Single Cell Micro-Pillar-Based Characterization of Endothelial and Fibroblast Cell Mechanics

Mechanotransduction, the ability of cells to sense and respond to the mechanical cues from their microenvironment, plays an important role in numerous cellular processes, ranging from cell migration to differentiation. Several techniques have been developed to investigate the underlying mechanisms of mechanotransduction, in particular, force measurement-based techniques. However, we still lack basic single cell quantitative comparison on the mechanical properties of commonly used cell types, such as endothelial and fibroblast cells. Such information is critical to provide a precedent for studying complex tissues and organs that consist of various cell types. In this short communication, we report on the mechanical characterization of the commonly used endothelial and fibroblast cells at the single cell level. Using a micropillar-based assay, we measured the traction force profiles of these cells. Our study showcases differences between the two cell types in their traction force distribution and morphology. The results reported can be used as a reference and to lay the groundwork for future analysis of numerous disease models involving these cells.

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Single cell micro-pillar-based characterization of endothelial and fibroblast cell mechanics

10.1101/2021.10.11.463878 ◽

2021 ◽

Author(s):

Julia Eckert ◽

Yasmine Abouleila ◽

Thomas Schmidt ◽

Alireza Mashaghi

Keyword(s):

Single Cell ◽

Force Measurement ◽

Traction Force ◽

Fibroblast Cell ◽

Cell Types ◽

Fibroblast Cells ◽

Cellular Processes ◽

Sense And Respond ◽

Underlying Mechanisms

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Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽

10.1186/s12864-020-07358-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Tracy M. Yamawaki ◽

Daniel R. Lu ◽

Daniel C. Ellwanger ◽

Dev Bhatt ◽

Paolo Manzanillo ◽

...

Keyword(s):

Single Cell ◽

High Throughput ◽

Immune Cell ◽

Cell Types ◽

Data Interpretation ◽

Detection Sensitivity ◽

Rna Seq ◽

Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

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Single Cell Atlas of Human Dura Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response

10.1101/2021.08.03.454066 ◽

2021 ◽

Author(s):

Anthony Z Wang ◽

Jay Bowman-Kirigin ◽

Rupen Desai ◽

Pujan Patel ◽

Bhuvic Patel ◽

...

Keyword(s):

Single Cell ◽

Immune Cell ◽

Immune Surveillance ◽

Copy Number Variant ◽

Cell Types ◽

Cell Receptor ◽

Immune Microenvironment ◽

Clinical Models ◽

Insight Into

Recent investigation of the meninges, specifically the dura layer, has highlighted its importance in CNS immune surveillance beyond a purely structural role. However, most of our understanding of the meninges stems from the use of pre-clinical models rather than human samples. In this study, we use single cell RNA-sequencing to perform the first characterization of both non-tumor-associated human dura and meningioma samples. First, we reveal a complex immune microenvironment in human dura that is transcriptionally distinct from that of meningioma. In addition, through T cell receptor sequencing, we show significant TCR overlap between matched dura and meningioma samples. We also identify a functionally heterogeneous population of non-immune cell types and report copy-number variant heterogeneity within our meningioma samples. Our comprehensive investigation of both the immune and non-immune cell landscapes of human dura and meningioma at a single cell resolution provide new insight into previously uncharacterized roles of human dura.

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Single-cell RNA-seq data clustering: A survey with performance comparison study

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720020400053 ◽

2020 ◽

Vol 18 (04) ◽

pp. 2040005

Author(s):

Ruiyi Li ◽

Jihong Guan ◽

Shuigeng Zhou

Keyword(s):

Single Cell ◽

Data Clustering ◽

Performance Metrics ◽

Clustering Algorithms ◽

Cell Types ◽

Performance Comparison ◽

Cellular Heterogeneity ◽

Clustering Methods ◽

Multiple Perspectives ◽

Underlying Mechanisms

Clustering analysis has been widely applied to single-cell RNA-sequencing (scRNA-seq) data to discover cell types and cell states. Algorithms developed in recent years have greatly helped the understanding of cellular heterogeneity and the underlying mechanisms of biological processes. However, these algorithms often use different techniques, were evaluated on different datasets and compared with some of their counterparts usually using different performance metrics. Consequently, there lacks an accurate and complete picture of their merits and demerits, which makes it difficult for users to select proper algorithms for analyzing their data. To fill this gap, we first do a review on the major existing scRNA-seq data clustering methods, and then conduct a comprehensive performance comparison among them from multiple perspectives. We consider 13 state of the art scRNA-seq data clustering algorithms, and collect 12 publicly available real scRNA-seq datasets from the existing works to evaluate and compare these algorithms. Our comparative study shows that the existing methods are very diverse in performance. Even the top-performance algorithms do not perform well on all datasets, especially those with complex structures. This suggests that further research is required to explore more stable, accurate, and efficient clustering algorithms for scRNA-seq data.

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Hypoxia. 4. Hypoxia and ion channel function

AJP Cell Physiology ◽

10.1152/ajpcell.00512.2010 ◽

2011 ◽

Vol 300 (5) ◽

pp. C951-C967 ◽

Cited By ~ 57

Author(s):

Larissa A. Shimoda ◽

Jan Polak

Keyword(s):

Ion Channels ◽

Cell Function ◽

Critical Role ◽

Cardiac Contractility ◽

Cell Types ◽

Cellular Processes ◽

Oxygen Sensitive ◽

Sense And Respond ◽

And Function ◽

And Control

The ability to sense and respond to oxygen deprivation is required for survival; thus, understanding the mechanisms by which changes in oxygen are linked to cell viability and function is of great importance. Ion channels play a critical role in regulating cell function in a wide variety of biological processes, including neuronal transmission, control of ventilation, cardiac contractility, and control of vasomotor tone. Since the 1988 discovery of oxygen-sensitive potassium channels in chemoreceptors, the effect of hypoxia on an assortment of ion channels has been studied in an array of cell types. In this review, we describe the effects of both acute and sustained hypoxia (continuous and intermittent) on mammalian ion channels in several tissues, the mode of action, and their contribution to diverse cellular processes.

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Evaluating sources of technical variability in the mechano-node-pore sensing pipeline and their effect on the reproducibility of single-cell mechanical phenotyping

PLoS ONE ◽

10.1371/journal.pone.0258982 ◽

2021 ◽

Vol 16 (10) ◽

pp. e0258982

Author(s):

Brian Li ◽

Kristen L. Cotner ◽

Nathaniel K. Liu ◽

Stefan Hinz ◽

Mark A. LaBarge ◽

...

Keyword(s):

Mechanical Properties ◽

Single Cell ◽

Mechanical Testing ◽

Cell Types ◽

Biologically Relevant ◽

Analytical Instruments ◽

Technical Variability ◽

Novice Users ◽

High Repeatability

Cellular mechanical properties can reveal physiologically relevant characteristics in many cell types, and several groups have developed microfluidics-based platforms to perform high-throughput single-cell mechanical testing. However, prior work has performed only limited characterization of these platforms’ technical variability and reproducibility. Here, we evaluate the repeatability performance of mechano-node-pore sensing, a single-cell mechanical phenotyping platform developed by our research group. We measured the degree to which device-to-device variability and semi-manual data processing affected this platform’s measurements of single-cell mechanical properties. We demonstrated high repeatability across the entire technology pipeline even for novice users. We then compared results from identical mechano-node-pore sensing experiments performed by researchers in two different laboratories with different analytical instruments, demonstrating that the mechanical testing results from these two locations are in agreement. Our findings quantify the expectation of technical variability in mechano-node-pore sensing even in minimally experienced hands. Most importantly, we find that the repeatability performance we measured is fully sufficient for interpreting biologically relevant single-cell mechanical measurements with high confidence.

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Bulk Tissue Cell Type Deconvolution with Multi-Subject Single-Cell Expression Reference

10.1101/354944 ◽

2018 ◽

Cited By ~ 1

Author(s):

Xuran Wang ◽

Jihwan Park ◽

Katalin Susztak ◽

Nancy R. Zhang ◽

Mingyao Li

Keyword(s):

Single Cell ◽

Cell Types ◽

Cellular Heterogeneity ◽

Tissue Cell ◽

Specific Gene ◽

Rna Seq ◽

Cell Type ◽

Cell Type Specific ◽

Cell Expression

AbstractWe present MuSiC, a method that utilizes cell-type specific gene expression from single-cell RNA sequencing (RNA-seq) data to characterize cell type compositions from bulk RNA-seq data in complex tissues. When applied to pancreatic islet and whole kidney expression data in human, mouse, and rats, MuSiC outperformed existing methods, especially for tissues with closely related cell types. MuSiC enables characterization of cellular heterogeneity of complex tissues for identification of disease mechanisms.

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Systematic Comparison of High-Throughput Single-Cell RNAseq Methods for Immune Cell Profiling

10.21203/rs.3.rs-72851/v1 ◽

2020 ◽

Author(s):

Chi-Ming Kevin Li ◽

Tracy M Yamawaki ◽

Daniel R Lu ◽

Daniel C Ellwanger ◽

Dev Bhatt ◽

...

Keyword(s):

Single Cell ◽

High Throughput ◽

Immune Cell ◽

Cell Types ◽

Drop Out ◽

Detection Sensitivity ◽

Rna Seq ◽

Cell Recovery

Abstract Background: Elucidation of immune populations with single-cell RNA-seq has greatly benefited the fieldof immunology by deepening the characterization of immune heterogeneity and leading to thediscovery of new subtypes. However, single-cell methods inherently suffer from limitations in therecovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropoutevents. This issue is often compounded by limited sample availability and limited prior knowledge ofheterogeneity, which can confound data interpretation.Results: Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. Weprepared 21 libraries under identical conditions of a defined mixture of two human and two murinelymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluatemethods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expressionsignatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5’v1 and 3’ v3 methods. We demonstrate that these methods have fewer drop-out events whichfacilitates the identification of differentially-expressed genes and improves the concordance of singlecellprofiles to immune bulk RNA-seq signatures.Conclusion: Overall, our characterization of immune cell mixtures provides useful metrics, which canguide selection of a high-throughput single-cell RNA-seq method for profiling more complex immunecellheterogeneity usually found in vivo.

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Intrinsic OXPHOS limitations underlie cellular bioenergetics in leukemia

eLife ◽

10.7554/elife.63104 ◽

2021 ◽

Vol 10 ◽

Author(s):

Margaret A M Nelson ◽

Kelsey L McLaughlin ◽

James T Hagen ◽

Hannah S Coalson ◽

Cameron Schmidt ◽

...

Keyword(s):

Cancer Biology ◽

Atp Synthesis ◽

Therapeutic Index ◽

Cell Types ◽

Mitochondrial Metabolism ◽

Metabolic Phenotype ◽

Hematopoietic Stem ◽

Cellular Processes ◽

Underlying Mechanisms ◽

Primary Output

Typified by oxidative phosphorylation (OXPHOS), mitochondria catalyze a wide variety of cellular processes seemingly critical for malignant growth. As such, there is considerable interest in targeting mitochondrial metabolism in cancer. However, notwithstanding the few drugs targeting mutant dehydrogenase activity, nearly all hopeful 'mito-therapeutics' cannot discriminate cancerous from non-cancerous OXPHOS and thus suffer from a limited therapeutic index. The present project was based on the premise that the development of efficacious mitochondrial-targeted anti-cancer compounds requires answering two fundamental questions: 1) is mitochondrial bioenergetics in fact different between cancer and non-cancer cells? and 2) If so, what are the underlying mechanisms? Such information is particularly critical for the subset of human cancers, including acute myeloid leukemia (AML), in which alterations in mitochondrial metabolism are implicated in various aspects of cancer biology (e.g., clonal expansion and chemoresistance). Herein, we leveraged an in-house diagnostic biochemical workflow to comprehensively evaluate mitochondrial bioenergetic efficiency and capacity in various hematological cell types, with a specific focus on OXPHOS dynamics in AML. Consistent with prior reports, clonal cell expansion, characteristic of leukemia, was universally associated with a hyper-metabolic phenotype which included increases in basal and maximal glycolytic and respiratory flux. However, despite having nearly 2-fold more mitochondria per cell, clonally expanding hematopoietic stem cells, leukemic blasts, as well as chemoresistant AML were all consistently hallmarked by intrinsic limitations in oxidative ATP synthesis (i.e., OXPHOS). Remarkably, by performing experiments across a physiological span of ATP free energy (i.e, ΔGATP), we provide direct evidence that, rather than contributing to cellular ΔGATP, leukemic mitochondria are particularly poised to consume ATP. Relevant to AML biology, acute restoration of OXPHOS kinetics proved highly cytotoxic to leukemic blasts, suggesting that active OXPHOS repression supports aggressive disease dissemination in AML. Taken together, these findings argue against ATP being the primary output of mitochondria in leukemia and provide proof-of-principle that restoring, rather than disrupting, OXPHOS and/or cellular ΔGATP in cancer may represent an untapped therapeutic avenue for combatting hematological malignancy and chemoresistance.

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An acoustic platform for single-cell, high-throughput measurements of the viscoelastic properties of cells

10.1101/2020.09.07.286898 ◽

2020 ◽

Author(s):

Valentin Romanov ◽

Giulia Silvani ◽

Huiyu Zhu ◽

Charles D Cox ◽

Boris Martinac

Keyword(s):

Mechanical Properties ◽

Single Cell ◽

High Throughput ◽

Single Cells ◽

Adherent Cells ◽

Dependent Manner ◽

Cellular Processes ◽

Membrane Cytoskeleton ◽

Change Temperature

ABSTRACTCellular processes including adhesion, migration and differentiation are governed by the distinct mechanical properties of each cell. Importantly, the mechanical properties of individual cells can vary depending on local physical and biochemical cues in a time-dependent manner resulting in significant inter-cell heterogeneity. While several different methods have been developed to interrogate the mechanical properties of single cells, throughput to capture this heterogeneity remains an issue. While new high-throughput techniques are slowly emerging, they are primarily aimed at characterizing cells in suspension, whereas high-throughput measurements of adherent cells have proven to be more challenging. Here, we demonstrate single-cell, high-throughput characterization of adherent cells using acoustic force spectroscopy. We demonstrate that cells undergo marked changes in viscoelasticity as a function of temperature, the measurements of which are facilitated by a closed microfluidic culturing environment that can rapidly change temperature between 21 °C and 37 °C. In addition, we show quantitative differences in cells exposed to different pharmacological treatments specifically targeting the membrane-cytoskeleton interface. Further, we utilize the high-throughput format of the AFS to rapidly probe, in excess of 1000 cells, three different cell-lines expressing different levels of a mechanosensitive protein, Piezo1, demonstrating the ability to differentiate between cells based on protein expression levels.

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