Penitrems are fungal indole diterpene-derived tremorgenic secondary metabolites, which are mainly produced by Penicillium spp. Several cases of intoxications with penitrems and subsequent occurrences of penitrem A in foodstuff underline the need for reliable quantitation methods for the detection of these mycotoxins in food. In this study, a simple and fast high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for the quantitative analysis of penitrems A-F in cheese was developed. Therefore, penitrems A-F were isolated from Penicillium crustosum as analytical reference standards. The analysis of 60 cheese samples from the European single market (EU) revealed the occurrence of penitrem A in 10% of the analyzed samples with an average concentration of 28.4 μg/kg and a maximum concentration of 429 μg/kg. In addition to penitrem A, other members of the group of penitrems, namely, penitrems B, C, D, E, and F, were for the first time quantitatively detected in food samples, although in lower concentrations and with lower incidence in comparison to penitrem A. Moreover, we report cytotoxic effects of all penitrems on two cell lines (HepG2 and CCF-STTG1). This clearly underlines their relevance and the importance to analyze food samples in order to get insights into the human exposure toward these mycotoxins.
The genus Erythrina, Fabaceae, is widely distributed in tropical and subtropical regions. Their flowers, fruits, seeds and bark are frequently used in folk medicine for its effects on the central nervous system such as anticonvulsant, antidepressant, analgesic, sedative, and hypnotic effects. Erythraline has been reported as one of the active compounds from Erythrina, but until now there are no pharmacokinetics data about this compound and only few results showing a putative metabolism were reported. To improve the information about erythraline metabolism, this article reports and discusses, for the first time, the in vitro metabolism biotransformation of erythraline by cytochrome P450 enzymes.
Leishmaniasis is one of the World’s most problematic diseases in developing countries. Traditional medicines to treat leishmaniasis have serious side effects, as well as significant parasite resistance problems. In this work, two alkaloids 1 and 2 were obtained from Corydalis govaniana Wall and seven alkaloids 3–9, were obtained from Erythrina verna. The structures of the compounds were confirmed by mass spectrometry and 1D- and 2D-NMR spectroscopy. The leishmanicidal activity of compounds 1–9 against Leishmania amazonensis was tested on promastigote forms and cytotoxicity against J774 (macrophage cell line) was assessed in vitro. Compound 1 showed potent activity (IC50 = 0.18 µg/mL), compared with the standard amphotericin B (IC50 = 0.20 µg/mL). The spirocyclic erythrina-alkaloids showed lower leishmanicidal activity than dibenzoquinolizine type alkaloids.
In the field of natural products, moulds provide a large spectrum of bioactive compounds and are therefore important targets to analyse. One of these moulds is Fusarium fujikuroi, a rice pathogen causing the foolish seedling disease due to its secretion of the secondary metabolites gibberellic acids, a group of highly bioactive phytohormones [1]. Besides these isoprenoids, it produces a broad range of other interesting compounds, e.g. the cyclic tetrapeptide apicidin F which shows antimalarial activity [2]. The genome of F. fujikuroi was fully sequenced, revealing the presence of altogether 47 putative secondary metabolite gene clusters, most without yet assigned product [3]. Besides, global regulatory genes that encode positive or negative regulators of secondary metabolite gene clusters are under investigation. With the help of genetic engineering, overexpression and deletion mutants of biosynthetic genes and/or global regulator genes were generated. In this study, we present several identified metabolites, including the products of a dimethylallyl tryptophan synthase, a polyketide synthase (PKS) and a PKS-non ribosomal peptide hybrid (see Fig. 1). Those were identified by HPLC-UV-HRMS measurements of the created mutants in comparison to the wild type. To enhance the identification process, the secondary metabolite profiles were analysed with the software tool MZmine 2 [4], resulting in the identification of new or missing peaks, respectively. The compounds were isolated by different methods and their structures were elucidated in detail by NMR and HPLC-HRMS. With this procedure, known secondary metabolites [5,6] as well as new, yet unknown compounds were identified, and corresponding gene clusters characterized [7].
O gênero Piper pertencente à família Piperaceae, encontra-se distribuído nas regiões tropicais e subtropicais do globo.Estudos químicos têm demonstrado diversidade de metabólitos secundários com atividade biológica.Os alcalóides são metabólitos característicos.A piplartina, (E)-1-(3-(3,4,5-trimetoxifenil)acriloil)-5,6diidropiridin-2(1H)-ona, é um alcalóide encontrado em muitas espécies.Tem atividade citotóxica contra células de linhagem tumoral, ansiolítica, antidepressiva, antifúngica e antiagregação plaquetária, sendo dessa forma, uma molécula candidata a um novo fármaco.O conhecimento do metabolismo de um candidato a fármaco é um fator importante na avaliação da sua segurança e eficácia.Ensaios in vitro estão crescentemente sendo utilizados como screening e os microssomas hepáticos representam o sistema in vitro mais utilizado.Dessa forma, o presente trabalho tem como objetivo determinar os parâmetros cinéticos enzimáticos in vitro da piplartina utilizando microssomas de fígado de ratos, bem como a determinação dos possíveis metabólitos formados.Para tanto, foi desenvolvido um método de quantificação da piplartina utilizando cromatografia líquida de alta eficiência.Como condição de análise, empregou-se uma coluna C18, fase móvel acetonitrila:água (40:60, v/v) e vazão de 1 mL min -1 .Para extração da piplartina dos microssomas hepático de ratos foi empregado a extração líquido-líquido utilizando 4,0 mL de hexano como solvente extrator.Após otimização da extração, o método foi validado, mostrando-se linear na faixa de 2,4-157,7 µM, obtendo-se uma equação da reta y= 0,0934x + 0,0027, (r= 0,99) e limite de quantificação de 2,4 µM.A recuperação média foi de 85%.A precisão e exatidão apresentaram resultados dentro do recomendável pela ANVISA.A piplartina manteve-se estável até 50 minutos em condições de incubação, e até 6h sob a bancada.Após validação da metodologia, estabeleceram-se as condições lineares para a quantidade de proteínas microssomais: 0,28 mg mL -1 e para o tempo de incubação: 16 minutos no consumo da piplartina no meio microssomal, e então efetuou-se a determinação dos parâmetros cinéticos enzimáticos da piplartina empregando as condições de V 0.Nesse estudo foi observado um V max = 4,74 ± 0,26 µM/µg mL -1 /min, h= 2,53 ± 0,37, S 50 = 44,69 ± 0,32 µM e CL max = 0,054 µL/min/mg proteina, um perfil cinético indicativo de cooperatividade.Um estudo qualitativo para determinação dos possíveis metabólitos foi feito utilizando-se a espectrometria de massas, por meio da qual foi possível identificar a formação de dois produtos hidroxilados.Deste modo, os microssomas mostraram-se uma ferramenta útil, rápida e simples para determinação da cinética enzimática, e na condução dos estudos preliminares de metabolismo in vitro.
Summary The human metabolome has remained largely unknown, with most studies annotating ∼10% of features. In nucleic acid sequencing, annotating transcripts by source has proven essential for understanding gene function. Here we generalize this concept to stool, plasma, urine and other human metabolomes, discovering that food-based annotations increase the interpreted fraction of molecular features 7-fold, providing a general framework for expanding the interpretability of human metabolomic “dark matter.”
Bioengineering has origin in different fields of knowledge like Physics, Mathematics, Chemistry, Biology and Computational Science, so an increasing number of information is available in the World Wide Web. The purpose of this work are the introduction of webometric methods to analyze the contribution of this new field as a tool to create new strategies and design for research and development activity in Bioengineering and Health Science. For this intention we use dedicated software to analyze the quantitative information resources on the World Wide Web.