Dataset Information

Antimicrobial Diterpenes from Rough Goldenrod (Solidago rugosa Mill.).

ABSTRACT: Solidago rugosa is one of the goldenrod species native to North America but has sporadically naturalized as an alien plant in Europe. The investigation of the root and leaf ethanol extracts of the plant using a bioassay-guided process with an anti-Bacillus assay resulted in the isolation of two antimicrobial components. Structure elucidation was performed based on high-resolution tandem mass spectrometric and one- and two-dimensional NMR spectroscopic analyses that revealed (-)-hardwickiic acid (Compound 1) and (-)-abietic acid (Compound 2). The isolates were evaluated for their antimicrobial properties against several plant pathogenic bacterial and fungal strains. Both compounds demonstrated an antibacterial effect, especially against Gram-positive bacterial strains (Bacillus spizizenii, Clavibacter michiganensis subsp. michiganensis, and Curtobacterium flaccumfaciens pv. flaccumfaciens) with half maximal inhibitory concentration (IC₅₀) between 1 and 5.1 µg/mL (5-20 times higher than that of the positive control gentamicin). In the used concentrations, minimal bactericidal concentration (MBC) was reached only against the non-pathogen B. spizizenii. Besides their activity against Fusarium avenaceum, the highest antifungal activity was observed for Compound 1 against Bipolaris sorokiniana with an IC₅₀ of 3.8 µg/mL.

SUBMITTER: Baglyas M

PROVIDER: S-EPMC10180332 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Antimicrobial Diterpenes from Rough Goldenrod (Solidago rugosa Mill.).

Baglyas Márton M Ott Péter G PG Schwarczinger Ildikó I Nagy Judit Kolozsváriné JK Darcsi András A Bakonyi József J Móricz Ágnes M ÁM

Molecules (Basel, Switzerland) 20230428 9

Solidago rugosa is one of the goldenrod species native to North America but has sporadically naturalized as an alien plant in Europe. The investigation of the root and leaf ethanol extracts of the plant using a bioassay-guided process with an anti-Bacillus assay resulted in the isolation of two antimicrobial components. Structure elucidation was performed based on high-resolution tandem mass spectrometric and one- and two-dimensional NMR spectroscopic analyses that revealed (-)-har ...[more]

PMID: 37175200

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Project description:New substances with antimicrobial properties are needed to successfully treat emerging human, animal, or plant pathogens. Seven clerodane diterpenes, previously isolated from giant goldenrod (Solidago gigantea) root, were tested against Gram-positive Bacillus subtilis, Bacillus spizizenii and Rhodococcus fascians by measuring minimal bactericidal concentration (MBC), minimal inhibitory concentration (MIC) and half-maximal inhibitory concentration (IC50). Two of them, Sg3a (a dialdehyde) and Sg6 (solidagoic acid B), were proved to be the most effective and were selected for further study. Bacillus spizizenii was incubated with the two diterpenes for shorter (1 h) or longer (5 h) periods and then subjected to genome-wide transcriptional analyses. Only a limited number of common genes (28 genes) were differentially regulated after each treatment, and these were mainly related to the restoration of cell membrane integrity and to membrane-related transports. Changes in gene activity indicated that, among other things, K+ and Na+ homeostasis, pH and membrane electron transport processes may have been affected. Activated export systems can be involved in the removal of harmful molecules from the bacterial cells. Inhibition of bacterial chemotaxis and flagellar assembly, as well as activation of genes for the biosynthesis of secondary metabolites, were observed as a general response. Depending on the diterpenes and the duration of the treatments, down-regulation of the protein synthesis-related, oxidative phosphorylation, signal transduction and transcription factor genes was found. In other cases, up-regulation of the genes of oxidation-reduction processes, sporulation and cell wall modification could be detected. Comparison of the effect of diterpenes with the changes induced by different environmental and nutritional conditions revealed several overlapping processes with stress responses. For example, the Sg6 treatment seems to have caused a starvation-like condition. In summary, there were both common and diterpene-specific changes in the transcriptome, and these changes were also dependent on the length of treatments. The results also indicated that Sg6 exerted its effect more slowly than Sg3a, but ultimately its effect was greater.

Project description:The late goldenrod (Soldiago gigantea Aiton; Asteraceae) is one of the most abundant invasive species in various types of habitats. Its long-creeping plagiotropic rhizomes enable the plant to build up dense, monospecific stands within a short time. Particularly in nature conservation areas, the invasion of goldenrod can cause severe disruptions in the naturally occuring mutualims between plants, insects and higher trophic levels, subsequently impeding the achievement of nature conservation goals. As management options of goldenrod in nature conservation areas are limited, this three-year study aimed to test the effectiveness of three management treatments (two-time mowing, triticale cultivation, and reverse rotary cutting) on four different sites in the Austrian Donau-Auen National Park. The number and height of goldenrod shoots were recorded three times a year on twelve permanent trial plots on each site to test for the effectiveness of the treatments. In addition, vegetation surveys were performed to observe the recovery potential of native plant species. Even though the three-years mowing and the triticale cultivation reduced goldenrod by 95.6% and 97.2% resp., we could find no relation between the effectiveness of the treatment and the intensity of disturbance created by the control option. On the contrary, with a reduction of only 5.4% in goldenrod density the most intensive treatment, the rotary cutting, showed the lowest efficiency. The highest positive effect on the re-establishment of native plant species was recorded with two mowing events per year. Even though the study revealed that certain management options have the potential to effectively reduce goldenrod and to simultaneously increase the establishment success of native species, results can only be seen as so-called snapshots. For example, as shown on site EJW one unforeseeable wild boar digging event transformed a 84.5% reduction into a 4.7% increase in goldenrod density. Therefore, a proper and regular monitoring is essential to be able to react to the effects of unpredictable events that can have severe impact on vegetation dynamics.

Project description:BackgroundAntimicrobial peptides attract considerable interest as novel agents to combat infections. Their long-time potency across bacteria, viruses and fungi as part of diverse innate immune systems offers a solution to overcome the rising concerns from antibiotic resistance. With the rapid increase of antimicrobial peptides reported in the databases, peptide selection becomes a challenge. We propose similarity analyses to describe key properties that distinguish between active and non-active peptide sequences building upon the physicochemical properties of antimicrobial peptides. We used an iterative supervised machine learning approach to classify active peptides from inactive peptides with low false discovery rates in a relatively short computational search time.ResultsBy generating explicit boundaries, our method defines new categories of active and inactive peptides based on their physicochemical properties. Consequently, it describes physicochemical characteristics of similarity among active peptides and the physicochemical boundaries between active and inactive peptides in a single process. To build the similarity boundaries, we used the rough set theory approach; to our knowledge, this is the first time that this approach has been used to classify peptides. The modified rough set theory method limits the number of values describing a boundary to a user-defined limit. Our method is optimized for specificity over selectivity. Noting that false positives increase activity assays while false negatives only increase computational search time, our method provided a low false discovery rate. Published datasets were used to compare our rough set theory method to other published classification methods and based on this comparison, we achieved high selectivity and comparable sensitivity to currently available methods.ConclusionsWe developed rule sets that define physicochemical boundaries which allow us to directly classify the active sequences from inactive peptides. Existing classification methods are either sequence-order insensitive or length-dependent, whereas our method generates the rule sets that combine order-sensitive descriptors with length-independent descriptors. The method provides comparable or improved performance to currently available methods. Discovering the boundaries of physicochemical properties may lead to a new understanding of peptide similarity.

Dataset Information

Antimicrobial Diterpenes from Rough Goldenrod (Solidago rugosa Mill.).

Publications

Antimicrobial Diterpenes from Rough Goldenrod (<i>Solidago rugosa</i> Mill.).

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