Microscale 3D Collagen Cell Culture Assays in Conventional Flat-Bottom 384-Well Plates

Brendan M. Leung, Christopher Moraes, Stephen P. Cavnar, Kathryn E. Luker, Gary D. Luker, Shuichi Takayama

Résultat de recherche: Articleexamen par les pairs

26 Citations (Scopus)

Résumé

Three-dimensional (3D) culture systems such as cell-laden hydrogels are superior to standard two-dimensional (2D) monolayer cultures for many drug-screening applications. However, their adoption into high-throughput screening (HTS) has been lagging, in part because of the difficulty of incorporating these culture formats into existing robotic liquid handling and imaging infrastructures. Dispensing cell-laden prepolymer solutions into 2D well plates is a potential solution but typically requires large volumes of reagents to avoid evaporation during polymerization, which (1) increases costs, (2) makes drug penetration variable and (3) complicates imaging. Here we describe a technique to efficiently produce 3D microgels using automated liquid-handling systems and standard, nonpatterned, flat-bottomed, 384-well plates. Sub-millimeter-diameter, cell-laden collagen gels are deposited on the bottom of a ~2.5 mm diameter microwell with no concerns about evaporation or meniscus effects at the edges of wells, using aqueous two-phase system patterning. The microscale cell-laden collagen-gel constructs are readily imaged and readily penetrated by drugs. The cytotoxicity of chemotherapeutics was monitored by bioluminescence and demonstrated that 3D cultures confer chemoresistance as compared with similar 2D cultures. Hence, these data demonstrate the importance of culturing cells in 3D to obtain realistic cellular responses. Overall, this system provides a simple and inexpensive method for integrating 3D culture capability into existing HTS infrastructure.

Langue d'origineEnglish
Pages (de-à)138-145
Nombre de pages8
JournalJournal of laboratory automation
Volume20
Numéro de publication2
DOI
Statut de publicationPublished - avr. 1 2015
Publié à l'externeOui

Note bibliographique

Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors would like to acknowledge funding support from the National Institutes of Health (CA170198) and the mCube grant from the University of Michigan. C.M. was supported by a Banting postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada. S.C. was supported by a National Science Foundation predoctoral fellowship (F031543) and the Advanced Proteome informatics of Cancer Training Grant (T32 CA140044).

Publisher Copyright:
© 2014, 2014 Society for Laboratory Automation and Screening.

ASJC Scopus Subject Areas

  • Computer Science Applications
  • Medical Laboratory Technology

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