified 23 cell types in the lungs after HIR and found that this highly complex ecosystem was formed by subpopulations of bone marrow-derived cells that signaled each other and mediated inflammatory responses in different states and different intervals. We described the unique transcriptional profiles of lung cell clusters and discovered two novel cell subtypes (Tspo+Endothelial cells and Vcan+ monocytes), as well as the endothelial cell-immune cell and immune cell-T cell clusters interactome. In addition, we found that S100 calcium binding protein (S100a8/a9), specifically and highly expressed in immune cell clusters of lung tissues and exhibited detrimental effects. Finally, the cellular landscape of the lung tissues after HIR was established, highlighting the heterogeneity and cellular interactions between major immune cells in HIR-induced lungs. Our findings provided new insights into the mechanisms of HIR-induced ALI and offered potential therapeutic target to prevent ALI after liver transplantation.

Biocatalytic Buoyancy-Driven Nanobots for Autonomous Cell Recognition and Enrichment

Autonomously self-propelled nanoswimmers represent the next-generation nano-devices for bio- and environmental technology. However, current nanoswimmers generate limited energy output and can only move in short distances and duration, thus are struggling to be applied in practical challenges, such as living cell transportation. Here, we describe the construction of biodegradable metal-organic framework based nanobots with chemically driven buoyancy to achieve highly efficient, long-distance, directional vertical motion to "find-and-fetch" target cells. Nanobots surface-functionalized with antibodies against the cell surface marker carcinoembryonic antigen are exploited to impart the nanobots with specific cell targeting capacity to recognize and separate cancer cells. We demonstrate that the self-propelled motility of the nanobots can sufficiently transport the recognized cells autonomously, and the separated cells can be easily collected with a customized glass column, and finally regain their full metabolic potential after the separation. The utilization of nanobots with easy synthetic pathway shows considerable promise in cell recognition, separation, and enrichment.

High-throughput single-cell sorting by stimulated Raman-activated cell ejection

Single-cell sorting is essential to explore cellular heterogeneity in biology and medicine. Recently developed Raman-activated cell sorting (RACS) circumvents the limitations of fluorescence-activated cell sorting, such as the cytotoxicity of labels. However, the sorting throughputs of all forms of RACS are limited by the intrinsically small cross-section of spontaneous Raman scattering. Here, we report a stimulated Raman-activated cell ejection (S-RACE) platform that enables high-throughput single-cell sorting based on high-resolution multi-channel stimulated Raman chemical imaging, in situ image decomposition, and laser-induced cell ejection. The performance of this platform was illustrated by sorting a mixture of 1 μm polymer beads, where 95% yield, 98% purity, and 14 events per second throughput were achieved. Notably, our platform allows live cell ejection, allowing for the growth of single colonies of bacteria and fungi after sorting. To further illustrate the chemical selectivity, lipid-rich Rhodotorula glutinis cells were successfully sorted from a mixture with Saccharomyces cerevisiae, confirmed by downstream quantitative PCR. Furthermore, by integrating a closed-loop feedback control circuit into the system, we realized real-time single-cell imaging and sorting, and applied this method to precisely eject regions of interest from a rat brain tissue section. The reported S-RACE platform opens exciting opportunities for a wide range of single-cell applications in biology and medicine.

Microfluidic pumps for cell sorting

Microfluidic cell sorting has shown promising advantages over traditional bulky cell sorting equipment and has demonstrated wide-reaching applications in biological research and medical diagnostics. The most important characteristics of a microfluidic cell sorter are its throughput, ease of use, and integration of peripheral equipment onto the chip itself. In this review, we discuss the six most common methods for pumping fluid samples in microfluidic cell sorting devices, present their advantages and drawbacks, and discuss notable examples of their use. Syringe pumps are the most commonly used method for fluid actuation in microfluidic devices because they are easily accessible but they are typically too bulky for portable applications, and they may produce unfavorable flow characteristics. Peristaltic pumps, both on- and off-chip, can produce reversible flow but they suffer from pulsatile flow characteristics, which may not be preferable in many scenarios. Gravity-driven pumping, and similarly hydrostatic pumping, require no energy input but generally produce low throughputs. Centrifugal flow is used to sort cells on the basis of size or density but requires a large external rotor to produce centrifugal force. Electroosmotic pumping is appealing because of its compact size but the high voltages required for fluid flow may be incompatible with live cells. Emerging methods with potential for applications in cell sorting are also discussed. In the future, microfluidic cell sorting methods will trend toward highly integrated systems with high throughputs and low sample volume requirements.

Metabolomics: A useful tool for ischemic stroke research

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

Advances in single-cell RNA sequencing and its applications in cancer research

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

Advancing Breast Cancer Heterogeneity Analysis: Insights from Genomics, Transcriptomics and Proteomics at Bulk and Single-Cell Levels

Breast cancer continues to pose a significant healthcare challenge worldwide for its inherent molecular heterogeneity. This review offers an in-depth assessment of the molecular profiling undertaken to understand this heterogeneity, focusing on multi-omics strategies applied both in traditional bulk and single-cell levels. Genomic investigations have profoundly informed our comprehension of breast cancer, enabling its categorization into six intrinsic molecular subtypes. Beyond genomics, transcriptomics has rendered deeper insights into the gene expression landscape of breast cancer cells. It has also facilitated the formulation of more precise predictive and prognostic models, thereby enriching the field of personalized medicine in breast cancer. The comparison between traditional and single-cell transcriptomics has identified unique gene expression patterns and facilitated the understanding of cell-to-cell variability. Proteomics provides further insights into breast cancer subtypes by illuminating intricate protein expression patterns and their post-translational modifications. The adoption of single-cell proteomics has been instrumental in this regard, revealing the complex dynamics of protein regulation and interaction. Despite these advancements, this review underscores the need for a holistic integration of multiple 'omics' strategies to fully decipher breast cancer heterogeneity. Such integration not only ensures a comprehensive understanding of breast cancer's molecular complexities, but also promotes the development of personalized treatment strategies.

Selective expansion of target cells using the Enrich TROVO platform

Enriching target cell clones from diverse cell populations is vital for many life science applications. We have developed a novel method to rapidly and efficiently purify specific clonal cell populations from a larger, heterogeneous group using the Enrich TroVo system (Enrich Biosystems Inc., CT, USA). This system takes advantage of microfabrication and optical technologies by utilizing small hydrogel wells to separate desired cell populations and an innovative patching technique to selectively eliminate undesired cells. This method allows the isolation and growth of desired cells with minimal impact on their viability and proliferation. We successfully isolated and expanded clonal cell populations of desired cells using two model cells. Compared with fluorescence-activated cell sorting, Enrich TroVo system offers a promising alternative for isolating of sensitive, adherent cells, that is, patient-derived cells.

Cell-Type-Specific Neuroproteomics of Synapses

In the last two decades, our knowledge of synaptic proteomes and their relationship to normal brain function and neuropsychiatric disorders has been expanding rapidly through the use of more powerful neuroproteomic approaches. However, mass spectrometry (MS)-based neuroproteomic studies of synapses still require cell-type, spatial, and temporal proteome information. With the advancement of sample preparation and MS techniques, we have just begun to identify and understand proteomes within a given cell type, subcellular compartment, and cell-type-specific synapse. Here, we review the progress and limitations of MS-based neuroproteomics of synapses in the mammalian CNS and highlight the recent applications of these approaches in studying neuropsychiatric disorders such as major depressive disorder and substance use disorders. Combining neuroproteomic findings with other omics studies can generate an in-depth, comprehensive map of synaptic proteomes and possibly identify new therapeutic targets and biomarkers for several central nervous system disorders.

Cell-type-specific metabolism in plants

Every plant organ contains tens of different cell types, each with a specialized function. These functions are intrinsically associated with specific metabolic flux distributions that permit the synthesis of the ATP, reducing equivalents and biosynthetic precursors demanded by the cell. Investigating such cell-type-specific metabolism is complicated by the mosaic of different cells within each tissue combined with the relative scarcity of certain types. However, techniques for the isolation of specific cells, their analysis in situ by microscopy, or modeling of their function in silico have permitted insight into cell-type-specific metabolism. In this review we present some of the methods used in the analysis of cell-type-specific metabolism before describing what we know about metabolism in several cell types that have been studied in depth; (i) leaf source and sink cells; (ii) glandular trichomes that are capable of rapid synthesis of specialized metabolites; (iii) guard cells that must accumulate large quantities of the osmolytes needed for stomatal opening; (iv) cells of seeds involved in storage of reserves; and (v) the mesophyll and bundle sheath cells of C4 plants that participate in a CO₂ concentrating cycle. Metabolism is discussed in terms of its principal features, connection to cell function and what factors affect the flux distribution. Demand for precursors and energy, availability of substrates and suppression of deleterious processes are identified as key factors in shaping cell-type-specific metabolism.

Production of MSTN Gene-Edited Embryos of Buffalo Using the CRISPR/Cas9 System and SCNT

The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system and somatic cell nuclear transfer (SCNT) have been used to produce genome-edited farm animal species for improved production and health traits; however, these tools are rarely used in the buffalo and can play a pivotal role in milk and meat production in tropical and subtropical countries. In this study, we aimed to produce myostatin (MSTN) gene-edited embryos of the Murrah buffalo using the CRISPR/Cas9 system and SCNT. For this, fibroblast cells were electroporated with sgRNAs carrying all-in-one CRISPR/Cas9 plasmids targeting the first exon of the MSTN gene. Following puromycin selection, single-cell clonal populations were established and screened using the TA cloning and Sanger sequencing methods. Of eight single-cell clonal populations, one with a monoallelic and another with a biallelic heterozygous gene editing event were identified. These two gene-edited clonal cell populations were successfully used to produce blastocyst-stage embryos using the handmade cloning method. This work establishes the technical foundation for generation of genome-edited cloned embryos in the buffalo.

Single-cell RNA sequencing in skeletal muscle developmental biology

Skeletal muscle is the most extensive tissue in mammals, and they perform several functions; it is derived from paraxial mesodermal somites and undergoes hyperplasia and hypertrophy to form multinucleated, contractile, and functional muscle fibers. Skeletal muscle is a complex heterogeneous tissue composed of various cell types that establish communication strategies to exchange biological information; therefore, characterizing the cellular heterogeneity and transcriptional signatures of skeletal muscle is central to understanding its ontogeny's details. Studies of skeletal myogenesis have focused primarily on myogenic cells' proliferation, differentiation, migration, and fusion and ignored the intricate network of cells with specific biological functions. The rapid development of single-cell sequencing technology has recently enabled the exploration of skeletal muscle cell types and molecular events during development. This review summarizes the progress in single-cell RNA sequencing and its applications in skeletal myogenesis, which will provide insights into skeletal muscle pathophysiology.

Approaches for single-cell RNA sequencing across tissues and cell types

Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.

Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects

Gastric cancer is one of the most serious malignant tumor and threatens the health of people worldwide. Its heterogeneity leaves many clinical problems unsolved. To treat it effectively, we need to explore its heterogeneity. Single-cell transcriptome sequencing, or single-cell RNA sequencing (scRNA-seq), reveals the complex biological composition and molecular characteristics of gastric cancer at the level of individual cells, which provides a new perspective for understanding the heterogeneity of gastric cancer. In this review, we first introduce the current procedure of scRNA-seq, and discuss the advantages and limitations of scRNA-seq. We then elaborate on the research carried out with scRNA-seq in gastric cancer in recent years, and describe how it reveals cell heterogeneity, the tumor microenvironment, oncogenesis and metastasis, as well as drug response in to gastric cancer, to facilitate early diagnosis, individualized therapy, and prognosis evaluation.

Single-Cell Proteomics with Spatial Attributes: Tools and Techniques

Now-a-days, the single-cell proteomics (SCP) concept is attracting interest, especially in clinical research, because it can identify the proteomic signature specific to diseased cells. This information is very essential when dealing with the progression of certain diseases, such as cancer, diabetes, Alzheimer's, etc. One of the major drawbacks of conventional destructive proteomics is that it gives an average idea about the protein expression profile in the disease condition. During the extraction of the protein from a biopsy or blood sample, proteins may come from both diseased cells and adjacent normal cells or any other cells from the disease environment. Again, SCP along with spatial attributes is utilized to learn about the heterogeneous function of a single protein. Before performing SCP, it is necessary to isolate single cells. This can be done by various techniques, including fluorescence-activated cell sorting (FACS), magnetic-activated cell sorting (MACS), laser capture microdissection (LCM), microfluidics, manual cell picking/micromanipulation, etc. Among the different approaches for proteomics, mass spectrometry-based proteomics tools are widely used for their high resolution as well as sensitivity. This Review mainly focuses on the mass spectrometry-based approaches for the study of single-cell proteomics.

Technologies and applications of single-cell DNA methylation sequencing

DNA methylation is the most stable epigenetic modification. In mammals, it usually occurs at the cytosine of CpG dinucleotides. DNA methylation is essential for many physiological and pathological processes. Aberrant DNA methylation has been observed in human diseases, particularly cancer. Notably, conventional DNA methylation profiling technologies require a large amount of DNA, often from a heterogeneous cell population, and provide an average methylation level of many cells. It is often not realistic to collect sufficient numbers of cells, such as rare cells and circulating tumor cells in peripheral blood, for bulk sequencing assays. It is therefore essential to develop sequencing technologies that can accurately profile DNA methylation using small numbers of cells or even single cells. Excitingly, many single-cell DNA methylation sequencing and single-cell omics sequencing technologies have been developed, and applications of these methods have greatly expanded our understanding of the molecular mechanism of DNA methylation. Here, we summaries single-cell DNA methylation and multi-omics sequencing methods, delineate their applications in biomedical sciences, discuss technical challenges, and present our perspective on future research directions.

Single-Cell Isolation Microfluidic Chip Based on Thermal Bubble Micropump Technology

The isolation of single cells is essential for the development of single cell analysis methods, such as single-cell sequencing, monoclonal antibodies, and drug development. Traditional single-cell isolation techniques include flow cytometry (FACS), laser capture microdissection (LCM), micromanipulation, etc., but their operations are complex and have low throughput. Here, we present a microfluidic chip that can isolate individual cells from cell suspension and release them onto a well plate. It uses thermal bubble micropump technology to drive the fluid flow, and single-cell isolation is achieved by matching the flow resistance of the flow channel. Therefore, injection pumps and peristaltic pumps are not required for cell loading. Because of its small size, we can integrate hundreds of single-cell functional modules, which makes high-throughput single-cell isolation possible. For polystyrene beads, the capture rate of the single bead is close to 100%. Finally, the method has been applied to cells, and the capture rate of the single cell is also about 75%. This is a promising method for single-cell isolation.