Application of a hemolysis assay for analysis of complement activation by perfluorocarbon nanoparticles

Abstract

Nanoparticles offer new options for medical diagnosis and therapeutics with their capacity to specifically target cells and tissues with imaging agents and/or drug payloads. The unique physical aspects of nanoparticles present new challenges for this promising technology. Studies indicate that nanoparticles often elicit moderate to severe complement activation. Using human in vitro assays that corroborated the mouse in vivo results we previously presented mechanistic studies that define the pathway and key components involved in modulating complement interactions with several gadolinium-functionalized perfluorocarbon nanoparticles (PFOB). Here we employ a modified in vitro hemolysis-based assay developed in conjunction with the mouse in vivo model to broaden our analysis to include PFOBs of varying size, charge and surface chemistry and examine the variations in nanoparticle-mediated complement activity between individuals. This approach may provide the tools for an in-depth structure-activity relationship study that will guide the eventual development of biocompatible nanoparticles.

From the clinical editor: Unique physical aspects of nanoparticles may lead to moderate to severe complement activation in vivo, which represents a challenge to clinical applicability. In order to guide the eventual development of biocompatible nanoparticles, this team of authors report a modified in vitro hemolysis-based assay developed in conjunction with their previously presented mouse model to enable in-depth structure-activity relationship studies.

Keywords: Complement; Hemolysis Assay; Mouse Model; Nanomedicine; Nanoparticles; Perfluorocarbon.

Figure 1

In vivo assay of NP-dependent C activity. (A) Each of the complement activation pathways (classical, lectin, and alternative) leads to the enzymatic cleavage of C3 and the formation of the membrane attack complex (MAC). Complement activity results in the consumption of the components indicated in red. (B) In vivo NP-dependent C activation was monitored in the mouse model system by ELISA-based quantification of plasma C3a. The data were derived from 22 naïve and 98 NP-treated animals. Each determination was performed at least 3 times except for the negative control particle (n = 2). (C) Activation of complement by the highly reactive PFOB incorporating 50 mol% DOTAP in the mouse model is dependent on antibody, C4, and factor B, but not MBL of the lectin pathway. The data were derived from n = 3–12 animals per treatment group. *P < 0.01; **P < 0.001.

Figure 2

Hemolysis assay of nanoparticle-dependent complement activation. (A) Each curve in a titration series is derived by plotting the volume of reaction mixture (V) in each titration point on the x-axis versus the fraction of EA lysed (Y) on the y-axis. The serum control titration curve reaches a plateau at complete cell lysis (Y = 1). Hemolysis requires the presence of the CP protein C1 and is inhibited by heat-inactivation of serum complement components. (B) Incubation with a strong C-activating NP (50 mol% DOTAP) leads to complete loss of serum complement components that is reflected by diminished hemolytic activity and a downward shift of the titration curve. Incubation with a negative control NP results in no C activation and a titration curve that is nearly superimposed on the serum control curve. Moderate C activation (with 20 mol% GdDOTA) results in an intermediate curve (C) Nanoparticle:C activity, assessed as residual hemolytic activity, is relatively constant over a broad range of CH50 values. (D) Dose-dependent depletion of hemolytic activity by standard the complement activators mannan, peroxidase/antiperoxidase complexes (PAP) and zymosan.

Figure 3

Correlation of the hemolysis assay to the animal model. (A) Sensitivity of the hemolysis assay is enhanced with low ionic strength DGVB++ buffer vs physiological ionic strength buffer (GVB⁺⁺). The data was derived from 18 pairs of experiments (see Supplementary Methods). Each NP was assayed at least 5 times in each buffer. (B) In vivo NP-dependent plasma C3a production (Figure 2, A) compared to in vitro CA as measured with DGVB⁺⁺ buffer (see also Supplemental Table 2). Trendline was derived by linear regression analysis (R² = 0.80). The data points also fitted a logarithmic regression with R² = 0.83.

Figure 4

Variation in the NP-dependent C response. NP-dependent complement reactivity of pooled serum was compared to that of sera derived from individual donors (BRC#75 and BRC#84). Values represent mean ± SD derived from at least 3 separate experiments. *P < 0.05; **P < 0.01; ****P < 0.0001 as determined by unpaired t-test.