Literature DB >> 24503696

Microfluidic single-cell analysis for systems immunology.

Michael Junkin1, Savaş Tay.   

Abstract

The immune system constantly battles infection and tissue damage, but exaggerated immune responses lead to allergies, autoimmunity and cancer. Discrimination of self from foreign and the fine-tuning of immunity are achieved by information processing pathways, whose regulatory mechanisms are little understood. Cell-to-cell variability and stochastic molecular interactions result in diverse cellular responses to identical signaling inputs, casting doubt on the reliability of traditional population-averaged analyses. Furthermore, dynamic molecular and cellular interactions create emergent properties that change over multiple time scales. Understanding immunity in the face of complexity and noisy dynamics requires time-dependent analysis of single-cells in a proper context. Microfluidic systems create precisely defined microenvironments by controlling fluidic and surface chemistries, feature sizes, geometries and signal input timing, and thus enable quantitative multi-parameter analysis of single cells. Such qualities allow observable dynamic environments approaching in vivo levels of biological complexity. Seamless parallelization of functional units in microfluidic devices allows high-throughput measurements, an essential feature for statistically meaningful analysis of naturally variable biological systems. These abilities recapitulate diverse scenarios such as cell-cell signaling, migration, differentiation, antibody and cytokine production, clonal selection, and cell lysis, thereby enabling accurate and meaningful study of immune behaviors in vitro.

Entities:  

Mesh:

Year:  2014        PMID: 24503696     DOI: 10.1039/c3lc51182k

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  20 in total

1.  Lab-on-a-chip workshop activities for secondary school students.

Authors:  Mohammad M N Esfahani; Mark D Tarn; Tahmina A Choudhury; Laura C Hewitt; Ashley J Mayo; Theodore A Rubin; Mathew R Waller; Martin G Christensen; Amy Dawson; Nicole Pamme
Journal:  Biomicrofluidics       Date:  2016-02-02       Impact factor: 2.800

2.  High-throughput microfluidic single-cell analysis pipeline for studies of signaling dynamics.

Authors:  Ryan A Kellogg; Rafael Gómez-Sjöberg; Anne A Leyrat; Savaş Tay
Journal:  Nat Protoc       Date:  2014-06-26       Impact factor: 13.491

3.  Microfluidics: A new tool for modeling cancer-immune interactions.

Authors:  Alexandra Boussommier-Calleja; Ran Li; Michelle B Chen; Siew Cheng Wong; Roger D Kamm
Journal:  Trends Cancer       Date:  2016-01-01

Review 4.  Bridging the gap: microfluidic devices for short and long distance cell-cell communication.

Authors:  Timothy Quang Vu; Ricardo Miguel Bessa de Castro; Lidong Qin
Journal:  Lab Chip       Date:  2017-03-14       Impact factor: 6.799

5.  Assessment of chimeric antigen receptor T cytotoxicity by droplet microfluidics in vitro.

Authors:  Kuan Un Wong; Jingxuan Shi; Peng Li; Haitao Wang; Yanwei Jia; Chuxia Deng; Lianmei Jiang; Ada Hang-Heng Wong
Journal:  Antib Ther       Date:  2022-03-24

6.  The effects of monocytes on tumor cell extravasation in a 3D vascularized microfluidic model.

Authors:  A Boussommier-Calleja; Y Atiyas; K Haase; M Headley; C Lewis; R D Kamm
Journal:  Biomaterials       Date:  2018-03-05       Impact factor: 12.479

7.  Characterisation of anticancer peptides at the single-cell level.

Authors:  L Armbrecht; G Gabernet; F Kurth; J A Hiss; G Schneider; P S Dittrich
Journal:  Lab Chip       Date:  2017-08-22       Impact factor: 6.799

8.  Digital microfluidic immunocytochemistry in single cells.

Authors:  Alphonsus H C Ng; M Dean Chamberlain; Haozhong Situ; Victor Lee; Aaron R Wheeler
Journal:  Nat Commun       Date:  2015-06-24       Impact factor: 14.919

9.  Digital signaling decouples activation probability and population heterogeneity.

Authors:  Ryan A Kellogg; Chengzhe Tian; Tomasz Lipniacki; Stephen R Quake; Savaş Tay
Journal:  Elife       Date:  2015-10-21       Impact factor: 8.140

10.  T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray.

Authors:  Saheli Sarkar; Vinny Motwani; Pooja Sabhachandani; Noa Cohen; Tania Konry
Journal:  J Clin Cell Immunol       Date:  2015-06-20
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