Corynebacterium diphtheriae Proteome Adaptation to Cell Culture Medium and Serum

Abstract

Host-pathogen interactions are often studied in vitro using primary or immortal cell lines. This set-up avoids ethical problems of animal testing and has the additional advantage of lower costs. However, the influence of cell culture media on bacterial growth and metabolism is not considered or investigated in most cases. To address this question growth and proteome adaptation of Corynebacterium diphtheriae strain ISS3319 were investigated in this study. Bacteria were cultured in standard growth medium, cell culture medium, and fetal calf serum. Mass spectrometric analyses and label-free protein quantification hint at an increased bacterial pathogenicity when grown in cell culture medium as well as an influence of the growth medium on the cell envelope.

Keywords: diphtheria; host-pathogen interaction; label-free quantification; metabolic pathway; proteomics.

Figure 1

Growth of C. diphtheriae ISS3319. (a) Optical density in brain heart infusion (BHI) medium (rhombi), RPMI 1640 (triangles), and fetal calf serum (FCS) (circles). (b) Colony forming units (CFU) at different time points for bacteria grown in BHI medium (light grey), RPMI 1640 (dark grey), and FCS (black). Three independent biological replicates were carried out for all experiments. Data show the calculated mean value and the resulting standard deviation.

Figure 2

Proteins identified under different growth conditions. Only proteins identified in all three independent replicates were considered for further analysis. The Venn diagram shows the common proteins as well as the unique proteins for all three growth conditions.

Figure 3

Proteome of C. diphtheriae strain ISS3319 grown in various culture media ((a): BHI; (b): RPMI 1640; (c): FCS). Percentage of different proteins located to the cytoplasm (red), extracellular (green), located to the membrane (purple), and proteins with ambiguous localization (blue). (d) shows the classification of secreted proteins and proteins with localization to the membrane regarding the secretion system. Blue: BHI, green: RPMI 1640 and purple: FCS.

Figure 4

ProteoTreeMap of the total protein content in all three samples. (a) level 1: metabolic pathway and (b) level 3: function.

Figure 5

Differences in expression level of common proteins. A high intensity is shown in red and goes to a low intensity in blue. The relative abundance was used for a multiple sample test (ANOVA). A Z-score was calculated for the resulting 41 proteins and clustered using the Euclidian algorithm.

Figure 6

Metabolic pathways of proteins exclusively found in different growth conditions. Information storage and processing: dark blue; metabolism: light blue; cellular processes and signaling: orange; involved in pathogenesis: red; uncharacterized: turquoise; poorly characterized: yellow. The size of the area is proportional to the abundance calculated based on the total protein approach (TPA) method for label-free quantification.