Team:FAU Erlangen/Measurement

iGEM Erlangen


Dynamic Lightscattering as Powerful Analysis Tool

The characterization of nanoscale protein assemblies is challenging for many imaging techniques as contrast is poor and to investigate a significant number of structures requires a tremendous amount of time. Dynamic and static light scattering (DLS and SLS) provide a fast and easy analysis of all structures in solution without using labeling or contrast agents. These non-invasive methods allow to determine the shape and give a size distribution of particles in solution. We used these techniques to investigate the assemblies of our mixed S-Layer aggregates. We successfully analyzed the composition of our aggregates and moreover determined occurring side products (such as micelles of detergents) in our solution. Conclusively, we introduced DLS and SLS as promising methods for the analysis of protein assemblies. These procedures accelerate characterization processes and provide higher statistical significance.

Basic Overview Dynamic Lightscattering (1)

The size determination of particles in general is based on their diffusion in solution, which correlates with the intensity fluctuation of the scattered light.
The size dependent diffusion of the particles in solution can be described via the Stokes Einstein equation (1).

with D as diffusion coefficient, RH as hydrodynamic radius of the particles, η as viscosity of the solvent and k as Boltzmann constant.
To obtain the hydrodynamic radius several processing steps have to be carried out, which will be explained further. A short overview of the processing steps is given in Figure 1.

Figure 1. Overview of data processing steps for a dynamic light scattering experiment

The time dependent intensity fluctuation is split into smaller time intervals dt, which are smaller than the fluctuation time to yield the intensity autocorrelation function.

normalization of equation (2) leads to

via Siegert relation (3)

the intensity autocorrelation function g2 is transformed into the autocorrelation function of the electric field g1 with B as a aperture parameter (4).


In case of a monodisperse system the autocorrelation of the electric field can be expressed as an exponential function (6).


and Γ as inverse relaxation time (7). The relation to the diffusion coefficient D can be used in the previously mentioned Stokes Einstein equation to yield the hydrodynamic radius RH. In case of polydispers solutions the autocorrelation of the electric field can be described as a sum of individual autocorrelation functions (8)

Including a weight factor A correlating with the number of scattering events, which can be used to identify multiple species in solution.

(1) W. Schärtel, Lightscattering from Polymer Solutions and Nanoparticle ^ Dispersion, Springer Verlag, 2007.

Identification of Protein Solution Quality with Dynamic Light Scattering

Figure 2. a) Autocorrelation function of the electric field (dots) and distribution function of decay times (line), b) scattering intensity weighted distribution function of hydrodynamic radii (from a), mass weighted distribution function of hydrodynamic radii of PS2 S-layer protein isolated with SDS.

From the DLS measurements in Figure 2 the first isolation of PS2 S-Layer protein solution was measured. For the isolation of PS2 sodium dodecylsulfate (SDS) is used as detergent, which cannot be removed with dialysis, which is a general drawback when investigating the assembly of S-Layer proteins. The result of this isolation are multiple species, which can be attributed to SDS micelles with an RH value of 1.4 nm (Afzal et al. 2017), PS2 protein with likely SDS integrated in the structure and cells (figure 2 b). The intensity weighted plot (figure 2 b) helps identifying all species in solution, whereas the mass weighted plot (figure 2 c) yields the mass distribution of species in the medium. Converted from intensity to mass weighted analysis, mainly SDS (>90 %) and protein structures are found in solution (figure 2c), whereas other impurities are present in a negligibly low amount. To circumvent this issue of SDS impurities, a novel isolation method was established leading to solely PS2 protein assemblies.

Figure 3.Autocorrelation function of the electric field (dots) and distribution function of decay times (line) of PS2 isolated according to the novel protocol.

The novel protocol yielded PS2 assembly sizes of RH = 405 nm in average, which is double the size of the previously found S-Layer proteins isolated with SDS. The impact on the size can be attributed to SDS which can interact with the hydrophobic parts of the surface protein and is likely integrated into the protein micelle. To further expand the system cellular traces should be analyzed which is a common trace in protein purification.

Figure 4. Distribution function of hydrodynamic radii from the solution of a RsaA isolation.

The isolation of the S-Layer protein suffered severely from cellular traces in the solution, which have to be centrifuged to circumvent these impurities. The cellular traces should be in the range of RH > 1 µm, which is the case for the third peak. With the measurement of DLS, the amount of traces and the purity of the solution can further be verified. Overall, for the detection of larger particles this method is extremely sensitive as larger aggregates such as cells result in a higher scattering intensity, which can be troublesome when released to the environment.

Afzal, Mohd; Kundu, Pronab; Das, Sinjan; Ghosh, Saptarshi; Chattopadhyay, Nitin (2017): A promising strategy for improved solubilization of ionic drugs simply by electrostatic pushing. In RSC Adv. 7 (69), pp. 43551–43559. DOI: 10.1039/c7ra08056e.

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