Biology subjects

Cunha, L.

Publications and source records attributed to Cunha, L..

5 recordsLinked to original sources

bioRxiv2025

Coping with extremes: How Epigenetic and Molecular Adaptations Enable Earthworms to Thrive in Volcanic Soils

Earthworms thriving in naturally occurring geothermal soils offer rare insight into rapid adaptation to environmental extremes. Here, we show that the pantropical earthworm Amynthas gracilis survives and flourishes in soils of the Furnas Volcano (Sao Miguel Island, Azores), where conditions include elevated temperatures (up to 40 {degrees}C), high CO2 (88.6%), low O2 (10%), toxic metals, and mildly acidic pH. In a reciprocal-transplant, mesocosm-based experiment between soils overlying areas of active degassing volcanic gassing (hereafter active degassing soils) and reference soils, convergence of the epidermal thickness of the transplanted earthworms to the resident-soil phenotype (24 {+/-} 3.9 {micro}m active degassing soil, 43.8 {+/-} 8 {micro}m reference soil), was observed within 31 days. Combining RNA-Seq, DNA (5-cytosine) methylation mapping, and microRNA profiling, this phenotypic change results from coordinated transcriptional and epigenetic reprogramming. While gene-body methylation occurred at [~]98 % of loci, levels varied, and differentially methylated regions were enriched ffor genes with altered expression under volcanic stress. Multi-omics network analysis identified epithelial morphogenesis, circulatory system formation, and neural development as regulatory hubs, highlighted by a set of 41 epithelial-morphogenesis genes showing consistent methylation and miRNA patterns. Additional modules governing ion transport and signal transduction complemented the adaptive response. Collectively these findings demonstrate that A. gracilis employs dynamic DNA methylation and microRNA regulation alongside transcriptional reprogramming to generate a persistent phenotypic adjustment to a volcanic stress. This work advances our understanding of extremophile resilience and provides a scalable model for predicting organismal adaptive capacity in the face of environmental extremes.

molecular biology↗

bioRxiv2025

Genomics insights reveal multi-year maintenance of a new Deltacoronavirus infecting Seabirds from the Cagarras Island Archipelago Natural Monument, Brazil

Previous studies have identified various pathogens in seabirds, notably coronaviruses (CoVs) and influenza A viruses (IAVs), due to their potential to cause significant morbidity and mortality. The Cagarras Island Archipelago Natural Monument, located near Rio de Janeiro, Brazil, serves as nesting site for two species, the magnificent frigatebird (Fregata magnificens) and the brown booby (Sula leucogaster). Despite its ecological importance, no prior studies have investigated viral infections in these species, which share habitat interfaces with densely populated human areas. To address this gap, we sampled and tested seabirds for CoVs and IAVs from January 2022 to April 2024. Birds were captured and identified by species, age, and sex. Oropharyngeal and cloacal swabs, as well as blood samples, were collected. Viral RNA was extracted using the QIAamp Viral RNA Mini Kit, and the presence of IAVs was screened via real-time RT-PCR, while CoVs were screened using semi-nested RT-PCR. Sanger and metatranscriptomic sequencing were performed to identify viral strains and assess phylogenetic relationships. Of the 153 seabirds sampled, CoVs were detected in 6 individuals (9.1%) of F. magnificens and 16 individuals (18.4%) of S. leucogaster. No IAVs were found in either oropharyngeal or cloacal swabs, and all serum samples were negative for the presence of antibodies against the virus. We recovered two full deltacoronavirus genomes and eight additional draft genomes from S. leucogaster samples obtained from distinct sampling expeditions and additional enteroviruses, passeriviruses, and picornaviruses. Phylogenetic analysis revealed that the detected CoVs are closely related to avian deltacoronaviruses from environmental samples of S. leucogaster in the Sao Pedro and Sao Paulo Archipelago, indicating potential viral exchange between these seabird populations living at these distant islands. Moreover, multiple detections in different individuals at different time points are associated with specific Spike NTD deletions that have been shown to accumulate in immune escape lineages, supporting the long-term maintenance through new infections and reinfection of this virus in these bird populations. This is the first detection of CoVs in F. magnificens, highlighting their circulation in marine ecosystems. Further research is needed to understand the ecological and epidemiological implications, including potential cross-species transmission.

microbiology↗

bioRxiv2024

Robust and cost-efficient single-cell sequencing through combinatorial pooling

Single-cell sequencing is widely used to study molecular cell-to-cell heterogeneity. Even though the cost of sequencing has dropped throughout the last decades, single-cell assays remain expensive, because they require strategies to index molecules by cells. The high costs of indexing can be mitigated by pooling samples prior to sequencing library preparation. Computational methods have been developed to leverage molecular features that are distinct between different samples to separate the pools into distinct datasets. However, since all multiplexed samples are processed in the same way, information on the origin of each demultiplexed dataset is lost. To map datasets to their sample of origin, additional information such as molecular indexing or additional genotyping is needed. Here, we propose a class of experimental designs that allows identifying the sample of origin of each demultiplexed dataset, only relying on the genetic profiles of the samples and the composition of pools. Our approach is based on splitting and pooling samples in specific combinations. We find a most cost-efficient experimental design in this class and prove its optimality. We present a dynamic programming algorithm to iteratively simplify an optimal experimental design by breaking it into several independent designs while maintaining optimality. Furthermore, we propose a subclass of experimental designs which allow robust sample identification even under partial failure of the experiment and present a provably optimal design in this subclass. We provide an implementation for automatic sample identification under these optimal combinatorial pooling strategies and demonstrate its functionality in a simulation study.

bioinformatics↗

bioRxiv2019

New High Throughput Approaches to Detect Partial-body and Neutron Exposures on an Individual Basis

Biodosimetry-based discrimination between homogeneous total-body photon exposure and complex irradiation scenarios (partial-body shielding and/or neutron + photon mixtures) can improve treatment decisions after mass-casualty radiation-related incidents. Our study objective was to use high-throughput biomarkers to: a) detect partial-body and/or neutron exposure on an individual basis, and b) estimate separately the photon and neutron doses in a mixed exposure. We developed a novel approach, where metrics related to the shapes of micronuclei distributions per binucleated cell in ex-vivo irradiated human lymphocytes (variance/mean, kurtosis, skewness, etc.) served as predictors in machine learning or parametric analyses of the following scenarios: (A) Homogeneous gamma-irradiation, mimicking total-body exposures, vs. mixtures of irradiated blood with unirradiated blood, mimicking partial-body exposures. (B) X rays vs. various neutron + photon mixtures. Classification of samples as homogeneously vs. heterogeneously irradiated (scenario A) achieved a receiver operating characteristic curve area (AUROC) of 0.931 (uncertainty range of 0.903-0.951), and R2 for actual vs. reconstructed mean dose was 0.87. Detection of samples with [≥]10% neutron contribution (scenario B) achieved AUROC of 0.916 (0.893-0.943), and R2 for reconstructing photon-equivalent dose was 0.77. These encouraging findings demonstrate a proof-of-principle for the proposed approach of analyzing micronuclei/cell distributions to detect clinically-relevant complex radiation exposure scenarios.

biophysics↗

bioRxiv2019

Cytogenetically-based biodosimetry after high doses of radiation

Dosimetry is an important tool for triage and treatment planning following any radiation exposure accident, and biological dosimetry, which estimates exposure dose using a biological parameter, is a practical means of determining the specific dose an individual receives. The cytokinesis-blocked micronucleus assay (CBMN) is an established biodosimetric tool to measure chromosomal damage in mitogen-stimulated human lymphocytes. The CBMN method is especially valuable for biodosimetry in triage situations thanks to simplicity in scoring and adaptability to high-throughput automated sample processing systems. While this technique produces dose-response data which fit very well to a linear-quadratic model for exposures to low linear energy transfer (LET) radiation and for doses up for 5 Gy, limitations to the accuracy of this method arise at larger doses. Resolution at higher doses is limited by the number of cells reaching mitosis. Whereas it would be expected that the yield of micronuclei increases with the dose, in many experiments it has been shown to actually decrease when normalized over the total number of cells. This variation from a monotonically increasing dose response poses a limitation for retrospective dose reconstruction. In this study we modified the standard CBMN assay to increase its resolution following exposures to higher doses of photons or a mixed neutron-photon beam. The assay is modified either through inhibitions of the G2/M and spindle checkpoints with the addition of caffeine and/or ZM447439 (an Aurora kinase inhibitor), respectively to the blood cultures at select times during the assay. Our results showed that caffeine addition improved assay performance for photon up to 10 Gy. This was achieved by extending the assay time from the typical 70 h to just 74 h. Compared to micronuclei yields without inhibitors, addition of caffeine and ZM447439 resulted in improved accuracy in the detection of micronuclei yields up to 10 Gy from photons and 4 Gy of mixed neutrons-photons. When the dose-effect curves were fitted to take into account the turnover phenomenon observed at higher doses, best fitting was achieved when the combination of both inhibitors was used. These techniques permit reliable dose reconstruction after high doses of radiation with a method that can be adapted to high-throughput automated sample processing systems.

cell biology↗