Biology subjects

Raju, A.

Publications and source records attributed to Raju, A..

10 recordsLinked to original sources

bioRxiv2025

Distinct geometrical landscapes distinguish between modes of tristability in gene regulatory networks

Geometrical models have been recently used to construct landscapes for cell-fate decisions, inferred directly from experimental data. However, such quantitative cell-fate data is available for a few systems only; instead, gene regulatory networks dynamics have been studied for a broader set of biological decision-making scenarios. Thus, connecting the geometry of cell-fate decisions to their underlying regulatory networks remains an open question. Recently, two regulatory networks have been shown to exhibit tristability - a toggle switch with self-activation, and a toggle triad. Here, we show that these two motifs are distinct from a geometrical point of view, and identify two bifurcations in their behaviour: the standard cusp and the elliptic umbillic. We study experimentally accessible signatures of the differences in tristability between the two motifs. We also show how the standard cusp can be used to quantitatively model cell fate transition data for the Epithelial to Mesenchymal transition on TGF-{beta} induction in the context of cancer cells. Our work uncovers geometrical signatures of gene regulatory motifs and demonstrates how different gene regulatory networks can encode tristability in dynamically distinct ways.

systems biology↗

bioRxiv2025

A Waddingtonian description of the dynamics of Turing patterns

Turing patterns are a well-studied model of reaction-diffusion equations for developmental patterning. Their applicability has often been limited by the difficulty in identifying candidate molecules that satisfy the requisite criteria for patterning. Here, we build on recent work on geometric models to describe Turing patterning as a potential flow. We show how the universal dynamics of Turing patterning is described by a landscape, largely independent of the underlying reaction-diffusion equations. We apply our framework to three-component systems and demonstrate that we can accurately capture the dynamics of any given component. We extend our framework to larger networks and to models of Turing patterns coupled with external morphogens that provide positional information. We provide a quantitative description of the dynamics of chosen markers and apply it to the dynamics of SOX9 expression during digit patterning.

systems biology↗

bioRxiv2025

Mapping allosteric rewiring in related protein structures from collections of crystallographic multiconformer models

How do related proteins with a common fold perform diverse biological functions? Although the average structure may be similar, structural excursions from this average may differ, giving rise to allosteric rewiring that enables differential activity and regulation. However, this idea has been difficult to test in detail. Here we used the qFit algorithm to model "hidden" alternate conformations from electron density maps for an entire protein family, the Protein Tyrosine Phosphatases (PTPs), spanning 26 enzymes and 221 structures. To interrogate these multiconformer models, we developed a new algorithm, Residue Interaction Networks From Alternate conformations In RElated structures (RINFAIRE), that calculates networks of interactions between flexible residues and quantitatively compares them. We show that PTPs share a common allosteric network which rewires dynamically in response to catalytic loop motions or active-site vs. allosteric ligand binding, but also that individual PTPs have unique allosteric signatures. As experimental validation, we show that targeted mutations at residues with varying sequence conservation but high network connectivity modulate enzyme catalysis, including a surprising enhancement of activity. Overall, our work provides new tools for understanding how evolution has recycled modular macromolecular building blocks to diversify biological function. RINFAIRE is available at https://github.com/keedylab/rinfaire.

biophysics↗

bioRxiv2025

Identifying memory gene expression from single sample scRNA-seq data using power law signatures

Genes with expression levels that fluctuate on time scales longer than cell division times are associated with cancer drug tolerance. However, current methods for identifying such memory genes rely on variants of the Luria-Delbruck experiment and require either multiple replicates or lineage information, limiting their use to model systems or in-vitro settings. We develop a new conceptual approach using recent results in Random Matrix Theory to demonstrate that the existence of memory genes results in a power-law signature in the cell covariance matrix eigenspectrum. Utilizing this theoretical framework, we develop Power-Seek, an algorithm to discover memory genes from a single time point scRNA-seq dataset. Without using prior information on lineages or cell-cycle times, Power-Seek correctly identifies memory genes in a melanoma cell line. Our results open up the possibility of identifying expression states driving drug tolerance in real-world scenarios, as we demonstrate using data from a human breast cancer tissue sample.

biophysics↗

bioRxiv2024

SUMO-mediated regulation of a H3K4me3 reader controls germline development in C. elegans

ULP-2 is a conserved SUMO protease required for embryonic development in C. elegans. Here we revealed that ULP-2 controls germline development by regulating the PHD-SET domain protein, SET-26. Specifically, the ulp-2 mutant hermaphrodites exhibit increased sterility and progressive elevation in global protein sumoylation. In the progeny of homozygous animals, meiosis is arrested at the diplotene stage and the cells in the proximal germline acquire a somatic fate. Germline RNAseq analysis revealed the downregulation of numerous germline genes, whereas somatic gene expression is upregulated in ulp-2 mutant gonads. To determine the key factors that are regulated by ULP-2, we performed a yeast two-hybrid screen and identified the H3K4me3 reader, SET-26. Genetic interaction was observed in double mutant ulp-2;set-26 resulting in enhanced sterility phenotype to complete sterility in the first generation of homozygous offspring. Consistently, SET-26 is sumoylated and its sumoylation levels are regulated by ULP-2. Moreover, we detected reduction in H3K4me3 levels bound to SET-26 in the ulp-2 mutant background. A comparative proteomics screen between WT and ulp-2 loss of activity identified the predicted methyltransferase SET-27 as a ULP-2-dependent SET-26-associated protein. SET-27 knockout genetically interacts with ULP-2 in the germline, but not with SET-26. Taken together, we revealed a ULP-2/SET-26 axis which is required for the maintenance and regulation of germline development.

cell biology↗

bioRxiv2023

A geometrical model of cell fate specification in the mouse blastocyst

The lineage decision that generates the epiblast and primitive endoderm from the inner cell mass (ICM) is a paradigm for cell fate specification. Recent mathematics has formalized Waddingtons landscape metaphor and proven that lineage decisions in detailed gene network models must conform to a small list of low dimensional stereotypic changes called bifurcations. The most plausible bifurcation for the ICM is the so-called heteroclinic flip that we define and elaborate here. Our reanalysis of recent data suggests that there is sufficient cell movement in the ICM so the FGF signal, which drives the lineage decision, can be treated as spatially uniform. We thus extend the bifurcation model for a single cell to the entire ICM by means of a self-consistently defined time-dependent FGF signal. This model is consistent with available data and we propose additional dynamic experiments to test it further. This demonstrates that simplified, quantitative, and intuitively transparent descriptions are possible when attention is shifted from specific genes to lineages. The flip bifurcation is a very plausible model for any situation where the embryo needs control over the relative proportions of two fates by a morphogen feedback.

developmental biology↗

bioRxiv2023

Super-silencer perturbation by EZH2 and REST inhibition leads to large loss of chromatin interactions and reduction in cancer growth

Human silencers have been shown to exist and regulate developmental gene expression. However, the functional importance of human silencers needs to be elucidated, such as whether they can form "super-silencers" and whether they are linked to cancer progression. Here, through interrogating two putative silencer components of FGF18 gene, we found that two nearby silencers can cooperate via compensatory chromatin interactions to form a "super-silencer". Furthermore, double knockout of two silencers exhibited synergistic upregulation of FGF18 expression and changes of cell identity. To perturb the "super-silencers", we applied combinational treatment of an EZH2 inhibitor GSK343, and a REST inhibitor, X5050 ("GR"). We found that GR led to severe loss of TADs and loops, while the use of one inhibitor by itself only showed mild changes. Such changes in TADs and loops were associated with reduced CTCF and TOP2A mRNA levels. Moreover, GSK343 and X5050 synergistically upregulated super-silencer-controlled genes related to cell cycle, apoptosis and DNA damage, leading to anticancer effects both in vitro and in vivo. Overall, our data demonstrated the first example of a "super-silencer" and showed that combinational usage of GSK343 and X5050 to disrupt "super-silencers" could potentially lead to cancer ablation.

molecular biology↗

bioRxiv2023

Uncovering Protein Ensembles: Automated Multiconformer Model Building for X-ray Crystallography and Cryo-EM

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift towards modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior Rfree and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g. Coot) and fit can be further improved by refinement using standard pipelines (e.g. Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.

biophysics↗

bioRxiv2022

Super-silencers regulated by chromatin interactions control apoptotic genes

Human silencers have been shown to exist and regulate developmental gene expression. However, the functional importance of human silencers needs to be elucidated such as the working mechanism and whether they can form "super-silencers". Here, through interrogating two putative silencer components of FGF18 gene, we found that two silencers can cooperate via compensated chromatin interactions to form a "super-silencer". Furthermore, double knock-out of two silencers exhibited synergistic upregulation of FGF18 expression and changes of cell identity. To disturb the "super-silencers", we applied combinational treatment of an EZH2 inhibitor GSK343, and a REST inhibitor, X5050 ("GR"). We found that GR led to severe loss of TADs and loops, while the use of just one inhibitor by itself only showed mild changes. Such changes of TADs and loops may due to reduced CTCF protein level observed upon GR treatment. Moreover, GSK343 and X5050 worked together synergistically to upregulate the apoptotic genes controlled by super-silencers, and thus gave rise to antitumor effects including apoptosis, cell cycle arrest and tumor growth inhibition. Overall, our data demonstrated the first example of a "super-silencer" and showed that combinational usage of GSK343 and X5050 could potentially lead to cancer ablation through disruption of "super-silencers".

genomics↗

bioRxiv2019

H3K27me3-rich genomic regions can function as silencers to repress gene expression via chromatin interactions

Gene repression and silencers are poorly understood. We reasoned that H3K27me3-rich regions (MRRs) of the genome defined from clusters of H3K27me3 peaks may be used to identify silencers that can regulate gene expression via proximity or looping. MRRs were associated with chromatin interactions and interact preferentially with each other. MRR component removal at interaction anchors by CRISPR led to upregulation of interacting target genes, altered H3K27me3 and H3K27ac levels at interacting regions, and altered chromatin interactions. Chromatin interactions did not change at regions with high H3K27me3, but regions with low H3K27me3 and high H3K27ac levels showed changes in chromatin interactions. The MRR knockout cells also showed changes in phenotype associated with cell identity, and altered xenograft tumor growth. MRR-associated genes and long-range chromatin interactions were susceptible to H3K27me3 depletion. Our results characterized H3K27me3-rich regions and their mechanisms of functioning via looping.

genomics↗