Time-of-Flight Secondary Ion Mass Spectrometry-Partial Least Square Regression for Quantifying Interleukin-8 in Biopolymer Matrices

Abstract

Unraveling the complexity of biomatrices is a persisting challenge in many areas of the life sciences. The detection of soluble signaling molecules—cytokines and growth factors—within multicomponent biopolymer scaffolds is of particular interest as they control important biological processes such as the development of tissues, pathologies, and regeneration. The application of time-of-flight secondary ion mass spectrometry (ToF-SIMS) for the detection of interleukin-8 (IL-8), a chemokine involved in inflammation and cancer, is explored within biopolymer matrices of different complexity. To establish the workflow, IL-8 is embedded with graded mass fractions in thin biopolymer matrices consisting of heparin and/or bovine serum albumin, followed by a comprehensive ToF-SIMS analysis of the prepared samples. Partial least square regression models are developed and successfully applied to detect IL-8 mass fractions down to 1 ppm on the basis of the measured ToF-SIMS spectra. The methodology is successfully applied to detect IL-8 in Matrigel and poly(ethylene glycol)-heparin matrices with similar sensitivity. Given the high performance of state-of-the-art SIMS instruments and the increasing power of machine learning algorithms, it is envisioned that the established approach, in combination with other methods, will enable a comprehensive assessment of soluble signaling molecules in (engineered) matrix-supported 3D cell and organoid cultures.