Biology subjects

Lourenco, A.

Publications and source records attributed to Lourenco, A..

3 recordsLinked to original sources

bioRxiv2025

Discovering the corky bark of Eucalyptus suberea from anatomical and chemical perspectives

This paper presents the first scientific investigation of the corky bark of Eucalyptus suberea (cork mallee). The study involved outer bark samples from two trees with diameters of 23 cm (A) and 47 cm (B), collected from a plantation in Portugal. Anatomical analysis was performed using light and scanning electron microscopy (SEM), enabling detailed observation of bark to reveal the cork cells presence. The chemical characterization included summative chemical analysis, FTIR, and GC-MS/FID for suberin composition and Py-GC-MS for lignin composition. The extractive-free bark mass of E. suberea from trees A and B contained 29% and 25% suberin, 30% and 37% lignin, and 39% and 38% polysaccharides, respectively. The bark A exhibited a higher extractives content (49%) than just 14% for bark B. Conversely, dichloromethane extract from bark A was notably rich in alkanol ferulates. FTIR spectra revealed a characteristic cork tissue pattern, showing a low suberin content but high levels of polysaccharides and free carboxylic acids. The main components of E. suberea A and B suberins were glycerol, with 15% and 11%, {omega}-hydroxyacids, with 45% and 50%, and ,{omega}-diacids, with 30% and 17%, representing a total of ca. 90% and 78% of E. suberea A and B suberins mass, respectively. Both suberins showed low contents of epoxides and vic-diols; also, both presented the particularity of having high contents of free acid groups, especially the suberin of bark B, suggesting a structure with short aliphatic chains. E. suberea corky bark presents a lignin composition that differentiates from the cork G-lignins analyzed until now with a monomer composition exhibiting a GS character, with more G- (53-56%) than S-units (34-37%) with an S/G ratio between 0.64 to 0.66, for A and B lignins, respectively.

plant biology↗

bioRxiv2024

Design of Novel Dehalogenases using Protein Large Language Models

Per- and polyfluoroalkyl substances (PFAS) are toxic compounds linked to cancers, infertility, and vaccine resistance at concentrations above 1 part per trillion. Owing to strong carbon-fluorine bonds, they are persistent in the environment, taking centuries to millennia to degrade. As part of the 2024 iGEM competition, several high school students local to the Pasadena area leveraged recently-developed bioinformatic tools and large language models to discover and design novel reductive dehalogenases predicted to degrade perfluorooctanoic acid (PFOA), a long chain PFAS whose manufacture is prohibited, yet still persists in the environment and drinking water. The team identified 68 enzymes with structural similarity to Acidimicrobium sp. Strain A6 RdhA, the only specific known PFAS degrading enzyme in nature, expressed and refolded 5 of these enzymes in addition to 1 rational, and 3 large language model designs. These designs all have diverse sequences yet all are predicted to retain key substrate and cofactor binding pockets. These enzymes will be assayed on the ability to defluorinate PFOA.

bioengineering↗

bioRxiv2017

Lessons Learned: Recommendations for Establishing Critical Periodic Scientific Benchmarking

The dependence of life scientists on software has steadily grown in recent years. For many tasks, researchers have to decide which of the available bioinformatics software are more suitable for their specific needs. Additionally researchers should be able to objectively select the software that provides the highest accuracy, the best efficiency and the highest level of reproducibility when integrated in their research projects.\n\nCritical benchmarking of bioinformatics methods, tools and web services is therefore an essential community service, as well as a critical component of reproducibility efforts. Unbiased and objective evaluations are challenging to set up and can only be effective when built and implemented around community driven efforts, as demonstrated by the many ongoing community challenges in bioinformatics that followed the success of CASP. Community challenges bring the combined benefits of intense collaboration, transparency and standard harmonization. Only open systems for the continuous evaluation of methods offer a perfect complement to community challenges, offering to larger communities of users that could extend far beyond the community of developers, a window to the developments status that they can use for their specific projects. We understand by continuous evaluation systems as those services which are always available and periodically update their data and/or metrics according to a predefined schedule keeping in mind that the performance has to be always seen in terms of each research domain.\n\nWe argue here that technology is now mature to bring community driven benchmarking efforts to a higher level that should allow effective interoperability of benchmarks across related methods. New technological developments allow overcoming the limitations of the first experiences on online benchmarking e.g. EVA. We therefore describe OpenEBench, a novel infra-structure designed to establish a continuous automated benchmarking system for bioinformatics methods, tools and web services.\n\nOpenEBench is being developed so as to cater for the needs of the bioinformatics community, especially software developers who need an objective and quantitative way to inform their decisions as well as the larger community of end-users, in their search for unbiased and up-to-date evaluation of bioinformatics methods. As such OpenEBench should soon become a central place for bioinformatics software developers, community-driven benchmarking initiatives, researchers using bioinformatics methods, and funders interested in the result of methods evaluation.

bioinformatics↗