A microfluidic robot for rare cell sorting based on machine vision identification and multi-step sorting strategy

Wang, Yu; Wang, Dong-Fei; Wang, Huifeng; Wang, Jianwei; Pan, Jian-Zhang; Guo, Xiaogang; Fang, Qun

doi:10.1016/j.talanta.2021.122136

Cited by 13 publications

(11 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Establishment of the PiSPA workflow. We first used an improved microfluidic liquid handling platform 26 in the picoliter to nanoliter range previously developed by the authors' group based on the sequential operation droplet array (SODA) technique 27 . It achieved the automated bright-field or fluorescence imaging and capture of single target cells from cell suspensions by a tapered capillary probe connected with a high-precision syringe pump under the probe pick-up mode.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Pick-up Single-Cell Proteomic Analysis for Quantifying up to 3000 Proteins in a Tumor Cell

Wang

Guan

Shi³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a tumor cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 1804-3349, 1778-3049 and 1074-2487 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27), respectively. Benefiting from the flexible cell picking-up ability, we study tumor cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.

show abstract

Section: Resultsmentioning

confidence: 99%

“…Single cell capture. We used the liquid handling robot modified from a system for singlecell soring 26 to achieve the operations of single cell capture and sample pretreatment. It consisted of a microscopic imaging module, a capillary probe (10 cm length, 250 μm o.d., 150 μm i.d., tip size, 35 μm i.d.)…”

Section: Methodsmentioning

confidence: 99%

Pick-up Single-Cell Proteomic Analysis for Quantifying up to 3000 Proteins in a Tumor Cell

Wang

Guan

Shi³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Robotic manipulation allowed for high precision contact of chip micropillars with pin tip, thus creating similar droplet microreactors. Very recently, the same research group [43] used a microfluidic robot and machine vision‐based detection for single cell sorting of endothelial progenitor cells in human blood samples. Here, 20–25 nL droplet reactors with single cells were formed with a high sorting purity of >90%.…”

Section: Approachesmentioning

confidence: 99%

Automation of single‐cell proteomic sample preparation

2021

View full text Add to dashboard Cite

Molecular heterogeneity exists at different spatial scales in biological samples and is an important parameter in the development of pathologies and resistances to therapies. When aiming to reach molecular heterogeneity of cells at extremely low spatial scales, single‐cell analysis can be the ultimate choice. Proteomics performed in bulk population of cells (macroproteomics) is prone to mask molecular heterogeneity. Mass spectrometry‐based single cell proteomics (SCP‐MS) is the right solution to overcome this issue. Three main problems can be identified using SCP‐MS: (i) analytical loss during sample preparation, (ii) inefficient microinjection/delivery of proteins/peptides from samples to MS and (iii) low analytical throughput. Technologies for automation of SCP have recently gained attention to improve methods accuracy, sensitivity, throughput and in‐depth and low‐biased proteome analysis. In this minireview, we therefore overview the state‐of‐the‐art of automation of SCP‐MS sample preparation approaches.

show abstract

“…The CellCelector is equipped with different picking modules using capillaries, metal scraping tips, or plastic tips. In addition to translation into commercially available instruments, computer vision and robotic sorting have also been incorporated into microfluidic cell sorting [44]. Similarly to LCM, robotic cell picking techniques are often lowerthroughput in comparison to other methods (e.g.…”

Section: Computer Vision and Robotic Cell Picking Techniquesmentioning

confidence: 99%

Preparation of Tissues and Heterogeneous Cellular Samples for Single-Cell Analysis

Welch¹,

Tripathi²

2021

Sample Preparation Techniques for Chemical Analysis

View full text Add to dashboard Cite

While sample preparation techniques for the chemical and biochemical analysis of tissues are fairly well advanced, the preparation of complex, heterogenous samples for single-cell analysis can be difficult and challenging. Nevertheless, there is growing interest in preparing complex cellular samples, particularly tissues, for analysis via single-cell resolution techniques such as single-cell sequencing or flow cytometry. Recent microfluidic tissue dissociation approaches have helped to expedite the preparation of single cells from tissues through the use of optimized, controlled mechanical forces. Cell sorting and selective cellular recovery from heterogenous samples have also gained traction in biosensors, microfluidic systems, and other diagnostic devices. Together, these recent developments in tissue disaggregation and targeted cellular retrieval have contributed to the development of increasingly streamlined sample preparation workflows for single-cell analysis technologies, which minimize equipment requirements, enable lower processing times and costs, and pave the way for high-throughput, automated technologies. In this chapter, we survey recent developments and emerging trends in this field.

show abstract

A microfluidic robot for rare cell sorting based on machine vision identification and multi-step sorting strategy

Cited by 13 publications

References 36 publications

Pick-up Single-Cell Proteomic Analysis for Quantifying up to 3000 Proteins in a Tumor Cell

Pick-up Single-Cell Proteomic Analysis for Quantifying up to 3000 Proteins in a Tumor Cell

Automation of single‐cell proteomic sample preparation

Preparation of Tissues and Heterogeneous Cellular Samples for Single-Cell Analysis

Contact Info

Product

Resources

About