scholarly journals High-Throughput Secretomic Analysis of Single Cells to Assess Functional Cellular Heterogeneity

2016 ◽  
pp. 41-54 ◽  
Author(s):  
Kathryn Miller-Jensen ◽  
Rong Fan
Keyword(s):  
High Throughput ◽  
Single Cells ◽  
Cellular Heterogeneity

scholarly journals Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sunny Z. Wu ◽  
Daniel L. Roden ◽  
Ghamdan Al-Eryani ◽  
Nenad Bartonicek ◽  
Kate Harvey ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cells ◽  
Cellular Heterogeneity ◽  
Tumour Heterogeneity ◽  
Fresh Tissue ◽  
Human Cancers ◽  
Cryopreserved Cell ◽  
Single Cell Rna Sequencing

Abstract Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

scholarly journals CoTECH for single-cell joint detection of transcriptome and chromatin occupancy

2021 ◽  
Author(s):  
Yingjie Luo ◽  
Haiqing Xiong ◽  
Qianhao Wang ◽  
Xianhong Yu ◽  
Aibin He
Keyword(s):  
Gene Regulation ◽  
Single Cell ◽  
High Throughput ◽  
Single Cells ◽  
Cellular Heterogeneity ◽  
Joint Detection ◽  
Biological Processes ◽  
Experimental Procedure ◽  
Higher Dimensional

Abstract Here we present CoTECH, a high-throughput co-aasay that measures chromatin occupancy and transcriptome in single cells. The CoTECH method adopts a combinatorial indexing strategy to enrich chromatin fragments of interest as reported in CoBATCH in combination with a modified Smart-seq2 procedure to simultaneously capture the 3’ mRNA profiles in the same single cells. The whole experimental procedure can be handled within three days.The CoTECH acquires data quality of 1000-9000 unique mapped reads (DNA partition) and 1500-4000 expressed genes (RNA partition) per cell. Experimentally linking chromatin occupancy to transcriptional outputs and inferred molecular association between multimodal omics datasets made possible by CoTECH enables reconstructions of higher dimensional epigenomic landscape, providing new insights into epigenome-centric gene regulation and cellular heterogeneity in many biological processes. This step-by-step protocol is related to the publication “Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions” in Nature Methods.

scholarly journals RefCell: Multi-dimensional analysis of image-based high-throughput screens based on ‘typical cells’

2018 ◽  
Author(s):  
Yang Shen ◽  
Nard Kubben ◽  
Julián Candia ◽  
Alexandre V. Morozov ◽  
Tom Misteli ◽  
...  
Keyword(s):  
Dimensional Analysis ◽  
High Throughput ◽  
High Throughput Screening ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Premature Aging ◽  
Cellular Heterogeneity ◽  
High Level ◽  
High Throughput Screens ◽  
High Throughput Imaging

AbstractBackgroundImage-based high-throughput screening (HTS) reveals a high level of heterogeneity in single cells and multiple cellular states may be observed within a single population. Cutting-edge high-dimensional analysis methods are successful in characterizing cellular heterogeneity, but they suffer from the “curse of dimensionality” and non-standardized outputs.ResultsHere we introduce RefCell, a multi-dimensional analysis pipeline for image-based HTS that reproducibly captures cells with typical combinations of features in reference states, and uses these “typical cells” as a reference for classification and weighting of metrics. RefCell quantitatively assesses the heterogeneous deviations from typical behavior for each analyzed perturbation or sample.ConclusionsWe apply RefCell to the analysis of data from a high-throughput imaging screen of a library of 320 ubiquitin protein targeted siRNAs selected to gain insights into the mechanisms of premature aging (progeria). RefCell yields results comparable to a more complex clustering based single cell analysis method, which both reveal more potential hits than conventional average based analysis.

scholarly journals Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Maeve O’Huallachain ◽  
Felice-Alessio Bava ◽  
Mary Shen ◽  
Carolina Dallett ◽  
Sri Paladugu ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Model Systems ◽  
Cellular Heterogeneity ◽  
Human Model ◽  
Targeted Analysis ◽  
Technological Advances ◽  
And Function

AbstractSingle-cell omics provide insight into cellular heterogeneity and function. Recent technological advances have accelerated single-cell analyses, but workflows remain expensive and complex. We present a method enabling simultaneous, ultra-high throughput single-cell barcoding of millions of cells for targeted analysis of proteins and RNAs. Quantum barcoding (QBC) avoids isolation of single cells by building cell-specific oligo barcodes dynamically within each cell. With minimal instrumentation (four 96-well plates and a multichannel pipette), cell-specific codes are added to each tagged molecule within cells through sequential rounds of classical split-pool synthesis. Here we show the utility of this technology in mouse and human model systems for as many as 50 antibodies to targeted proteins and, separately, >70 targeted RNA regions. We demonstrate that this method can be applied to multi-modal protein and RNA analyses. It can be scaled by expansion of the split-pool process and effectively renders sequencing instruments as versatile multi-parameter flow cytometers.

scholarly journals Probing Single-Cell Macrophage Polarization and Heterogeneity Using Thermo-Reversible Hydrogels in Droplet-Based Microfluidics

2021 ◽  
Vol 9 ◽  
Author(s):  
B. M. Tiemeijer ◽  
M. W. D. Sweep ◽  
J. J. F. Sleeboom ◽  
K. J. Steps ◽  
J. F. van Sprang ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Biological Function ◽  
Single Cells ◽  
Macrophage Polarization ◽  
Cell Polarization ◽  
Droplet Microfluidics ◽  
Cellular Heterogeneity ◽  
Adherent Cell ◽  
M2 Polarization

Human immune cells intrinsically exist as heterogenous populations. To understand cellular heterogeneity, both cell culture and analysis should be executed with single-cell resolution to eliminate juxtacrine and paracrine interactions, as these can lead to a homogenized cell response, obscuring unique cellular behavior. Droplet microfluidics has emerged as a potent tool to culture and stimulate single cells at high throughput. However, when studying adherent cells at single-cell level, it is imperative to provide a substrate for the cells to adhere to, as suspension culture conditions can negatively affect biological function and behavior. Therefore, we combined a droplet-based microfluidic platform with a thermo-reversible polyisocyanide (PIC) hydrogel, which allowed for robust droplet formation at low temperatures, whilst ensuring catalyzer-free droplet gelation and easy cell recovery after culture for downstream analysis. With this approach, we probed the heterogeneity of highly adherent human macrophages under both pro-inflammatory M1 and anti-inflammatory M2 polarization conditions. We showed that co-encapsulation of multiple cells enhanced cell polarization compared to single cells, indicating that cellular communication is a potent driver of macrophage polarization. Additionally, we highlight that culturing single macrophages in PIC hydrogel droplets displayed higher cell viability and enhanced M2 polarization compared to single macrophages cultured in suspension. Remarkably, combining phenotypical and functional analysis on single cultured macrophages revealed a subset of cells in a persistent M1 state, which were undetectable in conventional bulk cultures. Taken together, combining droplet-based microfluidics with hydrogels is a versatile and powerful tool to study the biological function of adherent cell types at single-cell resolution with high throughput.

scholarly journals High-Throughput Secretomic Analysis of Single Cells to Assess Functional Cellular Heterogeneity

2013 ◽  
Vol 85 (4) ◽  
pp. 2548-2556 ◽  
Author(s):  
Yao Lu ◽  
Jonathan J. Chen ◽  
Luye Mu ◽  
Qiong Xue ◽  
Yu Wu ◽  
...  
Keyword(s):  
High Throughput ◽  
Single Cells ◽  
Cellular Heterogeneity

scholarly journals Cellular lensing and near infrared fluorescent nanosensor arrays to enable chemical efflux cytometry

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Soo-Yeon Cho ◽  
Xun Gong ◽  
Volodymyr B. Koman ◽  
Matthias Kuehne ◽  
Sun Jin Moon ◽  
...  
Keyword(s):  
Near Infrared ◽  
Single Cells ◽  
Microfluidic Channel ◽  
Human Monocyte ◽  
Cellular Heterogeneity ◽  
Label Free ◽  
Nanotube Array ◽  
Chemical Cytometry ◽  
Rich Information ◽  
Non Destructive

AbstractNanosensors have proven to be powerful tools to monitor single cells, achieving spatiotemporal precision even at molecular level. However, there has not been way of extending this approach to statistically relevant numbers of living cells. Herein, we design and fabricate nanosensor array in microfluidics that addresses this limitation, creating a Nanosensor Chemical Cytometry (NCC). nIR fluorescent carbon nanotube array is integrated along microfluidic channel through which flowing cells is guided. We can utilize the flowing cell itself as highly informative Gaussian lenses projecting nIR profiles and extract rich information. This unique biophotonic waveguide allows for quantified cross-correlation of biomolecular information with various physical properties and creates label-free chemical cytometer for cellular heterogeneity measurement. As an example, the NCC can profile the immune heterogeneities of human monocyte populations at attomolar sensitivity in completely non-destructive and real-time manner with rate of ~600 cells/hr, highest range demonstrated to date for state-of-the-art chemical cytometry.

scholarly journals A platform for high-throughput bioenergy production phenotype characterization in single cells

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Laimonas Kelbauskas ◽  
Honor Glenn ◽  
Clifford Anderson ◽  
Jacob Messner ◽  
Kristen B. Lee ◽  
...  
Keyword(s):  
High Throughput ◽  
Single Cells ◽  
Bioenergy Production ◽  
Phenotype Characterization

scholarly journals P02.10 FocuSCOPE: a single cell, multi-omics solution to simultaneously analyze tumor variants and microenvironment

2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A12.1-A12
Author(s):  
Y Arjmand Abbassi ◽  
N Fang ◽  
W Zhu ◽  
Y Zhou ◽  
Y Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
High Throughput ◽  
Immune Cells ◽  
Genetic Variants ◽  
Expression Profiles ◽  
Single Cells ◽  
Gene Expression Profiles ◽  
Single Cell Sequencing

Recent advances of high-throughput single cell sequencing technologies have greatly improved our understanding of the complex biological systems. Heterogeneous samples such as tumor tissues commonly harbor cancer cell-specific genetic variants and gene expression profiles, both of which have been shown to be related to the mechanisms of disease development, progression, and responses to treatment. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in tumor responses to systematic therapy such as immunotherapy or cell therapy. However, most current high-throughput single cell sequencing methods detect only gene expression levels or epigenetics events such as chromatin conformation. The information on important genetic variants including mutation or fusion is not captured. To better understand the mechanisms of tumor responses to systematic therapy, it is essential to decipher the connection between genotype and gene expression patterns of both tumor cells and cells in the tumor microenvironment. We developed FocuSCOPE, a high-throughput multi-omics sequencing solution that can detect both genetic variants and transcriptome from same single cells. FocuSCOPE has been used to successfully perform single cell analysis of both gene expression profiles and point mutations, fusion genes, or intracellular viral sequences from thousands of cells simultaneously, delivering comprehensive insights of tumor and immune cells in tumor microenvironment at single cell resolution.Disclosure InformationY. Arjmand Abbassi: None. N. Fang: None. W. Zhu: None. Y. Zhou: None. Y. Chen: None. U. Deutsch: None.

scholarly journals Accurate classification of protein subcellular localization from high throughput microscopy images using deep learning

2016 ◽  
Author(s):  
Tanel Pärnamaa ◽  
Leopold Parts
Keyword(s):  
Deep Learning ◽  
Subcellular Localization ◽  
High Throughput ◽  
Single Cells ◽  
Cellular Compartment ◽  
Cell Localization ◽  
Image Characteristics ◽  
Basic Image ◽  
Training Examples

High throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high throughput microscopy.

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