Biology subjects

Duddu, A. S.

Publications and source records attributed to Duddu, A. S..

7 recordsLinked to original sources

bioRxiv2026

Endosomal pH Triggers Amyloid β Oligomerization and Maladaptive Phenotypic Plasticity in Alzheimers Disease

Endosomal dysfunction is a presymptomatic hallmark of neurodegeneration. Recent evidence highlights dysregulation of endosomal pH as a central pathogenic hub in Alzheimer's disease (AD); however, the mechanisms linking pH shifts to neurodegeneration remain incompletely defined. Here, we use a quantitative model of endosomal acidification driven by proton pumping via the vacuolar ATPase, proton leak via the endosomal Na/H exchanger NHE6, and other ion-regulating elements. The model recapitulates how downregulation of NHE6 in AD promotes endosomal hyperacidification, potentially triggering maladaptive phenotypic plasticity, an initially adaptive response that becomes pathological. Analysis of human brain datasets reveals reciprocal enrichment of NHE6 in neurons and the related NHE9 in glia, with NHE6 co-expression networks enriched for synaptic signalling. Systematic curation of NHE6 patient variants indicates that loss-of-function is associated with late regression, consistent with progressive endosomal hyperacidification, supporting a conceptual framework where early compensation transitions to neurodegeneration. Mathematical analyses calibrated for neuronal endosomes reveal a saturable relationship between luminal pH and NHE6 dosage, with threshold-like behaviour below ~50% expression that hyperacidifies endosomes, correlating with AD severity. Our model suggests this pH shift may exponentially accelerate A{beta} oligomerization and enhance {beta}-secretase activity. Furthermore, A{beta} oligomerization estimates correlate with dysregulation of calcium signalling and synaptic dysfunction. Model findings are compared with experimental results from NHE6-null mice and a cell culture model of AD. Drawing parallels to cancer, we propose that endosomal pH serves as a conserved regulator of adaptive-to-maladaptive transitions. Restoring physiological endosomal pH may offer a therapeutic window to prevent irreversible neurodegeneration in AD.

neuroscience↗

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↗

bioRxiv2024

Multistability and predominant double-positive states in a four node mutually repressive network: a case study of Th1/Th2/Th17/T-reg differentiation

Elucidating the emergent dynamics of complex regulatory networks enabling cellular differentiation is crucial to understand embryonic development and suggest strategies for synthetic circuit design. A well-studied network motif often driving cellular decisions is a toggle switch - a set of two mutually inhibitory lineage-specific transcription factors A and B. A toggle switch often enables two possible mutually exclusive states - (high A, low B) and (low A, high B) - from a common progenitor cell. However, the dynamics of networks enabling differentiation of more than two cell types from a progenitor cell is not well-studied. Here, we investigate the dynamics of four master regulators A, B, C and D inhibiting each other, thus forming a toggle tetrahedron. Our simulations show that a toggle tetrahedron predominantly allows for co-existence of six double positive or hybrid states where two of the nodes are expressed relatively high as compared to the remaining two - (high A, high B, low C, low D), (high A, low B, high C, low D), (high A, low B, low C, high D), (low A, high B, high C, low D), (low A, low B, high C, high D) and (low A, high B, low C, high D). Stochastic simulations showed state-switching among these phenotypes, indicating phenotypic plasticity. Finally, we apply our results to understand the differentiation of naive CD4+ T cells into Th1, Th2, Th17 and Treg subsets, suggesting Th1/Th2/Th17/Treg decision-making to be a two-step process. Our results reveal multistable dynamics and establish the stable co-existence of hybrid cell-states, offering a potential explanation for simultaneous differentiation of multipotent naive CD4+ T cells.

systems biology↗

bioRxiv2022

Functional resilience of mutually repressing motifs embedded in larger regulatory networks

Elucidating the design principles of regulatory networks driving cellular decision-making has important implications in understanding cell differentiation and guiding the design of synthetic circuits. Mutually repressing feedback loops between master regulators of cell-fates can exhibit multistable dynamics, thus enabling multiple "single-positive" phenotypes: (high A, low B) and (low A, high B) for a toggle switch, and (high A, low B, low C), (low A, high B, low C) and (low A, low B, high C) for a toggle triad. However, the dynamics of these two network motifs has been interrogated in isolation in silico, but in vitro and in vivo, they often operate while embedded in larger regulatory networks. Here, we embed these network motifs in complex larger networks of varying sizes and connectivity and identify conditions under which these motifs maintain their canonical dynamical behavior, thus identifying hallmarks of their functional resilience. We show that an increased number of incoming edges onto a motif leads to a decay in their canonical stand-alone behaviors, as measured by multiple metrics based on pairwise correlation among nodes, bimodality of individual nodes, and the fraction of "single-positive" states. We also show that this decay can be exacerbated by adding self-inhibition, but not self-activation, loops on the master regulators. These observations offer insights into the design principles of biological networks containing these motifs, and can help devise optimal strategies for integration of these motifs into larger synthetic networks.

systems biology↗

bioRxiv2021

Emergent dynamics of a three-node regulatory network explain phenotypic switching and heterogeneity during helper T-cell differentiation

Naive helper (CD4+) T-cells can differentiate into distinct functional subsets including Th1, Th2, and Th17 phenotypes. Each of these phenotypes has a master regulator - T-bet (Th1), GATA3 (Th2) and ROR{gamma}T (Th17) - that inhibits the other two master regulators. Such mutual repression among them at a transcriptional level can enable multistability, giving rise to six experimentally observed phenotypes - Th1, Th2, Th17, hybrid Th/Th2, hybrid Th2/Th17 and hybrid Th1/Th17. However, the dynamics of switching among these phenotypes, particularly in the case of epigenetic influence, remains unclear. Here, through mathematical modeling, we investigated the coupled transcription-epigenetic dynamics in a three-node mutually repressing network to elucidate how epigenetic changes mediated by any master regulator can influence the transition rates among different cellular phenotypes. We show that the degree of plasticity exhibited by one phenotype depends on relative strength and duration of mutual epigenetic repression mediated among the master regulators in a three-node network. Further, our model predictions can offer putative mechanisms underlying relatively higher plasticity of Th17 phenotype as observed in vitro and in vivo. Together, our modeling framework characterizes phenotypic plasticity and heterogeneity as an outcome of emergent dynamics of a three-node regulatory network, such as the one mediated by T-bet/GATA3/ROR{gamma}T.

systems biology↗

bioRxiv2021

Emergent properties of coupled bistable switches

Understanding the dynamical hallmarks of network motifs is one of the fundamental aspects of systems biology. Positive feedback loops constituting one or two nodes - self-activation, toggle switch, and double activation loops - are commonly observed motifs in regulatory networks underlying cell-fate decision systems. Their individual dynamics are well-studied; they are capable of exhibiting bistability. However, studies across various biological systems suggest that such positive feedback loops are interconnected with one another, and design principles of coupled bistable motifs remain unclear. We wanted to ask what happens to bistability or multistability traits and the phenotypic space (collection of phenotypes exhibited by a system) due to the couplings. In this study, we explore a set of such interactions using discrete and continuous simulation methods. Our results suggest that couplings that do not connect the bistable switches in a way that contradicts the connections within individual bistable switches lead to a steady state space that is strictly a subset of the set of possible combinations of steady states of bistable switches. Furthermore, adding direct and indirect self-activations to these coupled networks can increase the frequency of multistability. Thus, our observations reveal specific dynamical traits exhibited by various coupled bistable motifs.

systems biology↗

bioRxiv2020

Multistability in cellular differentiation enabled by a network of three mutually repressing master regulators

Identifying the design principles of complex regulatory networks driving cellular decision-making remains essential to decode embryonic development as well as enhance cellular reprogramming. A well-studied network motif involved in cellular decision-making is a toggle switch - a set of two opposing transcription factors A and B, each of which is a master regulator of a specific cell-fate and can inhibit the activity of the other. A toggle switch can lead to two possible states - (high A, low B) and (low A, high B), and drives the either-or choice between these two cell-fates for a common progenitor cell. However, the principles of coupled toggle switches remains unclear. Here, we investigate the dynamics of three master regulators A, B and C inhibiting each other, thus forming three coupled toggle switches to form a toggle triad. Our simulations show that this toggle triad can lead to co-existence of cells into three differentiated single positive phenotypes - (high A, low B, low C), (low A, high B, low C), and (low A, low B, high C). Moreover, the hybrid or double positive phenotypes - (high A, high B, low C), (low A, high B, high C) and (high A, low B, high C) - can co-exist together with single positive phenotypes. Including self-activation loops on A, B and C can increase the frequency of double positive states. Finally, we apply our results to understand the cellular decision-making in terms of differentiation of naive CD4+ T cells into Th1, Th2 and Th17 states, where hybrid Th1/Th2 and hybrid Th1/Th17 cells have been reported in addition to the Th1, Th2 and Th17 ones. Our results offer novel insights into the design principles of a multistable network topology and provides a framework for synthetic biology to design tristable systems.

systems biology↗