Berkchaetoazaphilone B has antimicrobial activity and affects energy metabolism

Abstract

Antimicrobial resistance has become one of the major threats to human health. Therefore, there is a strong need for novel antimicrobials with new mechanisms of action. The kingdom of fungi is an excellent source of antimicrobials for this purpose because it encompasses countless fungal species that harbor unusual metabolic pathways. Previously, we have established a library of secondary metabolites from 10,207 strains of fungi. Here, we screened for antimicrobial activity of the library against seven pathogenic bacterial strains and investigated the identity of the active compounds using ethyl acetate extraction, activity-directed purification using HPLC fractionation and chemical analyses. We initially found 280 antimicrobial strains and subsequently identified 17 structurally distinct compounds from 26 strains upon further analysis. All but one of these compounds, berkchaetoazaphilone B (BAB), were known to have antimicrobial activity. Here, we studied the antimicrobial properties of BAB, and found that BAB affected energy metabolism in both prokaryotic and eukaryotic cells. We conclude that fungi are a rich source of chemically diverse secondary metabolites with antimicrobial activity.

Figure 1

Initial screen for antimicrobial activity from fungal secondary metabolites library. Each row of the map shows the activity of a single fungus against seven different bacteria. Active, half-active and inactive are indicated as “1” (red), “0.5” (orange) and “0” (yellow), respectively.

Figure 2

Identification strategy of antimicrobial compounds from fungi. Fungi were inoculated on agar plates and subsequently cultured in liquid media, filtrated by 0.22 µm filter, and extracted with ethyl acetate as shown in Process A (red arrows). Next, samples were concentrated using a rotary evaporator and tested for their antimicrobial activity in 96-well plates. Active samples were fractionated by preparative-HPLC, followed by activity (96-well plates) and purity (analytical HPLC) check. Pure active fractions were then identified by a combination of several chemical analyses. If the yield of active compounds was not sufficient by culturing in liquid medium, plate extraction (Process B, green arrows) was applied by culturing fungi on agar plates and extracting compounds with ethyl acetate directly from cultures on agar.

Figure 3

Re-screen of antimicrobial activity from 56 hits. The extracts from 56 fungi were tested for their maximum inhibitory dilutions (MIDs) against B. subtilis. The MID of each fungus was plotted in a pie chart. Highest active dilution was 320 × diluted.

Figure 4

Identification of the antimicrobial activity from fungus Pleurostomophora richardsiae. (a) Preparative HPLC profiles of extracts from two batches of liquid culture using liquid–liquid extraction (LLE). (b) P. richardsiae cultured on different kinds of agar. (c) Comparison of different plate extractions (PE) on analytical HPLC. (d) UV spectrum of the active compound from this fungus. (e) Mass spectrum of the active compound. (f) Chemical structure of BAB, the antimicrobial activity from P. richardsiae.

Figure 5

Antimicrobial properties of BAB. (a) Growth curves of B. subtilis in the presence of a range of BAB concentrations. OD₆₀₀ was measured every 30 min. BAB was added at 2 h 45 min (arrow indicated). The graph depicts the average and the SEM of biological triplicates. (b) No sporulation in response to BAB. B. subtilis cells from high intensity overnight culture were treated with DMSO (control) or BAB (250 μg/mL, 5 × MIC), stained with FM4-64 and imaged by confocal fluorescence microscopy. Representative images are shown. Example spores in the DMSO control are indicated with arrows. Scale bar is 5 µm. (c) Effect on respiratory chain activity measured by the reduction from blue resazurin to red resorufin at 540 nm. The average intensity of DMSO control in each group was set as 100% intensity and the percentage of each treated sample was calculated. The mean from biological triplicates was plotted with error bars representing the SEM.

Figure 6

Cytotoxicity of BAB on HepG2 cells may be caused by effects on energy metabolism. (a) HepG2 cells with BAB in different concentrations were incubated for 20 h and afterwards resazurin was added. The ability to reduce blue resazurin to red resorufin was measured at 540 nm. The average intensity of DMSO control was set as 100% alive and the percentage of intensity from each treated sample was calculated. The mean from biological triplicates was plotted with error bars representing the SEM in black. Nonlinear regression was analyzed and plotted in red, on which IC₅₀ was based. (b,c) HepG2 cells either untreated or pre-treated with BAB were compared in a glycolysis and mitochondrial test using Seahorse technology to measure extracellular acidification rates (ECAR) in mpH/minute and oxygen consumption rates (OCR) in pmol O₂/minute. (b) For the glycolysis stress test, 10 mM glucose, 5 μM oligomycin and 100 mM 2-deoxyglucose (2-DG) were injected into each well after 18, 36 and 65 min respectively. (c) For the mitochondrial stress test, 5 μM oligomycin, 2 μM FCCP and 1 μM of Rotenone and Antimycin A were injected to each well after 18, 45 and 63 min respectively. Both ECAR and OCR were normalized to individual protein amount, and data from biological triplicates were presented by mean with error bars representing the SEM.