Processamento e caracterização de extratos fenólicos de macroalgas: uma abordagem sistémica

Mestrado em Biotecnologia MolecularAs políticas industriais do século XXI têm sido pressionadas para uma mudança que torne sustentável o atual paradigma dos mercados e do desenvolvimento económico. A bioeconomia – assente no aproveitamento integral, na valorização e na recirculação das matérias primas utilizadas na indústria, tanto quanto possível de origem biológica - tem sido vista como uma abordagem promissora. A bioprospecção da biomassa para o desenvolvimento de novas aplicações, nomeadamente no isolamento de compostos bioativos, representa uma das linhas de investigação e desenvolvimento (I&D) para a concretização deste objetivo global.A biomassa de origem marinha (e em particular as macroalgas) tem ganho reconhecimento como uma excelente fonte de produtos de valor biotecnológico acrescentado, e a sua exploração constitui a chamada Biotecnologia Azul; para países como Portugal (detentor da 11ª maior zona económica exclusiva do mundo), a valorização estratégica dos mares constitui um importante pilar para o desenvolvimento económico sustentável. Apesar de existirem no mercado produtos derivados de extratos de algas, apenas alguns compostos foram valorizados na sua forma isolada (essencialmente polissacarídeos). Não obstante, os Compostos Fenólicos de Macroalgas (CFMs) – e em especial os florotaninos - são alvo de elevadas expectativas dadas as suas promissoras propriedades biológicas. A valorização destes metabolitos tem ocorrido, contudo, a um ritmo inferior ao expectável, devido à dificuldade em extraí-los de modo sustentável e em caracterizá-los estruturalmente, permanecendo a maioria dos estudos baseada em ensaios espetrofotométricos (pouco específicos). Esta tese propõe, assim, numa primeira fase, uma análise crítica da literatura, de modo a valorizar a informação existente, atualmente dispersa e pouco clara. Como tal, os dados publicados sobre a extração, separação e análise dos CFMs foram compilados e discutidos de forma sistemática. A aplicação de extração assistida por microondas foi revista em maior detalhe, e o uso de cromatografia-espetrometria de massa adequada à análise de florotaninos foi abordada de forma crítica. Nesta secção clarificou-se uma clara deficiência na obtenção e processamento inicial de extratos polares de macroalgas, com o objectivo de estudar os CFMs. A presença de outros metabolitos em quantidades superiores aos de interesse torna-se impeditiva no isolamento e caracterização de CFMs, em contexto académico, e potencia o uso de extratos brutos em vez de frações de valor acrescentado, na indústria. Por isso, numa segunda fase, o problema da co-extração de polissacarídeos com os CFMs é abordado, através do estudo de um processo de adsorção, do qual resultados preliminares são apresentados. Para tal, padrões de compostos modelo (fucoidano e alginato vs. ácido gálico, floroglucinol e catequina) foram usados, e a sua partição entre o solvente e o adsorvente (filtros de celulose vs. celulose microcristalina) avaliada por gravimetria, espetrofotometria e FT-IR. Os dados já obtidos por FT-IR da matriz de celulose após adsorção de uma mistura de polissacarídeos e CFMs revelam que uma maior afinidade da celulose para os polissacarídeos de algas (mantendo a maioria dos CFMs em solução), confirmando o potencial da técnica para uma rápida e eficiente separação destas duas familias.Industrial and economic politics of the XXI century are urging a change towards a more sustainable market and economic development paradigm. Bioeconomy – a paradigm based on integral use, valorization and recirculation of the materials used in industry, as much as possible of biological origin – has been recognized as a potential approach. Bioprospecting biomass for the development of alternatives to current models of human activity, and particularly in the isolation of novel bioactive compounds, is one of the research and development trends towards such global objective. Marine biomass – particularly seaweed - is increasingly considered an excellent source of added-value bio-based assets, and its exploration has given rise to the field of Blue Biotechnology; for countries like Portugal (holding the 11th largest exclusive economic zone), the strategic valorization of the seas constitutes an important part of sustainable economic growth. Despite the existence of some seaweed-derived nutraceuticals and cosmetics in the market, only a few isolated, structurally characterized extractives have been developed so far (essentially polysaccharides used in the food industry). Much potential is, nonetheless, attributed to Seaweed Phenolic Compounds (SPCs) - specially on phlorotannins – due to their diverse, promissing biological properties. However, a gap between the expected potentials of these metabolites and their actual rate of implementation exists, which is mainly a consequence of SPCs being difficult to be sustainably extracted and structurally analyzed. Thus, the majority of the literature in extraction and characterization of SPCs is rather speculative (based on spectrophotometric, non-specific assays. In the first part of this thesis, a critical analysis of the literature is presented, with the goal of making sense of the already existent information, since it is highly dispersed and nuclear. The application of MAE to seaweed bioactives components was deeply dissected, and the use of chromatographic-mass spectrometric setups adequate for the analysis of phlorotannins was critically reviewed. In this part, it could be observed that the problems retarding the study and valorization of SPCs lie on the extraction and initial processing of the polar extracts of seaweed. The presence of other metabolites, more abundant than the target SPCs, impairs a thorough isolation and characterization of these compounds, in an academical context, and promotes the exploration of crude extracts rather than added-value phenolic fractions, in an industrial environment. Thus, in the second part of the thesis, the problem of co-extraction of polysaccharides and SPCs is being addressed by an adsorption-based process, for which preliminar results are here reported. Such experiments were conducted using standard compounds (fucoidan and alginic acid vs. gallic acid phloroglucinol and catechin) to analyze their partition between the solvente and the adsorption matrix (celulose filters vs microcrystaline celulose) by means of gravimetry, spectrophotometry and FT-IR. Data obtained so far from FT-IR of the dried adsorbent after contact with a mixture of polysaccharides-SPCs suggest revealed the higher affinity of celulose for the sugars (with most SPC remaining in solution), confirming the suspected potential of the technique for the separation of these two classes of biomolecules

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data