Single-cell Detection Research Articles

Bridging Ionic Current Rectification and Resistive-Pulse Sensing for Reliable Wide-Linearity Detection.

As two mainstream ionic detection techniques, ionic current rectification (ICR) suffers from large fluctuations in trace level detection, while resistive-pulse sensing (RPS) encounters easy clogs in high-concentration detection. By rationally matching the nanopore size with the DNA tetrahedron (TDN), this work bridges the two techniques to achieve reliable detection with wide linearity. As a representative analyte, miRNA-10b could specifically combine with and release TDN from the interior wall, which thus induced the simultaneous generation of distinct ICR and RPS signals. The ICR signals could be attributed to the balance between the effective orifice and surface charge density of the inner wall, while the RPS signals were induced by the complex of miRNA-10b and TDN passing through the nanopore. Such an operation contributed to a wide detection range of 1 fM-1 nM with a good linearity. The feasibility of this method is also validated in single-cell and real plasma detection.

Single cell analysis reveals the roles and regulatory mechanisms of type-I interferons in Parkinson’s disease

The pathogenesis of Parkinson’s disease (PD) is strongly associated with neuroinflammation, and type I interferons (IFN-I) play a crucial role in regulating immune and inflammatory responses. However, the specific features of IFN in different cell types and the underlying mechanisms of PD have yet to be fully described. In this study, we analyzed the GSE157783 dataset, which includes 39,024 single-cell RNA sequencing results for five PD patients and six healthy controls from the Gene Expression Omnibus database. After cell type annotation, we intersected differentially expressed genes in each cell subcluster with genes collected in The Interferome database to generate an IFN-I-stimulated gene set (ISGs). Based on this gene set, we used the R package AUCell to score each cell, representing the IFN-I activity. Additionally, we performed monocle trajectory analysis, and single-cell regulatory network inference and clustering (SCENIC) to uncover the underlying mechanisms. In silico gene perturbation and subsequent experiments confirm NFATc2 regulation of type I interferon response and neuroinflammation. Our analysis revealed that microglia, endothelial cells, and pericytes exhibited the highest activity of IFN-I. Furthermore, single-cell trajectory detection demonstrated that microglia in the midbrain of PD patients were in a pro-inflammatory activation state, which was validated in the 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model as well. We identified transcription factors NFATc2, which was significantly up-regulated and involved in the expression of ISGs and activation of microglia in PD. In the 1-Methyl-4-phenylpyridinium (MPP+)-induced BV2 cell model, the suppression of NFATc2 resulted in a reduction in IFN-β levels, impeding the phosphorylation of STAT1, and attenuating the activation of the NF-κB pathway. Furthermore, the downregulation of NFATc2 mitigated the detrimental effects on SH-SY5Y cells co-cultured in conditioned medium. Our study highlights the critical role of microglia in type I interferon responses in PD. Additionally, we identified transcription factors NFATc2 as key regulators of aberrant type I interferon responses and microglial pro-inflammatory activation in PD. These findings provide new insights into the pathogenesis of PD and may have implications for the development of novel therapeutic strategies.

An Assessment of the Mechanophysical and Hormonal Impact on Human Endometrial Epithelium Mechanics and Receptivity.

The endometrial epithelium and underlying stroma undergo profound changes to support and limit embryo adhesion and invasion, which occur in the secretory phase of the menstrual cycle during the window of implantation. This coincides with a peak in progesterone and estradiol production. We hypothesized that the interplay between hormone-induced changes in the mechanical properties of the endometrial epithelium and stroma supports this process. To study it, we used hormone-responsive endometrial adenocarcinoma-derived Ishikawa cells growing on substrates of different stiffness. We showed that Ishikawa monolayers on soft substrates are more tightly clustered and uniform than on stiff substrates. Probing for mechanical alterations, we found accelerated stress-relaxation after apical nanoindentation in hormone-stimulated monolayers on stiff substrates. Traction force microscopy furthermore revealed an increased number of foci with high traction in the presence of estradiol and progesterone on soft substrates. The detection of single cells and small cell clusters positive for the intermediate filament protein vimentin and the progesterone receptor further underscored monolayer heterogeneity. Finally, adhesion assays with trophoblast-derived AC-1M-88 spheroids were used to examine the effects of substrate stiffness and steroid hormones on endometrial receptivity. We conclude that the extracellular matrix and hormones act together to determine mechanical properties and, ultimately, embryo implantation.

Abstract 3694: Genomic profiling of single cancer cells using the novel single-cell integrated mutational profiling of actionable cancer targets (scIMPACT) assay

Abstract Liquid biopsy provides opportunities to guide therapy decisions using biomarkers such as circulating tumor cells (CTCs) even years after the primary tumor resection. For this, novel methods permitting the genomic profiling of CTCs are needed to characterize systemic cancer spread and identify clinically targetable genomic alterations. Hence, we developed an assay based on the FDA-approved MSK-IMPACT® assay to analyze the genomes of single-cells. We present a series of benchmarking experiments using well-characterized cell lines to demonstrate the performance of our new Single-Cell Integrated Mutation Profiling of Actionable Cancer Targets (scIMPACT) assay.The scIMPACT assay was developed using Ampli1® WGA products of single-cell and pool samples. The workflow consists of an optimized library preparation protocol followed by targeted sequencing with the scIMPACT panel. A bioinformatics mutation calling workflow facilitates the detection of single nucleotide variations (SNVs), indels, and copy number variations (CNVs). To account for WGA associated bias, we developed an in-house proprietary machine learning based classifier algorithm. Two sample collectives were prepared and used for training and validating the workflow. The first collective, including genomic libraries of MDA-MB-453, BT474, BT549 and ZR-75.1 samples, was used for training of the mutation detection workflow. The second collective, consisting of HCC1395/HCC1395BL cell lines representing matched tumor and normal cells, was used to validate the performance of the assay. The scIMPACT assay identified somatic mutations in all WGA products as predicted from bulk gDNA samples and published literature. Notably, evidence of genetic heterogeneity was reported at the single cell level. Pertaining to the SNV detection, the training collective displayed 91% sensitivity and 96% specificity (AUC=0.98) while the validation collective demonstrated similar performance with 84% sensitivity and 96% specificity (AUC=0.90) proving the applicability of our workflow across different datasets. Furthermore, CNV analysis showed high concordance between matching gDNA and WGA samples. Our workflow enables mutational profiling with high specificity and sensitivity and accurate CNV detection in single cells. The scIMPACT assay has been successfully adapted to analyze samples at the single-cell level. Therefore, our method can be applied for the genomic profiling of patient-derived CTCs. Citation Format: Clara Chaiban, Adithi Ravikumar Varadarajan, Jonas Grote, Thomas Ragg, Isabell Blochberger, Vadim Dechand, Jens Warfsmann, Christoph A. Klein, Zbigniew T. Czyż. Genomic profiling of single cancer cells using the novel single-cell integrated mutational profiling of actionable cancer targets (scIMPACT) assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3694.

Abstract 540: Identification of therapy resistance mediating extracellular vesicles in single-cell level via a novel microfluidic co-culture device development

Abstract Once cancer has metastasized, it is incurable because tumors evolve resistance to all systemically administered anti-cancer therapies. Resistance to therapy has classically been attributed to the presence of a cancer stem cell or genetic tumor cell heterogeneity. Extracellular vesicles (EVs) are nano-sized (40-1000 nm) vesicles that are released by all cells into the extracellular space. EVs carry diverse cargo dependent on the cell of origin and have been studied as a source of novel cancer-specific liquid biopsy biomarkers and contributors to tumor progression and metastasis. However, the paracrine function of EVs in promoting therapy resistance is under-studied, and the impact of EVs released from therapy-resistant cancer cells on surrounding therapy-sensitive cancer cells is unknown. In this study, we develop an innovative microfluidic device, TREVCo, to enable simultaneous single-cell trap, EV detection, and co-culture modules to evaluate EVs-mediated transfer of cellular information between therapy-resistant cancer cells and adjacent cells, and to characterize EVs released from resistant cells and determine their impact on the resistance phenotype of adjacent therapy-sensitive cancer cells. We utilize resistant cells from multiple prostate (PCa) cell lines that have been selected for therapy resistance by culture with increasing dosages of cancer drugs such as cisplatin, docetaxel. We use the matched untreated therapy-sensitive parental cell lines as the sensitive cells. We hypothesize a novel model of therapy resistance in lethal PCa: EVs released from resistant cells contain pro-resistance factors that are transferred to adjacent sensitive cells upon EV uptake, thus directly enabling therapeutic resistance. We will assess the impact of resistant cell-EVs at a single cell level via a novel device, TREVCo, that enables comprehensive downstream analysis. This single-cell approach enables dissection of critical EV-associated therapy-resistant factors within the large heterogeneity of resistant PCa. Co-culture of a single resistant cell and a hundred adjacent sensitive cells mimicking intra-tumoral interactions is also critical to demonstrate evidence of resistant cell secreting factors inducing a pro-resistance phenotype. These studies will be the first-in-field to assess the impact of resistant PCa cell-derived EVs at single-cell resolution. An understanding of resistant cell-derived EVs and the impact of that EV cargo on adjacent sensitive cells will provide critical insight into the acquisition of therapy resistance in lethal PCa. The novel approach to apply resistant cell-derived EVs in co-culture assay with sensitive cells will enable the screening of transmittable resistance-associated factors and provides critical opportunities for accelerating precision medicine for advanced PCa patients. Citation Format: Chi-Ju Kim, Sarah Amend, Kenneth Pienta. Identification of therapy resistance mediating extracellular vesicles in single-cell level via a novel microfluidic co-culture device development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 540.

Bimodal analysis of intracellular in situ self-assembled Au complexes based on single-cell electrochemistry

Gold complexes have shown great potential for clinical applications in cancer chemotherapy. However, the unclear mechanisms of tumor heterogeneity and induced drug resistance hinder the effectiveness of gold complex therapy. To address this issue, single-cell electrochemical detection strategies have been widely reported for bioimaging and bioanalysis, due to their in-situ, real-time, and high-resolution characteristics. In this study, the self-assembled process of gold complexes was investigated by detecting hydrogen peroxide release at the single-cell level using nanoelectrodes and scanning electrochemical microscopy. This detection strategy could provide more spatio-temporal information on the synthesis of bioresponsive fluorescent nanoprobes.

Prediction of protein-RNA interactions from single-cell transcriptomic data.

Proteins are crucial in regulating every aspect of RNA life, yet understanding their interactions with coding and noncoding RNAs remains limited. Experimental studies are typically restricted to a small number of cell lines and a limited set of RNA-binding proteins (RBPs). Although computational methods based on physico-chemical principles can predict protein-RNA interactions accurately, they often lack the ability to consider cell-type-specific gene expression and the broader context of gene regulatory networks (GRNs). Here, we assess the performance of several GRN inference algorithms in predicting protein-RNA interactions from single-cell transcriptomic data, and propose a pipeline, called scRAPID (single-cell transcriptomic-based RnA Protein Interaction Detection), that integrates these methods with the catRAPID algorithm, which can identify direct physical interactions between RBPs and RNA molecules. Our approach demonstrates that RBP-RNA interactions can be predicted from single-cell transcriptomic data, with performances comparable or superior to those achieved for the well-established task of inferring transcription factor-target interactions. The incorporation of catRAPID significantly enhances the accuracy of identifying interactions, particularly with long noncoding RNAs, and enables the identification of hub RBPs and RNAs. Additionally, we show that interactions between RBPs can be detected based on their inferred RNA targets. The software is freely available at https://github.com/tartaglialabIIT/scRAPID.

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.

Iontronic Photoelectrochemical Biorecognition Probing.

Herein, the first iontronic photoelectrochemical (PEC) biorecognition probing is devised by rational engineering of a dual-functional bioconjugate, i.e., a light-sensitive intercalated structural DNA, as a smart gating module confined within a nanotip, which could respond to both the incident light and biotargets of interest. Light stimulation of the bioconjugate could intensify the negative charge at the nano-orifice to sustain enhanced ionic current. The presence of proteins (e.g., acetylcholinesterase, AChE) or nucleic acids (e.g., microRNA (miR)-10b) could lead to bioconjugate release with altered ionic signaling. The practical applicability of the methodology is confirmed by AChE detection in human serum and miR-10b detection in single cells.

Abstract A024: B cells facilitate lymph node colonization in pancreatic ductal adenocarcinoma

Abstract Pancreatic ductal adenocarcinoma (PDAC) has a low survival rate. Several factors contribute to its dismal prognosis, including resistance to available therapies and high invasiveness. Lymph nodes act as an early systemic source of circulating malignant cells in PDAC, allowing their dissemination to other organs early in disease progression. Lymphatic colonization is linked to worse prognosis. Therefore, a better understanding of mechanisms regulating lymph node metastasis is clinically needed. To study each step in the metastatic cascade to the lymph nodes, we have developed a mouse co-clinical model of resectable pancreatic cancer. This model consists of subcutaneous injection of highly metastatic pancreatic cancer cells, followed by surgical resection of the primary tumor. Following resection, mice spontaneously develop lymph nodes metastasis at a comparable frequency to human PDAC post-surgical recurrence, on a similar time scale relative to the lifespans of mice and humans. Expression of nuclear tdTomato allows detection of single cancer cells seeding the draining lymph nodes early in disease progression, even before metastases are histological detectable. Using this model, we are gaining insights into the first steps of metastatic seeding of lymph nodes, and have identified a pro-metastatic role for B cells. These findings will enhance our understanding of lymphatic colonization in PDAC and potentially inform immunotherapeutic interventions to disrupt the metastatic cascade. Citation Format: Alice Bertocchi, Megan T. Hoffman, Li Qiang, Lauren Hsu, Michael Dougan, Judith Agudo, Stephanie K. Dougan. B cells facilitate lymph node colonization in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A024.

Lanthanide-Complex-Enhanced Bioorthogonal Branched DNA Amplification.

Fluorescence in situ hybridization (FISH) is a widely used technique for detecting intracellular nucleic acids. However, its effectiveness in detecting low-copy nucleic acids is limited due to its low fluorescence intensity and background autofluorescence. To address these challenges, we present here an approach of lanthanide-complex-enhanced bioorthogonal-branched DNA amplification (LEBODA) with high sensitivity for in situ nuclear acid detection in single cells. The approach capitalizes on two levels of signal amplification. First, it utilizes click chemistry to directly link a substantial number of bridge probes to target-recognizing probes, providing an initial boost in signal intensity. Second, it incorporates high-density lanthanide complexes into each bridge probe, enabling secondary amplifications. Compared to the traditional "double Z" probes used in the RNAscope method, LEBODA exhibits 4 times the single enhancement for RNA detection signal with the click chemistry approach. Using SARS-CoV-2 pseudovirus-infected HeLa cells, we demonstrate the superiority in the detection of viral-infected cells in rare populations as low as 20% infectious rate. More encouragingly, the LEBODA approach can be adapted for DNA-FISH and single-molecule RNA-FISH, as well as other hybridization-based signal amplification methods. This adaptability broadens the potential applications of LEBODA in the sensitive detection of biomolecules, indicating promising prospects for future research and practical use.

Recent advances of nanopore technique in single cell analysis.

Single cells and their dynamic behavior are closely related to biological research. Monitoring their dynamic behavior is of great significance for disease prevention. How to achieve rapid and non-destructive monitoring of single cells is a major issue that needs to be solved urgently. As an emerging technology, nanopores have been proven to enable non-destructive and label-free detection of single cells. The structural properties of nanopores enable a high degree of sensitivity and accuracy during analysis. In this article, we summarize and classify the different types of solid-state nanopores that can be used for single-cell detection and illustrate their specific applications depending on the size of the analyte. In addition, their research progress in material transport and microenvironment monitoring is also highlighted. Finally, a brief summary of existing research challenges and future trends in nanopore single-cell analysis is tentatively provided.

An Ultrasensitive and Efficient microRNA Nanosensor Empowered by the CRISPR/Cas Confined in a Nanopore.

This work presents a clustered regularly interspaced short palindromic repeat (CRISPR)/Cas-nanopipette nano-electrochemistry (Cas = CRISPR-associated proteins) capable of ultrasensitive microRNA detection. Nanoconfinement of the CRISPR/Cas13a within a nanopipette leads to a high catalytic efficacy of ca. 169 times higher than that in bulk electrolyte, contributing to the amplified electrochemical responses. CRISPR/Cas13a-enabled detection of representative microRNA-25 achieves a low limit of detection down to 10 aM. Practical application of this method is further demonstrated for single-cell and real human serum detection. Its general applicability is validated by addressing microRNA-141 and the SARS-CoV-2 RNA gene fragment. This work introduces a new CRISPR/Cas-empowered nanotechnology for ultrasensitive nano-electrochemistry and bioanalysis.

DNA Probes for Cas12a-Based Assay with Fluorescence Anisotropy Enhanced Due to Anchors and Salts.

CRISPR/Cas12a is a potent biosensing tool known for its high specificity in DNA analysis. Cas12a recognizes the target DNA and acquires nuclease activity toward single-stranded DNA (ssDNA) probes. We present a straightforward and versatile approach to transforming common Cas12a-cleavable DNA probes into enhancing tools for fluorescence anisotropy (FA) measurements. Our study involved investigating 13 ssDNA probes with linear and hairpin structures, each featuring fluorescein at one end and a rotation-slowing tool (anchor) at the other. All anchors induced FA changes compared to fluorescein, ranging from 24 to 110 mr. Significant FA increases (up to 180 mr) were obtained by adding divalent metal salts (Mg2+, Ca2+, Ba2+), which influenced the rigidity and compactness of the DNA probes. The specific Cas12a-based recognition of double-stranded DNA (dsDNA) fragments of the bacterial phytopathogen Erwinia amylovora allowed us to determine the optimal set (probe structure, anchor, concentration of divalent ion) for FA-based detection. The best sensitivity was obtained using a hairpin structure with dC10 in the loop and streptavidin located near the fluorescein at the stem in the presence of 100 mM Mg2+. The detection limit of the dsDNA target was equal to 0.8 pM, which was eight times more sensitive compared to the common fluorescence-based method. The enhancing set ensured detection of single cells of E. amylovora per reaction in an analysis based on CRISPR/Cas12a with recombinase polymerase amplification. Our approach is universal and easy to implement. Combining FA with Cas12a offers enhanced sensitivity and signal reliability and could be applied to different DNA and RNA analytes.

Self-enhanced Electrochemiluminescence Luminophore Based on Pd Nanocluster-Anchored Metal Organic Frameworks via Ion Annihilation for Sensitive Cell Assay of Human Lung Cancer.

Electrochemiluminescence (ECL) has attracted significant interest in the analysis of cancer cells, where the ruthenium(II)-based emitter demonstrates urgency and feasibility to improve the ECL efficiency. In this work, the self-enhanced ECL luminophore was prepared by covalent anchoring of Pd nanoclusters on aminated metal organic frameworks (Pd NCs@MOFs), followed by linkage with bis(2,2'-bipyridine)-5-amino-1,10-phenanthroline ruthenium(II) (RuP). The resultant luminophore showed 214-fold self-magnification in the ECL efficiency over RuP alone, combined by promoting the interfacial photoelectron transfer. The enhanced mechanism through ion annihilation was critically proved by controlled experiments and density functional theory (DFT) calculations. Based on the above, a "signal off" ECL biosensor was built by assembly of tyrosine kinase 7 (PTK-7) aptamer (Apt) on the established sensing platform for analysis of human lung cancer cells (A549). The built sensor showed a lower detection limit of 8 cells mL-1, achieving the single-cell detection. This work reported a self-enhanced strategy for synthesis of advanced ECL emitters, combined by exploring the ECL biosensing devices in the single-cell analysis of cancers.

Recent Progress in Mass Spectrometry-Based Single-Cell Metabolic Analysis.

Single-cell analysis enables the measurement of biomolecules at the level of individual cells, facilitating in-depth investigations into cellular heterogeneity and precise interpretation of the related biological mechanisms. Among these biomolecules, cellular metabolites exhibit remarkable sensitivity to environmental and biochemical changes, unveiling a hidden world underlying cellular heterogeneity and allowing for the determination of cell physiological states. However, the metabolic analysis of single cells is challenging due to the extremely low concentrations, substantial content variations, and rapid turnover rates of cellular metabolites. Mass spectrometry (MS), characterized by its high sensitivity, wide dynamic range, and excellent selectivity, is employed in single-cell metabolic analysis. This review focuses on recent advances and applications of MS-based single-cell metabolic analysis, encompassing three key steps of single-cell isolation, detection, and application. It is anticipated that MS will bring profound implications in biomedical practices, serving as advanced tools to depict the single-cell metabolic landscape.

Photothermal optical coherence tomography for 3D live cell detection and mapping.

Imaging cells in their 3D environment with molecular specificity is important to cell biology study. Widely used microscopy techniques, such as confocal microscopy, have limited imaging depth when probing cells in optically scattering media. Optical coherence tomography (OCT) can provide millimeter-level depth for imaging of highly scattering media but lacks the contrast to distinguish cells from extracellular matrix or to distinguish between different types of cells. Photothermal OCT (PT-OCT) is a promising technique to obtain molecular contrast at the imaging scale of OCT. Here, we report PT-OCT imaging of live, nanoparticle-labeled cells in 3D. In particular, we demonstrate detection and mapping of single cell in 3D without causing call death, and show the feasibility of 3D cell mapping through optical scattering media. This work presents live cell detection and mapping at an imaging scale that complements the major microscopy techniques, which is potentially useful to study cells in their 3D native or culture environment.

Label-Free Single-Cell SERS Detection and Fluorescence Imaging of Molecular Responses to Endoplasmic Reticulum Stress under Electrical Stimulation.

The endoplasmic reticulum (ER) is one of the most important organelles in eukaryotic cells, in which most proteins and lipids are synthesized to regulate complex cellular processes. Generally, the excessive accumulation of unfolded or misfolded proteins can disturb ER homeostasis and induce endoplasmic reticulum stress (ERS). Howbeit, the molecular stress responses within ERS and metastatic behaviors of tumor cells during electrical stimulation (ES) are still poorly investigated and remain a challenge. In this study, by the combined use of fluorescence imaging, ER-targeting plasmonic nanoprobes were developed to trace molecular stress response profiling within the ER during a constant-voltage ES process at ∼1 V based on label-free surface-enhanced Raman spectroscopy (SERS). The excess accumulation of β-misfolded proteins was found after the ES, leading to breaking of the ER homeostasis and further inducing mitochondrial dysfunction. Notably, the excessive stress of ER under ES can destroy the calcium ion balance and induce significant upregulation of calreticulin expression. Importantly, the content ratio of two kinds of cadherin between E-cadherin and N-cadherin was gradually improved with the voltages boosted. Meanwhile, the epithelial adhesion factor expression was ascended with voltages amplified, leading to inhibiting tumor cell migration at low voltages or death under higher voltages (∼1 V). This study provides cellular insights into the ES approach for tumor therapy and also provides a simple and effective method for detecting molecular stress responses in endoplasmic reticulum stress.

A simple joint detection platform for high-throughput single-cell heterogeneity screening

Single cell heterogeneity plays an important role in many biological phenomena and distinguishing cells that exhibit certain mutation in sample could benefit clinical diagnose and drug screening. Typical single cell detection methods such as flow cytometry, in-situ hybridization, real-time amplification or sequencing test either protein or nucleic acid as target and usually require specialized instruments. Joint measurement of the both types of targets could be done by combining the above strategies precisely but also unwieldly. Methods for rapidly and parallelly screening single cells with target genotype and antigen is needed. In this study, we describe a gel plate platform to distinguish cell types based on their phenotypes on target gene and antigen with low equipment requirement. Integrated cell lysis and immobilization were done in the gel solidification step, after which antibody hybridization and real-time amplification were sequentially carried out without losing the original loci information of individual single cells so the three types of information of individual single cells could be combined to distinguished cells with expected genotype and phenotype. The easy-to-use gel platform has potential in point-of-care circumstances and single-cell stimulation response that have high requirements on efficiency and simplicity.

ScLSTM: single-cell type detection by siamese recurrent network and hierarchical clustering

MotivationCategorizing cells into distinct types can shed light on biological tissue functions and interactions, and uncover specific mechanisms under pathological conditions. Since gene expression throughout a population of cells is averaged out by conventional sequencing techniques, it is challenging to distinguish between different cell types. The accumulation of single-cell RNA sequencing (scRNA-seq) data provides the foundation for a more precise classification of cell types. It is crucial building a high-accuracy clustering approach to categorize cell types since the imbalance of cell types and differences in the distribution of scRNA-seq data affect single-cell clustering and visualization outcomes.ResultTo achieve single-cell type detection, we propose a meta-learning-based single-cell clustering model called ScLSTM. Specifically, ScLSTM transforms the single-cell type detection problem into a hierarchical classification problem based on feature extraction by the siamese long-short term memory (LSTM) network. The similarity matrix derived from the improved sigmoid kernel is mapped to the siamese LSTM feature space to analyze the differences between cells. ScLSTM demonstrated superior classification performance on 8 scRNA-seq data sets of different platforms, species, and tissues. Further quantitative analysis and visualization of the human breast cancer data set validated the superiority and capability of ScLSTM in recognizing cell types.