Search

Although microfluidic micro-electromechanical systems (MEMS) are well suited to investigate the effects of mechanical force on large populations of cells, their high-throughput capabilities cannot be fully leveraged without optimizing the experimental conditions of the fluid and particles flowing through them. Parameters such as flow velocity and particle size are known to affect the trajectories of particles in microfluidic systems and have been studied extensively, but the effects of temperature and buffer viscosity are not as well understood. In this paper, we explored the effects of these parameters on the timing of our own cell-impact device, the μHammer, by first tracking the velocity of polystyrene beads through the device and then visualizing the impact of these beads. Through these assays, we find that the timing of our device is sensitive to changes in the ratio of inertial forces to viscous forces that particles experience while traveling through the device. This sensitivity provides a set of parameters that can serve as a robust framework for optimizing device performance under various experimental conditions, without requiring extensive geometric redesigns. Using these tools, we were able to achieve an effective throughput over 360 beads/s with our device, demonstrating the potential of this framework to improve the consistency of microfluidic systems that rely on precise particle trajectories and timing.

A reliable identification of cells on the basis of their surface markers is of great interest for diagnostic and therapeutic applications. We present a multiplexed labeling and detection strategy that is applied to four microparticle populations, each mimicking cellular or bacterial samples with varying surface concentrations of up to four epitopes, using four distinct biotags that are meant to be used in conjunction with surface enhanced Raman spectroscopy (SERS) instead of fluorescence, together with microfluidics. Four populations of 6 μm polystyrene beads were incubated with different mixtures, "cocktails" of four SERS biotags (SBTs), simulating the approach that one would follow when seeking to identify multiple biomarkers encountered in biological applications. Populations were flowed in a microfluidic flow-focusing device and the SERS signal from individual beads was acquired during continuous flow. The spectrally rich SERS spectra enabled us to separate confidently the populations by utilizing principal component analysis (PCA). Also, using classical least squares (CLS), we were able to calculate the contributions of each SBT to the overall signal in each of the populations, and showed that the relative SBT contributions are consistent with the nominal percentage of each marker originally designed into that bead population, by functionalizing it with a given SBT cocktail. Our results demonstrate the multiplexing capability of SBTs in potential applications such as immunophenotyping.

Reliable identification and collection of cells from bodily fluids is of growing interest for monitoring patient response to therapy and for early detection of disease or its recurrence. We describe a detection platform that combines microfluidics with surface-enhanced Raman spectroscopy (SERS) for the identification of individual mammalian cells continuously flowing in a microfluidics channel. A mixture of cancerous and noncancerous prostate cells was incubated with SERS biotags (SBTs) developed and synthesized by us, then injected into a flow-focused microfluidic channel, which forces the cells into a single file. The spectrally rich SBTs are based on a silver nanoparticle dimer core labeled with a Raman-active small reporter molecule paired with an affinity biomolecule, providing a unique barcode whose presence in a composite SERS spectrum can be deconvoluted. Individual cancer cells passing through the focused laser beam were correctly identified among a proportionally larger number of other cells by their Raman signatures. We examine two deconvolution strategies: principal component analysis and classical least-squares. The deconvolution strategies are used to unmix the overall spectrum to determine the relative contributions between two SBT barcodes, where one SBT barcode indicates neuropilin-1 overexpression, while a second SBT barcode is more universal and indicates unspecific binding to a cell's membrane. Highly reliable results were obtained for all of the cell mixture ratios tested, the lowest being 1 in 100 cells.

The aggregation kinetics of silver nanoparticles in sessile droplets were investigated both experimentally and through numerical simulations as a function of temperature gradient and evaporation rate, in order to determine the hydrodynamic and aggregation parameters that lead to optimal surface-enhanced Raman spectroscopic (SERS) detection. Thermal gradients promote effective stirring within the droplet. The aggregation reaction ceases when the solvent evaporates forming a circular stain consisting of a high concentration of silver nanoparticle aggregates, which can be interrogated by SERS leading to analyte detection and identification. We introduce the aggregation parameter, Γa ≡ τ(evap)/τ(a), which is the ratio of the evaporation to the aggregation time scales. For a well-stirred droplet, the optimal condition for SERS detection was found to be Γ(a,opt) = kc(NP)τ(evap) ≈ 0.3, which is a product of the dimerization rate constant (k), the concentration of nanoparticles (cNP), and the droplet evaporation time (τ(evap)). Near maximal signal (over 50% of maximum value) is observed over a wide range of aggregation parameters 0.05 < Γa < 1.25, which also defines the time window during which trace analytes can be easily measured. The results of the simulation were in very good agreement with experimentally acquired SERS spectra using gas-phase 1,4-benzenedithiol as a model analyte.

We present a microfluidic device that detects trace concentrations of drugs of abuse in saliva within minutes using surface-enhanced Raman spectroscopy (SERS). Its operation is demonstrated using methamphetamine. The detection scheme exploits concentration gradients of chemicals, fostered by the laminar flow in the device, to control the interactions between the analyte, silver nanoparticles (Ag-NPs), and a salt. Also, since all species interact while advecting downstream, the relevant reaction coordinates occur with respect to the position in the channel. The system was designed to allow the analyte first to diffuse into the side stream containing the Ag-NPs, on which it is allowed to adsorb, before salt ions are introduced, causing the Ag-NPs to aggregate, and so creating species with strong SERS signal. The device allows partial separation via diffusion of the analyte from the complex mixture. Also, the reproducible salt-induced NP aggregation decouples the aggregation reaction (necessary for strong SERS) from the analyte concentration or charge. This method enables the creation of a region where detection of the analyte of interest via SERS is optimal, and dramatically extends the classes of molecules and quality of signals that can be measured using SERS, compared to bulk solution methods. The spatial distribution of the SERS signals was used to map the degree of nanoparticle aggregation and species diffusion in the channel, which, together with numerical simulations, was used to describe the kinetics of the colloid aggregation reaction, and to determine the optimal location in the channel for SERS interrogation.