Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Antioxidant potential of two Apiaceae plant extracts: a comparative study focused on the phenolic composition

The present study aimed to characterize the extracts prepared from Pimpinella anisum L. (anise) and Coriandrum sativum L. (coriander) (Apiaceae plants) seeds in terms of phenolic composition, and to correlate the obtained profiles with the antioxidant activity. Anise gave the highest abundance in phenolic compounds (42.09± 0.11 mg/g extract), mainly flavonoids (28.08±0.17 mg/g extract) and phenolic acids (14.01±0.06 mg/g extract), and also the highest antioxidant potential, accessed for the ability to inhibit lipid peroxidation and -carotene bleaching, reducing power and free radical scavenger activity. Apigenin and luteolin derivatives, as also caffeoylquinic acid derivatives appear to be directly related with the higher in vitro antioxidant potential of the anise extract.. In contrast, the weak antioxidant potential of coriander seems to be due to their lower abundance in phenolic compounds (2.24±0.01 mg/g extract). Further studies are necessary to evaluate the in vivo antioxidant potential of the tested extracts, but the performed in vitro experiments highlight them as potential health promoters.

Biotechnological approaches for yield improvement of anticancer alkaloids in the plant Catharanthus roseus

Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

Saprotrophic fungi Hypholoma fasciculare effect on the fungal community associated to Castanea sativa

Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

Pharmacological evaluation of plant extracts from Chapada Diamantina (Bahia, Brazil): Focus on antioxidant and cytotoxic properties

Tese de Doutoramento em Biologia de Plantas MAP - Bioplant

Synthetic biology approaches to engineer new pathways for the production of plant secondary metabolites

Secondary metabolites from plants are important sources of high-value chemicals, many of them being pharmacologically active. These metabolites are commonly isolated through inefficient extractions from natural biological sources and are often difficult to synthesize chemically. Therefore, their production using engineered organisms has lately attracted an increased attention. Curcuminoids, an example of such metabolites, are produced in Curcuma longa and exhibit anti-cancer and anti-inflammatory activities. Herein we report the construction of an artificial biosynthetic pathway for the curcuminoids production in Escherichia coli. Different 4-coumaroyl-CoA ligases (4CL) and polyketide synthases (diketide-CoA synthase (DCS), curcumin synthase (CURS) and curcuminoid synthase) were tested. The highest curcumin production (70 mg/L) was obtained by feeding ferulic acid and with the Arabidopsis thaliana 4CL1 and C. longa DCS and CURS enzymes. Other curcuminoids (bisdemethoxy- and demethoxycurcumin) were also produced by feeding coumaric acid or a mixture of coumaric and ferulic acids, respectively. Curcuminoids, including curcumin, were also produced from tyrosine through the caffeic acid pathway. To produce caffeic acid, tyrosine ammonia lyase and 4-coumarate 3-hydroxylase were used. Caffeoyl-CoA O-methyltransferase was used to convert caffeoyl-CoA to feruloyl-CoA. This pathway represents an improvement of the curcuminoids heterologous production. The construction of this pathway in another model organism is being considered, as well as the introduction of alternative enzymes.

Evaluation of bioactivities of a propolis sample (Gerês) of Portuguese origin

Dissertação de mestrado em Genética Molecular

Brazelton Neonatal Behavioral Assessment Scale: a psychometric study in a Portuguese sample

Background: The Neonatal Behavioral Assessment Scale (NBAS, Brazelton & Nugent, 1995) is an instrument conceived to observe the neonatal neurobehavior. Data analysis is usually performed by organizing items into groups. The most widely used data reduction for the NBAS was developed by Lester, Als, and Brazelton (1982). Objective: Examine the psychometric properties of the NBAS items in a sample of 213 Portuguese infants. Method: The NBAS was performed in the first week of infant life (3 days±2) and in the seventh week of life (52 days±5). Results: Principal component analyses yielded a solution of four components explaining 55.13% of total variance. Construct validity was supported by better neurobehavioral performance of 7-week-old infants compared with 1-week-old infants. Conclusion: Changes in the NBAS structure for the Portuguese sample are suggested compared to Lester factors in order to reach better internal consistency of the scale.

Characterization of microbial populations in a wastewater treatment plant focusing on Staphylococcus aureus and Pseudomonas aeruginosa

Dissertação de mestrado em Bioengenharia