Biology subjects

Reddy, G.

Publications and source records attributed to Reddy, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Interactions between epistasis and pleiotropy in generic models of complex traits

Evolution in fluctuating environments depends critically on epistatic interactions between mutations and the pleiotropic effects these mutations have on fitness across multiple conditions. However, while these effects of epistasis and pleiotropy have been extensively studied individually, the interactions between them are less well understood. In this study, we analyze how genetic background shapes the effects of mutations across multiple environmental conditions in generic models of complex traits. We show that when epistasis is widespread and random, systematic patterns of cross-environment pleiotropy can emerge naturally. Specifically we outline two regimes, widespread random epistasis (WRE) and structured pleiotropy (SP), in which patterns of global epistasis in one environment can be predicted from those in other conditions. We outline these predictions in several classes of generic null models, and test these predictions in laboratory budding yeast by measuring the fitness effects of a large set of mutations across many genetic backgrounds in several growth environments. We find that only a subset of mutations fall within the WRE and SP regimes, but that in these cases two of our models provide accurate fits to the data. Finally, we use this framework to show how modular, pleiotropic architectures shape long-term evolutionary steady states in fluctuating environments, revealing how tradeoffs between environments can develop from the geometry of shared latent interaction structure.

evolutionary biology↗

bioRxiv2026

Conformational Switching between ON and OFF States Proceeds through Multiple Pathways in the SAM-III Translational Riboswitch

Gene regulation by translational riboswitches relies on repeated and reversible conformational switching between ON (apo) and OFF (holo) states. The switching mechanism often involves significant structural rearrangement, and the role of the metal ions in this mechanism is unclear. Using molecular dynamics simulations, we studied the switching transition of a translational riboswitch that regulates the concentration of S-adenosyl methionine (SAM), the `universal methyl donor'. We show that Mg2+ ions are essential for stabilizing the ON-state, and the three-way junction exhibits a `breathing-like' dynamic interconversion between open and closed modes. The riboswitch has a low population of a holo-like READY (R) state with a partially organized SAM-binding pocket prior to ligand binding. Multiple intermediates are observed in the switching landscape, contributing to the gradual stepwise structural transition between the ON and R states, and proceeding through multiple competing pathways. Interestingly, Mg2+ ions influence the dominant pathway for the ON to R state transition, whereas the reverse transition shows a weak dependence. These results provide broad insights into the function of translational riboswitches, which repeatedly and rapidly respond to changes in metabolite concentrations, in contrast to transcriptional riboswitches.

biophysics↗

bioRxiv2026

Mg2+-Dependent Multistep Folding and Stabilization of the GAAA Tetraloop-Receptor Interaction in a Group I Intron

Group I Introns are non-coding regions of pre-mRNA that catalyze their splicing from the RNA sequence by folding to a specific structure. We used computer simulations to study the folding mechanism of the P4-P6 domain in the Tetrahymena thermophila group I intron, focusing on the GAAA tetraloop-receptor (TL-R) interaction, which is a ubiquitous tertiary interaction in RNA structures. We show that the intron folds via a multistep pathway, populating seven states with distinct tertiary contacts. Under physiological Mg2+ concentrations ([Mg2+]), the loop-bulge-P4 tertiary interaction is essential to stabilize the docked TL-R complex, whereas in high [Mg2+], the TL-R complex is stable by itself. The solvated Mg2+ ions modulate the TL-R docking-undocking dynamics and stabilize non-native intermediate states. The condensation of Mg2+ in the major grooves of the TL and R helices is critical for them to attain specific stiffness essential for their facile docking. The results highlight the critical role of Mg2+ ions in facilitating TL-R interaction formation, which stabilizes long-range tertiary contacts in RNA structures. For Table of Contents Use Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/700762v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@142852org.highwire.dtl.DTLVardef@1632ad1org.highwire.dtl.DTLVardef@190021aorg.highwire.dtl.DTLVardef@17a1261_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Phenotypic heterogeneity in lag reflects an evolutionarily stable bet-hedging strategy

Single-cell experiments in yeast reveal two distinct heritable phenotypes-- arresters and recoverers--when a clonal population experiences a negative shift in its growth environment. Recoverers exhibit a variable yet finite lag before resuming growth in the new environment, whereas arresters remain in a non-growing, arrested state until more favorable conditions return. Although the diversification of individual cells into arresters and recoverers is a robust phenomenon, it remains unclear whether this coexistence constitutes an evolutionarily stable strategy. Here, we demonstrate that a heterogeneous strategy composed of both arrester and recoverer phenotypes maximizes long-term population fitness across a broad spectrum of growth-lag trade-offs. Our analysis employs a dynamic programming framework to identify the fitness-maximizing distribution of phenotypes for populations that stochastically switch between preferred and non-preferred environments. We propose a minimal model incorporating metabolism, growth, and enzyme allocation to explain the physiological origin of a power-law growth-lag trade-off that favors phenotypic heterogeneity. The theory predicts a nontrivial relationship between the fraction of recoverers and their lag time, which aligns with existing data from wild yeast strains, evolved isolates, and variations in pre-shift growth conditions. This relationship suggests an evolutionary rheostat-like mechanism that enables populations to rapidly adapt to changing environmental conditions.

systems biology↗

bioRxiv2025

Dimerization Mechanism of HIV-1 RNA Hairpins to Extended Duplex Structures

Genomic RNA (gRNA) dimerization is essential for retroviral replication. In the gRNA of human immunodeficiency virus (HIV-1), the hairpin-like dimerization initiation sequence (DIS) forms a kissing-complex (KC) with the DIS sequence in another gRNA, which later converts into a stable extended-duplex (ED). Using coarse-grained simulations, we mapped the transition of HIV-1 DIS RNA hairpins (HPs) to ED and identified multiple intermediates beyond the KC. The KC has an anionic pocket stabilized through the condensation of Mg2+ ions. Hence, when only K+ ions are present at physiological levels, the HPs to ED transitions occur through a different dominant pathway devoid of the KC. We also observed purine base flipping near KC hydrogen bonds, revealing the population of a sub-ensemble of intermediates. The proposed dimerization mechanism of HPs to ED, along with the sub-ensemble of KC conformations and its anionic pocket, provides a strategic framework for designing specific retroviral drugs targeting this pathway. For Table of Contents Use Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/683870v1_ufig1.gif" ALT="Figure 1"> View larger version (94K): org.highwire.dtl.DTLVardef@2cb0f5org.highwire.dtl.DTLVardef@15c8d1org.highwire.dtl.DTLVardef@3321cborg.highwire.dtl.DTLVardef@efd30d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Transition Metal Binding Drives Folding of a Metalloregulatory Riboswitch by Modulating Conformational Flexibility at Helical Junctions

Transition metal ions are crucial for bacterias survival. Bacteria employ metalloregulatory riboswitches to respond to varying metal ion concentrations. The czcD (NiCo) transcription riboswitch specifically senses Co2+, Ni2+, and Fe2+ ions at micromolar concentrations amid millimolar Mg2+. We used computer simulations with multi-resolution RNA models to understand how global conformational changes in the NiCo riboswitch are coupled to the remarkable specific binding of Co2+. We show that the riboswitch folds through an intermediate state, where a partially folded four-way junction (4WJ) creates an anionic pocket large enough to accommodate the binding of solvated divalent ions. The binding of Co2+ is coupled to the stability of the weak non-canonical G{middle dot}A base pairs at the helical junction that drive the formation of native-like coaxial stacking of four helices. The Co2+ binding further twists the 4WJ, which locks the ions in the bound state. Electronic structure calculations show that enhanced orbital interactions between conserved guanines in the 4WJ and Co2+ are responsible for the high specificity of the riboswitch in binding to Co2+ over Mg2+. We provide a framework for understanding and engineering tunable RNA-based biosensors and developing antimicrobials, as metal intoxication is an evolutionary strategy to inhibit bacterial growth.

biophysics↗

bioRxiv2025

Conformational Pathways of Translational T-box Riboswitch Governing tRNA Recognition for Gene Regulation

The availability of various amino acids is essential for the synthesis of proteins during translation. In bacteria, T-box riboswitches play a critical role in regulating the concentrations of amino acids by sensing and decoding the aminoacylation status of tRNAs for precise control of amino acid biosynthesis and transport pathways. We used computer simulations to probe the mechanism of tRNA recognition by a translational T-box riboswitch using the iles T-box riboswitch as a model system. We show that the T-box aptamer populates three distinct thermodynamic states - undocked, predocked, and docked - depending on the relative orientation between its three stems (stem I, II, and IIA/B). The relative population of the three states is strongly dependent on the Mg2+ concentration. In the undocked and predocked states, the freely moving stem I catches the tRNA from the solution using the fly-casting mechanism. Subsequently, the tRNA-bound stem I docks to stem II in a specific orientation with the help of noncanonical intra- and inter-backbone hydrogen bonds, which facilitate tRNA interaction with the discriminator domain to detect the aminoacylation state of tRNA and regulate the gene. Since T-box riboswitches are prime targets in designing antibiotics, our proposed mechanism of tRNA recognition by T-box reveals multiple critical sites in the riboswitch that can be targeted for developing new antibiotics. Interestingly, molecules acting as antibiotics exist targeting one of the proposed sites. These results also have broad implications for understanding the role of specific RNA-RNA interactions in various cellular processes.

biophysics↗

bioRxiv2025

Manifold learning for olfactory habituation to strongly fluctuating backgrounds

Animals rely on their sense of smell to survive, but important olfactory cues are mixed with confounding background odors that fluctuate due to atmospheric turbulence. It is unclear how the olfactory system habituates to such stochastic backgrounds to detect behaviorally important odors. Here, we explicitly consider the high-dimensional nature of odor coding, the natural statistics of odor fluctuations and the architecture of the early olfactory pathway. We show that their combination favors a manifold learning mechanism for olfactory habituation over alternatives based on predictive filtering. Manifold learning is implemented in our model by a biologically plausible network of inhibitory interneurons in the early olfactory pathway. We demonstrate that plasticity rules based on IBCM or online PCA are effective at implementing this mechanism in turbulent conditions and outperform previous models relying on mean background subtraction. Interneurons with an IBCM plasticity rule acquire selectivity to independently varying odors. This manifold learning mechanism offers a path towards distinguishing plasticity rules in experiments and could be leveraged by other biological circuits facing fluctuating environments.

neuroscience↗

bioRxiv2025

Inferring genotype-phenotype maps using attention models

Predicting phenotype from genotype is a central challenge in genetics. Traditional approaches in quantitative genetics typically analyze this problem using methods based on linear regression. These methods generally assume that the genetic architecture of complex traits can be parameterized in terms of an additive model, where the effects of loci are independent, plus (in some cases) pair-wise epistatic interactions between loci. However, these models struggle to analyze more complex patterns of epistasis or subtle gene-environment interactions. Recent advances in machine learning, particularly attention-based models, offer a promising alternative. Initially developed for natural language processing, attention-based models excel at capturing context-dependent interactions and have shown exceptional performance in predicting protein structure and function. Here, we apply attention-based models to quantitative genetics. We analyze the performance of this attention-based approach in predicting phenotype from genotype using simulated data across a range of models with increasing epistatic complexity, and using experimental data from a recent quantitative trait locus mapping study in budding yeast. We find that our model demonstrates superior out-of-sample predictions in epistatic regimes compared to standard methods. We also explore a more general multi-environment attention-based model to jointly analyze genotype-phenotype maps across multiple environments and show that such architectures can be used for "transfer learning" - predicting phenotypes in novel environments with limited training data.

genetics↗

bioRxiv2025

Reconciling time and prediction error theories of associative learning

Learning involves forming associations between sensory events that have a consistent temporal relationship. Influential theories based on prediction errors explain numerous behavioral and neurobiological observations but do not account for how animals measure the passage of time. Here, we propose a Bayesian theory for temporal causal learning, where the structure of inter-stimulus intervals is used to infer the singular cause of a rewarding stimulus. We show that a single assumption of timescale invariance, formulated as an hierarchical generative model, is sufficient to explain a puzzling set of learning phenomena, including the power-law dependence of acquisition on inter-trial intervals and timescale invariance in response profiles. A biologically plausible algorithm for inference recapitulates salient aspects of both timing and prediction error theories. The theory predicts neural signals with distinct dynamics that encode causal associations and temporal structure.

animal behavior and cognition↗

bioRxiv2024

Metal Ion Sensing by Tetraloop-Like RNA Fragment: Role of Compact Intermediates with Non-Native Metal Ion-RNA Inner Shell Contacts

Divalent metal ions influence the folding and function of RNA in the cells. The mechanism of how RNA structural elements in riboswitches sense specific metal ions is unclear. RNA interacts with ions through two distinct binding modes: direct interaction between the ion and RNA (inner-shell (IS) coordination) and indirect interaction between the ion and RNA mediated through water molecules (outer-shell (OS) coordination). To understand how RNA senses metal ions such as Mg2+ and Ca2+, we studied the folding of a small RNA segment from the Mg2+ sensing M-Box riboswitch using computer simulations. This RNA segment has the characteristics of a GNRA tetraloop motif and interestingly requires binding of a single Mg2+ ion. The folding free energy surface of this simple tetraloop system is multidimensional, with a population of multiple intermediates where the tetraloop and cation interact through IS and OS coordination. The partially folded compact tetraloop intermediates form multiple non-native IS contacts with the metal ion. Thermal fluctuations should break these strong non-native IS contacts so that the tetraloop can fold to the native state, resulting in higher folding free energy barriers. Ca2+ undergoes rapid OS to IS transitions and vice-versa due to its lower charge density than Mg2+. However, the ability of Ca2+ to stabilize the native tetraloop state is weaker as it could not hold the loop-closing nucleotides together due to its weaker interactions with the nucleotides. These insights are critical to understanding the specific ion sensing mechanisms in riboswitches, and the predictions are amenable for verification by NMR experiments.

biophysics↗

bioRxiv2023

Adaptive algorithms for shaping behavior

Dogs and laboratory mice are commonly trained to perform complex tasks by guiding them through a curriculum of simpler tasks ( shaping). What are the principles behind effective shaping strategies? Here, we propose a machine learning framework for shaping animal behavior, where an autonomous teacher agent decides its students task based on the students transcript of successes and failures on previously assigned tasks. Using autonomous teachers that plan a curriculum in a common sequence learning task, we show that near-optimal shaping algorithms adaptively alternate between simpler and harder tasks to carefully balance reinforcement and extinction. Based on this intuition, we derive an adaptive shaping heuristic with minimal parameters, which we show is near-optimal on the sequence learning task and robustly trains deep reinforcement learning agents on navigation tasks that involve sparse, delayed rewards. Extensions to continuous curricula are explored. Our work provides a starting point towards a general computational framework for shaping animal behavior.

animal behavior and cognition↗

bioRxiv2023

Distinct information conveyed to the olfactory bulb by feedforward input from the nose and feedback from the cortex

Sensory systems are organized hierarchically, but feedback projections frequently disrupt this order. In the olfactory bulb (OB), cortical feedback projections numerically match sensory inputs. To unravel information carried by these two streams, we imaged the activity of olfactory sensory neurons (OSNs) and cortical axons in the mouse OB using calcium indicators, multiphoton microscopy, and diverse olfactory stimuli. Odorant mixtures of increasing complexity evoked progressively denser OSN activity, yet cortical feedback activity was of similar sparsity for all stimuli. Representations of complex mixtures were similar in OSNs but were decorrelated in cortical axons. While OSN responses to increasing odorant concentrations exhibited a sigmoidal relationship, cortical axonal responses were complex and non-monotonic, which could be explained by a model with activity-dependent feedback inhibition in the cortex. Our study indicates that early-stage olfactory circuits have access to both local feedforward signals and global, efficiently formatted information about odor scenes through cortical feedback.

neuroscience↗

bioRxiv2022

Inferring sparse structure in genotype-phenotype maps

Correlation among multiple phenotypes across related individuals may reflect some pattern of shared genetic architecture: individual genetic loci affect multiple phenotypes (an effect known as pleiotropy), creating observable relationships between phenotypes. A natural hypothesis is that pleiotropic effects reflect a relatively small set of common "core" cellular processes: each genetic locus affects one or a few core processes, and these core processes in turn determine the observed phenotypes. Here, we propose a method to infer such structure in genotype-phenotype data. Our approach, sparse structure discovery (SSD) is based on a penalized matrix decomposition designed to identify latent structure that is low-dimensional (many fewer core processes than phenotypes and genetic loci), locus-sparse (each locus affects few core processes) and/or phenotype-sparse (each phenotype is influenced by few core processes). Our use of sparsity as a guide in the matrix decomposition is motivated by the results of a novel empirical test indicating evidence of sparse structure in several recent genotype-phenotype data sets. First, we use synthetic data to show that our SSD approach can accurately recover core processes if each genetic locus affects few core processes or if each phenotype is affected by few core processes. Next, we apply the method to three datasets spanning adaptive mutations in yeast, genotoxin robustness assay in human cell lines, and genetic loci identified from a yeast cross, and evaluate the biological plausibility of the core process identified. More generally, we propose sparsity as a guiding prior for resolving latent structure in empirical genotype-phenotype maps.

evolutionary biology↗

bioRxiv2022

Local RNA Structure, Ion Hydration Shell and the Energy Barrier for Water Exchange from the Ion Hydration Shell Determine the Mechanism of Ion Condensation on Specific RNA Sites

RNA folding and functioning require the binding of metal ions in specific cavities of the folded structure. This property is critical to the functioning of riboswitches that especially regulate the metal ions concentration in bacteria. However, the fundamental principles governing the specific binding of metal ions in RNA are unclear. We probed the condensation mechanism of biologically relevant alkali (Na+ and K+), alkaline earth (Mg2+ and Ca2+), and transition metals (Mn2+, Co2+, Ni2+ and Zn2+) on a part of the Ni2+ and Co2+ (NiCo) sensing riboswitch aptamer domain using computer simulations. The selected structure has multiple secondary structural elements and a single site for the specific binding of a metal ion. We show that three factors primarily determine the binding of a metal ion to an RNA site - (1) The varying structural constraints from different RNA secondary structural elements strongly influence the metal ion binding. The mode of ion binding depends on the local structure around the RNAs ion-binding pocket. (2) The arrangement of water molecules in the ion hydration shell, and (3) the energy barrier for the ion to lose a water molecule from its hydration shell and transition from an outer to an inner shell interaction, which is primarily influenced by the metal ion charge density. These results have implications for designing biocompatible sensors using riboswitches to probe the concentration of intracellular metal ions.

biophysics↗

bioRxiv2022

pH Effect on Ligand Binding to an Enzyme Active Site

Understanding the mechanism of ligands binding to their protein targets and the influence of various factors governing the binding thermodynamics is essential for rational drug design. The solution pH is one of the critical factors that can influence ligand binding to a protein cavity, especially in enzymes whose function is sensitive to the pH. Using computer simulations, we studied the pH effect on the binding of a guanidinium ion (Gdm+) to the active site of hen-egg white lysozyme (HEWL). HEWL serves as a model system for enzymes with two acidic residues in the active site and ligands with Gdm+ moieties, which can bind to the active sites of such enzymes and are present in several approved drugs treating various disorders. The computed free energy surface (FES) shows that Gdm+ binds to the HEWL active site using two dominant binding pathways populating multiple intermediates. We show that the residues close to the active site that can anchor the ligand could play a critical role in ligand binding. Using a Markov state model, we quantified the lifetimes and kinetic pathways connecting the different states in the FES. The protonation and deprotonation of the acidic residues in the active site in response to the pH change strongly influence the Gdm+ binding. There is a sharp jump in the ligand-binding rate constant when the pH approaches the largest pKa of the acidic residue present in the active site. The simulations reveal that, at most, three Gdm+ can bind at the active site, with the Gdm+ bound in the cavity of the active site acting as a scaffold for the other two Gdm+ ions binding. This result implies the possibility of designing single large molecules containing multiple Gdm+ moieties that can have high binding affinities to inhibit the function of enzymes with two acidic residues in their active site.

biophysics↗

bioRxiv2022

pH Induced Switch in the Conformational Ensemble of an Intrinsically Disordered Protein Prothymosin-α and Its Implications to Amyloid Fibril Formation

Aggregation of intrinsically disordered proteins (IDPs) is the cause of various neu-rodegenerative diseases. Changes in solution pH can trigger IDP aggregation due to a shift in the IDP monomer population with a high aggregation propensity. Al-though there is experimental evidence that acidic pH promotes the compaction of IDP monomers, which subsequently leads to aggregation, the general mechanism is not clear. Using the IDP prothymosin- (proT), which is involved in multiple essential functions as a model system, we studied the pH effect on the conformational ensemble of proT and probed its role in aggregation using a coarse-grained IDP model and molecular dynamics simulations. We show that compaction in the proT dimension at low pH is due to the proteins collapse in the intermediate region (E41 - D80) rich in glutamic acid residues. Further, the {beta}-sheet content increases in this region upon pH change from neutral to acidic. We hypothesized that the conformations with high {beta}-sheet content could act as aggregation-prone (N*) states and nucleate the aggregation process. We validated our hypothesis by performing dimer simulations starting from N* and non-N* states. We show that simulations initiated using N* states as initial conformations form dimers within 1.5 s, whereas the non-N* states do not form dimers within this timescale. This study contributes to understanding the general principles of pH-induced IDP aggregation. The main result upon pH change from neutral to acidic, the intermediate region of proT is responsible for aggregation due to an increase in its {beta}-sheet forming propensity and forms the fibril core can be verified by experiments. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/497626v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@19971beorg.highwire.dtl.DTLVardef@fa98bforg.highwire.dtl.DTLVardef@422e5borg.highwire.dtl.DTLVardef@f18187_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2022

Mechanism of Mg2+ Mediated Encapsulation of an Anionic Cognate Ligand in a Bacterial Riboswitch

Riboswitches in bacteria regulate gene expression and are targets for antibiotic development. The fluoride riboswitch is essential for bacterias survival as it is critical to maintaining the F- ion concentration below the toxic level. The anionic cognate ligand, F- ion, is encapsulated by three Mg2+ ions in a trigonal pyramidal arrangement bound to the ligand-binding domain (LBD) of the riboswitch. The assembly mechanism of this intriguing LBD structure and its role in transcription initiation are not clear. Computer simulations using both coarse-grained and all-atom RNA models show that F- and Mg2+ binding to the LBD are essential to stabilize the LBD structure and tertiary stacking interactions. We propose that the first two Mg2+ ions sequentially bind to the LBD through water-mediated outer-shell coordination. The first bound Mg2+ should undergo a transition to a direct inner shell interaction through dehydration to strengthen its interaction with LBD before the binding of the second Mg2+ ion. The binding of the third Mg2+ and F- to the LBD occurs in two modes. In the first mode, the third Mg2+ binds first to the LBD, followed by F- binding. In the second mode, Mg2+ and F- form a water-mediated ion pair and bind to the LBD simultaneously, which we propose to be the efficient binding mode. We show that the linchpin hydrogen bonds involved in the antiterminator helix formation and transcription initiation are stable only after F- binding. The intermediates populated during riboswitch folding and cognate-ligand binding are potential targets for discovering new antibiotics.

biophysics↗