Search PubMed⌕ Search

PubMed · 16905357

Merging microfluidics with microarray-based bioassays.

Abstract

Microarray technologies provide powerful tools for biomedical researchers and medicine, since arrays can be configured to monitor the presence of molecular signatures in a highly parallel fashion and can be configured to search either for nucleic acids (DNA microarrays) or proteins (antibody-based microarrays) as well as different types of cells. Microfluidics on the other hand, provides the ability to analyze small volumes (micro-, nano- or even pico-liters) of sample and minimize costly reagent consumption as well as automate sample preparation and reduce sample processing time. The marriage of microarray technologies with the emerging field of microfluidics provides a number of advantages such as, reduction in reagent cost, reductions in hybridization assay times, high-throughput sample processing, and integration and automation capabilities of the front-end sample processing steps. However, this potential marriage is also fraught with some challenges as well, such as developing low-cost manufacturing methods of the fluidic chips, providing good interfaces to the macro-world, minimizing non-specific analyte/wall interactions due to the high surface-to-volume ratio associated with microfluidics, the development of materials that accommodate the optical readout phases of the assay and complete integration of peripheral components (optical and electrical) to the microfluidic to produce autonomous systems appropriate for point-of-care testing. In this review, we provide an overview and recent advances on the coupling of DNA, protein and cell microarrays to microfluidics and discuss potential improvements required for the implementation of these technologies into biomedical and clinical applications.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Catherine Situma, Masahiko Hashimoto, Steven A Soper. 2006-07-07. Merging microfluidics with microarray-based bioassays.. https://doi.org/10.1016/j.bioeng.2006.03.002

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

The statistical performance of an MCF-7 cell culture assay evaluated using generalized linear mixed models and a score test.

Biological assays often utilize experimental designs where observations are replicated at multiple levels, and where each level represents a separate component of the assay's overall variance. Statistical analysis of such data usually ignores these design effects, whereas more sophisticated methods would improve the statistical power of assays. This report evaluates the statistical performance of an in vitro MCF-7 cell proliferation assay (E-SCREEN) by identifying the optimal generalized linear mixed model (GLMM) that accurately represents the assay's experimental design and variance components. Our statistical assessment found that 17beta-oestradiol cell culture assay data were best modelled with a GLMM configured with a reciprocal link function, a gamma error distribution, and three sources of design variation: plate-to-plate; well-to-well, and the interaction between plate-to-plate variation and dose. The gamma-distributed random error of the assay was estimated to have a coefficient of variation (COV) = 3.2 per cent, and a variance component score test described by X. Lin found that each of the three variance components were statistically significant. The optimal GLMM also confirmed the estrogenicity of five weakly oestrogenic polychlorinated biphenyls (PCBs 17, 49, 66, 74, and 128). Based on information criteria, the optimal gamma GLMM consistently out-performed equivalent naive normal and log-normal linear models, both with and without random effects terms. Because the gamma GLMM was by far the best model on conceptual and empirical grounds, and requires only trivially more effort to use, we encourage its use and suggest that naive models be avoided when possible.

Biological Assay↗

Reactivation of Kaposi's sarcoma-associated herpesvirus by natural products from Kaposi's sarcoma endemic regions.

Kaposi's sarcoma (KS) and its causative agent, Kaposi's sarcoma associated herpesvirus (KSHV/HHV-8), a gamma2 herpesvirus, have distinctive geographical distributions that are largely unexplained. We propose the "oncoweed" hypothesis to explain these differences, namely that environmental cofactors present in KS endemic regions cause frequent reactivation of KSHV in infected subjects, leading to increased viral shedding and transmission leading to increased prevalence of KSHV infection as well as high viral load levels and antibody titers. Reactivation also plays a role in the pathogenesis of KSHV-associated malignancies. To test this hypothesis, we employed an in vitro KSHV reactivation assay that measured increases in KSHV viral load in KSHV infected primary effusion lymphoma (PEL) cells and screened aqueous natural product extracts from KS endemic regions. Of 4,842 extracts from 38 countries, 184 (5%) caused KSHV reactivation. Extracts that caused reactivation came from a wide variety of plant families, and extracts from Africa, where KSHV is highly prevalent, caused the greatest level of reactivation. Time course experiments were performed using 28 extracts that caused the highest levels of reactivation. The specificity of the effects on viral replication was examined using transcriptional profiling of all viral mRNAs. The array data indicated that the natural extracts caused an ordered cascade of lytic replication similar to that seen after induction with synthetic activators. These in vitro data provide support for the "oncoweed" hypothesis by demonstrating basic biological plausibility.

Biological Assay↗

A novel E3 ubiquitin ligase substrate screen identifies Rho guanine dissociation inhibitor as a substrate of gene related to anergy in lymphocytes.

Ubiquitination of eukaryotic proteins regulates a broad range of cellular processes, including regulation of T cell activation and tolerance. We have previously demonstrated that gene related to anergy in lymphocytes (GRAIL), a ring finger ubiquitin E3 ligase, is required for the induction of T cell anergy; however, the substrate(s) for GRAIL E3 ligase activity is/are unknown. In this study, we report a novel prokaryotic system developed to screen for substrates of E3 ligases. Using this screen, Rho guanine dissociation inhibitor (RhoGDI) was identified as a potential substrate of GRAIL. GRAIL was subsequently demonstrated to bind and ubiquitinate RhoGDI, although GRAIL-mediated ubiquitination of RhoGDI did not result in proteosomal degradation. Expression of GRAIL in T cells resulted in specific inhibition of RhoA GTPase activation; activation of Rac1, cdc42, and Ras GTPases were not affected. Interestingly, stable T cell lines expressing dominant-negative RhoA mimicked the GRAIL-mediated IL-2 inhibition phenotype, and T cells expressing constitutively active RhoA were able to overcome GRAIL-mediated inhibition of IL-2 expression. These findings validate our prokaryotic screen as a method of identifying substrates for ubiquitin E3 ligases and suggest a role for Rho effector molecules in T cell anergy.

Biological Assay↗