Biology subjects

Shrestha, P.

Publications and source records attributed to Shrestha, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Management of Root-Knot Nematode-Fusarium Wilt Complex with different Bio-management methods in Tomato (Solanum lycopersicum L.) var Srijana

The root-knot nematode-Fusarium complex is a major constraint to protected tomato cultivation in Nepal, particularly on the widely grown Srijana hybrid, which lacks Mi-mediated nematode resistance. The present study was conducted to identify the most effective biocontrol agent, to identify the most effective Solanum rootstock, and to compare the overall efficacy of grafting versus biocontrol agents under polyhouse conditions. For the management of the root knot nematode-Fusarium complex, a pot experiment was set up in a completely randomized design at Pokhara, Kaski. Treatments comprised Trichoderma viride, Pseudomonas fluorescens, their half-dose combination, self-grafted Srijana, and four resistant rootstocks (S. sisymbriifolium, S. melongena, S. torvum, and VNRRs-10), together with nematode-only, Fusarium-only, complex (Nematode + Fusarium), and disease-free controls. Each plant was inoculated with approximately 2,000 nematode eggs, followed by 25 ml of 10^6 spores per ml of Fusarium seven days later to mimic the field complex. Plant growth parameters and nematode infestation data were recorded and analyzed via RStudio v. 2026.04.0. The root knot nematode-Fusarium complex caused significantly greater reductions in vegetative biomass than root knot nematode and Fusarium alone (20.32 gm vs 38.40 gm vs 51.32 gm) at 45 DAT. Single-agent biocontrol gave intermediate protection (T. viride 64.9%; P. fluorescens 47.9% nematode management efficiency), whereas combined T. viride + P. fluorescens treatment produced the highest vegetative biomass but the weakest nematode suppression (320 galls, reproduction factor: 38). Grafting onto S. torvum and S. melongena resulted in the greatest nematode suppression, achieving 97.9% and 93.6% management efficiency, respectively, while S. torvum alongside VNRRs-10 maintained the highest Fusarium suppression (92.5%). Overall resistant rootstocks consistently outperformed biological control in reducing disease severity. These findings indicate that grafting onto resistant solanum rootstocks, particularly S. torvum and S. melongena, was observed as the most effective strategy for managing the root knot nematode-Fusarium complex under protected cultivation, offering a viable chemical-free management option. Keywords: Root-Knot Nematode, Fusarium oxysporum, RKN-Fusarium-complex, Solanum torvum

pathology↗

bioRxiv2026

How optimal control of cellular cost shapes population-level tumor growth dynamics

Tumor progression is often modeled as a passive response to external therapy or immune pressure, but tumor populations may also exhibit population-level regulation of proliferation and apoptosis. We develop a continuous-time Markov decision framework in which a controlled birth--death process represents a tumor population modulating the balance between proliferation and susceptibility to apoptosis in the presence of extrinsic death pressure. We examine threshold and quadratic costs, an unbounded linear reward, and constrained linear and quadratic formulations to determine how objective structure shapes optimal policies and induced population drift. Threshold and quadratic penalties generate restoring dynamics, with transitions from growth to suppression and regions of near-neutral drift associated with regulated or near-dormant behavior. An unbounded linear reward instead produces sustained or near-neutral growth without a restoring regime. Under constraints, a linear reward expands the region of positive drift as capacity increases, whereas a quadratic reward generates restoring, logistic-like drift around an interior population scale. These results show that regulated tumor dynamics depend on how growth incentives, extrinsic death pressure, penalties, and constraints scale with population size.

cancer biology↗

bioRxiv2026

Lytic bacteriophages against Salmonella Typhi as a potential alternative to antibiotics

IntroductionEnteric fever, being endemic with seasonal peaks in low- and middle-income countries, is a major health concern. Moreover, the rise in antibiotic resistance has exacerbated the situation. This study was undertaken to investigate the lytic bacteriophages against Salmonella Typhi with a potential for phage therapy. Materials and MethodsA hospital-based cross-sectional study was conducted from October 2023 to March 2024. Blood cultures were processed by the BACTEC automated culture system following standard microbiological techniques to isolate typhoidal Salmonella. Antibiotic susceptibility was tested by the modified Kirby-Bauer disc diffusion method. Lytic bacteriophages isolated by the double-layer agar method were assessed for their host range and lytic ability with spot and turbidimetric assays. ResultsOf the total 1054 blood specimens, 35 (3.2%) were positive for S. Typhi. All the isolates were susceptible to first-line antibiotics--ampicillin, chloramphenicol, and cotrimoxazole. The isolates were also sensitive to nalidixic acid (80%) as well as fluoroquinolones; ciprofloxacin (62.86%), levofloxacin (77.14%), and ofloxacin (80%). Fifteen lytic phages were isolated against S. Typhi Ty2 and CT18 strains. Four phages--vB_SaTy_ST2, vB_SaTy_ST7, vB_SaTy_ST17, and vB_SaTy_ST18--lysed all 35 clinical S. Typhi isolates. While vB_SaTy_ST17 and vB_SaTy_ST18 also lysed 7 out of 20 S. Paratyphi A isolates. Three phages (vB_SaTy_ST2, vB_SaTy_ST7, vB_SaTy_ST17) were tested against S. Typhi isolate S30. Individually, vB_SaTy_ST17 suppressed the growth for 13 hours, vB_SaTy_ST2 and vB_SaTy_ST7 for 10 hours. The phage cocktail vB_SaTy_ST2 + vB_SaTy_ST17 was the most effective, which extended the inhibition time to 15 hours. ConclusionThis study highlights the ongoing burden of enteric fever in Nepal and the increase in susceptibility of S. Typhi to nalidixic acid and fluoroquinolones. It also demonstrates the promising lytic potential of bacteriophages, particularly vB_SaTy_ST17 and the phage cocktail vB_SaTy_ST2 + vB_SaTy_ST17, against clinical S. Typhi, highlighting their potential as alternatives to antibiotics.

microbiology↗

bioRxiv2026

Scalable multi-group nonnegative spatial factorization for spatial genomics data with cell-type heterogeneity

Spatial transcriptomics (ST) technologies enable the study of gene expression within the spatial context of tissues, providing insights into tissue structure, cellular interactions, and disease progression. However, existing dimension reduction methods often overlook spatial information or struggle to distinguish spatial gene patterns from those driven by cell-type differences, limiting biological interpretability by convolving differences in gene expression patterns with differences in cell-type proportions. To address these challenges, we introduce the scalable multi-group nonnegative spatial factorization (smNSF), a computationally-tractable probabilistic framework that integrates spatial coordinates and cell-type labels into a unified matrix factorization model. By using multi-group Gaussian processes (MGGPs) as priors, our model captures complex spatial variation in a cell-type specific way while enforcing nonnegativity to enhance interpretability. We develop a variational inference framework for MGGPs that supports scalable optimization and improves the numerical stability of smNSF. Across seven spatial transcriptomics datasets spanning diverse technologies and tissues, smNSF recovers sparse, interpretable spatial factors and, through its cell-type conditional posteriors, organizes them into cell-type enriched, cell-type specific, and universal spatial programs that are not apparent from marginal factors alone. Given cell-type labels in ST data, smNSF enables cell-type aware spatial decompositions and supports cell-type conditional posteriors for in silico exploration of relationships between spatial patterns and cellular identity. Author summaryMost current analysis methods for spatial transcriptomics either ignore spatial structure or fail to separate gene-driven spatial patterns from cell-type driven differences. In this work, we develop a method that uses spatial coordinates and cell-type labels together to better uncover patterns of gene expression. Our approach, scalable multi-group nonnegative spatial factorization (smNSF), uses Gaussian processes to model spatial structure, which we extend to capture both spatial structure and cell type within a unified framework called multi-group Gaussian processes. Applying smNSF to spatial transcriptomics datasets from mouse brain and human tissues, we find that conditioning on different cell types reveals spatial patterns that are invisible in standard analyses: some cell types suppress a pattern, others sharpen it, and some reveal structure that only emerges after conditioning. This helps us understand how cell-type specific spatial programs contribute to tissue organization. To make this analysis tractable on the scale of modern spatial experiments, we also introduce a new computational approximation for Gaussian processes that is directly applicable in principle to other latent variable GP models. Together, these tools help disentangle biological sources of variation and support in silico exploration of how gene expression might change under different tissue or cell-type compositions.

genomics↗

bioRxiv2026

Matrix nucleotide homeostasis couples energetic state to mitochondrial translation

Mitochondrial protein synthesis is essential for oxidative phosphorylation, yet how organellar energetic state regulates the mitochondrial translation machinery remains poorly understood. Here, we show that mitochondrial translation is acutely sensitive to ATP synthase-dependent bioenergetic state. Pharmacological inhibition of the F1Fo-ATP synthase with oligomycin or citreoviridin rapidly and selectively suppresses mitochondrial protein synthesis, while mitoribosome profiling reveals a genome-wide loss of productive ribosome engagement. ATP synthase inhibition induces inner-membrane hyperpolarization, depletes bioavailable matrix ATP, and reduces matrix GTP availability. Relieving hyperpolarization restores nucleotide pools and mitochondrial translation despite persistent ATP synthase inhibition, whereas selective restoration of matrix GTP markedly rescues protein synthesis when adenine nucleotide exchange is restricted. These findings identify matrix GTP availability as a proximal energetic constraint on mitochondrial translation and reveal an organelle-intrinsic mechanism coupling ATP synthase-dependent bioenergetic state to mitoribosome activity.

cell biology↗

bioRxiv2026

Ploidy shapes gemcitabine response through altered potency and delayed cell death

Aberrant tumor ploidy is a near-universal hallmark of cancer and increasingly recognized as a determinant of therapeutic response, but the mechanisms by which ploidy shapes sensitivity to specific cytotoxic agents remain unclear. Here, we investigated the relationship between ploidy and therapeutic response using pharmacogenomic reanalysis, isogenic cancer cell systems, live-cell imaging, intracellular pharmacokinetic/ pharmacodynamic (PK/PD) measurements, and mathematical modeling. Across public pharmacogenomic datasets, gemcitabine emerged as a low-ploidy-selective cytotoxic agent. In matched isogenic low- and high-ploidy cell systems, higher-ploidy cells were consistently less sensitive to gemcitabine across multiple lineages. Live-cell imaging and PK/PD measurements in near-diploid and near-tetraploid SUM-159 cells showed that both states formed intracellular dFdCTP, active form of gemcitabine; but, high-ploidy cells exhibited weaker and slower treatment responses, with delayed accumulation of cell death. To quantify these differences, we developed a delay-aware live/dead model driven by intracellular dFdCTP exposure. The model identified both reduced effective gemcitabine potency and a substantially longer delay from intracellular drug action to observed death in high-ploidy cells (17.5 hours in near-diploid cells versus 42.5 hours in near-tetraploid cells). Interpreting these fitted quantities alongside checkpoint signaling and metabolomic profiling suggests that high-ploidy cells convert intracellular gemcitabine exposure less efficiently into replication-stress signaling, nucleotide-metabolic disruption, and cytotoxic commitment. Together, these results establish ploidy as a determinant of both the magnitude and timing of gemcitabine response and provide a quantitative framework for linking intracellular drug exposure to delayed cytotoxic outcomes across ploidy states.

cancer biology↗

bioRxiv2026

A prelimbic molecular clock of protein synthesis for memory persistence

Emotionally salient associative memories can endure for long periods, yet the mechanisms that determine their long-term stability remain unclear. Here we show that the prelimbic (PL) cortex integrates temporally structured translational programs to control both the consolidation and reconsolidation of cued threat memories. Using Pavlovian threat conditioning with in vivo fiber photometry, we found that PL calcium dynamics tightly track memory strength: discrete threat-predictive cues evoked robust activity during recent and single-timepoint remote retrieval, whereas prior retrieval selectively weakened remote expression, independent of contextual influences. Translational profiling of PL Camk2a cells uncovered a biphasic consolidation program, with an early phase characterized by ER stress-linked translational repression and robust oligodendrocyte plasticity, followed by a delayed phase engaging synaptic growth pathways. Loss- and gain-of-function approaches demonstrated that eIF2-regulated, cap-independent translation is essential for recent consolidation and for the enduring stabilization of remote memory, whereas retrieval-induced destabilization engages a mechanistically distinct, eIF4E-dependent translational pathway required for reconsolidation. These findings identify the PL cortex as a dynamic node in which discrete modes of translational control govern the long-term persistence of emotional memories.

neuroscience↗

bioRxiv2025

Tyrosine phosphorylation and the inhibitory C-terminal SAM domain moderately affect transient interactions in a EphA2 cytoplasmic fragment in solution: A combined experimental and molecular modeling study.

Eph receptors, the largest family of receptor tyrosine kinases (RTKs), orchestrate diverse developmental processes, including axon guidance, tissue patterning, and cell positioning, while also contributing to adult functions such as synaptogenesis and tissue homeostasis. Proteolytic cleavage of Eph receptors by neurodegeneration-associated proteases generates a membrane-detached intracellular region (ICR) fragment whose structural organization and signaling remain poorly understood. Here, we characterize a model for such a fragment from EphA2 and discover that the juxtamembrane region, the kinase domain, and the C-terminally linked sterile alpha motif (SAM) domain comprise a configurational ensemble of domain contacts and orientations which inhibit the intermolecular interactions and tyrosine cross-phosphorylation. Recombinant EphA2 ICR expressed in E. coli retains catalytic activity and undergoes autophosphorylation at multiple tyrosine residues which have previously been identified in eukaryotic systems. Phosphorylation weakens intramolecular interactions, as measured by microscale thermophoresis, indicating a phosphorylation-dependent remodeling of the ICR. While AlphaFold2-Multimer (AF2M) and Alphafold3 (AF3) predictions as well as available crystal structures provide only limited insight into these configurational states, coarse-grained molecular dynamics simulations using the Martini 3 force field reveal highly dynamic and predominantly transient interactions between the kinase and SAM domains that cluster at two discrete regions on the kinase surface. NMR spectroscopy of isotopically labeled EphA2 SAM suggests non-canonical intramolecular contacts that preserve the canonical SAM interaction interface for binding of partner proteins. Addition of the SHIP2 SAM domain promotes formation of the canonical EphA2 and SHIP2 SAM complex while also revealing previously unrecognized interactions of the kinase domain on the SHIP2 SAM domain. Collectively, these findings establish the EphA2 ICR as a dynamic, phosphorylation-responsive signaling module in which transient intramolecular interactions regulate accessibility of several interfaces for binding. Thus, the proteolytically released EphA2 intracellular fragment is likely to have distinct characteristics in cancer and neurodegenerative disease, compared to the membrane bound form in the full receptor.

biophysics↗

bioRxiv2025

Coupled SDE-ODE Modeling of Tumor-Immune Dynamics to Infer Biomarker Release

Tumor-immune interactions are central to cancer progression and treatment response, driving cell death through immune-mediated killing and resource-limited competition. In early-stage disease or following effective treatment, cancer populations are often small and difficult to observe directly. Disease monitoring therefore relies on the detection of biomarkers such as circulating tumor DNA (ctDNA) as noisy proxies to cancer size. However, existing approaches lack robust frameworks to infer tumor burden from these signals when populations approach detection thresholds. To address this, we present a coupled deterministic-stochastic framework that links tumor-immune dynamics to biomarker release. A two-prey, one-predator Lotka-Volterra model captures interactions between immune cells and competing tumor subpopulation under shared resource constraints. Biomarker production is modeled using a linear stochastic differential equation, incorporating ctDNA release from both apoptotic death (immune-mediated) and necrotic death (due to intra-tumor competition). We derive analytical solutions for the resulting biomarker trajectories, including mean detection time under a minimal detection threshold. These results show how volatility in measured biomarker signal, disease heterogeneity, and immune pressure jointly shape signal emergence and persistence. Finally, to model situations in which the observer has access to future information--such as the terminal biomarker signal or sampling time in retrospective studies--we adopt an anticipative theoretic perspective. Using anticipative stochastic calculus, we derive path solutions to the resulting anticipating stochastic differential equation, capturing how future observations influence the inferred biomarker dynamics. This approach links the dynamics of underlying tumor-immune interactions to the corresponding detectable biomarker levels, with implications for early detection, immune monitoring, and retrospective reconstruction of disease progression.

biophysics↗

bioRxiv2025

Single-molecule Mechanostructural Fingerprinting of Nucleic Acid Conformations

Understanding the three-dimensional structure and mechanical response of biomolecules is key to uncovering their molecular mechanisms, particularly in contexts where force plays a regulatory role. Structural methods such as X-ray crystallography, cryo-electron microscopy, and NMR spectroscopy provide high-resolution conformational data, while single-molecule force spectroscopy reveals mechanical properties--but these approaches are rarely integrated. A more comprehensive understanding of structure-function relationships, including non-equilibrium conformations and transitions under force, calls for methods capable of simultaneously resolving structural and mechanical properties at the single-molecule level. To meet this need, we present a DNA nanoswitch calipers platform capable of both measuring multiple intramolecular distances and mechanically unfolding individual biomolecules along defined axes. Using human telomeric DNA G-quadruplexes as a model system, we mapped distances between labeled sites to distinguish conformational states and performed directional unfolding to characterize mechanical stability along defined axes. This integrative approach revealed subtle conformational and mechanical differences, showcasing DNA nanoswitch calipers as a modular, broadly applicable approach for mechanostructural analysis of complex biomolecular systems.

biophysics↗

bioRxiv2025

Caspase Cleavage of Kaposi Sarcoma-Associated Herpesvirus Proteins: A role for K5 in Preventing Caspase-Mediated Cell Death during Lytic Replication

We previously reported that Kaposi sarcoma-associated herpesvirus (KSHV) latency-associated nuclear antigen (LANA) acts as a pseudo-substrate for caspases-1 and 3, thereby interfering with their inflammatory and apoptotic activity, respectively. To determine if other KSHV proteins undergo caspase cleavage, we screened the KSHV proteome for potential caspase cleavage sites. Using SitePrediction (SP), 30 KSHV proteins with potential caspase-cleavage sites were identified. Among those with highest SP score was an early lytic protein, K5. Treatment of BJAB K5-FLAG cells with Fas, an apoptotic stimulus, led to caspase-processing of full length K5-FLAG and generation of a C-terminal peptide fragment. Using mass spectrometry, we determined that K5-FLAG undergoes caspase cleavage at D222. K5 was also cleaved by caspases in KSHV infected cells induced to lytic replication. Importantly, the expression of K5-FLAG significantly inhibited Fas-induced caspase-mediated cell death. To determine if K5 plays a protective role in KSHV infected cells, iSLKK cells infected with wild type or K5 knockout BAC16 virus were induce to lytic replication to activate caspases. Although lytic induction showed little effect on the viability of WT infected cells, the viability of K5-knockout cells decreased by 25%. Thus, K5 may protect KSHV-infected cells from caspase-mediated cell death during lytic replication. Interestingly, cleavage of K5 by caspases did not affect its ability to downregulate MHC-1 surface expression. Overall, these data suggest that K5 not only downregulates immunologic surface marker expression to avoid immune recognition but may also play an additional role in mitigating caspase-mediated cell death during KSHV lytic replication.

biochemistry↗

bioRxiv2025

Nearest-neighbor nonnegative spatial factorization to study spatial and temporal transcriptomics

Nonnegative spatial factorization (NSF) is a spatially-aware factorization method that uses Gaussian processes (GPs) as spatial priors in a Poisson latent factor model to robustly identify interpretable, parts-based representations in spatial transcriptomics data. However, NSF scales poorly with modern datasets due to the computational complexity of Gaussian processes, which scales cubically with the number of points used for inference O(N 3). To address this limitation, we propose a modified version of NSF that leverages variational nearest neighbor Gaussian processes (VNNGPs), resulting in a substantial reduction in inference complexity from O(NM 2) in the current version of NSF to O(MNK2) for M inducing points, N total points and K nearest neighbors. Our method, nearest-neighbor NSF (NNNSF), is benchmarked on synthetic and real-world spatial and temporal transcriptomics datasets. Experimental results demonstrate that NNNSF achieves linear scaling with the number of neighbors and points used for inference in contrast with NSF, which has exponential computational complexity as the number of points used in inference increases. By restricting covariance calculations to the K-nearest neighbors of the points used in inference, NNNSF allows the use of more inducing points, leading to lower reconstruction loss. Nearest-neighbor NSF (NNNSF), which replaces standard variational inference with inducing points in NSF with the VNNGP, leads to a computationally efficient and scalable version of NSF that can be applied to large existing and forthcoming spatial genomics data. We added VNNGP and NNNSF to the GPZoo package, an an ongoing open source project developing a modular Gaussian process library in Python making use of the PyTorch interface. Source code and demonstrations are available at https://github.com/luisdiaz1997/GPzoo/tree/main.

bioinformatics↗

bioRxiv2024

How Modulation of the Tumor Microenvironment Drives Cancer Immune Escape Dynamics

Metastatic disease is the leading cause of cancer-related death, despite recent advances in therapeutic interventions. Prior modeling approaches have accounted for the adaptive immune systems role in combating tumors, which has led to the development of stochastic models that explain cancer immunoediting and tumor-immune co-evolution. However, cancer immunemediated dormancy, wherein the adaptive immune system maintains a micrometastatic population by keeping its growth in check, remains poorly understood. Immune-mediated dormancy can significantly delay the emergence (and therefore detection) of metastasis. An improved quantitative understanding of this process will thereby improve our ability to identify and treat cancer during the micrometastatic period. Here, we introduce a generalized stochastic model that incorporates the dynamic effects of immunomodulation within the tumor microenvironment on T cell-mediated cancer killing. This broad class of nonlinear birth-death model can account for a variety of cytotoxic T cell immunosuppressive effects, including regulatory T cells, cancer-associated fibroblasts, and myeloid-derived suppressor cells. We develop analytic expressions for the likelihood and mean time of immune escape. We also develop a method for identifying a corresponding diffusion approximation applicable to estimating population dynamics across a wide range of nonlinear birth-death processes. Lastly, we apply our model to estimate the nature and extent of immunomodulation that best explains the timing of disease recurrence in bladder and breast cancer patients. Our findings quantify the effects that stochastic tumor-immune interaction dynamics can play in the timing and likelihood of disease progression. Our analytical approximations provide a method of studying population escape in other ecological contexts involving nonlinear transition rates.

cancer biology↗

bioRxiv2024

Multivalent binding model quantifies antibody species from systems serology

Systems serology aims to broadly profile the antigen binding, Fc biophysical features, immune receptor engagement, and effector functions of antibodies. This experimental approach excels at identifying antibody functional features that are relevant to a particular disease. However, a crucial limitation of this approach is its incomplete description of what structural features of the antibodies are responsible for the observed immune receptor engagement and effector functions. Knowing these antibody features is important for both understanding how effector responses are naturally controlled through antibody Fc structure and designing antibody therapies with specific effector profiles. Here, we address this limitation by modeling the molecular interactions occurring in these assays and using this model to infer quantities of specific antibody species among the antibodies being profiled. We used several validation strategies to show that the model accurately infers antibody properties. We then applied the model to infer previously unavailable antibody fucosylation information from existing systems serology data. Using this capability, we find that COVID-19 vaccine efficacy is associated with the induction of afucosylated spike protein-targeting IgG. Our results also question an existing assumption that controllers of HIV exhibit gp120-targeting IgG that are less fucosylated than those of progressors. Additionally, we confirm that afucosylated IgG is associated with membrane-associated antigens for COVID-19 and HIV, and present new evidence indicating that this relationship is specific to the host cell membrane. Finally, we use the model to identify redundant assay measurements and subsets of information-rich measurements from which they can be inferred. In total, our modeling approach provides a quantitative framework for the reasoning typically applied in these studies, improving the ability to draw mechanistic conclusions from these data. Author summaryAntibodies play an important role in our immune response by binding to pathogens and engaging other immune cells to eliminate threats. Mounting evidence points toward the importance of which immune cells are being engaged by antibodies in determining the effectiveness of an immune response. While sophisticated experimental methods such as systems serology have been developed to broadly profile the engagement activities of antibodies, determining the presence of antibody structural features relevant to immune engagement remains challenging. Our study addresses this gap by developing a computational model that interprets data from systems serology, allowing us to infer detailed, engagement-relevant structural information about antibodies that are difficult to measure directly. We applied our approach to existing data from COVID-19 and HIV studies, revealing new insights into how antibody structure relates to vaccine efficacy and disease progression. For instance, we found that COVID-19 vaccine effectiveness is linked to the production of certain antibodies lacking a sugar residue called fucose. Our model also helps identify which measurements in systems serology are most informative, potentially streamlining future studies. This work enhances our ability to understand antibody function in disease and may guide the development of more effective antibody-based therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/602296v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@16e8b3forg.highwire.dtl.DTLVardef@77ffe3org.highwire.dtl.DTLVardef@40d0f2org.highwire.dtl.DTLVardef@155fd8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2024

Aberrant TSC-Rheb axis in Oxytocin receptor+ cells mediate stress-induced anxiety

Stress is a major risk for the onset of several maladaptive processes including pathological anxiety, a diffuse state of heightened apprehension over anticipated threats1. Pathological anxiety is prevalent in up to 59% of patients with Tuberous Sclerosis complex (TSC)2, a neurodevelopmental disorder (NDD) caused by loss-of-function mutations in genes for Tuberin (Tsc2) and/or Hamartin (Tsc1) that together comprise the eponymous protein complex. Here, we generated cell type-specific heterozygous knockout of Tsc2 in cells expressing oxytocin receptor (OTRCs) to model pathological anxiety-like behaviors observed in TSC patient population. The stress of prolonged social isolation induces a sustained negative affective state that precipitates behavioral avoidance, often by aberrant oxytocin signaling in the limbic forebrain3,4. In response to social isolation, there were striking sex differences in stress susceptibility in conditional heterozygote mice when encountering situations of approach-avoidance conflict. Socially isolated male mutants exhibited behavioral avoidance in anxiogenic environments and sought more social interaction for buffering of stress. In contrast, female mutants developed resilience during social isolation and approached anxiogenic environments, while devaluing social interaction. Systemic and medial prefrontal cortex (mPFC)-specific inhibition of downstream effector of TSC, the integrated stress response (ISR), rescued behavioral approach toward anxiogenic environments and conspecifics in male and female mutant mice respectively. Further, we found that Tsc2 deletion in OTRCs leads to OTR-signaling elicited network suppression, i.e., hypofrontality, in male mPFC, which is relieved by inhibiting the ISR. Our findings present evidence in support of a sexually dimorphic role of prefrontal OTRCs in regulating emotional responses in anxiogenic environments, which goes awry in TSC. Our work has broader implications for developing effective treatments for subtypes of anxiety disorders that are characterized by cell-autonomous ISR and prefrontal network suppression.

neuroscience↗

bioRxiv2023

The SAM Domain of EphA2 Inhibits Ligand-Independent Clustering and Activation

Eph receptors are the largest family of receptor tyrosine kinases (RTKs). They play a role in the pathogenesis of various diseases including cancer, atherosclerosis, fibrosis, infectious diseases, diseases of the central nervous system and age-related cataract. EphA2 has attracted much attention over the years owing to its dysregulation in many diseases. Previous studies have revealed the unique molecular organizations of Eph receptors, and particularly EphA2, into large clusters of receptor-ligand complexes. One unique feature of Eph receptors is a C-terminal sterile alpha motif (SAM) domain, which has been proposed to alter dimerization and kinase activity in EphA2. However, the precise role of the SAM domain in regulating the function and oligomerization state of EphA2 has not been reported. Here we apply a time-resolve fluorescence spectroscopy, PIE-FCCS, to characterize the oligomerization state of EphA2 in live cells and determine the role of the SAM domain. We deleted the SAM domain in the context of full length EphA2 and an intracellular domain (ICD) construct to assess the effect of the SAM domain on oligomerization state, kinase activity, and cellular behavior. Overall, we find that the SAM domain inhibits ligand-independent clustering and kinase activity in both full-length EphA2 and the isolated ICD construct at the cell membrane. These results are consistent with the autoinhibitory features of the C-terminal tail of EGFR and may help resolve the allosteric regulation of other RTKs.

biophysics↗

bioRxiv2023

Opto4E-BP, an optogenetic tool for inducible, reversible, and cell type-specific inhibition of translation initiation

The protein kinase mechanistic target of rapamycin complex 1 (mTORC1) is one of the primary triggers for initiating cap-dependent translation. Amongst its functions, mTORC1 phosphorylates eIF4E-binding proteins (4E-BPs), which prevents them from binding to eIF4E and thereby enables translation initiation. mTORC1 signaling is required for multiple forms of protein synthesis-dependent synaptic plasticity and various forms of long-term memory (LTM), including associative threat memory. However, the approaches used thus far to target mTORC1 and its effectors, such as pharmacological inhibitors or genetic knockouts, lack fine spatial and temporal control. The development of a conditional and inducible eIF4E knockdown mouse line partially solved the issue of spatial control, but still lacked optimal temporal control to study memory consolidation. Here, we have designed a novel optogenetic tool (Opto4E-BP) for cell type-specific, light-dependent regulation of eIF4E in the brain. We show that light-activation of Opto4E-BP decreases protein synthesis in HEK cells and primary mouse neurons. In situ, light-activation of Opto4E-BP in excitatory neurons decreased protein synthesis in acute amygdala slices. Finally, light activation of Opto4E-BP in principal excitatory neurons in the lateral amygdala (LA) of mice after training blocked the consolidation of LTM. The development of this novel optogenetic tool to modulate eIF4E-dependent translation with spatiotemporal precision will permit future studies to unravel the complex relationship between protein synthesis and the consolidation of LTM.

neuroscience↗

bioRxiv2023

Mapping Single-molecule Protein Complexes in 3D with DNA Nanoswitch Calipers

The ability to accurately map the 3D geometry of single-molecule complexes in trace samples would lead to new insights into molecular mechanics and provide an approach for single-molecule structural proteomics. To enable this, we have developed a high-resolution force-spectroscopy method capable of measuring multiple distances between labeled sites in natively folded protein complexes. Our approach combines reconfigurable nanoscale devices we call DNA Nanoswitch Calipers, which we have previously introduced, with a force-based barcoding system to distinguish each measurement location. We demonstrate our approach by reconstructing the tetrahedral geometry of biotin-binding sites in natively folded streptavidin, with 1.5-2.5[A] agreement to previously reported structures.

biophysics↗