Single-cell analysis of circadian dynamics in tissue explants

Tracking molecular dynamics in single cells in vivo is instrumental to understanding how cells act and interact in tissues. Current tissue imaging approaches focus on short-term observation and typically nonendogenous or implanted samples. Here we develop an experimental and computational setup that allows for single-cell tracking of a transcriptional reporter over a period of >1 wk in the context of an intact tissue. We focus on the peripheral circadian clock as a model system and measure the circadian signaling of hundreds of cells from two tissues. The circadian clock is an autonomous oscillator whose behavior is well described in isolated cells, but in situ analysis of circadian signaling in single cells of peripheral tissues is as-yet uncharacterized. Our approach allowed us to investigate the oscillatory properties of individual clocks, determine how these properties are maintained among different cells, and assess how they compare to the population rhythm. These experiments, using a wide-field microscope, a previously generated reporter mouse, and custom software to track cells over days, suggest how many signaling pathways might be quantitatively characterized in explant models.

Download Full-text

Functional single cell proteomic profiling of cells with abnormal DNA damage response dynamics

10.1101/2021.10.13.464241 ◽

2021 ◽

Author(s):

Pin-Rui Su ◽

Li You ◽

Cecile Beerens ◽

Karel Bezstarosti ◽

Jeroen Demmers ◽

...

Keyword(s):

Dna Damage ◽

Single Cell ◽

Dna Damage Response ◽

Cell Tracking ◽

Single Cells ◽

Proteomic Profiling ◽

Response Dynamics ◽

Isolated Cells ◽

Cellular Dynamics ◽

Damage Response

Tumor heterogeneity is an important source of cancer therapy resistance. Single cell proteomics has the potential to decipher protein content leading to heterogeneous cellular phenotypes. Single-Cell ProtEomics by Mass Spectrometry (SCoPE-MS) is a recently developed, promising, unbiased proteomic profiling techniques, which allows profiling several tens of single cells for >1000 proteins per cell. However, a method to link single cell proteomes with cellular behaviors is needed to advance this type of profiling technique. Here, we developed a microscopy-based functional single cell proteomic profiling technology, called FUNpro, to link the proteome of individual cells with phenotypes of interest, even if the phenotypes are dynamic or the cells of interest are sparse. FUNpro enables one i) to screen thousands of cells with subcellular resolution and monitor (intra)cellular dynamics using a custom-built microscope, ii) to real-time analyze (intra)cellular dynamics of individual cells using an integrated cell tracking algorithm, iii) to promptly isolate the cells displaying phenotypes of interest, and iv) to single cell proteomically profile the isolated cells. We applied FUNpro to proteomically profile a newly identified small subpopulation of U2OS osteosarcoma cells displaying an abnormal, prolonged DNA damage response (DDR) after ionizing radiation (IR). With this, we identified PDS5A and PGAM5 proteins contributing to the abnormal DDR dynamics and helping the cells survive after IR.

Download Full-text

A strategy to address dissociation-induced compositional and transcriptional bias for single-cell analysis of the human mammary gland

10.1101/2021.02.11.430721 ◽

2021 ◽

Author(s):

Lisa K. Engelbrecht ◽

Alecia-Jane Twigger ◽

Hilary M. Ganz ◽

Christian J. Gabka ◽

Andreas R. Bausch ◽

...

Keyword(s):

Mammary Gland ◽

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Cellular Heterogeneity ◽

Normal Mammary Gland ◽

Isolated Cells ◽

Tissue Dissociation ◽

New Strategy ◽

Gland Function

SummarySingle-cell transcriptomics provide insights into cellular heterogeneity and lineage dynamics that are key to better understanding normal mammary gland function as well as breast cancer initiation and progression. In contrast to murine tissue, human mammary glands require laborious dissociation protocols to isolate single cells. This leads to unavoidable procedure-induced compositional and transcriptional bias. Here, we present a new strategy on how to identify and minimize systematic error by combining different tissue dissociation strategies and then directly comparing composition and transcriptome of isolated cells using single-cell RNA sequencing and flow cytometry. Depending on the tissue isolation strategy, we found dramatic differences in abundance and heterogeneity of certain stromal cells types. Moreover, we identified lineage-specific dissociation-induced gene expression changes that, if left unchecked, could lead to misinterpretation of cellular heterogeneity and, since the basal epithelial population is particularly affected by this, wrongful assignment of putative stem cell populations.

Download Full-text

Natural Barcodes for Longitudinal Single Cell Tracking of Leukemic and Immune Cell Dynamics

Frontiers in Immunology ◽

10.3389/fimmu.2021.788891 ◽

2022 ◽

Vol 12 ◽

Author(s):

Livius Penter ◽

Satyen H. Gohil ◽

Catherine J. Wu

Keyword(s):

Single Cell ◽

Cell Tracking ◽

Immune Cell ◽

Single Cell Analysis ◽

Cell Populations ◽

Cellular Interactions ◽

Nucleotide Polymorphisms ◽

Hematopoietic Stem ◽

Disease Evolution

Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences to serve as personal natural barcodes and review technical implementations in single-cell analysis workflows. Applications of these methodologies include the study of acquired therapeutic resistance and the dissection of donor- and host cellular interactions in the context of allogeneic hematopoietic stem cell transplantation.

Download Full-text

Voltage-gated ion channels mediate the electrotaxis of glioblastoma cells in a hybrid PMMA/PDMS microdevice

10.1101/2020.02.14.948638 ◽

2020 ◽

Author(s):

Hsieh-Fu Tsai ◽

Camilo IJspeert ◽

Amy Q. Shen

Keyword(s):

Machine Learning ◽

Ion Channels ◽

Single Cell ◽

Cell Tracking ◽

Cancer Metastasis ◽

Single Cell Analysis ◽

Single Cells ◽

Patient Specific ◽

Glioblastoma Cells ◽

Voltage Gated

Transformed astrocytes in the most aggressive form cause glioblastoma, the most common cancer in central nervous system with high mortality. The physiological electric field by neuronal local field potentials and tissue polarity may guide the infiltration of glioblastoma cells through the electrotaxis process. However, microenvironments with multiplex gradients are difficult to create. In this work, we have developed a hybrid microfluidic platform to study glioblastoma electrotaxis in controlled microenvironments with high through-put quantitative analysis by a machine learning-powered single cell tracking software. By equalizing the hydrostatic pressure difference between inlets and outlets of the microchannel, uniform single cells can be seeded reliably inside the microdevice. The electrotaxis of two glioblastoma models, T98G and U-251MG, require optimal laminin-containing extracellular matrix and exhibits opposite directional and electro-alignment tendencies. Calcium signaling is a key contributor in glioblastoma pathophysiology but its role in glioblastoma electrotaxis is still an open question. Anodal T98G electrotaxis and cathodal U-251MG electrotaxis require the presence of extracellular calcium cations. U-251MG electrotaxis is dependent on the P/Q-type voltage-gated calcium channel (VGCC) and T98G is dependent on the R-type VGCC. U-251MG and T98G electrotaxis are also mediated by A-type (rapidly inactivating) voltage-gated potassium channels and acid-sensing sodium channels. The involvement of multiple ion channels suggests that the glioblastoma electrotaxis is complex and patient-specific ion channel expression can be critical to develop personalized therapeutics to fight against cancer metastasis. The hybrid microfluidic design and machine learning-powered single cell analysis provide a simple and flexible platform for quantitative investigation of complicated biological systems.

Download Full-text

pcnaDeep: A Fast and Robust Single-Cell Tracking Method Using Deep-Learning Mediated Cell Cycle Profiling

10.1101/2021.09.19.460933 ◽

2021 ◽

Author(s):

Yifan Gui ◽

Shuang Shuang Xie ◽

Yanan Wang ◽

Ping Wang ◽

Renzhi Yao ◽

...

Keyword(s):

Cell Cycle ◽

Deep Learning ◽

Single Cell ◽

Cell Tracking ◽

Single Cell Analysis ◽

Single Cells ◽

Time Lapse ◽

Molecular Control ◽

A Cell ◽

User Friendly

Motivation: Computational methods that track single-cells and quantify fluorescent biosensors in time-lapse microscopy images have revolutionised our approach in studying the molecular control of cellular decisions. One barrier that limits the adoption of single-cell analysis in biomedical research is the lack of efficient methods to robustly track single-cells over cell division events. Results: Here, we developed an application that automatically tracks and assigns mother-daughter relationships of single-cells. By incorporating cell cycle information from a well-established fluorescent cell cycle reporter, we associate mitosis relationships enabling high fidelity long-term single-cell tracking. This was achieved by integrating a deep-learning based fluorescent PCNA signal instance segmentation module with a cell tracking and cell cycle resolving pipeline. The application offers a user-friendly interface and extensible APIs for customized cell cycle analysis and manual correction for various imaging configurations. Availability and Implementation: pcnaDeep is an open-source Python application under the Apache 2.0 licence. The source code, documentation and tutorials are available at https://github.com/chan-labsite/PCNAdeep.

Download Full-text

Optical and genetic tools for in vivo single cell tracking

Journal of Neuroscience Methods ◽

10.1016/j.jneumeth.2021.109192 ◽

2021 ◽

Vol 358 ◽

pp. 109192

Author(s):

Yajie Liang ◽

Liset M. de la Prida

Keyword(s):

Single Cell ◽

Cell Tracking ◽

Genetic Tools

Download Full-text

Microfluidic platform accelerates tissue processing into single cells for molecular analysis and primary culture models

Nature Communications ◽

10.1038/s41467-021-23238-1 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Jeremy A. Lombardo ◽

Marzieh Aliaghaei ◽

Quy H. Nguyen ◽

Kai Kessenbrock ◽

Jered B. Haun

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Cell Analysis ◽

Processing Technologies ◽

Microfluidic Platform ◽

Tissue Processing ◽

Single Cell Rna Sequencing ◽

Culture Models ◽

Tissue Digestion

AbstractTissues are complex mixtures of different cell subtypes, and this diversity is increasingly characterized using high-throughput single cell analysis methods. However, these efforts are hindered, as tissues must first be dissociated into single cell suspensions using methods that are often inefficient, labor-intensive, highly variable, and potentially biased towards certain cell subtypes. Here, we present a microfluidic platform consisting of three tissue processing technologies that combine tissue digestion, disaggregation, and filtration. The platform is evaluated using a diverse array of tissues. For kidney and mammary tumor, microfluidic processing produces 2.5-fold more single cells. Single cell RNA sequencing further reveals that endothelial cells, fibroblasts, and basal epithelium are enriched without affecting stress response. For liver and heart, processing time is dramatically reduced. We also demonstrate that recovery of cells from the system at periodic intervals during processing increases hepatocyte and cardiomyocyte numbers, as well as increases reproducibility from batch-to-batch for all tissues.

Download Full-text

Multiplexed profiling of single-cell extracellular vesicles secretion

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1814348116 ◽

2019 ◽

Vol 116 (13) ◽

pp. 5979-5984 ◽

Cited By ~ 22

Author(s):

Yahui Ji ◽

Dongyuan Qi ◽

Linmei Li ◽

Haoran Su ◽

Xiaojie Li ◽

...

Keyword(s):

Single Cell ◽

Cell Lines ◽

Extracellular Vesicles ◽

Single Cell Analysis ◽

Comprehensive Evaluation ◽

Single Cells ◽

Deep Understanding ◽

Principal Component ◽

Cell Heterogeneity ◽

Indispensable Tool

Extracellular vesicles (EVs) are important intercellular mediators regulating health and diseases. Conventional methods for EV surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EV secretion. Herein, by using spatially patterned antibody barcodes, we realized multiplexed profiling of single-cell EV secretion from more than 1,000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to a deep understanding of previously undifferentiated single-cell heterogeneity underlying EV secretion. Notably, we observed that the decrement of certain EV phenotypes (e.g.,CD63+EV) was associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EV secretion and cytokines secretion simultaneously from the same single cells to investigate the multidimensional spectrum of cellular communications, from which we resolved tiered functional subgroups with distinct secretion profiles by visualized clustering and principal component analysis. In particular, we found that different cell subgroups dominated EV secretion and cytokine secretion. The technology introduced here enables a comprehensive evaluation of EV secretion heterogeneity at single-cell level, which may become an indispensable tool to complement current single-cell analysis and EV research.

Download Full-text