Biology subjects

Ramakrishnan, R.

Publications and source records attributed to Ramakrishnan, R..

6 recordsLinked to original sources

bioRxiv2026

Identifying Putative Pathogenic Non-Coding Variants in Unresolved Rare Disease Patients Using Topologically Associated Domains

Unresolved rare disease is a major public health challenge affecting ~300 million people worldwide. At least 50% of these individuals remain genetically unresolved after applying exome sequencing and/or whole genome sequencing. One source of these missing diagnoses is the presence of rare variants within the non-coding genome that are detected but not interpreted by whole genome sequencing. In order to systematically evaluate candidate pathogenic non-coding variants, we created the Genomic Analysis of Variants in Unresolved Rare Disease (GAVURD) system. GAVURD leverages trio whole genome sequencing alignment data to produce a short list of putative pathogenic non-coding variants for a given proband. GAVURD uses best practices for de novo and rare inherited variant identification, links variants to human disease genes harnessing topologically associated domain (TAD) data, and rank prioritizes variants based on phenotypic overlap. As a proof-of-concept, we applied GAVURD to ten probands with unresolved rare disease and implicated six potentially causal non-coding variants based on a confluence of evidence supportive of pathogenicity. The GAVURD system serves an important role in prioritizing candidate non-coding causal variants for unresolved rare disease that can serve as the high value and informed focus of additional functional follow-up studies.

genomics↗

bioRxiv2026

Dityrosine photocrosslinking of native collagen bioinks for controlled shape-fidelity of bioprinted cardiac tissue constructs: probing the interplay between fibrillogenesis and covalent bond formation

Collagen bioinks are widely used in biofabrication, but their relatively soft mechanical properties can lead to structural instabilities under cell-generated contraction forces. While synthetic functional groups can be conjugated for covalent crosslinking, these methods often disrupt natural protein fibrillogenesis, thereby compromising collagen fibre architecture. This work presents a strategy for the direct covalent stabilisation of native collagen bioinks with dityrosine bonds via visible-light photocrosslinking with ruthenium (Ru) and sodium persulfate (SPS), avoiding the need for polymer pre-functionalisation. Multimodal characterisation, including high-resolution microscopy, spectroscopy, mass spectrometry, and nanoindentation, identified photocrosslinking conditions that enhance collagen fibrillogenesis and reduce off-target polymer oxidation. Interestingly, the biofabrication process itself affected ultimate collagen fibre architecture, with shear-induced alignment during extrusion enhancing fibril proximity and self-assembly, overcoming inhibitory effects the crosslinkers had on fibrillogenesis via ionic and electrostatic interactions. Leveraging these insights, embedded bioprinting was used to fabricate cardiac constructs with high cell viability (>80%), where dityrosine crosslinking could be tuned to modulate geometric shape changes under cell-generated forces (1-15% shrinkage). Finally, the platform was used to bioprint anatomically accurate double-ventricle human heart models with robust shape fidelity. This research establishes a versatile photocrosslinking framework for bioprinting cardiac constructs with tunable shape stability using native collagen bioinks.

bioengineering↗

bioRxiv2025

Indistinguishability domains of neural microcircuit motifs mapped through classification scores of postsynaptic spike counts

In the kinetic modeling of a chemical synapse, the reversal potential (Esyn) and conductance amplitude ([Formula]) of the synapse jointly regulate the spike-induced activity of the postsynaptic neuron. We simulate two-neuron microcircuit motifs of feedforward (i [->] j ) and feedback (i {rightleftharpoons} j ) types using random external current pulses provided only at the presynaptic neuron. For combinations of Esyn and [Formula], corresponding to an excitatory synapse, a supervised machine learning method for classification distinguishes the motifs perfectly with a score of 1.0 when using binned counts of postsynaptic spikes as the input. Strongly inhibitory combinations of these parameters result in no postsynaptic response in both types of microcircuit motifs; hence, the classifier does not improve upon a random assignment with a score of 0.5. In other domains of the parameter space spanned by Esyn and [Formula], corresponding to diminished excitation/inhibition, the classifier fails (0.5 < score < 1), indicating the challenge in identifying the nature of the synapse inferred exclusively from postsynaptic spikes. For this task, the gradient boosting classifier gives higher classification accuracies that improve with further training, compared to other classifiers explored in this study.

neuroscience↗

bioRxiv2024

Estimating Organ-to-Plasma Ratios in physiologically based PK modeling: a simplified approach for early drug discovery

Physiologically based pharmacokinetics (PBPK) modeling is a valuable tool in drug development and candidate selection. However, its widespread adoption in early stages of drug discovery remains limited. This study proposes a novel simplified approach to estimate organ-to-plasma ratio (Kp) values based on measured or estimated volume of distribution (VDss) to eliminate the reliance on additional in vitro data such as blood to plasma partition, LogP and pKa, which may not be available for newly synthesized molecules. The study includes 11 simulations across 4 compounds and 5 species. When simulations were based on ideal VDss and clearance (CL) values determined through non-compartmental analysis (NCA), the observed average absolute fold error (AAFE) aligned with experimental variability in the in vivo experiments (AAFE=1.3). However, when in vitro to in vivo correlation approaches were used to predict VDss and CL starting from in vitro intrinsic CL, plasma protein binding and microsomal binding, the AAFE increased to 1.7, reflecting the additional error introduced by the use of in vitro data to determine PK properties. Overall, this work provides a starting point for the facile implementation of PBPK models to meet the needs of early drug discovery projects.

pharmacology and toxicology↗

bioRxiv2021

Delineating the molecular and phenotypic spectrum of the SETD1B-related syndrome

Pathogenic variants in SETD1B have been associated with a syndromic neurodevelopmental disorder including intellectual disability, language delay and seizures. To date, clinical features have been described for eleven patients with (likely) pathogenic SETD1B sequence variants. We perform an in-depth clinical characterization of a cohort of 36 unpublished individuals with SETD1B sequence variants, describing their molecular and phenotypic spectrum. Selected variants were functionally tested using in vitro and genome-wide methylation assays. Our data present evidence for a loss-of-function mechanism of SETD1B variants, resulting in a core clinical phenotype of global developmental delay, language delay including regression, intellectual disability, autism and other behavioral issues, and variable epilepsy phenotypes. Developmental delay appeared to precede seizure onset, suggesting SETD1B dysfunction impacts physiological neurodevelopment even in the absence of epileptic activity. Interestingly, males are significantly overrepresented and more severely affected, and we speculate that sex-linked traits could affect susceptibility to penetrance and the clinical spectrum of SETD1B variants. Finally, despite the possibility of non-redundant contributions of SETD1B and its paralogue SETD1A to epigenetic control, the clinical phenotypes of the related disorders share many similarities, indicating that elucidating shared and divergent downstream targets of both genes will help to understand the mechanism leading to the neurobehavioral phenotypes. Insights from this extensive cohort will facilitate the counseling regarding the molecular and phenotypic landscape of newly diagnosed patients with the SETD1B-related syndrome.

genetics↗

bioRxiv2020

Activation of endogenous retroviruses during brain development causes neuroinflammation

Endogenous retroviruses (ERVs) make up a large fraction of mammalian genomes and are thought to contribute to human disease, including brain disorders. In the brain, aberrant activation of ERVs is a potential trigger for neuroinflammation, but mechanistic insight into this phenomenon remains lacking. Using CRISPR/Cas9-based gene disruption of the epigenetic co-repressor protein Trim28, we found a dynamic H3K9me3-dependent regulation of ERVs in proliferating neural progenitor cells (NPCs), but not in adult neurons. In vivo deletion of Trim28 in cortical NPCs during mouse brain development resulted in viable offspring expressing high levels of ERV expression in excitatory neurons in the adult brain. Neuronal ERV expression was linked to inflammation, including activated microglia, and aggregates of ERV-derived proteins. This study demonstrates that brain development is a critical period for the silencing of ERVs and provides causal in vivo evidence demonstrating that transcriptional activation of ERV in neurons results in neuroinflammation.

neuroscience↗