Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells

Abstract

Background: Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine.

Results: Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity.

Conclusions: The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics.

Figure 1

Structure of IQ-143. Shown is the structure of the environmental challenge and xenobiotic chosen, isoquinolinium salt IQ-143, a structurally simplified analogue of a new subclass of bioactive natural products, the N,C-coupled naphthyl-isoquinolines alkaloids.

Figure 2

Changes in extreme modes in S. epidermidis RP62A with three different concentrations of IQ-143. Red shading indicates lower activities after IQ-143 administration, green shading indicates higher activities, and 'ser' denotes S. epidermidis. Each row displays the changes for six extreme modes (continuously numbered from 1 to 197); numbers given in the fields are the activities for each mode under different concentrations of IQ-143. Also given are the pathways in which the modes are involved. Abbreviations: A, amino acids; E, energy metabolism; F, fatty acids; N, nucleotide metabolism; O, oxidative phosphorylation; T, transporters. All details are also shown in Additional file 1 (Tables S10, S11, and S12; key changes in Tables S16 and S17).

Figure 3

Changes in extreme modes in S. aureus USA300 with three different concentrations of IQ-143. Red shading indicates lower activities after IQ-143 administration, green shading indicates higher activities, and 'sau' denotes S. aureus. Each row displays six extreme modes (continuously numbered from 1 to 198); numbers given in the fields are the activities for each mode under different concentrations of IQ-143. Also given are the pathways in which the modes are involved. Abbreviations: A, amino acids; E, energy metabolism; F, fatty acids; N, nucleotide metabolism; O, oxidative phosphorylation; T, transporters. All details are also shown in Additional file 1 (Tables S7, S8, and S9; key changes in Tables S18 and S19).

Figure 4

Simplified view of the metabolic chart for S. aureus and S. epidermidis, focusing on central metabolic pathways of interest. This flow chart illustrates which pathways of the primary metabolism are incorporated into our models. Note that the secondary metabolism is not a part of our model. TCA, tricarboxylic acid.

Figure 5

Effects of IQ-143 on metabolic enzymes of S. aureus. Detailed data are given in Table 4. The insert shows the different enzyme color codes. Many differences are apparent after applying metabolic modeling; bars with dotted outlines and brackets around the enzyme name highlight those enzymes in which the different gene expression values already indicate a significant change after administration of IQ-143.

Figure 6

Effects of IQ-143 on metabolic enzymes of S. epidermidis. Detailed data are given in Table 4. The insert shows the different enzyme color codes. Many differences are apparent after applying metabolic modeling; bars with dotted outlines and brackets around the enzyme name highlight those enzymes in which the different gene expression values already indicate a significant change after administration of IQ-143.

Figure 7

Measured changes of nucleotides upon addition of 0.16 μM and 1.25 μM IQ-143. The results represent mean values of triplicate measurements (± standard deviation). For further details see Tables 5 and 6.

Figure 8

Measured changes of energy metabolism upon addition of 0.16 μM and 1.25 μM IQ-143. The results represent mean values of triplicate measurements (± standard deviation). For further details see Tables 5 and 6.