Biology subjects

Nambiar, A.

Publications and source records attributed to Nambiar, A..

13 recordsLinked to original sources

bioRxiv2026

APOE4 reduction in vascular-associated fibroblasts decreases cerebral amyloid angiopathy and associated vascular dysfunction

Cerebral amyloid angiopathy (CAA), characterized by cerebrovascular amyloid deposition, is strongly associated with Alzheimers disease, ischemic injury, and lobar hemorrhages. APOE4 is the strongest known genetic risk factor for CAA, yet the cellular sources of APOE4 that drive pathogenic vascular amyloid deposition remain poorly defined. Here, we identify vascular-associated fibroblasts (VAFs) as a key source of APOE4 that mediates CAA and cerebrovascular dysfunction. In post-mortem brain tissue from APOE4/E4 patients with confirmed CAA, APOE colocalizes with COL6 VAFs around A{beta}-laden vessels. Therefore, to study the contribution of APOE4 derived from VAFs in CAA, independently of parenchymal sources, we used 5xFAD mice in which the endogenous mouse Apoe coding exons are replaced with floxed human APOE4 sequences. This enables selective suppression of APOE4 expression in VAFs upon tamoxifen induction of Col1a2-CreERT+. APOE4 reduction in VAFs markedly reduced CAA, with the strongest effects observed in leptomeningeal vessels. Additionally, A{beta}40, which preferentially associates with vascular amyloid, was significantly reduced in the vascular fraction. VAF APOE4 depletion resulted in fewer small microbleeds and an approximately 50% reduction in parenchymal border macrophages within the leptomeningeal compartment, whereas astrocytic reactivity remained unchanged. Functional assessment using in vivo multi-parametric photoacoustic microscopy revealed improved arterial dilation and blood flow in amyloid-laden leptomeningeal arteries. Together, these findings establish VAF-derived APOE4 as a compartment-specific driver of CAA and cerebrovascular dysfunction. One Sentence SummaryVascular-associated fibroblasts are a major source of pathogenic APOE4 that drives vascular dysfunction in cerebral amyloid angiopathy.

neuroscience↗

bioRxiv2026

Protein expression is amplified by stabilizing mRNA using gene-specific antisense oligonucleotides

Effective and safe strategies to restore gene expression in haploinsufficiency disorders or to augment protective protein signaling have long been attractive but challenging therapeutic goals. Here, we demonstrate the potential of antisense oligonucleotides (ASOs) to upregulate gene targets through mRNA stabilization. The 3 untranslated regions (UTRs) of mRNAs regulate stability via activating and repressive elements. One prominent destabilizing cis-element found in ~30% of transcripts is the Pumilio RNA-binding protein recognition element (PRE), which can be targeted to enable gene-specific protein upregulation. A scan for PREs highlights hundreds of disease-relevant transcripts that may be targetable via ASO-mediated gene-specific blocking of Pumilio binding. We show that masking specific PREs with ASOs produces sustained protein upregulation through mRNA stabilization using multiple reporter and endogenous gene targets. Using PRE-masking ASOs, we neutralized PRE-mediated destabilization of TANK-binding kinase-1 (TBK1) mRNA and restored TBK1 protein expression in participant-derived fibroblasts with TBK1 haploinsufficiency, causal for amyotrophic lateral sclerosis. Additionally, by targeting PRE sites in the myoprotective gene follistatin (FST), we achieved effective FST mRNA upregulation in tested mouse tissues. These findings suggest that ASO strategies that neutralize destabilizing 3UTR sequences like PREs may provide a powerful approach to upregulate haploinsufficiency-related genes or enhance protective protein levels for therapeutic benefit.

molecular biology↗

bioRxiv2026

Unified imputation of missing data modalities and features in multi-omic data via shared representation learning

Multi-omic studies promise a more comprehensive view of biological systems by jointly measuring multiple molecular layers. In practice, however, such datasets are rarely complete: entire molecular modalities may be missing for many samples, and observed modalities often contain substantial feature-level missingness. Existing imputation approaches typically address only one of these two problems, relying either on feature-level imputation within a single modality or on pairwise translation models that cannot accommodate arbitrary combinations of missing modalities. We present MIMIR, a deep learning framework for unified multi-omic imputation of bulk data that addresses both missing modalities and missing values through shared representation learning. MIMIR first learns modality-specific representations using masked autoencoders and then projects these representations into a common latent space, enabling reconstruction from any subset of observed modalities. Evaluated on pan-cancer multi-omic data from The Cancer Genome Atlas, MIMIR consistently outperforms baseline methods across a range of missing-modality and missing-value scenarios, including missing completely at random and missing not at random settings. Analysis of the learned shared space reveals structured cross-modal dependencies that explain modality-specific differences in imputation accuracy, with transcriptional and epigenetic modalities forming a strongly aligned core and copy number variation contributing more distinct signal. Together, these results demonstrate that shared representation learning provides an effective and flexible foundation for multi-omic imputation under heterogeneous patterns of missingness.

bioinformatics↗

bioRxiv2025

Protein Language Models Capture Structural and Functional Epistasis in a Zero-Shot Setting

Protein language models (PLMs) learn from large collections of natural sequences and achieve striking success across prediction tasks, yet it remains unclear what biological principles underlie their representations. We use epistasis, the dependence of a mutations effect on its sequence context, as a lens to probe what PLMs capture about proteins. Comparing PLM-derived scores with deep mutational scanning data, we find that epistasis emerges naturally from pretrained models, without supervision on experimental fitness. Raw model scores align with residue-residue contacts, indicating that PLMs internalize structural proximity. Applying a nonlinear transformation to bring model outputs onto the experimental scale, however, shifts the signal toward functional couplings between distant sites. These findings show that PLMs capture both structural and functional dependencies from sequence data alone, and that epistasis provides a powerful window into the biological principles embedded in their representations.

bioinformatics↗

bioRxiv2025

Trait reward sensitivity and behavioral motivation shape connectivity between the default mode network and the striatum during reward anticipation

Individuals vary substantially in their responses to rewarding events and their motivation to pursue rewards. While the ventral striatum (VS) plays a central role in reward anticipation, its functional connectivity with the default mode network (DMN)--critical for self-referential processing and value integration--potentially represents a key mechanism through which trait differences manifest in reward-related behavior. Here, we examine how trait reward sensitivity and state-level behavioral motivation relate to connectivity between the DMN and VS during reward anticipation. Forty-six participants completed the Monetary Incentive Delay task while undergoing fMRI, with trial types reflecting varying levels of reward and loss salience. Behavioral motivation, indexed by reaction time modulation across high-stakes and low-stakes trials, and self-report measures of anticipatory pleasure and reward sensitivity were assessed. Reward sensitivity interacted with anticipatory pleasure to predict behavioral motivation, such that individuals with higher anticipatory pleasure showed weaker behavioral motivation when reward sensitivity was greater, while those with lower anticipatory pleasure showed stonger behavioral motivation when reward sensitivity was greater. Critically, during high-stakes trials, reward sensitivity was associated with stronger DMN-VS connectivity in highly motivated individuals and weaker connectivity in less motivated participants. This moderation effect was consistent across gain and loss contexts, though with distinct directionality patterns. These findings provide novel insights into the neural correlates of individual differences in reward processing, demonstrating that trait reward sensitivity, anticipatory pleasure, and behavioral motivation are associated with distinct patterns of DMN-VS interactions during reward anticipation. These findings highlight the importance of considering motivational context when investigating reward-related neural mechanisms.

neuroscience↗

bioRxiv2024

Expansion of a neural crest gene signature following ectopic MYCN expression in sympathoadrenal lineage cells in vivo

Neural crest cells (NCC) are multipotent migratory stem cells which originate from the neural tube during early vertebrate embryogenesis. NCC give rise to a variety of cell types within the developing organism, including neurons and glia of the sympathetic nervous system. It has been suggested that failure in correct NCC differentiation leads to several diseases, including neuroblastoma (NB). During normal NCC development, MYCN is transiently expressed to promote NCC migration, and its downregulation precedes neuronal differentiation. Overexpression of MYCN has been linked to high-risk and aggressive NB progression. For this reason, understanding the effect overexpression of this oncogene has on development of NCC-derived sympathoadrenal progenitors (SAP), which later give rise to sympathetic nerves, will help elucidate the developmental mechanisms that may prime the onset of NB. Here, we found that overexpressing human EGFP-MYCN within SAP lineage cells in zebrafish led to the transient formation of an abnormal SAP population which displayed expanded and elevated expression of NCC markers, while paradoxically also co-expressing SAP and neuronal differentiation markers. The aberrant NCC signature was corroborated with in vivo time lapse confocal imaging in zebrafish larvae, which revealed transient expansion of sox10 reporter expression in MYCN overexpressing SAPs during the early stages of SAP development. In these aberrant MYCN overexpressing SAP cells, we also found evidence of dampened BMP signaling activity, indicating that BMP signaling disruption occurs following elevated MYCN expression, and suggesting BMP is functionally important for the NCC to SAP differentiation transition. In agreement, we discovered that pharmacological inhibition of BMP signaling was sufficient to create an aberrant NCC gene signature in SAP cells, phenocopying MYCN overexpression. Together, our results suggest that MYCN overexpression in SAPs disrupts their differentiation by eliciting abnormal NCC gene expression programs, and dampening BMP signaling response, having developmental implications for the priming of NB in vivo.

developmental biology↗

bioRxiv2024

SPLICER: A Highly Efficient Base Editing Toolbox That Enables In Vivo Therapeutic Exon Skipping

Exon skipping technologies enable exclusion of targeted exons from mature mRNA transcripts, which has broad applications in molecular biology, medicine, and biotechnology. Existing exon skipping techniques include antisense oligonucleotides, targetable nucleases, and base editors, which, while effective for specific applications at some target exons, remain hindered by shortcomings, including transient effects for oligonucleotides, genotoxicity for nucleases and inconsistent exon skipping for base editors. To overcome these limitations, we created SPLICER, a toolbox of next-generation base editors consisting of near-PAMless Cas9 nickase variants fused to adenosine or cytosine deaminases for the simultaneous editing of splice acceptor (SA) and splice donor (SD) sequences. Synchronized SA and SD editing with SPLICER improves exon skipping, reduces aberrant outcomes, including cryptic splicing and intron retention, and enables skipping of exons refractory to single splice-site editing. To demonstrate the therapeutic potential of SPLICER, we targeted APP exon 17, which encodes the amino acid residues that are cleaved to form the A{beta} plaques in Alzheimers disease. SPLICER reduced the formation of A{beta}42 peptides in vitro and enabled efficient exon skipping in a mouse model of Alzheimers disease. Overall, SPLICER is a widely applicable and efficient toolbox for exon skipping with broad therapeutic applications.

bioengineering↗

bioRxiv2023

Upstream regulator of genomic imprinting in rice endosperm is a small RNA-associated chromatin remodeler

Genomic imprinting is observed in endosperm, a placenta-like seed tissue, where transposable elements (TEs) and repeat-derived small(s)RNAs mediate epigenetic changes in plants. In imprinting, uniparental gene expression arises due to parent-specific epigenetic marks on one allele but not on the other. The importance of sRNAs and their regulation in endosperm development or in imprinting is poorly understood in crops. Here we show that a previously uncharacterized CLASSY (CLSY)-family chromatin remodeler named OsCLSY3 is essential for rice endosperm development and imprinting, acting as an upstream player in sRNA pathway. Comparative transcriptome and genetic analysis indicated its endosperm-preferred expression and its paternally imprinted nature. These important features were modulated by RNA-directed DNA methylation (RdDM) of tandemly arranged TEs in its promoter. Upon perturbation of OsCLSY3 in transgenic lines we observed defects in endosperm development and loss of around 70% of all sRNAs. Interestingly, well-conserved endosperm-specific sRNAs (siren) that are vital for reproductive fitness in angiosperms were dependent on OsCLSY3. We also observed many imprinted genes and seed development-associated genes under the control of CLSY3-dependent RdDM. These results support an essential role of OsCLSY3 in rice endosperm development and imprinting, and propose similar regulatory strategies involving CLSY3 homologs among other cereals. HighlightsO_LIUnlike among dicots, in rice and maize, CLSY3 is a maternally expressed imprinted gene majorly expressed in endosperm. C_LIO_LIEndosperm-preferred expression of OsCLSY3 is regulated by RNA-directed DNA methylation at two tandem transposon elements present in its promoter. C_LIO_LIOsCLSY3 is crucial for endosperm development and grain filling. It regulates expression of key seed development and endosperm-specific imprinted genes through RNA directed DNA methylation. C_LI

plant biology↗

bioRxiv2023

DR-BERT: A Protein Language Model to Annotate Disordered Regions

Despite their lack of a rigid structure, intrinsically disordered regions in proteins play important roles in cellular functions, including mediating protein-protein interactions. Therefore, it is important to computationally annotate disordered regions of proteins with high accuracy. Most popular tools use evolutionary or biophysical features to make predictions of disordered regions. In this study, we present DR-BERT, a compact protein language model that is first pretrained on a large number of unannotated proteins before being trained to predict disordered regions. Although it does not use any explicit evolutionary or biophysical information, DR-BERT shows a statistically significant improvement when compared to several existing methods on a gold standard dataset. We show that this performance is due to the information learned during pretraining and DR-BERTs ability to use contextual information. A web application for using DR-BERT is available at https://huggingface.co/spaces/nambiar4/DR-BERT and the code to run the model can be found at https://github.com/maslov-group/DR-BERT.

bioinformatics↗

bioRxiv2022

FUN-PROSE: A Deep Learning Approach to Predict Condition-Specific Gene Expression in Fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important for the task of metabolic engineering of these organisms to produce desired chemicals in industrially scalable conditions. Most of the previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE - a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species: Saccharomyces cerevisiae, Neurospora crassa and Issatchenkia orientalis and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

bioinformatics↗

bioRxiv2020

Transforming the Language of Life: Transformer Neural Networks for Protein Prediction Tasks

AO_SCPLOWBSTRACTC_SCPLOWThe scientific community is rapidly generating protein sequence information, but only a fraction of these proteins can be experimentally characterized. While promising deep learning approaches for protein prediction tasks have emerged, they have computational limitations or are designed to solve a specific task. We present a Transformer neural network that pre-trains task-agnostic sequence representations. This model is fine-tuned to solve two different protein prediction tasks: protein family classification and protein interaction prediction. Our method is comparable to existing state-of-the art approaches for protein family classification, while being much more general than other architectures. Further, our method outperforms all other approaches for protein interaction prediction. These results offer a promising framework for fine-tuning the pre-trained sequence representations for other protein prediction tasks.

bioinformatics↗

bioRxiv2019

Transcription factor NF-κB in a basal metazoan, the sponge, has conserved and unique sequences, activities, and regulation

Biological and biochemical functions of immunity transcription factor NF-{kappa}B in basal metazoans are largely unknown. Herein, we characterize transcription factor NF-{kappa}B from the demosponge Amphimedon queenslandica (Aq), in the phylum Porifera. Structurally and phylogenetically, the Aq-NF-{kappa}B protein is most similar to NF-{kappa}B p100 and p105 among vertebrate proteins, with an N-terminal DNA-binding/dimerization domain, a C-terminal Ankyrin (ANK) repeat domain, and a DNA binding-site profile more similar to human NF-{kappa}B proteins than Rel proteins. Aq-NF-{kappa}B also resembles the mammalian NF-{kappa}B protein p100 in that C-terminal truncation results in translocation of Aq-NF-{kappa}B to the nucleus and increases its transcriptional activation activity. Overexpression of a human or sea anemone I{kappa}B kinase (IKK) can induce C-terminal processing of Aq-NF-{kappa}B in vivo, and this processing requires C-terminal serine residues in Aq-NF-{kappa}B. Unlike human NF-{kappa}B p100, however, the C-terminal sequences of Aq-NF-{kappa}B do not effectively inhibit its DNA-binding activity when expressed in human cells. Tissue of another demosponge, a black encrusting sponge, contains NF-{kappa}B site DNA-binding activity and an NF-{kappa}B protein that appears mostly processed and in the nucleus of cells. NF-{kappa}B DNA-binding activity and processing is increased by treatment of sponge tissue with LPS. By transcriptomic analysis of A. queenslandica we identified likely homologs to many upstream NF-{kappa}B pathway components. These results present a functional characterization of the most ancient metazoan NF-{kappa}B protein to date, and show that many characteristics of mammalian NF-{kappa}B are conserved in sponge NF-{kappa}B, but the mechanism by which NF-{kappa}B functions and is regulated in the sponge may be somewhat different.

cell biology↗

bioRxiv2019

Investigating Transfusion-Related Sepsis using Culture-Independent Metagenomic Sequencing

BackgroundTransfusion-related sepsis remains an important hospital infection control challenge. Investigating septic transfusion events is often restricted by the limitations of bacterial culture in terms of time requirements and low yield in the setting of prior antibiotic administration.\n\nMethodsIn three Gram-negative septic transfusion cases, we performed mNGS of direct clinical blood specimens in addition to standard culture-based approaches utilized for infection control investigations. Pathogen detection leveraged IDSeq, a new open-access microbial bioinformatics portal. Phylogenetic analysis was performed to assess microbial genetic relatedness and understand transmission events.\n\nResultsmNGS of direct clinical blood specimens afforded precision detection of pathogens responsible for each case of transfusion-related sepsis, and enabled discovery of a novel Acinetobacter species in a platelet product that had become contaminated despite photochemical pathogen reduction. In each case, longitudinal assessment of pathogen burden elucidated the temporal sequence of events associated with each transfusion-transmitted infection. We found that informative data could be obtained from culture-independent mNGS of residual platelet products and leftover blood specimens that were either unsuitable or unavailable for culture, or that failed to grow due to prior antibiotic administration. We additionally developed methods to enhance accuracy for detecting transfusion-associated pathogens sharing taxonomic similarity to contaminants commonly found in mNGS library preparations.\n\nConclusionsCulture-independent mNGS of blood products afforded rapid and precise assessment of pathogen identity, abundance and genetic relatedness. Together, these challenging cases demonstrated the potential for metagenomics to advance existing methods for investigating transfusion-transmitted infections.

microbiology↗