Biology subjects

Maie, T.

Publications and source records attributed to Maie, T..

10 recordsLinked to original sources

bioRxiv2026

PDE3A-SLFN12 Molecular Glues Target Multiple KIT D816V Cell Types in Preclinical Models of Mast Cell Malignancies

A drug discovery approach was used to specifically target malignant cells with KIT D816V mutation, which is the predominant disease-causing mutation in clonal mast cell malignancies. To this end, KIT D816V cells derived from induced pluripotent stem cells (iPS cells) of KIT D816V patients were employed to screen a library of FDA approved and experimental drugs for specific killing of KIT D816V cells. We discovered the novel compound LDC 3416, which targets multiple malignant KIT D816V cell types, including hematopoietic stem/progenitor cells and mast cells. Importantly, by exploring the LDC 3416 targeting profile, we identified the phosphodiesterase 3A-Schlafen 12 (PDE3A-SLFN12) molecular glue pathway as a novel approach for specific targeting of malignant KIT D816V cells. We found that the KIT D816V mutant protein leads to increased expression of PDE3A and SLFN12 and thus confers a selective molecular vulnerability to PDE3A-SLFN12 molecular glues. Primary malignant mast cells of KIT D816V patients with indolent and advanced systemic mastocytosis also exhibit increased expression of PDE3A and SLFN12. We extended our study to include additional PDE3A-SLFN12 molecular glues and demonstrate their synergistic action with KIT D816V selective tyrosine kinase inhibitors (TKIs) in killing KIT D816V cells. Furthermore, the PDE3A-SLFN12 molecular glues also target KIT D816V megakaryocytes, a cell type that has been underestimated in malignant mast cell pathophysiology and molecular targeting. The identified molecular glues, along with their synergy with TKIs and their simultaneous targeting of multiple KIT D816V cell types, open novel treatment options for KIT D816V mast cell malignancies and other KIT D816V associated diseases.

cancer biology↗

bioRxiv2025

Developmental factors drive the compartmentalised and discontinuous maturation of the small intestinal epithelium during the early postnatal period

The temporal, spatial and cellular diversity of the small intestinal epithelium during the postnatal period, a critical time window that accompanies the transition from placental energy supply to enteral feeding, the establishment of the enteric microbiota and postnatal immune maturation, has not been systematically investigated. Here, we used laser capture microdissection and bulk RNA-Seq, proteomics, and single cell RNA-Seq to analyse the total, organ site, crypt- and villus-specific intestinal epithelium of specific pathogen-free, germ-free and Salmonella-infected mice during the postnatal period. We identified key temporal and organ-site specific expression patterns that revealed a weak effect of the microbiota but strong influence of developmental regulators during early life. We also determined age-dependent signalling pathway and transcription factor activity and characterised age- and cell type-specific developmental trajectories revealing a distinct compartmentalised maturation process along the proximal-to-distal length and crypt-villus axis and a discontinuous appearance of goblet/Paneth cell and absorptive enterocyte transcriptional profiles. Finally, we described the cell type-specific response to neonatal enteric infection. Taken together, our findings identify the epithelium as an integral element in the maturation of postnatal mucosal tissues and in the establishment of host-microbe homeostasis.

immunology↗

bioRxiv2025

PILOT-GM-VAE: Patient-Level Analysis of single cell Disease Atlas with Optimal Transport of Gaussian Mixture Variational Autoencoders

MotivationThe analysis of single cell disease atlases represents a challenge due to the presence of batch effects, low quality of disease samples, and the multi-scale nature of the data, i.e., samples are described by different cell distributions. Because of these, few computational approaches are performing sample-level disease progression analysis so far. ResultsHere, we introduce Patient-Level Analysis with Optimal Transport based on Gaussian Mixture Variational Autoencoders (PILOT-GM-VAE). PILOT-GM-VAE explores the power of GM-VAE to estimate models describing complex single cell distributions through efficient optimal transport algorithms for estimating the distance between Gaussian Mixtures. Extensive benchmarking on several single cell disease atlases and competing approaches demonstrates the performance of PILOT-GM-VAE in sample-level clustering, sample-level trajectory inference, and batch correction tasks. Moreover, we performed a case study on a breast cancer disease atlas, where PILOT-GM-VAE highlighted cellular and molecular changes associated with breast cancer disease progression. AvailabilityThe software, code, and data for benchmarking are available at https://github.com/CostaLab/PILOT-GM-VAE/tree/main

bioinformatics↗

bioRxiv2024

Estimating the effective population size across space and time in the Critically Endangered western chimpanzee in Guinea-Bissau: challenges and implications for conservation management

Effective population size (Ne) is a key concept in evolutionary and conservation biology. The western chimpanzee (Pan troglodytes verus) is a Critically Endangered taxon. In Guinea-Bissau, chimpanzees are mainly threatened by habitat loss, hunting and diseases. Guinea-Bissau is considered a key area for its conservation. Genetic tools have not yet been applied to inform management and no estimates of Ne have been obtained. In this study, we use countrys range-wide microsatellite data and five whole-genome sequences to estimate several Ne and infer the recent and ancient demographic history of populations using different methods. We also aim to integrate the different Ne estimates to improve our understanding of the evolutionary history and current demography of this great ape and to discuss strengths and limitations of each estimator and their complementarity in informing conservation decisions. Results from the PSMC method suggest a large ancestral Ne, likely due to ancient structure over the whole subspecies distribution until approximately 10-15,000 years ago. After that, a change in connectivity, a real decrease in size or a combination of both occurred, which reduced the then still large ancestral population to a smaller size (MSVAR: [~]10,000 decreasing to 1,000-6,000 individuals), possibly indicating a fragmentation into coastal and inner subpopulations. In the most recent past, contemporary Ne is below or close to 500 (GONE: 116-580, NeEstimator: 107-549), suggesting a high risk of extinction. The populations at coastal Parks may have been small or isolated for several generations whereas the Boe Park one exhibit higher long-term Ne estimates and can be considered a stronghold of chimpanzee conservation. Through combining different types of molecular markers and analytical methodologies, we try to overcome the limitations of obtaining high quality DNA sampling from wild threatened populations and estimate Ne at different temporal and spatial scales, which is crucial information to make informed conservation decisions at local and regional scales.

genomics↗

bioRxiv2024

Life history traits influence the dynamics of genetic diversityin a refugium population undergoing expansion andcontraction

Species ranges are dynamic, experiencing expansions, contractions or shifts as a response to habitat changes induced by extrinsic factors such as climate change and, more recently, human activities. While the scientific literature has explored the genetic effects of spatial processes, published studies rarely incorporate life-history traits to study the effect of such changes on species living in the same environments. There is thus a gap in our understanding regarding the variation in genetic diversity patterns among species with distinct life-history traits such as growth rates and generation times, experiencing the same habitat change scenarios. In this study, we first used spatial simulations to investigate the temporal dynamics of genetic diversity within refugium populations experiencing a range expansion followed by a stationary and a contraction period. We explored different scenarios, varying both the speed of contraction and the life-history traits of the simulated species. In addition, we used a simpler panmictic model for which we derived analytical results. Altogether, we identified three temporal dynamics of genetic diversity in the refugium population during the contraction phase: scenarios where genetic diversity i) decreased throughout the contractions, ii) increased for periods that could be greater than thousands of years before plateauing and then decreasing or iii) followed a persistent increasing trend, without any visible effect of the expansion or contraction. We show that these different temporal dynamics can be predicted by comparing the observed expected heterozygosity (He) to the values expected if the species were at equilibrium within the refuge (He refuge) and within the whole landscape (He landscape). We also observe that there are scenarios where a rapid contraction maintains more diversity just at the end of the contraction, as widely believed and as reported in a previous simulation study. However, we also observe the opposite pattern for a wide range of parameters. The widespread idea that observing high diversity levels in a refugium population is due to a recent and rapid habitat loss is thus not necessarily true and will depend on various life history traits and how they relate to habitat change dynamics.

evolutionary biology↗

bioRxiv2024

Cancer-associated fibroblasts reveal aberrant DNA methylation across different types of cancer

Cancer-associated fibroblasts (CAFs) are critical components of the tumor microenvironment. Several studies demonstrated molecular differences between CAFs and normal tissue-associated fibroblasts (NAFs). In this study, we isolated CAFs and NAFs from liver tumors and analyzed their DNA methylation profiles. A subset of the CAFs exhibited aberrant DNA methylation, which was also reflected on gene expression level. The DNA methylation at liver-CAF-specific CG dinucleotides (CpGs) was associated with survival in liver cancer data. An integrative analysis with public datasets of CAF versus NAF in different cancer types, including lung, prostate, esophagus, and gastric cancer, revealed overlapping epigenetic aberrations. CpGs with common aberrations in DNA methylation included cg09809672 (EDARADD), cg07134930 (HDAC4), and cg05935904 (intergenic). Aberrant DNA methylation at these sites was associated with prognosis in several cancer types. Thus, activation of CAFs by the tumor environment is associated with characteristic epigenetic modifications that could be used as biomarkers for disease stratification.

cancer biology↗

bioRxiv2022

The effect of habitat loss and fragmentation on isolation-by-distance and time

Throughout Earths natural history, habitats have undergone drastic changes in quality and extent, influencing the distribution of species and their diversity. In the last few hundred years, human activities have destroyed natural habitats at an unprecedent rate, converting continuous habitat into fragmented and isolated patches. Recent global metanalyses suggest that habitat loss and fragmentation (HL&F) has negatively impacted the genetic diversity of many taxa across the world. These conclusions have been drawn by comparing present-day genetic patterns from populations occurring in continuous and fragmented landscapes. In this work, we attempted to go beyond pattern and investigate through simulations some of the processes that influence genetic variation in the context of HL&F. Since most species have a geographically restricted dispersal (known as "isolation-by-distance", IBD), we studied the impact of HL&F on isolation-by-distance. We characterised the behaviour of IBD in the case of i) instantaneous HL&F, ii) gradual (two-steps) HL&F, and iii) instantaneous HL&F following range expansion. In addition, we propose a spatially-explicit theoretical framework by modifying the original theoretical results on isolation-by-distance (Slatkin, 1991; Slatkin, 1993) and apply them to a toroidal stepping-stone model in the context of HL&F. Our results suggest that isolation-by-distance can be maintained for relatively long time after HL&F, thus pointing to the long-term importance of spatial genetic structure in species genetic diversity. In addition, our results may explain why present-day fragmented population still show significant IBD pattern although being disconnected.

evolutionary biology↗

bioRxiv2022

On the genetic consequences of habitat contraction: edge effects and habitat loss

Natural climate change and recent anthropogenic activities have largely contributed to habitat loss and fragmentation across the world, leading to 70% of worldwide remaining forests to be within 1 km of forests edges (Haddad et al., 2015). Ecological studies have shown that edge-effect influences ecological communities, species richness and abundance across many taxa, contributing to worldwide decline in biodiversity. Since edge-effect reduces species abundance and connectivity, it is also expected to negatively influence species genetic variation. In fact, previous theoretical studies had showed that populations closer to the edges of a finite stepping-stone model tends to have shorter coalescence times, and therefore, lower genetic diversity, than central populations. However, predicting the impact of edge effect on local genetic diversity remains challenging in realistic and more complex habitat fragments, where the additive effect of multiple edges is expected to take place. In the present study we explore the genetic consequence of habitat loss at the scale of a habitat fragment (patch-scale), looking at the interplay between patch-size and edge-effect on spatial genetic diversity. We propose a statistical approach to estimate edge-impacted effective population size from habitat cover information and use this measure to predict spatial genetic diversity in both equilibrium and non-equilibrium populations. We address these questions using spatially-explicit simulations and propose a spatially-explicit analytical framework able to model spatio-temporal changes in genetic diversity due to edge-effect and habitat loss.

evolutionary biology↗

bioRxiv2022

CimpleG: Finding simple CpG methylation signatures

DNA methylation (DNAm) at specific CG dinucleotides (CpG sites) in the genome provides powerful biomarkers for a wide range of applications, such as epigenetic clocks, cell type deconvolution, and stratification of cancer patients. Such epigenetic signatures are usually based on multivariate approaches that require hundreds of DNAm sites for predictions. In contrast, targeted assays for only a few selected CpGs may facilitate faster turnover, better standardisation, and reduced costs. Here, we propose a computational framework named CimpleG for the detection of small CpG methylation signatures, exemplarily used for cell type classification. We evaluate the performance of CimpleG and competing methods on two distinct datasets in regard to the cell-type classification of blood cells and of other somatic cells. Furthermore, we evaluate how well these classifiers perform cellular deconvolution of blood cell mixtures. We show that CimpleG is both time efficient and performs as well as Elastic Net, while basing its prediction on a single DNAm site per cell type. Altogether, CimpleG provides a complete computational framework for the delineation of DNAm signatures and cellular deconvolution.

bioinformatics↗

bioRxiv2020

Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites

BackgroundThe complex composition of different cell types within a tissue can be estimated by deconvolution of omics datasets. For example, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. In this study, we investigated if deconvolution is also feasible with individual cell-type-specific CG dinucleotides (CpG sites), which can be addressed by targeted analysis, such as pyrosequencing. ResultsWe compiled and curated a dataset of 579 samples from Illumina 450k BeadChip technology that comprised 14 different purified and characterized human cell types. A training and validation strategy was applied to identify and test cell-type-specific CpGs. Initially, the amount of fibroblasts was estimated using two CpGs that were either hypermethylated or hypomethylated in fibroblasts. This FibroScore correlated with the state of fibrosis and was associated with overall survival in various types of cancer. Furthermore, we identified hypomethylated CpGs for leukocytes, endothelial cells, epithelial cells, hepatocytes, glia, neurons, fibroblasts and induced pluripotent stem cells. Using previously published BeadChip datasets with cell mixtures the accuracy of this eight CpG signature was comparable to previously published signatures based on several thousand CpGs. Finally, we established and validated pyrosequencing assays for the relevant CpGs that can be utilized for classification and deconvolution of cell types. ConclusionThis proof of concept study demonstrates that DNAm analysis at individual CpGs reflects the cellular composition of cellular mixtures and different tissues. Targeted analysis of these genomic regions facilitates robust methods for application in basic research and clinical settings.

genomics↗