An Optimized P. berghei Liver Stage-HepG2 Infection Model for Simultaneous Quantitative Bioimaging of Host and Parasite Nascent Proteomes

Abstract

The Plasmodium parasites that cause malaria undergo an obligate, asymptomatic developmental stage in the host liver before initiating the symptomatic blood-stage infection. The parasite liver stage is a key intervention point for antimalarial chemoprophylaxis: successful targeting of liver-stage parasites prevents disease development in individuals and can help to reduce parasite transmission in populations, as the gametocyte forms that transmit infection to mosquitos are exclusively found in the blood stage. Antimalarial drugs that can target multiple parasite stages are thus highly desirable, and one emerging cellular target for such multistage active compounds is the process of protein synthesis or translation. Quantitative study of liver stage translation, and thus mechanistic evaluation of translation inhibitors against liver stage parasites, is not amenable to the methods allowing quantification of asexual blood stage translation, such as radiolabeled amino acid incorporation or lysate-based translation of reporter transcripts. Here, we present a method using o-propargyl puromycin (OPP) labeling of host and parasite nascent proteomes in the P. berghei-HepG2 infection model, followed by automated confocal image acquisition and computational separation of P. berghei vs. H. sapiens nascent proteome signals to allow simultaneous readout of the effects of translation inhibitors on both host and parasite. This protocol details our HepG2 cell culture and infected monolayer handling optimized for microscopy, our OPP labeling workflow, and our approach to automated confocal imaging, image processing, and data analysis. Key features • Uses the o-propargyl puromycin labeling technique developed by Liu et al. to quantitatively analyze protein synthesis in Plasmodium berghei liver-stage parasites in actively translating hepatoma cells. • This quantitative approach should be adaptable for other puromycin-sensitive intracellular pathogens residing in actively translating host cells. • The P. berghei-infected HepG2 recovery and reseeding protocol presented here is of use in applications beyond nascent proteome labeling and quantification.

Keywords: Antimalarial drug discovery; Automated confocal feedback microscopy; HepG2 cell culture; Liver stage; Plasmodium berghei; Protein synthesis; Quantitative bioimaging; Translation.

Figure 1.. Counting chamber example formula.

Illustration of counting chamber showing four quadrants used for counting with an explanation for calculating the cells/µL and the total number of cells in suspension.

Figure 2.. Tiled image example generated in CellProfiler.

Tiled images provide a visual overview of the raw images, objects identified, and masking. They can be very helpful in understanding how to optimize batch segmentation parameters for a given dataset. Each tiled image is metadata-linked to the corresponding data, and image tiles for data points of interest in quality control or exploratory data analysis are routinely inspected via an interactive KNIME workflow ( https://hub.knime.com/-/spaces/-/~TZCrKvv3sbJwM_xP/current-state/). The representative parasite in this tiled image is from a 48 hours post-infection (hpi) timepoint. The shrunken exoerythrocytic form (EEF) outline indicated by the orange arrow is inside of the expanded EEF outline indicated by the blue arrow. OPP, o-propargyl puromycin.

Figure 3.. Image data quality control steps with example images.

Quality control filters designed to identify and remove confounding image data are consistently applied across the entire dataset prior to data normalization or analysis. Example images are representative of image artifacts and image segmentation artifacts from a 28 hours post-infection (hpi) dataset. Several types of artifacts would be recognized and removed by more than one filter. ACFM, automated confocal feedback microscopy; EEF, exoerythrocytic form.