Biology subjects

Cunha, E.

Publications and source records attributed to Cunha, E..

7 recordsLinked to original sources

bioRxiv2026

Nutrient control enables metabolic reconstruction of L. rhamnosus GG and analysis of secretions

Lacticaseibacillus rhamnosus GG (LGG) is an important gut commensal bacterial strain that has been extensively studied in both industrial and health settings. Despite its long history of study, a high-quality genome-scale metabolic network model (GEM) for LGG has yet to be reconstructed. Only automatically-generated draft models have been published, which have notoriously limited functional accuracy. Furthermore, comprehensive nutrient requirements have not been established for well-controlled in vitro study. Here we present the first curated GEM for LGG using a new approach for reconstruction and validation that leverages multiple automatically-generated draft models, applied study literature, and high-throughput defined media experiments. In addition, our results include a series of chemically defined media, extensive single-component nutrient dropout growth data, insights from in silico and in vitro experiments into major secretion products lactate and indole-3-carboxaldehyde, a minimal medium and in silico characterization of LGGs nutrient requirements. Our approach for developing interdisciplinary research tools for LGG metabolism comprises a new framework that could be applied to many understudied microorganisms, particularly useful in studying bacteria within the human microbiome.

systems biology↗

bioRxiv2024

FROG Analysis Ensures the Reproducibility of Genome Scale Metabolic Models

Genome-scale metabolic models (GEMs) and other constraint-based models (CBMs) play a pivotal role in understanding biological phenotypes and advancing research in areas like metabolic engineering, human disease modelling, drug discovery, and personalized medicine. Despite their growing application, a significant challenge remains in ensuring the reproducibility of GEMs, primarily due to inconsistent reporting and inadequate model documentation of model results. Addressing this gap, we introduce FROG analysis, a community-driven initiative aimed at standardizing reproducibility assessments of CBMs and GEMs. The FROG framework encompasses four key analyses--Flux variability, Reaction deletion, Objective function, and Gene deletion--to produce standardized, numerically reproducible FROG reports. These reports serve as reference datasets, enabling model evaluators, curators, and independent researchers to verify the reproducibility of GEMs systematically. BioModels, a leading repository of systems biology models, has integrated FROG analysis into its curation workflow, enhancing the reproducibility and reusability of submitted GEMs. In our study evaluating 65 GEM submissions from the community, approximately 40% reproduced without intervention, 28% requiring minor adjustments, and 32% needing input from authors. The standardization introduced by FROG analysis facilitated the detection and resolution of issues, ultimately leading to the successful reproduction of all models. By establishing a standardized and comprehensive approach to evaluating GEM reproducibility, FROG analysis significantly contributes to making CBMs and GEMs more transparent, reusable, and reliable for the broader scientific community.

systems biology↗

bioRxiv2024

The genetic history of Portugal over the past 5,000 years

BackgroundRecent ancient DNA studies uncovering large-scale demographic events in Iberia have focused primarily on Spain, with limited reports for Portugal, a country located at the westernmost edge of continental Eurasia. Here, we introduce the largest collection of ancient Portuguese genomic datasets (n = 68) to date, spanning 5,000 years, from the Neolithic to the 19th century. ResultsWe found evidence of patrilocality in Neolithic Portugal, with admixture from local hunter-gatherers and Anatolian farmers, and persistence of Upper Paleolithic Magdalenian ancestry. This genetic profile persists into the Chalcolithic, reflecting diverse local hunter- gatherer contributions. During the Bronze Age, local genetic ancestry persisted, particularly in southern Iberia, despite influences from the North Pontic Steppe and early Mediterranean contacts. The Roman period highlights Idanha-a-Velha as a hub of migration and interaction, with a notably diverse genetic profile. The Early Medieval period is marked by Central European ancestry linked to Suebi/Visigoth migrations, adding to coeval local, African, and Mediterranean influences. The Islamic and Christian Conquest periods show strong genetic continuity in northern Portugal and significant African admixture in the south, with persistent Jewish and Islamic ancestries suggesting enduring influences in the post-Islamic period. ConclusionsThis study represents the first attempt to reconstruct the genetic history of Portugal from the analysis of ancient individuals. We reveal dynamic patterns of migration and cultural exchange across millennia, but also the persistence of local ancestries. Our findings integrate genetic information with historical and archaeological data, enhancing our understanding of Iberias ancient heritage.

genomics↗

bioRxiv2022

Exploring Xylella fastidiosa's metabolic traits using a GSM model of the phytopathogenic bacterium

Xylella fastidiosa is a gram-negative phytopathogenic bacterium that caused a significant economic impact around the world. In the last decade, genome-scale metabolic models have become important systems biology tools for studying the metabolic behaviour of different pathogens and driving the discovery of novel drug targets. This work is a second iteration of the iMS508 model for X. fastidiosa subsp. pauca De Donno. The model comprises 1138 reactions, 1234 metabolites, and 509 genes. in silico validation of the metabolic model was achieved through the comparison of simulations with available experimental data. Aerobic metabolism was simulated properly and fastidian gum production rates predicted accurately.

bioinformatics↗

bioRxiv2021

TranSyT, the Transport Systems Tracker

The importance and rate of development of genome-scale metabolic models have been growing for the last years, increasing the demand for software solutions that automate several steps of this process. However, since TRIAGEs release, software development for automatic integration of transport reactions into models has stalled. Here we present the Transport Systems Tracker (TranSyT), the next iteration of TRIAGE. Unlike its predecessor, TranSyT does not rely on manual curation to expand its internal database, derived from highly-curated records retrieved from the Transporters Classification Database and complemented with information from other data sources. TranSyT compiles information regarding transporters families, transport proteins, and derives reactions into its internal database, making it available for rapid annotation of complete genomes. All transport reactions have GPR associations and can be exported with identifiers from four different metabolite databases. TranSyT is currently available as a plugin for merlin v4.0 and an app for KBase.

bioinformatics↗

bioRxiv2021

iEC7871 Quercus suber model: the first multi-tissue diel cycle genome-scale metabolic model of a woody tree

In the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behavior at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871), the first of a woody plant. The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyze the pathways associated with the synthesis of suberin monomers. Nevertheless, the models developed in this work can provide insights into other aspects of the metabolism of Q. suber, such as its secondary metabolism and cork formation.

systems biology↗

bioRxiv2021

merlin v4.0: an updated platform for the reconstruction of high-quality genome-scale metabolic models

Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models reconstruction process, conjugating manual and automatic procedures, while leveraging the users expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features have been implemented in merlin, along with deep changes in the software architecture, operational flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates increased the user base, resulting in multiple published works, including genome metabolic (re-)annotations and model reconstructions of multiple (lower and higher) eukaryotes and prokaryotes. merlin version 4.0 is the only tool able to perform template based and non-template based draft reconstructions, while achieving competitive performance compared to state-of-the art tools both for well and less-studied organisms.

bioinformatics↗