Loading...
Please wait, while we are loading the content...
Similar Documents
A Metabolomic Approach to Identify Novel Natural Products from Marine Sponges
| Content Provider | Semantic Scholar |
|---|---|
| Author | Olsen, Elisabeth K. Søderholm, Kine Lethigangas Isakson, Johan Andersen, Jeanette H. Hansen, Espen |
| Copyright Year | 2015 |
| Abstract | A metabolomic approach was used to identify known and novel natural products from the marine sponges Geodia baretti and G. macandrewii. G. baretti is known to produce bioactive natural products like barettin, 8,9-dihydrobarettin and bromobenzisoxazolone barettin, while secondary metabolites from G. macandrewii are not reported in the literature. Specimens of the two sponges were collected from different sites along the coast of Norway and their extracts were analyzed with UHPLC-HR-MS. Metabolomic analyses revealed that extracts from both species contained barettin and 8,9dihydrobarettin, and all samples of G. baretti contained higher amounts of both compounds compared to G. macandrewii. The analysis of the MS data also revealed that samples of G. macandrewii contained a compound that was not present in any of the G. baretti samples. This was a novel compound identified as an N-Acyl-Taurine and was tested for antioxidant, anticancer and antibacterial properties. Introduction Geodia barretti (Bowerbank) is a marine sponge of the class Demospongiae. It is found on continental shelves and slopes of the north Atlantic, and it is common along the coast of Norway at depths between 10 and 500 meters. Specimens of G. barretti are irregular in shape, and they can be up to 80 cm in diameter and weigh up to 80 kg . As with many other sponges, the lack of epibionts on the surface of G. barretti is striking, and this observation led to the isolation of three strucurally related secondary metabolites with anti-fouling properties: barettin, 8,9-dihydrobarettin and bromobenzisoxazolone barettin (Figure 1). As a part of the MabCent screening campaign , extracts of G. barretti collected along the coast of Norway where tested in a panel of bioactivity assays, and we found that barettin also had anti-oxidative and anti-inflammatory properties. G. macandrewii (Bowerbank) is a related species also commonly found along the coast of Norway. Younger specimen of G. macandrewii have spherical bodies which tends to become more irregular when they grow larger than 10 cm in diameter, and they typically reach a size of 35-42 cm (diameter). There is no records in the literature of bioactive secondary metabolites isolated from G. macandrewii. Figure 1: Molecular structures of barettin, 8,9-dihydrobarettin and bromobenzisoxazolone. The MabCent screening campaign has been based on a classic bioassay-guided fractionation approach. Extracts of the marine organisms are prefractionated by HPLC or Flash-chromatography and the fractions are tested for biological activity in a panel of assays. Prefractionation is done to reduce the complexity, e.g. decrease the amount of non-selective compounds and inorganic salts, of crude extracts prior to bioactivity profiling. Any fraction with interesting bioactivity is purified in a series of subsequent fractionation steps, and the bioactivity is traced by screening all fractions in the relevant bioassay. There is a high probability that the isolated compounds have defined bioactivities, but on the other hand it will skew the generated natural products library against the bioactivities selected for the primary screening. Metabolomics is an alternative approach to detect samples and target compounds for lead identification. This technique can be used to select extracts based on chemical profiling rather than a pre-screened bioactivity. The metabolomics technology is used to identify and quantify molecules in a metabolome, the total of small (< 1500 Da) metabolites or chemicals formed by a cell, tissue, organ or organism, at a specific time and under a specific influence. By employing a metabolomics approach an extract can be assessed for chemical novelty or the presence of compounds with specific chemical features. The metabolome can be analyzed using different techniques, where mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) are considered to be the most universal approaches. MS is utilized due to its high sensitivity and that it can detect a wide range of molecular weights, while NMR gives direct structural information about molecular structures. The current study presents the results from an investigation of two closely related species of sponges, G. baretti and G. macandrewii, using a metabolomic approach. During a research cruise in 2013, specimens of both species were collected at four different locations along the coast of Norway. By comparing metabolic profiles of the samples we wanted to investigate whether i) both species produced barettin or related compounds, ii) the production of barettin was correlated to sampling location, and iii) G. macandrewii produce secondary metabolites not found in G. baretti. Results and discussion Sponges were collected on a research cruise at four different locations. Two stations were located in Saltenfjorden in Nordland and two were located in Trondeimsfjorden in Trøndelag. At the stations “Nordland 1” and “Nordland 2” both G. baretti and G. macandrewii were found, however only G. baretti was found at “Trøndelag 1” and “Trøndelag 2”. The sponges were extracted by a two-step protocol where the samples first were extracted in pure water, and followed by extraction in a mixture of methanol and dichloromethane. This protocol is used by the Developmental Therapeutics Program (DTP) of the National Cancer Institute (Frederick, MD, USA) for the extraction of marine invertebrates. The initial aqueous extraction can be regarded as a purification step as most of the inorganic salts and highly polar compounds such as carbohydrates and amino acids with little interest for drug discovery are efficiently removed from the organic extract. As the overall goal of this study was to identify new potential drug leads the aqueous extracts were not included in the metabolomic analysis. A combination of ultra-high performance liquid chromatography (UHPLC) and highresolution mass spectrometry (HR-MS) were used to generate data for the metabolomic analysis. UHPLC-HR-MS is well suited for these kind of analyses as the extracts are complex and contains a wide array of different compounds. The high resolution of the chromatographic separations obtained with this technique makes it possible to separate closely eluting compounds whereas the high resolution of the mass measurements separates compounds with similar masses. To ease the post-acquisition processing of data the analysis was restricted to positive electrospray (ESI+). We are aware of the fact than many acidic and non-polar compounds do not ionize well in ESI+, and that the number of detected compounds could be increased if ESI÷ was included, although this would have generated a separate data-set. With the parameters applied for collection of markers (i.e. a unique combination of retention time and mass, see experimental section) approximately 500 markers were identified in total. The metabolic profiles, i.e. the collected markers, for all the samples were compared using a principal components analysis (PCA). The scores plot of the data (Figure 2) revealed that the two G. macandrewii samples (M1 and M2) were similar as they grouped closely together, and the same was the case for three of the four samples of G. baretti (B1, B2 and B3). The clusters of the two different species were well separated, indicating that there were differences in metabolic profiles. The fourth sample of G. baretti (B4) was well separated from the other three samples (B1, B2 and B3), again suggesting that this sample had a unique metabolic profile. Figure 2. A scores plot based on collected markers for two G. macandrewii samples (M1 and M2) and four samples of G. baretti (B1, B2, B3 and B4). All samples were found to contain significant amounts of barettin (m/z 419.0829, protonated C17H20N6O2Br) and 8,9-dihydrobarettin (m/z 421.0988, protonated C17H22N6O2Br), and the samples of the same species collected at different sites contained similar amounts of both compounds. However, the two samples of G. macandrewii contained 80% less barettin and 95 % less 8,9-dihydrobarettin compared to the samples of G. baretti. The production of secondary metabolites in sponges are known to vary with both location and season. All the samples compared in this metabolomics study were collected at the same cruise and only days apart, thus potential seasonal variations did not affect the data set. Since all samples of G. baretti contained more of barettin and 8,9-dihydrobarettin than the G. macandrewii samples, the difference in natural products was recognized as species related rather than due to geographical variations. Although our observations indicate that there are no geographical variations between G. barretti’s content of the barettins it should be noted that the collection stations of “Nordland” and “Trøndelag” are separated by approx. four degrees of latitude. Hence, sampling of G. barretti further distances apart may give different results from those presented here. Barettin has been isolated from G. baretti samples collected at different locations along the Swedish and Norwegian coast-line and in the Barents sea, which indicates a wide geographical distribution of this compound. In order to reveal other differences in the metabolic profiles of the two species, one sample of each species (M1 and B1) were selected and compared in an S-plot. In this plot the x-axis denotes the contribution of a marker to the grouping differences, and the y-axis denotes the confidence of this contribution. Thus the markers in the lower left corner are characteristic for the sample of G. macandrewii, whereas the markers in the upper right corner are characteristic for the G. baretti sample (Figure 3). The two markers in the upper right corner represent two isomers of barettin (m/z 419 and 421) and the next two represents two isomers of 8,9-dihydrobarettin (m/z 421 and 423). Thus, the main contribution from G. baretti to the observed difference in grouping is the higher content |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://munin.uit.no/bitstream/handle/10037/8145/Paper_III.pdf?isAllowed=y&sequence=6 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
