detection for yeast and bacteria in wood slabs by RNA FISH

The deterioration of cultural heritage objects and assets (mural paintings, statues, and many other art objects made of wood, stone, paper, ceramic, glass, inter alia) can be caused by microorganisms [1]. One of the most important steps for applying adequate conservation and protection measures is early identification and monitorization of microbial colonization. The conventional culture-based methods used so far have become insufficient to detect/identify the biodeteriogenic agents. Thus, molecular techniques have started to attract considerable interest [2,3]. Our group is focused on detecting and identifying microorganisms that cause biodeterioration on artworks using the RNA-FISH molecular technique [4]. It is a simple, rapid and promising molecular technique enabling the detection, visualization and identification of the viable microorganisms of interest [5,6]. As any other technique, RNA-FISH has its own minimum Limit Of Detection (LOD) and for ensuring the reliability of RNA-FISH analyses, determination of the associated LODs is imperative. Thus, the aim of this work was to determine the LOD for yeast and bacteria in wood slabs by RNA-FISH. Universal probes for targeting eukaryotes (EUK516) and bacteria (EUB338) labeled with Cy3 or Atto-647N dyes were used.This work was co-financed by ALT20-03-0246-FEDER-000004-ALENTEJO 2020 project and by FCT through the project PTDC/BBB-IMG/0046/2014 and grants SFRH/BD/118028/2016 and SFRH/BPD/100754/2014

Microanalysis Characterization of Bioactive Protein-Bound Polysaccharides Produced by Amanita Ponderosa Cultures

Different compounds of edible mushrooms are responsible for their bioactivity. The ability to synthesize polysaccharides, namely protein–polysaccharide (PPS) complexes, is related to the antioxidant capacity of these compounds and present great interest in preventing a number of diseases, including cancer, cardiovascular and auto-immune diseases, and accelerated aging. Amanita ponderosa are wild edible mushrooms that grow in Mediterranean “montado” areas [Portuguese name given to cork oak (Quercus suber) and holm oak (Quercus ilex) forests]. The aim of this study was to evaluate the production of PPS complexes obtained from A. ponderosa cultures using a new microanalytical approach to quickly and easily monitor the production process. Microanalysis using Fourier-transform infrared using attenuated total reflection and Raman spectroscopy of PPS samples showed spectra compatible with identification of this type of compound in culture extracts. PPS separated by size-exclusion chromatography showed seven main complexes. Molecular weights of the main PPS complexes isolated from cultures ranged between 1.5 and 20 kDa and did not present toxicity against Artemia salina, demonstrating the potential of A. ponderosa as a source of biologically active compounds with nutraceutical value. Application of this microanalytical approach to monitoring the production of PPS compounds can be successfully applied in biotechnological processes

Combined use of LC–ESI-MS and antifungal tests for rapid identification of bioactive lipopeptides produced by Bacillus amyloliquefaciens CCMI 1051

The strain Bacillus amyloliquefaciens CCMI 1051 used in this study has been isolated in our laboratory from healthy Quercus suber in the south of Portugal and shows high levels of antagonistic properties against filamentous fungi that attack forest products industry due to the production of bioactive peptides. A combined use of LC–ESI-MS and antifungal tests allowed a rapid identification of lipopeptides as active compounds produced. Applying autobiographic methods it was possible to obtain active compounds. LC–ESI-MS, a powerful tool for rapid identification, indicates the presence of lipopeptides and MS2 electrospray ionization showed the partial sequence Tyr–Asn–Pro–Glu in the peptidic portion of some compounds produced. The association of mass spectrometry and chromatography, used in parallel with antifungal tests proved to be an efficient approach for the characterization of active lipopeptides without the need of previous total isolation. This methodology can be employed for screening and optimization the production of antifungal iturinic lipopeptides, showing a great potential for future application

Innovative approaches for immunodetection of proteic binders in art

The characterization and identification of the proteinaceous compounds in a complex and multi-layered painting is crucial for studying the technique used by the artist and for conservation and restoration purposes. These organic compounds, such as animal glues, milk and egg, have a particular importance since they are widely used as binders and adhesives in paintings. Proteins are typically detected by methods like chromatographic and proteomic techniques. However, the immunodetection approach shows to be a powerful method in protein analysis. In this study immunologic techniques, based on enzyme-linked immunosorbent assay (ELISA), were used in order to identify different proteic binders used in easel paintings. The methodology based on indirect ELISA allows the detection of the target antigen in paint models microsamples. These approach is very promising with regard to the possibility of apply these methodology in the detection of proteinaceous binders in real samples

Oxalate biofilm formation in mural paintings due to microorganismse -A comprehensive study

Oxalate film formation is a pathology that often occurs in mural paintings and may result from the concomitant action of microorganisms and environmental conditions. Low Choir of the Convent of Nossa Senhora da Saudação (Portugal) has mural paintings with an extraordinary beauty, which over time have been suffered polychromy degradation and biofilm formation, presenting an ideal case study to investigate the role and impact of microorganisms in the biodeterioration process. Bacterial populations, filamentous fungi belonging to the genera Cladosporium, Penicillium, Nectria and yeast strain of the genera Rhodotorula were isolated from these wall paintings. The penetration of fungal hyphae in the microstructure of mortars, observed by scanning electron microscopy, seems to be responsible for cracking and detachments in some areas of the painting. The study revealed that the veils on the surface of the paintings are essentially oxalates and that these biofilms are caused by metabolic activity of bacterial communities. Furthermore, the colour alteration of green areas due to microorganisms was detected by Raman microscopy, in real samples and under in vitro conditions, being the result of the metabolic activity of microorganisms present on the paintings, which promote calcium oxalates formation over the malachite paint layers

Caracterização Inorgânica de Cogumelos Amanita Ponderosa: Abordagem em Data Mining

A espécie silvestre de cogumelos Amanita ponderosa é característica de microclimas da Península Ibérica. Gastronomicamente é muito relevante, devido não só ao consumo tradicional das populações rurais, mas também devido ao seu valor comercial nos mercados gourmet. Desta forma a caracterização mineral de cogumelos comestíveis torna-se extremamente importante para os processos de certificação e comercialização. O objetivo deste estudo focou a análise da composição inorgânica de corpos de frutificação de A. ponderosa (Ca, K, Mg, Na, P, Ag, Al, Ba, Cd, Cr, Cu, Fe, Mn, Pb e Zn) e seus respetivos substratos de solo de 24 pontos de amostragem diferentes do sudoeste da Península Ibérica (nomeadamente Alentejo, Andaluzia e Extremadura). A análise da composição mineral revelou alto conteúdo em macroelementos, tais como: potássio, fósforo e magnésio, presença de oligoelementos importantes e baixos teores de metais pesados nos limites da Dose Diária Recomendada (DDR). O fenómeno de bioconcentração foi observado para alguns macro e microelementos, tais como K, Cu, Zn, Mg, P, Ag e Cd. Por outro lado, observou-se que os corpos de frutificação de Amanita ponderosa apresentam diferentes perfis inorgânicos de acordo com a sua localização. Metodologias de Data Mining foram aplicadas de forma a estudar a composição mineral dos corpos de frutificação de A. ponderosa, tendo sido utilizado o método de agrupamento "k-means" recorrendo a Árvores de Decisão (DTs) de forma a explicar o modelo de segmentação. Os resultados apontaram que é possível gerar um modelo explicativo de segmentação, realizado com dados baseados na composição inorgânica de cogumelos e conteúdo mineral do solo, mostrando a possibilidade de relacionar esses dois tipos de dados

Molecular evaluation of some Amanita ponderosa and fungal strains living in association with these mushrooms in the south western Iberian Peninsula

Amanita ponderosa are wild edible mushrooms that grow only in some microclimates, particularly those in the southwestern part of the Iberian Peninsula. Due to the vast diversity of mushrooms in nature, as well as nutrient variability, which is highly dependent on soil type and environmental conditions, it is essential to be able to characterize fungal microbiota that lives in association with mushrooms and to differentiate A. ponderosa strains of different regions for certification purposes. In this study, we characterized the genetic profile of A. ponderosa mushrooms and the fungal strains that live in association with them in their natural habitat and compared the fingerprinting profiles obtained by M13-PCR amplification of the genomic DNA.We found that the predominant fungal isolates living in association with A. ponderosa were Aspergillus spp., Penicillium spp. and Mucor spp. M13-PCR molecular analysis showed that different fungal isolates had different genetic profiles. This approach allowed us to differentiate the different fungi strains isolated from fruiting bodies of A. ponderosa both rapidly and in a reproducible manner and to group them according to genus. Our fingerprinting analyses also distinguished different A. ponderosa mushrooms collected from different regions. Consequently, we conclude that this method is a very discriminatory approach for differentiating both A. ponderosa from different sites and the fungal microbiota that lives in association with these mushrooms

Mesoporous Silica Based Protein Release Systems

Mesoporous silica nanoparticles (MSNs) such as MCM41 are effective support carriers with excellent adsorption properties and large surface areas [1-3]. Bioactive molecules like proteins such as albumin, casein and collagen are universally present in nature and products. Interaction of these proteins and MCM41 have not been widely explored. The aim of this study is to assess how these proteins behave in the presence of MCM41 and assess its protein release properties for the purpose of interdisciplinary applications

Biodeterioration in Art: a case study of Munch´s paintings.

Biocolonization and biodeterioration phenomena in Cultural Heritage is presently considered a relevant issue when planning conservation strategies and preservation measures in museum collections. Artworks such as easel paintings are source of various ecological niches for microbial communities’ growth due to the presence of several organic resources. Therefore, the identification of proteinaceous materials may play an important role in the evaluation of their conservation status, in the characterisation of the artistic technique, and in the definition of compatible conservation/restoration processes. Another challenge is to understand the microbiota associated to the degradative processes when developing conservation strategies in CH artworks. For this study Edvard Munch paintings belonging to Munch Museum in Oslo presenting surface alterations were analysed to increase the knowledge about the materials used by the painter and try to understand the source and the dynamics of the associated colonising microbiota, helping in devising a conservation intervention plan. Immunoenzymatic assays was carried out in microsamples allowing the detection of casein as the binder used by the artist. The high throughput sequencing approaches allowed us to explore and characterise the microbial communities that colonise these artworks. Bacterial communities found in these artworks were mainly composed by species characterised by proteolytic capacity, an important biodeteriogenic characteristic for these paintings. Simulation assays performed in paint models prepared with casein as binder display signs of degradative action promoted by the proteolytic strains isolated from the damaged areas. This approach can be useful to promote effective intervention processes in E. Munch’s paintings with the same pathologies

Modelling of Bacillus Amyloliquefaciens CCMI 1051 Cultures Using Artificial Intelligence Based Tools

It is well known that Bacillus species produce a wide variety of metabolites with interesting biological activities, namely antibiotic compounds as iturinic lipopeptides, being the aspartic acid a favourable nitrogen source for iturinic compounds production by B. subtilis and by B. amyloliquefaciens. The incubation time is another factor to be considered on antibiotic production. On the other hand, Artificial Neural Networks (ANN) are widely accepted as a tool that offers an alternative way to tackle complex problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. The prediction of Bacillus sporulation (BS) and antifungal activity of compounds (AFA), from incubation time of cultures (IT) and from aspartic acid concentration (AA) is a complex and highly nonlinear problem for which there are no known methods to predict them directly and accurately. The aim of this study is to optimize the production of antifungal compounds in B. amyloliquefaciens CCMI 1051 cultures using ANN. The database to be used contains antifungal data of cultures with different IT (1-9 days) using AA (0.4-5.6 g/L) as nitrogen source. In order to obtain the best prediction of the AFA and BS, different network structures and architectures have to be elaborated. The optimum number of hidden layers and the optimum number of nodes in each of these will be found by trial and error. The model being depicted above was in mean time accomplished, and the results obtained with it appointed that the maximum AFA is achieved with 2.6 g/L of aspartic acid on day 9. However, with AA of 4.8 g/L a similar maximum value of activity is obtained for incubation time over 6 days. The model shows a dual behaviour for AFA, depending of the IT. When the IT is higher than 5 days the AFA versus AA shows a pronounced sigmoid profile, converging to a common maximum value of AFA. On the other hand, for IT lower than 5 days mentioned profile is ill-defined and the common converging point isn’t observed. The conclusion is that the use of ANNs show to be a potent computational tool that must be present in any intelligent predictive task applied to Bacillus cultures, evidencing nitrogen source as key factor to be considered in these kind of problems, where the time of incubation plays a role in secondary production of active compounds