Biology subjects

Assis, J.

Publications and source records attributed to Assis, J..

8 recordsLinked to original sources

bioRxiv2026

Beyond establishment: incorporating physiological performance into predictions of invasion risk

Biological invasions are a major driver of global change, reshaping ecosystems and threatening biodiversity worldwide. Anticipating where invaders will establish and where they will exert the strongest ecological impacts are key challenges for early detection and targeted management. Although Species Distribution Models (SDMs) are widely used to forecast biological invasions, they often provide uncertain estimates of establishment ranges and limited insight into invader performance, making it difficult to anticipate ecological impacts. Here, we address these limitations by integrating physiological information on invader performance with SDMs to identify regions of high invasion risk. Using the brown alga Rugulopteryx okamurae, one of the most prominent marine invaders in Europe, we first test alternative hypotheses of northern establishment limits: (i) a cold-survival constraint driven by winter temperatures and (ii) a growth constraint derived from the species' thermal performance. To identify the more likely scenario, we combine cold-tolerance experiments with seasonal growth comparisons between the invader and a native macroalga Dictyota dichotoma, whose established distribution allows physiological performance to be directly related to realised presence. Finally, we project seasonal growth of the invader across the predicted establishment range as a proxy for biomass accumulation and potential ecological impacts. Our results indicate that northern limit in Europe will be more likely constrained by winter survival rather than growth, extending the potential establishment range of Rugulopteryx to mid-Norway. In contrast, the highest impacts are likely to remain concentrated in southern Europe, where thermal conditions sustain high year-round growth. Overall, our approach illustrates how understanding the physiological response of invaders to their environment can improve the interpretation of SDM outputs and help identify areas at greatest risk of impact within their potential establishment range.

ecology↗

bioRxiv2026

Single-Cell Metagenomics Links Plasmid-Derived Antimicrobial Resistance to Hosts in the Pig Gut Microbiome

Antimicrobial exposure can alter gut resistance reservoirs, but bulk metagenomics alone often cannot distinguish whether observed changes reflect expansion of bacterial hosts, altered abundance of plasmid-derived sequences, or redistribution of mobile elements across host backgrounds. Here, we combined longitudinal bulk short-read metagenomics with selected bulk long-read and single-cell shotgun metagenomic sequencing to analyse faecal samples from six Danish pigs over 11 weeks, including an unplanned tiamulin exposure affecting the three pigs housed on the right side of the stable. We constructed a catalogue of 885 plasmid-derived sequences collapsed into 195 bins. Twenty-eight bins and 212 contigs carried resistance annotations, including ribosomal-target markers relevant to pleuromutilin exposure. Single-cell evidence linked subsets of plasmid-derived bins and contigs to bacterial host taxa, enabling host-resolved inspection of resistance-associated plasmid-derived features in longitudinal bulk metagenomes. The microbiome-wide plasmid-derived-sequence prevalence screen identified two bins with post-event associations, whereas resistance-gene abundance and host-attributed plasmid-derived-sequence abundance screens identified no significant host-resolved associations. Because exposure was unplanned and confounded with pen side and disease signs, treatment-response results are exploratory. The main contribution is a single-cell-informed microbial ecology workflow for linking plasmid-derived resistance features to host backgrounds and longitudinal abundance patterns in complex gut

microbiology↗

bioRxiv2025

ABaCo: Addressing Heterogeneity Challenges in Metagenomic Data Integration with Adversarial Generative Models

The rapid advancement of high-throughput metagenomics has produced extensive and heterogeneous datasets with significant implications for environmental and human health. Integrating these datasets is crucial for understanding the functional roles of microbiomes and the interactions within microbial communities. However, this integration remains challenging due to technical heterogeneity and the inherent complexity of these biological systems. To address these challenges, we introduce ABaCo, a generative model that combines a Variational Autoencoder (VAE) with an adversarial discriminator specifically designed to handle the unique characteristics of metagenomic data. Our results demonstrate that ABaCo effectively integrates metagenomic data from multiple studies, corrects technical heterogeneity, outperforms existing methods, and preserves taxonomic-level biological signals. We have developed ABaCo as an open-source, fully documented Python library to facilitate, support and enhance metagenomics research in the scientific community.

bioinformatics↗

bioRxiv2025

Early-life Helicobacter pylori infection worsens metabolic state in mice receiving a high-fat diet

Perturbations to early-life microbial colonization can shape immune and metabolic development, predisposing a host to obesity. We hypothesized that neonatal infection with the ancient human symbiont Helicobacter pylori exacerbates diet-induced metabolic responses and is accompanied by alterations in endocrine and inflammatory regulation. To test this, C57BL/6JRj neonatal mice were infected with H. pylori or left uninfected and, after weaning, exposed to a high-fat diet in a long-term (5-month) study of microbiome composition and a short-term (3-week) study of circulating biomarkers and microbiome composition. In the short-term intervention, infected mice showed increased visceral adiposity. Infection was associated with altered ghrelin and leptin responses across fasting conditions, accompanied by elevated MCP-1 and IL-6, particularly in males. H. pylori infection also reinforced diet-induced shifts in gastrointestinal microbiome composition. In the long-term study, there were no differences in adiposity between infected and control mice, suggesting that diet was the dominant determinant of adiposity at this stage. Together, our findings suggest that early-life H. pylori infection amplifies the initial endocrine, inflammatory, and adipose responses to a high-fat diet.

evolutionary biology↗

bioRxiv2024

Cardiomyocyte antisense transcription regulates exon usage in the elastic spring region of Titin to modulate sarcomere function

BackgroundThe spring-like sarcomere protein Titin (TTN) is a key determinant of cardiac passive stiffness and diastolic function. Alternative splicing of TTN I-band exons produce protein isoforms with variable size and elasticity, but the mechanisms regulating TTN exon skipping and isoform composition in the human heart are not well studied. Non-coding RNA transcripts from the antisense strand of protein-coding genes have been shown to regulate alternative splicing of the sense gene. The TTN gene locus harbours >80 antisense transcripts with unknown function in the human heart. The aim of this study was to determine if TTN antisense transcripts play a role in alternative splicing of TTN. MethodsRNA-sequencing and RNA in situ hybridization (ISH) of cardiac tissue from unused organ donor hearts (n=7) and human induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs) were used to determine the expression and localization of TTN antisense transcripts. The effect of siRNA-mediated knock down of TTN antisense transcripts on TTN exon usage in iPS-CMs was determined using RNA-sequencing. Live cell imaging with sarcomere tracking was used to analyze the effect of antisense transcript knock down on sarcomere length, organization and contraction dynamics. RNA ISH, immunofluorescence and high content microscopy was performed in iPS-CMs to study the interaction between antisense transcripts, TTN mRNA and splice factor protein RBM20. ResultsIn mapping TTN antisense transcription, we found that TTN-AS1-276 was the predominant transcript in the human heart and that it was mainly localized in cardiomyocyte nuclear chromatin. Knock down of TTN-AS1-276 in human iPS-CMs resulted in decreased interaction between the splicing factor RBM20 and TTN pre-mRNA, decreased TTN I-band exon skipping, and markedly lower expression of the less elastic TTN isoform N2B. The effect on TTN exon usage was independent of sense-antisense exon overlap and polymerase II elongation rate. Furthermore, knockdown resulted in longer sarcomeres with preserved alignment, improved fractional shortening and relaxation times. ConclusionsWe demonstrate a role for the cardiac TTN antisense transcript TTN-AS1-276 in facilitating alternative splicing of TTN and regulating sarcomere properties. This transcript could constitute a target for improving cardiac passive stiffness and diastolic function in conditions such as heart failure with preserved ejection fraction.

molecular biology↗

bioRxiv2024

Coastal oceanographic connectivity estimates at the global scale

MotivationOceanographic connectivity driven by ocean currents is critical in determining the distribution of marine biodiversity. It mediates the genetic and individual exchange between populations, from structuring dispersal barriers that promote long-term isolation to enabling long-distance dispersal that underpins species expansion and resilience against climate change. Despite its significance, comprehensive estimates of oceanographic connectivity on a global scale remain unavailable, while traditional approaches, often simplistic, fail to capture the complexity of oceanographic factors contributing to population connectivity. This gap hinders a deeper understating of species dispersal ecology, survival, and evolution, ultimately precluding the development of effective conservation strategies aimed at preserving marine biodiversity. To address this challenge, we present a comprehensive dataset of connectivity estimates along the worlds coastlines, known for their rich marine biodiversity. These estimates are derived from a biophysical modelling framework that combines high-resolution ocean current data with graph theory to predict multi-generational stepping-stone connectivity. Alongside, we provide coastalNet, an R package designed to streamline access, analysis, and visualization of connectivity estimates. This tool enhances the utility and application of the data, adhering to the FAIR principles of Findability, Accessibility, Interoperability, and Reusability. The dataset and package set a new benchmark for research in oceanographic connectivity, allowing a better exploration of the complex dynamics of coastal marine ecosystems. Main types of variables containedPairwise connectivity estimates (probability and time) between coastal sites. Spatial location and grainGlobal, equal-area hexagons with 8.45 km edge length. Time period and grainDaily, from 2000 to 2020. Major taxa and level of measurementCoastal marine biodiversity. Software formatA package of functions developed for R software.

ecology↗

bioRxiv2023

Unravelling the role of oceanographic connectivity in intra-specific diversity of marine forests at global scale

AimIntra-specific diversity results from complex interactions of intermingled eco-evolutionary processes along species history, but their relative contribution has not been addressed at the global scale. Here, we unravel the role of present-day oceanographic connectivity in explaining the genetic differentiation of marine forests across the ocean. LocationGlobal. Time periodContemporary. Major taxa studiedMarine forests of brown macroalgae (order Fucales, Ishigeales, Laminariales, Tilopteridale). MethodsThrough systematic literature revision, we compiled a comprehensive dataset of genetic differentiation, encompassing 662 populations of 34 species. A biophysical model coupled with network analyses estimated multigenerational oceanographic connectivity and centrality across the marine forest global distribution. This approach integrated species dispersive capacity and long-distance dispersal events. Linear mixed models tested the relative contribution of site-specific processes, connectivity, and centrality in explaining genetic differentiation. ResultsWe show that spatiality dependent eco-evolutionary processes, as described by our models, are prominent drivers of genetic differentiation in marine forests (significant models in 92.6 % of the cases with an average R2 of 0.49 {+/-} 0.07). Specifically, we reveal that 19.6 % of variance is explicitly induced by contemporary connectivity and centrality. Moreover, we demonstrate that LDD is key in connecting populations of species distributed across large water masses and continents. Main conclusionsWe deciphered the role of present-day connectivity in observed patterns of genetic differentiation of marine forests. Our findings significantly contribute to the understanding of the drivers of intra-specific diversity on a global scale, with implications for biogeography and evolution. These results can guide well-informed conservation efforts, including the designation of marine protected areas, as well as spatial planning for genetic diversity in aquaculture, which is particularly relevant for sessile ecosystems structuring species such as brown macroalgae.

ecology↗

bioRxiv2023

Influence of oceanography and geographic distance on genetic structure: how varying the sampled domain influences conclusions in Laminaria digitata

Understanding the environmental processes shaping connectivity can greatly improve management and conservation actions which are essential in the trailing edge of species distributions. In this study, we used a dataset built from 32 populations situated in the southern limit of the kelp species Laminaria digitata. By extracting data from 11 microsatellite markers, our aim was to (1) refine the analyses of population structure, (2) compare connectivity patterns and genetic diversity between island and mainland populations and (3) evaluate the influence of sampling year, hydrodynamic processes, habitat discontinuity, spatial distance and sea surface temperature on the genetic structure using a distance-based redundancy analysis (db-RDA). Analyses of population structure enabled to identify well connected populations associated to high genetic diversity, and others which appeared genetically isolated from neighboring populations and showing signs of genetic erosion verifying contrasting ecological (and demographic) status in Brittany and the English Channel. By performing db-RDA analyses on various sampling sizes, geographic distance appeared as the dominant factor influencing connectivity between populations separated by great distances, while hydrodynamic processes were the main factor at smaller scale. Finally, Lagrangian simulations enabled to study the directionality of gene flow which has implications on source-sink dynamics. Overall, our results have important significance in regard to the management of kelp populations facing pressures both from global warming and their exploitation for commercial use.

evolutionary biology↗