Biology subjects

Delgado, L. F.

Publications and source records attributed to Delgado, L. F..

5 recordsLinked to original sources

bioRxiv2026

The marine microbiome can accurately predict its chemical and biological environment

The microbiome responds to physicochemical changes in the environment, making it a sensitive indicator of ecosystem status. Monitoring microbial communities in aquatic systems is therefore essential for understanding ecosystem health and responses to change. Traditionally reliant on microscopy, monitoring programmes are increasingly incorporating DNA-based approaches leveraging on advances in high-throughput sequencing. In this study, we evaluate the potential of using DNA metabarcoding to predict abiotic and biotic parameters across the spatiotemporal gradients of the Baltic Sea. The dataset comprises 397 seawater samples integrating prokaryotic (16S rRNA gene) and eukaryotic (18S rRNA gene) metabarcoding data with environmental measurements and plankton microscopy counts. Random Forest models based on metabarcoding data accurately predicted a range of physicochemical parameters and showed performance comparably to more complex machine learning algorithms. Models based on 16S rRNA gene data tended to perform better than those based on 18S rRNA gene data, with amplicon sequence variant-level data yielding the best results. Metabarcoding outperformed plankton microscopy in predicting abiotic factors and effectively predicted the presence of phytoplankton and zooplankton genera using [≤]1 L of water. Models trained on independent datasets accurately predicted several of the physicochemical parameters, but performed weaker on others, highlighting the potential and challenges for their transferability. Furthermore, our predictions closely matched the observed HELCOM indicator values for assessing good environmental status, suggesting the utility of microbiome-based approaches in regional marine monitoring frameworks. These findings underscore the potential of environmental DNA as a tool for ecosystem monitoring and management in dynamic coastal systems.

microbiology↗

bioRxiv2025

Phylogeny-aware comparative genomics of Vibrio vulnificus links genetic traits to pathogenicity

Vibrio vulnificus is a natural inhabitant of coastal brackish waters worldwide and an opportunistic pathogen that can cause severe infections and septicemia through seafood consumption or wound exposure. Due to global warming, its abundance is increasing at high latitudes. While the species harbors diverse virulence factors, its precise disease mechanisms remain unclear. Comparative genomics between clinical and environmental isolates can help identify key virulence genes, but the limited availability of genomes from environmental isolates has hindered progress. In this study, we sequenced the genomes of 82 V. vulnificus isolates from water, sediment, and seagrass along the Baltic Sea coast and complemented with published genomes from 208 clinical and 117 globally distributed isolates for comparative analysis. Phylogenetic reconstruction confirmed four major lineages, with Baltic Sea strains confined to lineage L2 and L4, while clinical and environmental strains were distributed across all lineages. This suggests that the phylogenetic structure of V. vulnificus reflects adaptation to environmental conditions rather than pathogenicity. Using the PhyloBOTL pipeline developed here, we identified 128 orthologs significantly enriched in clinical isolates, grouped into 36 co-localization clusters based on proximity in the genomes. These included genes linked to virulence, such as those for capsular polysaccharide synthesis and biofilm formation, as well as previously unrecognized candidates, including chaperone-usher pilus biosynthesis, spermidine synthesis, Type VI secretion effectors, and an RTX toxin-like protein. Several of the clinically enriched gene clusters have been independently lost in three V. vulnificus clades, suggesting convergent evolution and a distinct ecological niche shared by these claded. Finally, we used the clinically enriched genes to design PCR primers for detecting and monitoring pathogenic V. vulnificus strains, providing a valuable tool for surveillance and public health efforts.

microbiology↗

bioRxiv2024

PathoFact 2.0: An Integrative Pipeline for Predicting Antimicrobial Resistance Genes, Virulence Factors, Toxins and Biosynthetic Gene Clusters in Metagenomes

SummaryAntimicrobial resistance genes (ARGs) and virulence factors (VFs) are central contributors to the global health crisis surrounding drug-resistant infections. PathoFact, a bioinformatics pipeline introduced in 2021, provides insights into ARGs, VFs, and bacterial toxins from metagenomic data. However, recent advancements in bioinformatics highlight the need for an updated version of PathoFact. We introduce PathoFact 2.0, an enhanced pipeline for improved ARG, VF, and toxin prediction. Key updates include an updated machine learning (ML) model for VF identification, a new ML model for toxin identification, expanded hidden Markov model profiles, and the antiSMASH 7.0 integration for predicting biosynthetic gene clusters. These upgrades make PathoFact 2.0 a more powerful, user-friendly platform for predicting microbiome-based pathogenicity and resistance, offering a crucial tool for better understanding and addressing the challenges posed by antimicrobial resistance and infectious diseases. Availability and ImplementationPathoFact 2.0 is available for download at https://gitlab.lcsb.uni.lu/ESB/PathoFact2/.

bioinformatics↗

bioRxiv2022

Large-scale phylogenomics of aquatic bacteria reveal molecular mechanisms for adaptation to salinity

The crossing of environmental barriers poses major adaptive challenges. Rareness of freshwater-marine transitions separates the bacterial communities, but how these are related to brackish counterparts remains elusive, as are molecular adaptations facilitating cross-biome transitions. Here, we conduct large-scale phylogenomic analysis of freshwater, brackish, and marine quality-filtered metagenome-assembled genomes (11,276 MAGs). Average nucleotide identity analyses showed that bacterial species rarely existed in multiple biomes. Distinct brackish basins co-hosted numerous species despite differences in salinity and geographic distance, the latter having stronger intra-species population structuring effects. We further identified the most recent cross-biome transitions, which were rare, ancient, and most commonly directed towards the brackish biome. Transitions were accompanied by changes in isoelectric point distribution and amino acid composition of inferred proteomes, as well as convergent gains or losses of specific gene functions. Therefore, adaptive challenges entailing proteome reorganization and specific changes in gene content result in species-level separation between aquatic biomes.

microbiology↗

bioRxiv2021

Evaluating metagenomic assembly approaches for biome-specific gene catalogues

For many environments, biome-specific microbial gene catalogues are being recovered using shotgun metagenomics followed by assembly and gene-calling on the assembled contigs. The assembly can be conducted either by individually assembling each sample or by co-assembling reads from all the samples. The co-assembly approach can potentially recover genes that display too low abundance to be assembled from individual samples. On the other hand, combining samples increases the risk of mixing data from closely related strains, which can hamper the assembly process. In this respect, assembly on individual samples followed by clustering of (near) identical genes is likely preferable. Thus, both approaches have pros and cons and it remains to be evaluated which assembly strategy is most effective. Here, we have evaluated three assembly strategies for generating gene catalogues from metagenomes using a dataset of 124 samples from the Baltic Sea: 1) assembly on individual samples followed by clustering of the resulting genes, 2) co-assembly on all samples, and 3) mix-assembly, combining individual and co-assembly. The mix-assembly approach resulted in a more extensive non-redundant gene set than the other approaches, and with more genes predicted to be complete and that could be functionally annotated. The mix-assembly consists of 67 million genes (Baltic Sea gene set; BAGS) that have been functionally and taxonomically annotated. The majority of the BAGS genes are dissimilar (<95% amino acid identity) to the Tara Oceans gene dataset, and hence BAGS represents a valuable resource for brackish water research. IMPORTANCESeveral ecosystem types, such as soils and oceans, are studied through metagenomics. It allows the analysis of genetic material of the microbes within a sample without the need for cultivation. When performing the DNA sequencing with an instrument that generates short sequence reads, these reads need to be assembled in order to obtain more complete gene sequences. In this paper, we have evaluated three strategies for assembling metagenome sequences using a large metagenomic dataset from the Baltic Sea. The method that we call mix-assembly generated the greatest number of non-redundant genes and the largest fraction of genes that were predicted to be complete. The resulting gene catalogue will serve as an important resource for brackish water research. We believe this method to be efficient also for generating gene catalogs for other biomes.

bioinformatics↗