Biology subjects

Araujo, G.

Publications and source records attributed to Araujo, G..

8 recordsLinked to original sources

bioRxiv2025

The eco-evolutionary assembly of complex communities with multiple interaction types

Identifying the mechanisms that generate structure in complex ecological communities is fundamental to understand their assembly. A comprehensive picture of how ecology and evolution act together to generate these patterns is in its infancy. We developed an eco-evolutionary model of community assembly that incorporates interaction-driven population dynamics and evolutionary processes, including speciation and the inheritance of interactions, to unveil the mechanisms of generation and maintenance of biodiversity in complex species interaction networks. Importantly, our model unpicks the effects of selection of interaction types from those of inheritance by comparing evolutionary assembly with assembly by invasion under different combinations of interaction types. We found that a cost-benefit balance of accumulating interactions separates communities into two distinct types. Interactions with weak benefits for the partners involved produce communities with sparse species interaction networks dominated by competition. Strongly beneficial interactions, on the other hand, give rise to highly mutualistic, more connected communities. Mutualism, driven by both selection and inheritance, facilitates the emergence of large yet stable communities with increased complexity. By contrasting the model results with empirical patterns from microbial communities, we identify potential drivers of the assembly of these complex ecosystems and their likely patterns of interaction. Our results provide a classification system of complex ecosystems based on their composition of ecological interactions, thus generating testable hypotheses on the conditions under which different community types (mutualistic vs. competitive) might emerge.

ecology↗

bioRxiv2025

Towards key principles of host-associated microbiome assembly

Symbiotic relationships between microbes and host organisms frequently involve the assembly of complex microbial communities (microbiomes) within hosts. Patterns at the community level influence life-history traits, the evolutionary trajectories of both microbes and their hosts, and are often critical for maintaining host health. These community-level patterns are dynamically driven by eco-evolutionary mechanisms acting at the individual level, such as microbial dispersal, host selection, and microbe-resource interactions. Critically, we still lack a clear picture of the ways in which these mechanisms interact to shape microbiome assembly. Here, we present a model of assembly to describe how distinct community structures can be characterised by underlying mechanisms. To illustrate the approach, we analyse microbiome data from marine sponges and simulate different structures of host-microbe associations, thereby bridging mechanistic models and empirical patterns. We further apply the model to human microbiome data to explore its relevance across biological systems, proposing that the combined effect of a small set of general mechanisms may govern diverse patterns of microbial diversity and abundance. Our findings advance ecological theory by linking individual-level processes to community-scale patterns, illuminating the key drivers underlying microbiome assembly.

microbiology↗

bioRxiv2025

Mapping Risk and Resilience Across Indo-Pacific Reefs with Shark Genomescapes

Overfishing has severely depleted marine populations worldwide, including within protected areas. Illegal and unreported fishing are major contributors to this decline. Large-bodied apex predators such as sharks are among the most affected, with overfishing causing dramatic species declines and ecosystem destabilization due to trophic downgrading. Key barriers to effective marine conservation and management include: Data deficiencies that hinder population benchmarks and impact assessments, limited surveillance, allowing illegal fisheries to disproportionately affect apex predators, and insufficient capacity in vulnerable nations to monitor and protect species within their waters. Our study addresses these challenges through a novel genomic framework that enables assessment of shark population diversity and health, while also improving fisheries traceability by detecting instances of illegal fishing across the Indian and Pacific Oceans. We present the Reefshark Genomescape, the first genome-wide reference database for Indo-Pacific reef sharks, an assessment of genetic diversity, structure, and connectivity of two key species across their Indo-Pacific range and geographic assignment of fished individuals using population-specific genetic signatures. We show that grey reef shark (Carcharhinus amblyrhynchos) populations exhibit high genetic diversity, strong population structure, and elevated Fst values, with previously unknown connectivity between the central and western Indian Ocean and clear isolation of populations in the Andaman Sea. In contrast, silvertip sharks (Carcharhinus albimarginatus) display high connectivity, but show genomic signals of declining population health, supporting a reassessment of their IUCN status. Using supervised machine learning with Monte Carlo cross-validation, we assigned geographic origins to fished grey reef sharks with 96% accuracy. These findings provide critical insights into population structure, connectivity, and health of two ecologically important reef shark species, while establishing a robust method for assigning geographic origin. We anticipate this framework will support regional conservation assessments and targeted management. Moreover, by enabling the identification of fishing hotspots and detection of IUU fishing, it lays the groundwork for a broader traceability system in marine ecosystems. Much like the landmark elephant ivory tracing study, our approach has the potential to transform marine conservation globally. Graphical AbstractWe developed the Reefshark Genomescape, a genomic framework for assessing shark population health and fisheries traceability across the Indo-Pacific. Genome-wide data from grey reef and silvertip sharks revealed contrasting patterns, unexpected connectivity, and genomic signals of decline. Geographic assignment of fished individuals reached 96% accuracy, enabling detection of illegal fishing and identification of hotspots. This framework strengthens regional management, supports IUCN reassessments, and lays the foundation for global marine traceability systems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC="FIGDIR/small/676358v2_ufig1.gif" ALT="Figure 1"> View larger version (84K): org.highwire.dtl.DTLVardef@1eafd3aorg.highwire.dtl.DTLVardef@96ebd1org.highwire.dtl.DTLVardef@541d02org.highwire.dtl.DTLVardef@3c9ca2_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Mutualism provides the basis for biodivesity in eco-evolutionary community assembly

Unveiling the ecological and evolutionary mechanisms underpinning the assembly of stable and complex ecosystems is a main focus of community ecology. Ecological theory predicts the necessity of structural constraints on the network of species interactions to allow for growth of complexity in assembling multispecies communities. A promising research avenue is the search for an understanding of how the coexistence of diverse species interaction types could influence the development of complexity and how an ideal composition could arise in nature. We propose an ecological model with mixed interaction types incorporating evolutionary assembly by speciation. This framework allows to investigate the eco-evolutionary assembly on complex species interaction networks with multiple interaction types and its consequences for ecosystem stability. Our results show that highly mutualistic communities are conducive of complexity and promote the emergence of consumer-resource interactions. Furthermore, we show that an evolutionary process is required to produce such condition. Moreover, this evolutionary assembly generates a diversity of outcomes and promotes two distinct types of complexity depending on speciation constraints. Assembled communities are thus either larger (more species) or more connected, in agreement with patterns previously observed in microbial communities. Our results produce invaluable theoretical insight into the mechanisms behind the emergence of ecological complexity and into the roles of mutualism and speciation on community formation.

ecology↗

bioRxiv2022

Phospholipase B is critical for Cryptococcus neoformans survival in the central nervous system

Cryptococcus neoformans (Cn) is an opportunistic, encapsulated, yeast-like fungus that causes severe meningoencephalitis, especially in countries with high HIV prevalence. In addition to its well-known polysaccharide capsule, Cn has other virulence factors such as phospholipases, a heterogeneous group of enzymes that hydrolyze ester linkages in glycerophospholipids. Phospholipase B (PLB1) has been demonstrated to play a key role in Cn pathogenicity. In this study, we used a PLB1 mutant (plb1) and its reconstituted strain (Rec1) to assess the importance of this enzyme on Cn brain infection in vivo and in vitro. Mice infected with plb1 strain survive significantly longer, have lower central nervous system (CNS) fungal load, and fewer and smaller cryptococcomas or biofilm-like brain lesions compared to H99- and Rec1-infected animals. plb1 cryptococci are significantly more phagocytosed and killed by NR-9460 microglia-like cells. plb1 cells have altered capsular polysaccharide biophysical properties that impair their ability to stimulate glia cell responses or morphological changes. We provide significant evidence demonstrating that Cn phospholipase is an important virulence factor for fungal colonization of and survival in the CNS as well as in the progression of cryptococcal meningitis. These findings may potentially help fill in a gap of knowledge in our understanding of cerebral cryptococcosis and may provide novel research avenues in Cn pathogenesis. IMPORTANCECryptococcal meningoencephalitis is a serious disease caused by infection of the neurotropic fungal pathogen Cryptococcus neoformans (Cn). Due to the increasing number of cases in HIV-infected individuals, as well as the limited therapies available, investigation into potential targets for new therapeutics has become critical. Phospholipase B (PLB1) is an enzyme synthesized by Cn that confers virulence to the fungus through capsular enlargement, immunomodulation, and intracellular replication. In this study, we examined the properties of PLB1 by comparing infection of Cn PLB1 mutant strain with both the wild-type and a PLB1 reconstituted strain. We show that PLB1 augments the survival and proliferation of the fungus in the CNS and strengthens virulence through modulation of the immune response and enhancement of specific biophysical properties of the fungus. The implications of PLB1 inhibition reveal its involvement in Cn infection and suggest that it may be a possible molecular target in the development of antifungal therapies. The results of this study support additional investigation into the mechanism of PLB1 to further understand the intricacies of Cn infection.

microbiology↗

bioRxiv2021

Straintables: An application that extracts sequences fromgenome assemblies and generates dissimilarity matrices

Background and ObjectivesThe dissimilarity matrix (DM) is an important component of phylogenetic analysis, and many software packages exist to build and show DMs. However, as the common input for this type of software are sequences in FASTA file format, the process of extracting and aligning each set of sequences to produce a big number of matrices can be laborious. Additionally, existing software do not facilitate the comparison of clusters of similarity across several DMs built for the same group of individuals, using different genomic regions. To address our requirements of such a tool, we designed Straintables to extract specific genomic region sequences from a group of intraspecies genomic assemblies, using extracted sequences to build dissimilarity matrices. MethodsA Python module with executable scripts was developed for a study on genetic diversity across strains of Toxoplasma gondii, being a general purpose system for DM calculation and visualization for preliminary phylogenetic studies. For automatic region sequence extraction from genomic assemblies we assembled a system that designs virtual primers using reference sequences located at genomic annotations, then matches those primers on genome files by using regex patterns. Extracted sequences are then aligned using Clustal Omega and compared to generate matrices. ResultsUsing this software saves the user from manual preparation and alignment of the sequences, a process that can be laborious when a large number of assemblies or regions are involved. The automatic sequence extraction process can be checked against BLAST results using extracted sequence as queries, where correct results were observed for same-species pools for various organisms. The package also contains a matrix visualization tool focused on cluster visualization, capable of drawing matrices into image files with custom settings, and features methods of reordering matrices to facilitate the comparison of clustering patterns across two or more matrices. ConclusionStraintables may replace and extend the functionality of existing matrix-oriented phylogenetic software, featuring automatic region extraction from genomic assemblies and enhanced matrix visualization capabilities emphasizing cluster identification. This module is open source, available at GitHub (https://github.com/Gab0/straintables) under a MIT license and also as a PIPY package. HighlightsSimple in-silico protocol for generation, visualization and comparison of dissimilarity matrices. Accurate automatic sequence extraction from multiple genomic assemblies by using virtual primers built from reference sequences in an annotation file. Draws matrices as images, with enhanced cluster visualization and customized options. Supports reordering of matrix indices to better visualize clustering pattern conservation across multiple regions.

bioinformatics↗

bioRxiv2021

Extracellular vesicles regulate yeast growth, biofilm formation, and yeast-to-hypha differentiation in Candida albicans

The ability to undergo morphological changes during adaptation to distinct environments is exploited by Candida albicans and has a direct impact on virulence. In this study, we investigated the influence of fungal extracellular vesicles (EVs) during yeast growth, biofilm formation, and morphogenesis in C. albicans. Addition of C. albicans EVs (Ca EVs) to the culture medium positively affected yeast growth. Using crystal violet staining and scanning electron microscopy (SEM), we demonstrated that Ca EVs inhibited biofilm formation by C. albicans in vitro. By time-lapse microscopy and SEM, we showed that Ca EV-treatment stops filamentation promoting pseudohyphae formation with multiple sites for yeast budding. The ability of Ca EVs to regulate dimorphism was further compared to EVs isolated from different C. albicans strains, Saccharomyces cerevisiae, and Histoplasma capsulatum. Ca EVs from distinct strains robustly inhibited yeast-to-hyphae differentiation with morphological changes occurring in less than 4 hours. A minor inhibitory effect was promoted by EVs from S. cerevisiae and H. capsulatum only after 24 hours of incubation. The inhibitory effect of Ca EVs was promoted by a combination of lipid compounds identified by gas chromatography-tandem mass spectrometry analysis as sesquiterpenes, diterpenes, and fatty acids. Remarkably, Ca EVs were also able to reverse filamentation, transforming hyphal growth to yeast forms. Transcriptomic analysis demonstrated that treatment with Ca EVs modified the expression of more than 300 genes. The most effectively upregulated pathways were related to DNA metabolism. The downregulated genes were mostly associated with extracellular and adhesion proteins. Finally, yeast cells treated with Ca EVs for 24 hours lost their agar invasive ability and were avirulent when inoculated in Galleria mellonella larvae. In summary, our results indicate that fungal EVs can profoundly modify C. albicans growth and regulate yeast-to-hypha differentiation inhibiting biofilm formation and virulence.

microbiology↗

bioRxiv2020

Assessment of a weak mode of bacterial adhesion by applying an electric field

Microbial attachment to surfaces is ubiquitous in nature. Most species of bacteria attach and adhere to surfaces via special appendages such as pili and fimbriae, the roles of which have been extensively studied. Here we report an experiment on pilus-less mutants of Caulobacter crescentus weakly attached to a plastic surface and subjected to an electric field parallel to the surface. We find that some individual cells transiently but repeatedly adhere to the surface in a stick-slip fashion in the presence of an electric field. Even while transiently detached, these bacteria move significantly slower than the unattached ones in the same field of view undergoing electrophoretic motion. We refer this behavior of repeated and transient attachment as "quasi-attachment". The speed of the quasi-attached bacteria exhibits large variations, frequently dropping close to zero for short intervals of time. This study suggests applying electric field as a useful method to investigate bacteria-surface interaction, which is significant in broader contexts such as infection and environmental control. SignificanceInteraction between bacteria and surfaces occur widely in nature, including those in industrial, environmental, and medical settings. It is therefore important to understand various mechanisms and factors that affect numerous forms of bacterium-surface interaction, particularly those resulting in adhesion or attachment, be they strong or weak, permanent or transient. This work takes a unique approach to identify a transient and reversible mode of bacterial attachment to a solid surface, by applying an electric field to exert a force for detachment. The force thus exerted proves to reach the amplitude required to detach bacteria of a pilus-less strain that weakly attach to a plastic surface. The method may be applied broadly to investigate bacteria-surface interaction.

microbiology↗