Alkaline phosphatase functionalized nanoparticles: attachment, enzyme kinetics and colloidal diffusion

Enzymes are proteins found in organisms that work as biological catalysts. In the last decade, some studies report that enzymes diffuse faster during catalysis [1], and recently others show the possibility of making enzyme-powered micromotors; where urease-functionalized microparticles appear to diffuse faster during catalysis as observed by trajectory tracking [2]. We studied the validity of using the enzyme alkaline phosphatase as a nanomotor on spherical polystyrene particles with a diameter of 200 nm (attached by glutaraldehyde coupling) using differential dynamic microscopy (DDM) and dynamic light scattering (DLS) to obtain the diffusion coefficient of those particles compared to bare particles of the same size looking for any enhanced particles motion. We will report on the existence (or absence) of enhancement in diffusivity. The enzyme activity of our alkaline phosphatase functionalized nanoparticles, obtained by spectroscopy and the Michaelis-Menten relation [3], was found to be very similar (slightly lower) to the bare alkaline phosphatase activity. DDM is a technique that exploits optical microscopy to obtain local quantitative information about dynamic samples (diffusion coefficient, particle size) by probing wave vector-dependent dynamics [4]. DDM could be used to study the dynamics in liquid suspensions, soft materials, cells, and tissues. In DDM, image sequences are analyzed via a combination of image differences and spatial Fourier transforms to obtain information equivalent to that obtained by means of dynamic light scattering (DLS) techniques. Compared to DLS and particle trajectory tracking, DDM offers obvious advantages, most importantly, providing high statistics by capturing a large number of particles, removing the static contributions along the optical path, flexibility of choosing an analysis region, and the power of simultaneous different microscopy contrast mechanisms. But those advantages come with a price; it is challenging to know the suitable settings (camera speed, objective magnification, sample dilution, etc.) for each measurement (i.e., each particle size). In order to validate our DDM setup, we studied a range of polystyrene particles size (60 nm-1 micron) suspended in water using different settings to conclude the suitable settings for each size in that range. Using previously published Python code [5] and modified by our group, we managed to analyze thousands of frames (images) with the speed of hundreds of frames per second for each measurement. All measurements were compared to DLS measurements on the same samples (but more diluted) for comparison