High-efficiency single cell encapsulation and size selective capture of cells in picoliter droplets based on hydrodynamic micro-vortices

Lab on a Chip ◽  
2017 ◽  
Vol 17 (24) ◽  
pp. 4324-4333 ◽  
Author(s):  
Gopakumar Kamalakshakurup ◽  
Abraham P. Lee
Keyword(s):  
Single Cell ◽  
Paradigm Shift ◽  
Cell Biology ◽  
High Efficiency ◽  
Single Cell Analysis ◽  
Cell Encapsulation ◽  
Cell Analysis ◽  
Single Cell Encapsulation

Single cell analysis has emerged as a paradigm shift in cell biology to understand the heterogeneity of individual cells in a clone for pathological interrogation.

scholarly journals Improving Single-Cell Encapsulation Efficiency and Reliability through Neutral Buoyancy of Suspension

Micromachines ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 94 ◽  
Author(s):  
Hangrui Liu ◽  
Ming Li ◽  
Yan Wang ◽  
Jim Piper ◽  
Lianmei Jiang
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Leukemia Cell ◽  
Cell Encapsulation ◽  
Leukemia Cell Line ◽  
Cell Analysis ◽  
Monocytic Leukemia ◽  
Neutral Buoyancy ◽  
Single Cell Encapsulation ◽  
Neutrally Buoyant

Single-cell analysis is of critical importance in revealing cell-to-cell heterogeneity by characterizing individual cells and identifying minority sub-populations of interest. Droplet-based microfluidics has been widely used in the past decade to achieve high-throughput single-cell analysis. However, to maximize the proportion of single-cell emulsification is challenging due to cell sedimentation and aggregation. The purpose of this study was to investigate the influence of single-cell encapsulation and incubation through the use of neutral buoyancy. As a proof of concept, OptiPrep™ was used to create neutrally buoyant cell suspensions of THP-1, a human monocytic leukemia cell line, for single-cell encapsulation and incubation. We found that using a neutrally buoyant suspension greatly increased the efficiency of single-cell encapsulation in microdroplets and eliminated unnecessary cell loss. Moreover, the presence of OptiPrep™ was shown to not affect cellular viability. This method significantly improved the effectiveness of single-cell study in a non-toxic environment and is expected to broadly facilitate single-cell analysis.

scholarly journals Accelerating a paradigm shift: The Common Fund Single Cell Analysis Program

2018 ◽  
Vol 4 (8) ◽  
pp. eaat8573 ◽  
Author(s):  
Ananda L. Roy ◽  
Richard Conroy ◽  
Jessica Smith ◽  
Yong Yao ◽  
Andrea C. Beckel-Mitchener ◽  
...  
Keyword(s):  
Single Cell ◽  
Paradigm Shift ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Analysis Program ◽  
Common Fund ◽  
The Common

Single-cell analysis based on lab on a chip fluidic system

2015 ◽  
Vol 7 (20) ◽  
pp. 8524-8533 ◽  
Author(s):  
Alireza Valizadeh ◽  
Ahmad Yari Khosroushahi
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Lab On A Chip ◽  
Spatiotemporal Analysis ◽  
Cell Analysis ◽  
System P

The combination of nano/microfabrication-based technologies with cell biology has laid the foundation for facilitating the spatiotemporal analysis of single cells under well-defined physiologically relevant conditions.

scholarly journals 12 Grand Challenges in Single-Cell Data Science

2019 ◽  
Author(s):  
David Laehnemann ◽  
Johannes Köster ◽  
Ewa Szczurek ◽  
Davis J McCarthy ◽  
Stephanie C Hicks ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Data Science ◽  
Single Cell Analysis ◽  
State Of The Art ◽  
Cell Analysis ◽  
Open Problems ◽  
Single Cell Sequencing ◽  
Current State ◽  
Cell Data

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.

scholarly journals 12 Grand challenges in single-cell data science

2019 ◽  
Author(s):  
David Laehnemann ◽  
Johannes Köster ◽  
Ewa Szcureck ◽  
Davis McCarthy ◽  
Stephanie C Hicks ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Data Science ◽  
Single Cell Analysis ◽  
State Of The Art ◽  
Cell Analysis ◽  
Open Problems ◽  
Single Cell Sequencing ◽  
Current State ◽  
Cell Data

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single Cell Data Science' for the coming years.

Development of Visible-Wavelength MALDI Cell Mass Spectrometry for High-Efficiency Single-Cell Analysis

2016 ◽  
Vol 88 (23) ◽  
pp. 11913-11918 ◽  
Author(s):  
Caiqiao Xiong ◽  
Xiaoyu Zhou ◽  
Qing He ◽  
Xi Huang ◽  
Jiyun Wang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Single Cell ◽  
High Efficiency ◽  
Single Cell Analysis ◽  
Cell Mass ◽  
Cell Analysis ◽  
Visible Wavelength ◽  
Cell Mass Spectrometry

scholarly journals 12 Grand Challenges in Single-Cell Data Science

2019 ◽  
Author(s):  
David Laehnemann ◽  
Johannes Köster ◽  
Ewa Szczurek ◽  
Davis J McCarthy ◽  
Stephanie C Hicks ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Data Science ◽  
Single Cell Analysis ◽  
State Of The Art ◽  
Cell Analysis ◽  
Open Problems ◽  
Single Cell Sequencing ◽  
Current State ◽  
Cell Data

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.

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