Biology subjects

Klein-Seetharaman, J.

Publications and source records attributed to Klein-Seetharaman, J..

9 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↗

bioRxiv2026

GO-Term Enrichment of Proteome-Scale Docking Profiles as a Biological Search-Space Reduction Layer for Protein Target Discovery

Identifying protein targets from phenotype-first or mechanism-uncertain compounds remains difficult because proteome-scale docking can generate thousands of structurally plausible interactions per compound. We developed a workflow that converts ranked proteome-scale docking profiles into stable Gene Ontology (GO) Biological Process enrichment signatures and evaluates whether those signatures can reduce the candidate target space while preferentially retaining known drug-target relationships. Docking targets were retained at the PDB-chain level, mapped to unique human gene identities, and analyzed with PANTHER overrepresentation against the screened structural gene universe. GO enrichment was evaluated from the top 25 through 505 ranked proteins in increments of 10, and a stable compound-level GO profile was selected using a Jaccard stability threshold of 0.80 across three consecutive transitions. Benchmarking used Yamanishi drug-target interactions, with 682 mapped compounds assigned to a prespecified development/held-out split (552/130) and evaluated at canonical, mechanistic, and fine-mechanistic biological resolutions. In the full corrected benchmark, 642 compounds with usable canonical GO profiles showed greater within-class than between-class similarity (0.1019 versus 0.0931; delta = 0.0088; 100,000-permutation p = 0.00222), and canonical class explained 1.34% of multivariate GO-profile variation by PERMANOVA (p < 1e-4). Fine-mechanistic labels showed stronger organization in the full dataset (delta = 0.0245; PERMANOVA R-squared = 0.0976; both p < 1e-4). Held-out validation was more modest and metric-dependent: mechanistic labels were significant by PERMANOVA (R-squared = 0.0626, p = 0.0437), whereas the frozen fine-mechanistic analysis showed greater within-class similarity (0.1350 versus 0.1110; p = 0.038) and significant nearest-neighbor recovery (p = 0.0495), but not significant PERMANOVA (p = 0.119). The principal held-out search-space experiment evaluated 107 compounds, 753,492 candidate protein rows, and 424 represented gold-standard targets. A direct GO gate retained 1.26% of candidates while retaining 11.32% of known targets (8.96-fold enrichment); ontology-propagated GO associations retained 5.10% of candidates and 21.46% of known targets (4.21-fold enrichment). At matched candidate-space sizes, GO-associated prioritization retained 27.59% versus 22.41% of known targets at approximately 5% of candidates, 39.39% versus 36.08% at 10%, and 58.73% versus 56.13% at 20%. By contrast, additive protein-level GO reranking was heterogeneous: among 605 evaluable compounds, 21.7% improved their best known-target rank, but mean reciprocal rank decreased from 0.0276 to 0.0189. These results support GO enrichment as an intermediate biological search-space reduction and prioritization layer rather than a universal direct target-scoring function. Keywords: proteome-scale docking; Gene Ontology; target discovery; targetome; PANTHER; target fishing; biological filtering; search-space reduction; Yamanishi benchmark

bioinformatics↗

bioRxiv2024

Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC

Despite the widespread availability of genome sequencing pipelines, many genes remain part of the genome's "dark matter," where existing inference tools cannot even begin to guess the biological function of their proteins from sequence alone. This challenge is especially pronounced in organisms that are highly evolutionarily distant from well-studied models, where homology-based methods break down. Here, we describe PHILHARMONIC, a computational method that combines deep learning-based de novo protein interaction network inference with robust unsupervised spectral clustering and remote homology to illuminate functional organization in any non-model organism. From only a sequenced proteome, we show PHILHARMONIC generates meaningful functional hypothesis for protein functions, functional communities, and higher-order network structure. We validate its performance using experimental gene expression and pathway data in D. melanogaster, and we demonstrate its broad utility by analyzing temperature sensing and stress response pathways in the reef-building coral P. damicornis and its algal symbiont C. goreaui. PHILHARMONIC provides a general-purpose engine for functional discovery and biological hypothesis generation in non-model organisms, enabling systems-level insights across the full diversity of life.

bioinformatics↗

bioRxiv2024

PRDX6 contributes to selenocysteine metabolism and ferroptosis resistance

Selenocysteine (Sec) metabolism is crucial for cellular function and ferroptosis prevention and has traditionally been thought to begin with the uptake of the Sec carrier selenoprotein P (SELENOP). Following uptake, Sec released from SELENOP undergoes metabolisation via selenocysteine lyase (SCLY), producing selenide, a substrate used by selenophosphate synthetase 2 (SEPHS2), which provides the essential selenium donor - selenophosphate - for the biosynthesis of the selenocysteine tRNA. Here, we report the discovery of an alternative pathway mediating Sec metabolisation that is independent of SCLY and mediated by peroxiredoxin 6 (PRDX6). Mechanistically, we demonstrate that PRDX6 can readily react with selenide and interact with SEPHS2, potentially acting as a selenium delivery system. Moreover, we demonstrate the presence and functional significance of this alternative route in cancer cells where we reveal a notable association between elevated expression of PRDX6 with a highly aggressive neuroblastoma subtype. Altogether, our study sheds light on a previously unrecognized aspect of Sec metabolism and its implications in ferroptosis, offering new avenues for therapeutic exploitation.

cell biology↗

bioRxiv2023

Low circulating choline, a modifiable dietary factor, is associated with the pathological progression and metabolome dysfunction in Alzheimers disease.

Most Americans ([~]90%) are deficient in dietary choline, an essential nutrient. Associations between circulating choline and pathological progression in Alzheimers disease (AD) remain unknown. Here, we examined these associations and performed a metabolomic analysis in blood serum from severe AD, moderate AD, and healthy controls. Additionally, to gain mechanistic insight, we assessed the effects of dietary choline deficiency (Ch-) in 3xTg-AD mice and choline supplementation (Ch+) in APP/PS1 mice. In humans, we found AD-associated reductions in choline, its derivative acetylcholine (ACh), and elevated pro-inflammatory cytokine TNF. Choline and ACh were negatively correlated with Plaque density, Braak stage, and TNF, but positively correlated with MMSE and brain weight. Metabolites L-Valine, 4-Hydroxyphenylpyruvic, Methylmalonic, and Ferulic acids were associated with choline levels. In mice, Ch-paralleled AD severe, but Ch+ was protective. In conclusion, low circulating choline is associated with AD-neuropathological progression, illustrating the importance of dietary choline consumption to offset disease.

pathology↗

bioRxiv2021

Quantification of allosteric communications in matrix metalloprotease-1 on alpha-synuclein aggregates and substrate-dependent virtual screening

Alpha-synuclein (aSyn) has implications in pathological protein aggregations observed in neurodegenerative disorders, including Parkinsons and Alzheimers diseases. There are currently no approved prevention and cure for these diseases. In this context, matrix metalloproteases (MMPs) provide an opportunity because MMPs are broad-spectrum proteases and cleave aSyn. Previously, we showed that allosteric communications between the two domains of MMP1 on collagen fibril and fibrin depend on substrates, MMP1 activity, and ligands. However, allosteric communications in MMP1 on aSyn-induced aggregates have not been explored. Here we report quantification of allostery using single molecule measurements of MMP1 dynamics on aSyn-induced aggregates by calculating Forster Resonance Energy Transfer (FRET) between two dyes attached to the catalytic and hemopexin domains of MMP1. The two domains of MMP1 prefer open conformations, with the two domains well-separated. These open conformations are inhibited by a single point mutation E219Q of MMP1 and tetracycline, an MMP inhibitor. A two-state Poisson process describes the interdomain dynamics. The best-fit parameters for a Gaussian fit to the distributions of FRET values provide the two states. The ratio of the kinetic rates between the two states comes from the ratio of fitted areas around the two states. The decay rate of an exponential fit to the correlations between FRET values provides the sum of the kinetic rates. Since a crystal structure of aSyn-bound MMP1 is not available, we performed molecular docking of MMP1 with aSyn using ClusPro. We simulated MMP1 dynamics using different docking poses and matched the experimental and simulated interdomain dynamics to determine the most appropriate pose. We performed virtual screening against the potential ligand-binding sites on the appropriate aSyn-MMP1 binding pose and showed that lead molecules differ between free MMP1 and substrate-bound MMP1. In other words, virtual screening needs to take substrates into account for substrate-specific control of MMP1 activity. Molecular understanding of interactions between MMP1 and aSyn-induced aggregates may open up the possibility of degrading pathological aggregates in neurodegeneration by targeting MMPs. SignificanceWe have quantified MMP1 interdomain dynamics on aSyn-induced aggregates by a two-state Poisson process. Histograms and correlations of FRET values determine the kinetic rates of interconversion between the two states. We quantify the conformational dynamics of the whole MMP1 and allosteric communications by the two-dimensional matrix of correlations between every pair of amino acids from experimentally-validated all-atom simulations. The two-dimensional correlations lead to a Gray Level Co-occurrence Matrix and a measure of Shannon entropy describing the conformational fluctuations. As such, we address the quantification of allosteric communications, a leading challenge in defining allostery. We report that the potential ligand-binding sites and lead molecules change for MMP1 upon binding alpha-synuclein and depend on the binding pose selected. This suggests that one needs to take the substrate into account while targeting MMPs.

biophysics↗

bioRxiv2020

Cephalosporins target quorum sensing and suppress virulence of Pseudomonas aeruginosa in Caenorhabditis elegans infection model

Pseudomonas aeruginosa utilizes a chemical social networking system referred to as quorum sensing (QS) to strategically co-ordinate the expression of virulence factors and biofilm formation. Virulence attributes damage the host cells, impair the host immune system, and protect bacterial cells from antibiotic attack. Thus, anti-QS agents may act as novel anti-infective therapeutics to treat P. aeruginosa infections. The present study was performed to evaluate the anti-QS, anti-biofilm, and anti-virulence activity of {beta}-lactam antibiotics (carbapenems and cephalosporins) against P. aeruginosa. The anti-QS activity was quantified using Chromobacterium violaceum CV026 as a QS reporter strain. Our results showed that cephalosporins including cefepime (CP), ceftazidime (CF), and ceftriaxone (CT) exhibited potent anti-QS and anti-virulence activities against P. aeruginosa PAO1. These antibiotics significantly impaired motility phenotypes, decreased pyocyanin production, and reduced the biofilm formation by P. aeruginosa PAO1. In the present study, we studied isogenic QS mutants of PAO1: {Delta}LasR, {Delta}RhlR, {Delta}PqsA, and {Delta}PqsR and found that the levels of virulence factors of antibiotic-treated PAO1 were comparable to QS mutant strains. Molecular docking predicted high binding affinities of cephalosporins for the ligand-binding pocket of QS receptors (CviR, LasR, and PqsR). In addition, our results showed that the anti-microbial activity of aminoglycosides increased in the presence of sub-inhibitory concentrations (sub-MICs) of CP against P. aeruginosa PAO1. Further, utilizing Caenorhabditis elegans as an animal model for the in vivo anti-virulence effects of antibiotics, cephalosporins showed a significant increase in C. elegans survival by suppressing virulence factor production in P. aeruginosa. Thus, our results indicate that cephalosporins might provide a viable anti-virulence therapy in the treatment of infections caused by multi-drug resistant P. aeruginosa.

microbiology↗

bioRxiv2019

Fibrinolytic activity of matrix metalloprotease-1

The roles of protein conformational dynamics and allostery in function are well-known. However, the roles that inter-domain dynamics have in function are not entirely understood. We used matrix metalloprotease-1 (MMP1) as a model system to study the relationship between inter-domain dynamics and activity because MMP1 has diverse substrates. Here we focus on fibrin, the primary component of a blood clot. Water-soluble fibrinogen, following cleavage by thrombin, self-polymerize to form water-insoluble fibrin. We studied the inter-domain dynamics of MMP1 on fibrin without crosslinks using single-molecule Forster Resonance Energy Transfer (smFRET). We observed that the distance between the catalytic and hemopexin domains of MMP1 increases or decreases as the MMP1 activity increases or decreases, respectively. We modulated the activity using 1) an active site mutant (E219Q) of MMP1, 2) MMP9, another member of the MMP family that increases the activity of MMP1, and 3) tetracycline, an inhibitor of MMP1. We fitted the histograms of smFRET values to a sum of two Gaussians and the autocorrelations to an exponential and power law. We modeled the dynamics as a two-state Poisson process and calculated the kinetic rates from the histograms and autocorrelations. Activity-dependent inter-domain dynamics may enable allosteric control of the MMP1 function.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗

bioRxiv2019

Allosteric communications between domains modulate activity of matrix metalloprotease-1

An understanding of the structure-dynamics relationship is essential for understanding how a protein works. Prior research has shown that the activity of a protein correlates with intra-domain dynamics occurring at picosecond to millisecond timescales. However, the correlation between inter-domain dynamics and the function of a protein is poorly understood. Here we show that communications between the catalytic and hemopexin domains of matrix metalloprotease-1 (MMP1) on type-1 collagen fibrils correlate with its activity. Using single-molecule FRET (smFRET), we identified functionally relevant open conformations where the two MMP1 domains are well-separated, which were significantly absent for catalytically inactive point mutant (E219Q) of MMP1 and could be modulated by an inhibitor or an enhancer of activity. The observed relevance of open conformations resolves the debate about the roles of open and closed MMP1 structures in function. A sum of two Gaussians fitted histograms, whereas an exponential fitted autocorrelations of smFRET values. We used a two-state Poisson process to describe the dynamics and used histograms and autocorrelations of conformations to calculate the kinetic rates between the two states. All-atom and coarse-grained simulations reproduced some of the experimental features and revealed substrate-dependent MMP1 dynamics. Our results suggest that an inter-domain separation facilitates opening up the catalytic pocket so that the collagen chains come closer to the MMP1 active site. Coordination of functional conformations at different parts of MMP1 occurs via allosteric communications that can take place via interactions mediated by collagen even if the linker between the domains is absent. Modeling dynamics as a Poisson process enables connecting the picosecond timescales of molecular dynamics simulations with the millisecond timescales of single molecule measurements. Water-soluble MMP1 interacting with water-insoluble collagen fibrils poses challenges for biochemical studies that the single molecule tracking can overcome for other insoluble substrates. Inter-domain communications are likely important for multidomain proteins. Statement of SignificanceIt is often challenging to distinguish functionally important dynamics because proteins are inherently flexible. MMP1 is a model enzyme because both the catalytic and hemopexin domains are necessary to degrade triple-helical type-1 collagen, the highly proteolysis-resistant structural component of the extracellular matrix. We report, for the first time, measurements of MMP1 inter-domain dynamics on type-1 collagen fibrils. We have identified functionally relevant MMP1 conformations where the two domains are far apart. Mutations and ligands can allosterically modulate the dynamics that correlate with activity. The dynamics follow a two-state Poisson process that connects the picosecond timescales of MD simulations with the millisecond timescales of experiments. The two domains can functionally communicate via collagen even when the physical linker is absent.

biophysics↗