Biology subjects

Dinu, V.

Publications and source records attributed to Dinu, V..

6 recordsLinked to original sources

bioRxiv2026

Developmental Convergence Across Diverse Genetic Architectures in Childhood Apraxia of Speech

Childhood apraxia of speech (CAS) is a neurodevelopmental disorder of speech-motor planning and programming, associated with literacy, academic, and psychosocial difficulties. We performed whole-exome sequencing in 11 families comprising 21 affected and 15 unaffected individuals with phenotyping spanning speech, language, cognition, literacy, and motor function. We identified 60 prioritized variant observations representing 22 unique variants across 20 genes with family-based segregation analysis assessed in informative relatives; 5 arose de novo. Our cohort included multiple affected siblings and extended relatives, with several families carrying multiple prioritized variants, suggesting cumulative or oligogenic susceptibility. Speech and literacy impairment co-occurred with oral-motor, feeding, and fine-motor difficulties. BrainSpan co-expression analysis identified MECP2 and ANK2 as the genes with the highest observed connectivity in the sampled postnatal network. Exploratory analysis of the KOLF2.1J perturbation atlas in undifferentiated human induced pluripotent stem cells identified a positive LMO3 expression-response score following NIPBL repression and opposing LMO3 and ANK2 response directions within a cohesin-associated perturbation cluster. These observations motivate testing in human neural cells. Functional enrichment, protein-association, and developmental-expression analyses supported shared biological themes involving chromatin regulation, neuronal signaling, and extracellular-matrix organization. Among six families, multiple affected relatives shared prioritized variants across a unique set of several genes, demonstrating multilocus candidate profiles whose individual and combined effects may contribute to CAS susceptibility. We propose four novel CAS candidate genes: LMO3 and PCDH10, previously linked to human accelerated regions, as well as MYCBP2 and PTPRS. Our work provides multiple testable hypotheses for future variant-specific functional validation in speech-motor development.

genetics↗

bioRxiv2025

Does ecological restoration align prokaryotic community structure with natural references across European coastal wetlands?

AbstractCoastal wetlands are crucial for biodiversity and act as critical buffers for carbon sequestration and atmospheric greenhouse gases (GHG) concentrations, yet their degradation often turns them into GHG sources. Restoration is widely implemented to recover these services, but it remains unclear whether interventions successfully reestablish the microbial functional diversity underpinning biogeochemical cycles. We tested the hypothesis that restoration aligns prokaryotic community structure with natural references, analyzing, a European gradient of coastal wetlands, comparing well-preserved, altered, and restored sites in water and sediment. Using 16SrRNA-metabarcoding and IndVal-Analysis, we characterized community assembly identifying diagnostic functional consortia. Results revealed a marked difference in water and sediment recovery after restoration. Bacterioplankton communities rapidly converge to natural references, while sediment microbiome displayed significant "ecological memory". Restored wetlands show sediment communities structurally distinct from well-preserved, retaining alteration-associated guilds decades. Results support the initial hypothesis: restoration processes in coastal wetlands can re-establish communities and metabolisms resembling well-preserved conditions in the water in the short term, while sediments retain microbial communities and metabolisms inherited from altered conditions for a long time. Future strategies must integrate active sediment interventions using molecular bioindicators to validate not only the landscape appearance, but the effective reactivation of ecosystem processes and microbiota-related services.

ecology↗

bioRxiv2024

Joint exome and metabolome analysis in individuals with dyslexia: Evidence for associated dysregulations of olfactory perception and autoimmune functions

Dyslexia is a learning disability that negatively affects reading, writing, and spelling development at the word level in 5%-9% of children. The phenotype is variable and complex, involving several potential cognitive and physical concomitants such as sensory dysregulation and immunodeficiencies. The biological pathogenesis is not well-understood. Toward a better understanding of the biological drivers of dyslexia, we conducted the first joint exome and metabolome investigation in a pilot sample of 30 participants with dyslexia and 13 controls. In this analysis, eight metabolites of interest emerged (pyridoxine, kynurenic acid, citraconic acid, phosphocreatine, hippuric acid, xylitol, 2-deoxyuridine, and acetylcysteine). A metabolite-metabolite interaction analysis identified Krebs cycle intermediates that may be implicated in the development of dyslexia. Gene ontology analysis based on exome variants resulted in several pathways of interest, including the sensory perception of smell (olfactory) and immune system-related responses. In the joint exome and metabolite analysis, the olfactory transduction pathway emerged as the primary pathway of interest. Although the olfactory transduction and Krebs cycle pathways have not previously been described in dyslexia literature, these pathways have been implicated in other neurodevelopmental disorders including autism spectrum disorder and obsessive-compulsive disorder, suggesting the possibility of these pathways playing a role in dyslexia as well. Immune system response pathways, on the other hand, have been implicated in both dyslexia and other neurodevelopmental disorders.

bioinformatics↗

bioRxiv2023

A data-fusion approach to identifying developmental dyslexia from multi-omics datasets

This exploratory study tested and validated the use of data fusion and machine learning techniques to probe high-throughput omics and clinical data with a goal of exploring the etiology of developmental dyslexia. Developmental dyslexia is the leading learning disability in school aged children affecting roughly 5-10% of the US population. The complex biological and neurological phenotype of this life altering disability complicates its diagnosis. Phenome, exome, and metabolome data was collected allowing us to fully explore this system from a behavioral, cellular, and molecular point of view. This study provides a proof of concept showing that data fusion and ensemble learning techniques can outperform traditional machine learning techniques when provided small and complex multi-omics and clinical datasets. Heterogenous stacking classifiers consisting of single-omic experts/models achieved an accuracy of 86%, F1 score of 0.89, and AUC value of 0.83. Ensemble methods also provided a ranked list of important features that suggests exome single nucleotide polymorphisms found in the thalamus and cerebellum could be potential biomarkers for developmental dyslexia and heavily influenced the classification of DD within our machine learning models.

bioinformatics↗

bioRxiv2022

Strong non-ideality effects at low protein concentrations: considerations for elongated proteins

A recent investigation was aimed at obtaining structural information on a highly extended protein via SEC-MALS-SAXS. Significantly broadened elution peaks were observed, reminiscent of a phenomenon known as viscous fingering. This phenomenon is usually observed above 50 mg/mL for proteins like bovine serum albumin (BSA). Interestingly, the highly extended protein (Brpt5.5) showed viscous fingering at concentrations lower than 5 mg/mL. The current study explores this and other non-ideal behavior, emphasizing the presence of these effects at relatively lower concentrations for extended proteins. BSA, Brpt5.5, and a truncated form of Brpt5.5 referred to as Brpt1.5 are studied systematically using size-exclusion chromatography (SEC), sedimentation velocity analytical ultracentrifugation (AUC), and viscosity. The viscous fingering effect is quantified using two approaches and is found to correlate well with the intrinsic viscosity of the proteins - Brpt5.5 exhibits the most severe effect and is the most extended protein tested in the study. By AUC, the hydrodynamic non-ideality was measured for each protein via global analysis of a concentration series. Compared to BSA, both Brpt1.5 and Brpt5.5 showed significant non-ideality that could be easily visualized at concentrations at or below 5 mg/mL and 1 mg/mL, respectively. A variety of relationships were examined for their ability to differentiate the proteins by shape using information from AUC and/or viscosity. Furthermore, these relationships were also tested in the context of hydrodynamic modeling. The importance of considering non-ideality when investigating the structure of extended macromolecules is discussed.

biophysics↗

bioRxiv2019

Pan-Cancer Exploration of mRNA Mediated Dysregulated Pathways in the Cancer Genomics Cloud

We performed a comprehensive pan-cancer analysis in the Cancer Genomics Cloud of HTSeq-FPKM normalized protein coding mRNA data from 17 cancer projects in the Cancer Genome Atlas, these are Adrenal Gland, Bile Duct, Bladder, Brain, Breast, Cervix, Colorectal, Esophagus, Head and Neck, Kidney, Liver, Lung, Pancreas, Prostate, Stomach, Thyroid and Uterus. The PoTRA algorithm was applied to the normalized mRNA protein coding data and detected dysregulated pathways that can be implicated in the pathogenesis of these cancers. Then the PageRank algorithm was applied to the PoTRA results to find the most influential dysregulated pathways among all 17 cancer types. Pathways in cancer is the most common dysregulated pathway, and the MAPK signaling pathway is the most influential (PageRank score = 0.2034) while the purine metabolism pathway is the most significantly dysregulated metabolic pathway.

bioinformatics↗