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.

Statistical single-cell analysis of cell cycle-dependent quantum dot cytotoxicity and cellular uptake using a microfluidic system

RSC Advances ◽  
2014 ◽  
Vol 4 (47) ◽  
pp. 24929-24934 ◽  
Author(s):  
Jing Wu ◽  
Haifang Li ◽  
Qiushui Chen ◽  
Xuexia Lin ◽  
Wu Liu ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Quantum Dot ◽  
Single Cell ◽  
Cellular Uptake ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Microfluidic System ◽  
Cell Analysis ◽  
System P ◽  
Cycle Dependent

The response of single cells in different cell cycle phases to QD cytotoxicity studied on a microfluidic device.

scholarly journals Specific splice junction detection in single cells with SICILIAN

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Roozbeh Dehghannasiri ◽  
Julia Eve Olivieri ◽  
Ana Damljanovic ◽  
Julia Salzman
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Simulated Data ◽  
Splice Junction ◽  
Cell Analysis ◽  
Statistical Confidence ◽  
Challenges And Opportunities ◽  
Splice Junctions

AbstractPrecise splice junction calls are currently unavailable in scRNA-seq pipelines such as the 10x Chromium platform but are critical for understanding single-cell biology. Here, we introduce SICILIAN, a new method that assigns statistical confidence to splice junctions from a spliced aligner to improve precision. SICILIAN is a general method that can be applied to bulk or single-cell data, but has particular utility for single-cell analysis due to that data’s unique challenges and opportunities for discovery. SICILIAN’s precise splice detection achieves high accuracy on simulated data, improves concordance between matched single-cell and bulk datasets, and increases agreement between biological replicates. SICILIAN detects unannotated splicing in single cells, enabling the discovery of novel splicing regulation through single-cell analysis workflows.

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

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.

Development of a platform for single cell genomics using convex lens-induced confinement

Lab on a Chip ◽  
2015 ◽  
Vol 15 (14) ◽  
pp. 3013-3020 ◽  
Author(s):  
Sara Mahshid ◽  
Mohammed Jalal Ahamed ◽  
Daniel Berard ◽  
Susan Amin ◽  
Robert Sladek ◽  
...  
Keyword(s):  
Single Cell ◽  
Base Pair ◽  
Single Cell Analysis ◽  
Lab On A Chip ◽  
Cell Analysis ◽  
Next Generation ◽  
Single Cell Genomics ◽  
Convex Lens ◽  
Genomic Dnas

We present a lab-on-a-chip for the next generation of single-cell genomics, performing full-cycle single-cell analysis by demonstrating mega-base pair genomic DNAs in nanochannels extracted in situ.

scholarly journals More than efficacy revealed by single-cell analysis of antiviral therapeutics

2019 ◽  
Author(s):  
Wu Liu ◽  
Mehmet U. Caglar ◽  
Zhangming Mao ◽  
Andrew Woodman ◽  
Jamie J. Arnold ◽  
...  
Keyword(s):  
Single Cell ◽  
Drug Targets ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Principal Component ◽  
Viral Population ◽  
Cell Analysis ◽  
Toxic Dose ◽  
Time Required

SUMMARYDevelopment of antiviral therapeutics emphasizes minimization of the effective dose and maximization of the toxic dose, first in cell culture and later in animal models. Long-term success of an antiviral therapeutic is determined not only by its efficacy but also by the duration of time required for drug-resistance to evolve. We have developed a microfluidic device comprised of ~6000 wells, with each well containing a microstructure to capture single cells. We have used this device to characterize enterovirus inhibitors with distinct mechanisms of action. In contrast to population methods, single-cell analysis reveals that each class of inhibitor interferes with the viral infection cycle in a manner that can be distinguished by principal component analysis. Single-cell analysis of antiviral candidates reveals not only efficacy but also properties of the members of the viral population most sensitive to the drug, the stage of the lifecycle most affected by the drug, and perhaps even if the drug targets an interaction of the virus with its host.

scholarly journals μCB-seq: Microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells

2020 ◽  
Author(s):  
Tyler N. Chen ◽  
Anushka Gupta ◽  
Mansi Zalavadia ◽  
Aaron M. Streets
Keyword(s):  
High Resolution ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Protein Localization ◽  
Single Cells ◽  
Optical Measurements ◽  
Detection Sensitivity ◽  
High Resolution Imaging ◽  
Cell Analysis ◽  
Resolution Imaging

AbstractSingle-cell RNA sequencing (scRNA-seq) enables the investigation of complex biological processes in multicellular organisms with high resolution. However, many phenotypic features that are critical to understanding the functional role of cells in a heterogeneous tissue or organ are not directly encoded in the genome and therefore cannot be profiled with scRNA-seq. Quantitative optical microscopy has long been a powerful approach for characterizing diverse cellular phenotypes including cell morphology, protein localization, and chemical composition. Combining scRNA-seq with optical imaging has the potential to provide comprehensive single-cell analysis, allowing for functional integration of gene expression profiling and cell-state characterization. However, it is difficult to track single cells through both measurements; therefore, coupling current scRNA-seq protocols with optical measurements remains a challenge. Here, we report Microfluidic Cell Barcoding and Sequencing (μCB-seq), a microfluidic platform that combines high-resolution imaging and sequencing of single cells. μCB-seq is enabled by a novel fabrication method that preloads primers with known barcode sequences inside addressable reaction chambers of a microfluidic device. In addition to enabling multi-modal single-cell analysis, μCB-seq improves gene detection sensitivity, providing a scalable and accurate method for information-rich characterization of single cells.

scholarly journals Methods and sensors for functional genomic studies of cell-cycle transitions in single cells

2020 ◽  
Vol 52 (10) ◽  
pp. 468-477
Author(s):  
Alexander C. Zambon ◽  
Tom Hsu ◽  
Seunghee Erin Kim ◽  
Miranda Klinck ◽  
Jennifer Stowe ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Imaging System ◽  
Single Cells ◽  
Cell Types ◽  
Cell Analysis ◽  
Mcf7 Cells ◽  
Genomic Studies ◽  
Cell Subpopulations

Much of our understanding of the regulatory mechanisms governing the cell cycle in mammals has relied heavily on methods that measure the aggregate state of a population of cells. While instrumental in shaping our current understanding of cell proliferation, these approaches mask the genetic signatures of rare subpopulations such as quiescent (G0) and very slowly dividing (SD) cells. Results described in this study and those of others using single-cell analysis reveal that even in clonally derived immortalized cancer cells, ∼1–5% of cells can exhibit G0 and SD phenotypes. Therefore to enable the study of these rare cell phenotypes we established an integrated molecular, computational, and imaging approach to track, isolate, and genetically perturb single cells as they proliferate. A genetically encoded cell-cycle reporter (K67p-FUCCI) was used to track single cells as they traversed the cell cycle. A set of R-scripts were written to quantify K67p-FUCCI over time. To enable the further study G0 and SD phenotypes, we retrofitted a live cell imaging system with a micromanipulator to enable single-cell targeting for functional validation studies. Single-cell analysis revealed HT1080 and MCF7 cells had a doubling time of ∼24 and ∼48 h, respectively, with high duration variability in G1 and G2 phases. Direct single-cell microinjection of mRNA encoding (GFP) achieves detectable GFP fluorescence within ∼5 h in both cell types. These findings coupled with the possibility of targeting several hundreds of single cells improves throughput and sensitivity over conventional methods to study rare cell subpopulations.

scholarly journals Synchrotron macro ATR-FTIR microspectroscopy for high-resolution chemical mapping of single cells

The Analyst ◽  
2019 ◽  
Vol 144 (10) ◽  
pp. 3226-3238 ◽  
Author(s):  
Jitraporn Vongsvivut ◽  
David Pérez-Guaita ◽  
Bayden R. Wood ◽  
Philip Heraud ◽  
Karina Khambatta ◽  
...  
Keyword(s):  
High Resolution ◽  
Single Cell ◽  
Spatial Resolution ◽  
Environmental Science ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Cell Analysis ◽  
Chemical Mapping ◽  
Ftir Microspectroscopy ◽  
Resolution Single

Coupling synchrotron IR beam to an ATR element enhances spatial resolution suited for high-resolution single cell analysis in biology, medicine and environmental science.

Microfluidic positioning of pollen grains in lab-on-a-chip for single cell analysis

2014 ◽  
Vol 117 (4) ◽  
pp. 504-511 ◽  
Author(s):  
Mahmood Ghanbari ◽  
Amir Sanati Nezhad ◽  
Carlos G. Agudelo ◽  
Muthukumaran Packirisamy ◽  
Anja Geitmann
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Pollen Grains ◽  
Lab On A Chip ◽  
Cell Analysis

The next frontier in single cell analysis: multimodal studies and clinical translation

Lab on a Chip ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 3573-3574 ◽  
Author(s):  
Pratip K. Chattopadhyay ◽  
Daniel T. Chiu
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Lab On A Chip ◽  
Clinical Translation ◽  
Cell Analysis ◽  
Thought Leaders

Thought leaders Pratip Chattopadhyay and Daniel Chiu introduce the Lab on a Chip single cell analysis thematic collection.

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