Biology subjects

Moretto, M.

Publications and source records attributed to Moretto, M..

7 recordsLinked to original sources

bioRxiv2026

Normative Modeling of Molecular-Enriched Functional Connectivity for Detecting Deviations from Healthy Brain Aging

Inter-individual variability in adult brain aging can obscure early pathological alterations and is only partly represented by population-average or scalar brain-aging measures. We combined Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) with normative modeling (NM) to derive spatially resolved, molecularly informed deviation scores for dopamine transporter (DAT)-, norepinephrine transporter (NET)-, and serotonin transporter (SERT)-enriched resting-state functional connectivity (FC). We first evaluated whether these normative models could be transferred to independently processed external data through local calibration and then explored whether the resulting deviation profiles differed with cerebral amyloid burden in cognitively unimpaired older adults. Hierarchical Bayesian regression (HBR) models with a SHASHb likelihood were estimated separately for 204 cortical molecular-enriched FC features in 4,152 healthy adults (18.0--89.8 years) from seven publicly available neuroimaging datasets and evaluated in a held-out healthy test set. Pretrained models were locally adapted to three AMYPAD-PNHS acquisition batches using cognitively unimpaired, amyloid-negative participants (global Clinical Dementia Rating [CDR] = 0; Centiloid [CL] [lt] 10). The independent primary comparison contrasted participants with intermediate amyloid burden (10 [≤] CL [lt] 30; n = 111) and amyloid-positive participants (CL [≥] 30; n = 66); secondary analyses tested linear associations with continuous CL within participants with CL [≥] 10. Of 204 normative reference models, 199 (97.5%) met the predefined diagnostic criteria; median held-out explained variance (EXPV) was 0.174. Of 612 feature-by-batch transfers, 541 (88.4%) met the strict transfer-diagnostic criteria. In the primary false discovery rate (FDR)-controlled regional analysis, DAT-enriched right caudal middle frontal cortex showed lower locally standardized deviation scores in the intermediate-amyloid-burden group than in the amyloid-positive group (adjusted difference = -0.582, q = 0.016). DAT extreme-deviation burden was also greater in the intermediate-amyloid-burden group (difference = 0.032, q = 0.044). The right frontal effect was reproduced with model-native scores across the three acquisition batches (pooled standardized effect = -0.698, q = 0.010). No NET- or SERT-enriched regional difference between these two groups survived FDR correction, and no regional or subject-level linear association with continuous CL values survived FDR correction in the CL [≥] 10 group. Normative modeling can provide spatially resolved reference distributions of molecular-enriched FC that are deployable in independently processed external data when local adaptation, calibration, and feature-level transfer diagnostics are incorporated. The AMYPAD-PNHS application identified modest, spatially selective, and molecular-system-specific categorical differences during a cognitively unimpaired stage of amyloid accumulation, while continuous analyses within CL [≥] 10 did not support a linear association. These findings support a methodological basis for distributed application of molecular-enriched normative models and motivate independent and longitudinal evaluation of their biological relevance.

bioengineering↗

bioRxiv2025

AEGIS: an annotation extraction and genomic integration resource

The GTF/GFF3 formats are the standard for storing and exchanging genome annotations. However, their flexibility often results in inconsistent and poorly formatted files across different sources, creating a major bottleneck for downstream bioinformatics analyses. Here, we present Annotation Extraction and Genomic Integration Suite (AEGIS), a comprehensive and user-friendly command-line toolkit designed to parse, validate and standardise genome annotation files. AEGIS robustly corrects common structural and formatting errors, ensuring interoperability with downstream tools. Beyond standardisation, the suite provides advanced modules for analysis, such as flexible sequence extraction (e.g. genes, CDS, proteins) with isoform handling, customisable promoter region definitions and targeted DNA motif searches. A key feature of AEGIS is its integrated workflow for comparative genomics, which combines multiple lines of evidence (i.e., sequence homology, synteny and coordinate-based lift-overs) to enable a robust gene ID correspondence and orthology assessment. We demonstrate the utility of AEGIS by comparing two major Arabidopsis thaliana annotations (TAIR10 vs. Araport11), successfully identifying and quantifying complex structural changes such as gene splits and fusions. AEGIS provides a unified solution for annotation quality control, feature extraction and comparative genomic analysis, simplifying complex workflows and enhancing reliability in bioinformatic research. The software is open-source, implemented in Python and is available on GitHub, PyPI, and as a Docker container to ensure accessibility and reproducibility.

bioinformatics↗

bioRxiv2025

Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis

Brain-age prediction from neuroimaging data provides a proxy of biological aging, yet most models rely on structural magnetic resonance imaging (MRI), a modality that captures macroanatomy but offers limited biological specificity. We tested whether integrating molecular-enriched functional connectivity (FC), from resting-state functional MRI (rs-fMRI) data, improves brain-age prediction and biological explainability. We analyzed MRI data of 2,120 healthy adults (1,243/877 F/M; 18-90 years) from three public datasets. Molecular-enriched connectivity maps were derived with Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) using receptor-density templates for the dopamine (DAT), norepinephrine (NET), and serotonin (SERT) transporter systems. Support vector regression models were applied to predict chronological age from molecular-enriched FC, structural morphometry, or both combined. The effect of multi-site variability was mitigated via ComBat harmonization with and without Empirical Bayes pooling. We additionally conducted a common-parcellation analysis to assess the impact of differing parcellations between modalities. Single-transporter molecular-enriched FC explained up to 51% of age variance. The most predictive transporter varied by dataset, with DAT dominating in the harmonized and common-parcellation settings. Combining the three molecular-enriched maps consistently improved prediction over any single map and increased explained variance up to 64%. In the merged multi-site cohort using a common parcellation, augmenting structural information with transporter-enriched FC reduced mean absolute error (MAE) from 6.02 to 5.81 years, supporting complementarity of the two modalities. In contrast, when different parcellations were applied, incorporating molecular-enriched FC into brain age prediction resulted in a 2% higher MAE compared to structural morphometry alone, suggesting that parcellation mismatch may obscure the functional contributions. In conclusion, molecular-enriched FC is a feasible and biologically informative extension to brain-age modeling, enhancing prediction and interpretability with respect to neurotransmitter systems.

neuroscience↗

bioRxiv2025

A Grapevine MYC2-MYB24 Regulatory Module Activates Terpenoid Biosynthesis Upon Methyl Jasmonate Elicitation

Terpenes contribute to the characteristic flavor and aroma of grapes and their derived products while serving protective roles in plants against radiation, oxidative stress, and biotic challenges. The phytohormone methyl jasmonate (MeJA) mediates many of these processes and enhances terpene content in grape berries, but its underlying regulatory mechanism remains unclear. To address this, we treated Vitis vinifera cv. Gamay Freaux berry cell suspensions with MeJA (100 M) and cyclodextrins (50 mM), generating transcriptomic data. Upregulated genes (URGs) were enriched in jasmonic acid biosynthesis and signaling pathways, and transcription factors (TF) that represent novel candidates modulating MeJA responses. Inspection of these TFs in terms of their co-expressed genes allowed us to focus on MYC2, the sole bHLH IIIe subgroup member in grapevine. Using DAP-seq, we identified MYC2-bound genes and integrated them with MeJA-URGs and MYC2 co-expressed genes (CEGs) to produce a high-confidence target list. These targets were bound via a conserved G-box motif and included jasmonate-related genes (e.g., LOX and JAZ) and TFs such as MYB24, previously found to interact with MYC2 to activate terpenoid biosynthesis genes. Consistently, MeJA treatment induced 15 terpene synthase genes (TPS), eleven of which were bound by MYB24, MYC2, or both. Terpenoid compounds associated with these induced TPSs accumulated both intra- and extracellularly following treatment with MeJA and cyclodextrins, but not with abscisic acid (ABA). Our findings suggest that MYC2 regulates the jasmonate pathway and cooperates with MYB24 to mediate MeJA-induced terpene biosynthesis, shedding light on mechanisms that may extend to flower and fruit development, where this MYB-bHLH complex is also expressed.

plant biology↗

bioRxiv2023

Discovery of New Broad-Spectrum Anti-Infectives for Eukaryotic Pathogens Using Bioorganometallic Chemistry

Drug resistance observed with many anti-infectives clearly highlights the need for new broad-spectrum agents to treat especially neglected tropical diseases (NTDs) caused by eukaryotic parasitic pathogens including fungal infections. Since these diseases target the most vulnerable communities who are disadvantaged by health and socio-economic factors, new agents should be, if possible, easy-to-prepare to allow for commercialization based on their low cost. In this study, we show that simple modification of one of the most well-known antifungal drugs, fluconazole, with organometallic moieties not only improves the activity of the parent drug but also broadens the scope of application of the new derivatives. These compounds were highly effective in vivo against pathogenic fungal infections and potent against parasitic worms such as Brugia, which causes lymphatic filariasis and Trichuris, one of the soil-transmitted helminths that infects millions of people globally. Notably, the identified molecular targets indicate a mechanism of action that differs greatly from the parental antifungal drug, including targets involved in biosynthetic pathways that are absent in humans, offering great potential to expand our armamentarium against drug-resistant fungal infections and NTDs targeted for elimination by 2030. Overall, the discovery of these new compounds with broad-spectrum activity opens new avenues for the development of treatments for several current human infections, either caused by fungi or by parasites, including other NTDs, as well as newly emerging diseases. ONE-SENTENCE SUMMARYSimple derivatives of the well-known antifungal drug fluconazole were found to be highly effective in vivo against fungal infections, and also potent against the parasitic nematode Brugia, which causes lymphatic filariasis and against Trichuris, one of the soil-transmitted helminths that infects millions of people globally.

pharmacology and toxicology↗

bioRxiv2021

The haplotype-resolved reference genome of lemon (Citrus limon L. Burm f.)

Lemon (Citrus limon (L.) Burm. f.) is an evergreen tree belonging to the genus Citrus. The fruits are particularly prized for their organoleptic and nutraceutical properties of the juice. Herein we report, for the first time, the release of a high-quality reference genome of the two haplotypes of lemon. The sequencing has been carried out coupling Illumina short reads and Oxford Nanopore data leading to the definition of a primary and an alternative assembly characterized by a genome size of 312.8 Mb and 324.74 Mb respectively. The analysis of the long terminal repeat (LTR) allowed the identification of 1921 regions on the primary and 1911 on the alternative assembly distributed across the nine chromosomes. Furthermore, an in-silico analysis of the microRNA genes was carried out using 246 mature miRNA and the respective pre-miRNA hairpin sequences of C. sinensis. Such analysis highlighted a high conservation between the two species with 233 mature miRNAs and 51 pre-miRNA stem-loops aligning with perfect match on the lemon genome. In parallel, total RNA was extracted from fruit, flower, leaf and root enabling the detection of 38,205 and 37,753 predicted transcripts on primary and alternative assemblies respectively. Among those, the highest and lowest number of tissue-specific transcripts were detected in flower (2.73% and 2.71% in primary and alternative assemblies respectively) and leaf (0.7% and 0.68%) while gene ontology analysis enables a more precise characterization of the expressed genes based on their function. The availability of a reference genome is an important prerequisite both for the set-up of high-throughput genotyping analysis and for functional genomic approaches toward the characterization of the genetic determinism of traits of agronomic interest.

genomics↗

bioRxiv2019

PulmonDB: a curated lung disease gene expression database

Chronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) have contrasting clinical and pathological characteristics, and interesting whole-genome transcriptomic profiles. However, data from public repositories are difficult to reprocess and reanalyze. Here we present PulmonDB, a web-based database (http://pulmondb.liigh.unam.mx/) and R library that facilitates exploration of gene expression profiles for these diseases by integrating transcriptomic data and curated annotation from different sources. We demonstrated the value of this resource by presenting the expression of already well-known genes of COPD and IPF across multiple experiments and the results of two differential expression analyses in which we successfully identified differences and similarities. With this first version of PulmonDB, we create a new hypothesis and compare the two diseases from a transcriptomics perspective.

bioinformatics↗