Metabolic fingerprinting of biofluids by infrared spectroscopy: modeling and optimization of flow rates for laminar fluid diffusion interface sample preconditioning

Abstract

The laminar fluid diffusion interface (LFDI) is a microfluidic tool that manipulates the composition of liquid mixtures by exploiting differences among diffusion coefficients of the dissolved components. One application is the preprocessing of (bio)fluids prior to spectroscopic characterization. For example, in the case of infrared (IR) spectroscopy, the technique can improve sensitivity to low-concentration serum metabolites. The practical benefit is "metabolic fingerprinting" measurements that are more sensitive to low-concentration metabolites than are the counterpart measurements for the original serum sample. Optimal use of the LFDI technique has proven elusive, since the composition of the product of interest is very sensitive to the choice of flow rates for the liquid streams entering and emerging from the LFDI channel. To provide the basis for optimal use, this study had the objective of developing a simulation package that predicts the composition of the LFDI product, given the LFDI structural and operating parameters. To demonstrate the utility of the simulations, composition of the LFDI products predicted for two illustrative sets of trials were compared with experimental data. The flow rates thus derived provided a LFDI product that is relatively rich in serum metabolites, while largely depleted of protein, and very well suited for subsequent IR spectroscopic characterization.