The printing of cells for microarray applications possesses significant challenges including the problem of maintaining physiologically relevant cell phenotype after printing, poor organization and distribution of desired cells, and the inability to deliver drugs and/or nutrients to targeted areas in the array. Our 3D microfluidic printing technology is uniquely capable of sealing and printing arrays of cells onto submerged surfaces in an automated and multiplexed manner. The design of the microfluidic cell array (MFCA) 3D fluidics enables the printhead tip to be lowered into a liquid-filled well or dish and compressed against a surface to form a seal. The soft silicone tip of the printhead behaves like a gasket and is able to form a reversible seal by applying pressure or backing away. Other cells printing technologies such as pin or ink-jet printers are unable to print in submerged applications. Submerged surface printing is essential to maintain phenotypes of cells and to monitor these cells on a surface without disturbing the material surface characteristics. By printing onto submerged surfaces, cell microarrays are produced that allow for drug screening and cytotoxicity assessment in a multitude of areas including cancer, diabetes, inflammation, infections, and cardiovascular disease.
Here, we demonstrate how array-based label-free biosensors can be applied to the multiplexed interaction analysis of large panels of analyte/ligand pairs, such as the epitope binning of monoclonal antibodies (mAbs). In this application, the larger the number of mAbs that are analyzed for cross-blocking in a pairwise and combinatorial manner against their specific antigen, the higher the probability of discriminating their epitopes. Since cross-blocking of two mAbs is necessary but not sufficient for them to bind an identical epitope, high-resolution epitope binning analysis determined by high-throughput experiments can enable the identification of mAbs with similar but unique epitopes. We demonstrate that a mAb's epitope and functional activity are correlated, thereby strengthening the relevance of epitope binning data to the discovery of therapeutic mAbs. We evaluated two state-of-the-art label-free biosensors that enable the parallel analysis of 96 unique analyte/ligand interactions and nearly ten thousand total interactions per unattended run. The IBIS-MX96 is a microarray-based surface plasmon resonance imager (SPRi) integrated with continuous flow microspotting technology whereas the Octet-HTX is equipped with disposable fiber optic sensors that use biolayer interferometry (BLI) detection. We compared their throughput, versatility, ease of sample preparation, and sample consumption in the context of epitope binning assays. We conclude that the main advantages of the SPRi technology are its exceptionally low sample consumption, facile sample preparation, and unparalleled unattended throughput. In contrast, the BLI technology is highly flexible because it allows for the simultaneous interaction analysis of 96 independent analyte/ligand pairs, ad hoc sensor replacement and on-line reloading of an analyte- or ligand-array. Thus, the complementary use of these two platforms can expedite applications that are relevant to the discovery of therapeutic mAbs, depending upon the sample availability, and the number and diversity of the interactions being studied.
The protein microarray platform while innovative still poses a number of challenges which can only be met through creative and sophisticated system design. Pin printing while allowing for flexibility as to the type of medium printed does not offer the kind of spot reproducibility that a very sensitive application may require. The Continuous Flow Microspotter (CFM) was designed to not only allow for flexibility and reproducibility but to also achieve solution stability through flow scaling. This study uses the emerging CFM for printing protein and antibodies three dimensionally for general protein microarray applications. Consistent spot morphology, a continual and persistent problem in traditional pin printed microarrays, was compared under variable printed flow rates. The final assessment was performed using a rudimentary shear model. Force effects discussion and statistical data was used to demonstrate the versatility of the system.
The promise of antibody and protein microarrays to revolutionize disease diagnostics has failed to live up to the hype primarily due to the problems associated with the printing of the antibodies and/or proteins onto the detection surface. The current standard in printing proteins is pin printing. An alternative to the pin printer is the continuous-flow microspotter (CFM), a protein printer that uses microfluidic flow to print down the proteins. The advantages of the CFM include consistent spot morphology, spot-to-spot uniformity and enhanced surface concentration. Further, the CFM is effective at capturing proteins and antibodies from either dilute or complex (e.g. blood or tissue) samples. In this study, the sensitivity of CFM printing Cy3 and Cy5 fluorescently labeled proteins was determined. Values were obtained at low concentrations tens of ng/mL with low coefficients of variation. Thus, the CFM can effectively print and quantify proteins and antibodies from low concentration and complex buffered samples.
We have developed a novel referencing technique for surface plasmon resonance imaging systems referred to as "spot and hop." The technique enables internal referencing for individual flow cells in a parallel processing microfluidic network. Internal referencing provides the ability to correct for nonspecific binding and instrument drift, significantly improving data quality at each region of interest. The performance of a 48-flow-cell device was demonstrated through a series of studies, including "rise and fall" time, ligand preconcentration, ligand immobilization, analyte binding, and regeneration tests. Interfacing parallel processing fluidics with imaging systems will significantly expand the throughput and applications of array-based optical biosensors while retaining high data quality.
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