Biology subjects

Parra, V.

Publications and source records attributed to Parra, V..

4 recordsLinked to original sources

bioRxiv2025

Effects of Willow and Pine tree growth in bacterial abundance, interactions and metabolic profile in a copper mine tailing

The Cauquenes tailings is one of the largest mine tailings in Chile and represents a significant environmental hazard due to its high copper levels and acidic pH. However, there is evidence of willow and pine tree growth in these terrains, which is unexpected given the extreme conditions of this environment. Considering the importance of plants in restoration strategies, the objective of this study was to analyze the effect that willow and pine growth have on the heavy metal contents of their surrounding soil, and the abundance, interaction, metabolic profile and assembly of the bacterial community. In the Cauquenes tailing, we collected samples from willow and pine vegetated soils as well as the surrounding non-vegetated soils. We analyzed characteristics such as heavy metal concentrations and pH levels in all sampled soils, and in tree leaves and roots. Vegetated sites exhibited lower copper levels and a neutral pH, while both tree species accumulated heavy metals in their tissues. We also determined bacterial abundance in all soil samples, and co-occurrence networks were constructed to assess bacterial interactions. Both trees promoted a higher abundance of Proteobacteria and had networks with higher modularity compared to non-vegetated soils. Finally, we estimated the metabolic profile of the bacterial community using PICRUSt 2 analysis and determined carbon source utilization with BioLog Ecoplates. PICRUSt 2 predicted higher metabolic activity in vegetated soils, and BioLog Ecoplate analysis revealed the utilization of a greater number of carbon sources. The microbial communities from vegetated soils were assembled in a deterministic manner, while the community from non-vegetated soils were stochastically assembled. In conclusion, tree growth mitigated the extreme conditions of the tailing and promoted a more active and healthier bacterial community. HighlightsO_LIWillow and pine tree can grow and mitigate toxic metal conditions in the tailings C_LIO_LIBoth trees provoked a shift in bacterial abundance and interaction network C_LIO_LIThe provoked shift was tree-dependent C_LIO_LIMicrobial activity was higher in vegetated soils C_LI

microbiology↗

bioRxiv2025

Reduced glutathione levels in Enterococcus faecalis trigger metabolic and transcriptional compensatory adjustments during iron exposure.

Enterococcus faecalis, a facultative anaerobic pathogen and common constituent of the gastrointestinal microbiota, must navigate varying iron levels within the host. This study explores its response to iron supplementation in a glutathione-deficient mutant strain ({Delta}gsh). We examined the transcriptomic and metabolic responses of a glutathione synthetase mutant strain ({Delta}gsh) exposed to iron supplementation, integrating these data into a genome-scale metabolic model (GSMM). Our results show that under glutathione deficiency, E. faecalis reduces intracellular iron levels and shifts its transcriptional response to prioritize energy production genes. Notably, basal metabolites, including arginine, increase. The GSMM highlights the importance of arginine metabolism, particularly the arc operon (anaerobic arginine catabolism), as a compensatory mechanism for reduced glutathione during iron exposure. These findings provide insights into how E. faecalis adjusts metal homeostasis and transcriptional/metabolic processes to mitigate the effects of oxidative stress caused by iron. IMPORTANCEIron is essential for bacterial survival, yet its excess can be harmful through increase of oxidative stress. Enterococcus faecalis, a bacterium common member of the human gut, must carefully balance its iron levels in order to survive in changing environments. This study studies how E. faecalis compensates the reduced levels of glutathione --a key antioxidant-- when exposed to high iron concentrations. We discovered that E. faecalis lowers its intracellular iron levels under glutathione decrease and reprograms its metabolism to prioritize energy production. These findings provide valuable insights into bacterial adaptation mechanisms under oxidative stress conditions, which could influence the development of new strategies to combat bacterial infections.

systems biology↗

bioRxiv2024

Profiling extremophile bacterial communities recovered from a mining tailing against soil ecosystems through comparative genome-resolved metagenomics and evolutionary analysis

Microbial communities inhabiting mining environments harbor a diverse array of bacteria with specialized metabolic capacities adapted to extreme conditions. Here, we utilized comparative genome-resolved metagenomics of a high-quality Illumina-sequenced sample from the Cauquenes copper tailing in central Chile. We investigate the metabolic roles and evolutionary behaviors of the resident microorganisms, focusing on capacities related to copper, iron, and sulfur metabolism. We recovered 44 medium and high-quality metagenome-assembled genomes (MAGs), primarily classified belonging to phylum Actinobacteriota (21), Proteobacteria (10), and Acidobacteriota (6). These MAGs were compared to the Global Soil MAGs project (SMAG catalog), which includes bacteria from conventional or natural ecosystems, to uncover specialized properties of mining bacteria. Notably, we discovered a new phylum, Nitrospirota_A, and provided insights into the unexplored taxonomic classifications at the lowest ranks such as genus and species. Functional potential analysis revealed that the mining community has enhanced molecular capabilities associated with sulfur and copper metabolism. Evolutionary analysis revealed that mining genes involved in targeted metabolism are under strong negative selection, indicating conservative evolutionary pressure within the mining environment. In particular, it was possible to identify a MAG from the genus Acidithrix with a global dN/dS ratio greater than 1, suggesting positive selection. Additionally, core proteins essential for bacterial survival, such as flagellar motors, cell cycle regulators, and biogenesis proteins, were also under positive selection. The latter points to the need for enhanced mobility in these microorganisms to locate resources efficiently. We demonstrate that copper mining communities are diverse and possess a significant metabolic repertoire under extreme conditions in sulfur and copper proteins. Those specialized genes appear to be in a conservative state rather than undergoing adaptive evolution. This study enhances our understanding of extremophile mining microbiomes, highlighting their high variability in classification, metabolic functions, evolution, and adaptation, which can be leveraged for further biotechnological applications.

genomics↗

bioRxiv2022

Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT)

Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell and pathomics data to find sample level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics and pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell and pathomics data. Moreover, PILOT provides a statistical approach to delineate non-linear changes in cell populations, gene expression, and tissue structures related to the disease trajectories supporting interpretation of predictions.

bioinformatics↗