Integrated measurement of intracellular proteins and transcripts in single cells

Simultaneous deep transcriptome and proteome profiling in a single mouse oocyte

Although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing, and mass spectrometry technology to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19,948 genes and 2,663 protein groups in single mouse oocytes. In particular, we analyzed the correlation of individual RNA and protein pairs, as well as the meiosis regulatory network with unprecedented depth, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, which could be productive for exploring transcriptional and translational regulatory features during oocyte meiosis.

Recent advances in microfluidics for single-cell functional proteomics

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.

Integrating Micro and Nano Technologies for Cell Engineering and Analysis: Toward the Next Generation of Cell Therapy Workflows

The emerging field of cell therapy offers the potential to treat and even cure a diverse array of diseases for which existing interventions are inadequate. Recent advances in micro and nanotechnology have added a multitude of single cell analysis methods to our research repertoire. At the same time, techniques have been developed for the precise engineering and manipulation of cells. Together, these methods have aided the understanding of disease pathophysiology, helped formulate corrective interventions at the cellular level, and expanded the spectrum of available cell therapeutic options. This review discusses how micro and nanotechnology have catalyzed the development of cell sorting, cellular engineering, and single cell analysis technologies, which have become essential workflow components in developing cell-based therapeutics. The review focuses on the technologies adopted in research studies and explores the opportunities and challenges in combining the various elements of cell engineering and single cell analysis into the next generation of integrated and automated platforms that can accelerate preclinical studies and translational research.

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

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

The Intriguing Landscape of Single-Cell Protein Analysis

Profiling protein expression at single-cell resolution is essential for fundamental biological research (such as cell differentiation and tumor microenvironmental examination) and clinical precision medicine where only a limited number of primary cells are permitted. With the recent advances in engineering, chemistry, and biology, single-cell protein analysis methods are developed rapidly, which enable high-throughput and multiplexed protein measurements in thousands of individual cells. In combination with single cell RNA sequencing and mass spectrometry, single-cell multi-omics analysis can simultaneously measure multiple modalities including mRNAs, proteins, and metabolites in single cells, and obtain a more comprehensive exploration of cellular signaling processes, such as DNA modifications, chromatin accessibility, protein abundance, and gene perturbation. Here, the recent progress and applications of single-cell protein analysis technologies in the last decade are summarized. Current limitations, challenges, and possible future directions in this field are also discussed.

Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line

The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge for understanding biological changes ranging from cellular differentiation to epigenetic responses of diseased cells upon drugging. We integrate experiments and theory to determine the trajectories that single BRAFV600E mutant melanoma cancer cells take between drug-naive and drug-tolerant states. Although single-cell omics tools can yield snapshots of the cell-state landscape, the determination of individual cell trajectories through that space can be confounded by stochastic cell-state switching. We assayed for a panel of signaling, phenotypic, and metabolic regulators at points across 5 days of drug treatment to uncover a cell-state landscape with two paths connecting drug-naive and drug-tolerant states. The trajectory a given cell takes depends upon the drug-naive level of a lineage-restricted transcription factor. Each trajectory exhibits unique druggable susceptibilities, thus updating the paradigm of adaptive resistance development in an isogenic cell population.

Development of microfluidic platform capable of high-throughput absolute quantification of single-cell multiple intracellular proteins from tumor cell lines and patient tumor samples

Quantification of single-cell proteins plays key roles in cell heterogeneity while due to technical limitations absolute numbers of multiple intracellular proteins from large populations of single cells were still missing, leading to compromised results in cell-type classifications. This paper presents a microfluidic platform capable of high-throughput absolute quantification of single-cell multiple types of intracellular proteins where cells stained with fluorescent labelled antibodies are aspirated into the constriction microchannels with excited fluorescent signals detected and translated into numbers of binding sites of targeted proteins based on calibration curves formed by flushing gradient solutions of fluorescent labelled antibodies directly into constriction microchannels. Based on this approach, single-cell numbers of binding sites of β-actin, α-tubulin and β-tubulin from tens of thousands of five representative tumor cell lines were first quantified, reporting cell-type classification rates of 83.0 ± 7.1%. Then single-cell numbers of binding sites of β-actin, biotin and RhoA from thousands of five tumor cell lines with varieties in malignant levels were quantified, reporting cell-type classification rates of 93.7 ± 2.8%. Furthermore, single-cell numbers of binding sites of Ras, c-Myc and p53 from thousands of cells derived from two oral tumor lines of CAL 27, WSU-HN6 and two oral tumor patient samples were quantified, contributing to high classifications of both tumor cell lines (98.6%) and tumor patient samples (83.4%). In conclusion, the developed microfluidic platform was capable of quantifying multiple intracellular proteins from large populations of single cells, and the collected data of protein expressions enabled effective cell-type classifications.

Single-Cell Multi-Omics and Its Prospective Application in Cancer Biology

In recent years, the emergence of single-cell omics technologies, which can profile genomics, transcriptomics, epigenomics, and proteomics, has provided unprecedented insights into characteristics of cancer, enabling higher resolution and accuracy to decipher the cellular and molecular mechanisms relating to tumorigenesis, evolution, metastasis, and immune responses. Single-cell multi-omics technologies, which are developed based on the combination of multiple single-cell mono-omics technologies, can simultaneously analyze RNA expression, single nucleotide polymorphism, epigenetic modification, or protein abundance, enabling the in-depth understanding of gene expression regulatory mechanisms. In this review, the state-of-the-art single-cell multi-omics technologies are summarized and the prospects of their application in cancer biology are discussed.