Biology subjects

Sinha, P.

Publications and source records attributed to Sinha, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Serum nutritional-metabolic recovery during tuberculosis treatment across BMI-defined undernutrition strata: A longitudinal proteomic reanalysis

Background Tuberculosis remains the leading cause of death from a single infectious agent, and undernutrition is a major modifiable risk factor. Serum proteomics can capture systemic host recovery during therapy, but whether baseline BMI-defined undernutrition alters this trajectory is unclear. Methods We reanalysed processed longitudinal tandem-mass-tag serum proteomics from 30 adults with pulmonary tuberculosis and durable cure sampled at baseline and weeks 8, 17, 26 and 52. Thirteen participants had baseline BMI <18.5 kg/m2 and 17 had BMI >=18.5 kg/m2. Protein-level analyses evaluated baseline differences and week-specific within-participant change; module and recovery-axis models evaluated BMI-by-time interactions, with random-intercept mixed models added as a repeated-measures sensitivity analysis. Three complementary treatment-responsive modules were integrated into an exploratory, nonredundant 36-protein nutritional-metabolic summary axis. Results The reconstructed dataset contained 1,923 quantified features across 150 participant-visits. Inflammatory/acute-phase and metal-handling/nutritional-immunity module scores declined during follow-up, whereas lipid/apolipoprotein-transport, nutritional-carrier and endocrine-immunometabolic scores increased. In the primary week-specific paired-change analyses, no protein-level between-BMI difference in longitudinal change survived false-discovery-rate correction; no curated-module BMI-by-time interaction survived correction. The 36-protein summary axis increased in both BMI strata from week 17 onward. In a random-intercept model without interaction, the BMI <18.5 kg/m2 stratum had a lower average axis score across visits than the BMI >=18.5 kg/m2 comparison stratum, although the confidence interval included zero (difference -1.34, 95% CI -2.76 to 0.08; p = .064). Categorical and continuous BMI-by-time interaction tests did not detect differential axis trajectories. Conclusions Tuberculosis treatment was accompanied by broad longitudinal remodelling of circulating inflammatory and nutritional-metabolic protein systems. An exploratory 36-protein summary axis increased in both baseline BMI strata, while formal interaction tests did not detect BMI-dependent trajectories and remained too imprecise to establish equivalence. BMI should be regarded as an anthropometric proxy rather than a comprehensive measure of nutritional state. The defined axis provides a framework for prospective validation alongside direct measures of body composition, micronutrients, treatment exposure and clinical outcomes.

bioinformatics↗

bioRxiv2026

Distinct transcriptional remodeling of immune and metabolic pathways in severe undernutrition during latent tuberculosis infection does not consistently predict tuberculosis progression across independent cohorts

Background: Undernutrition increases tuberculosis (TB) risk, but whether severe undernutrition during latent TB infection (LTBI) produces blood transcriptional changes that resemble active disease or identify future TB remains unclear. Methods: We reanalyzed whole-blood RNA sequencing from adults with LTBI in GSE152218, comparing severe undernutrition (BMI <16 kg/m2; n=16) with adequate nutrition (BMI >=18.5 kg/m2; n=11). Genes and Reactome pathways were evaluated. A seven-module summary was compared with active TB among severely undernourished adults and tested prospectively in GSE79362 and GC6-74/GSE94438 after pathway-representation assessment. Results: No genes reached FDR <0.05 in the primary model; two did only in sensitivity analysis. In contrast, 241 Reactome pathways were significant and directionally concordant in both models (NES rho=0.954), including complement/Fc-receptor, B-cell, phospholipid/phagocytosis, neutrophil, vascular, autophagy, and cytokine-signaling pathways. Most changed opposite to the active-TB comparison (178/241; pathway rho=-0.390). The seven-module score was unrelated to baseline progression in GSE79362 (adjusted OR per SD=1.090; P=0.6922). In GC6, four modules met the prespecified representation criterion; their baseline score was inversely associated with progression (adjusted OR per SD=0.711; P=0.0218), but secondary and longitudinal analyses were non-confirmatory. Conclusions: Severe undernutrition during LTBI is associated with reproducible immune- and metabolism-related transcriptional remodeling that differs from active-TB biology and does not consistently identify future TB progression.

molecular biology↗

bioRxiv2026

Self-Exciting Population Event Models Reveal Abnormal Temporal Amplification in MAPT-Mutant Human Brain Assembloids

Human brain assembloids provide a tractable platform for studying mutation-specific network dysfunction, but most studies do not distinguish whether abnormal activity arises from increased spontaneous initiation or stronger history-dependent amplification. We introduce a low-dimensional discrete-time self-exciting population model for calcium-imaging event sequences that separates baseline initiation (%[mu]), integrated history-dependent gain (%[eta]), and memory decay (%[tau]). Across 175 recordings from 13 MAPT p.R406W or CRISPR-corrected isogenic assembloids, biological-unit inference identified a 4.31-fold increase in %[eta] in mutants (95% CI 3.20- 5.84; exact p=7.8x10-4), without increased baseline activity. Parametric predictive checks exposed residual Poisson overdispersion; fixed-decay and beta-binomial sensitivity analyses nevertheless preserved the mutant history effect. Median %[eta] separated all 13 held-out assembloids, while a multifeature recording-level RBF-SVM achieved AUC 0.816 under nested whole-assembloid holdout. These results identify robust history-dependent temporal amplification as a functional MAPT-mutant network phenotype.

neuroscience↗

bioRxiv2026

Phytometabolite-Enriched Edible Plant-Derived Extracellular Vesicles Exhibit Source-Specific Bioactives with Distinct Pharmacological Potential

Edible plant derived extracellular vesicles (PDEVs) are emerging as biocompatible, orally deliverable nanocarriers with therapeutic potential; however, their phytometabolite cargo, gastrointestinal stability, and source specific biological functions remain poorly characterized. Here, PDEVs were isolated from four phytochemically distinct plant based foods (black carrot, ginger, garlic, and turmeric), selected for their diverse bioactivity, and characterized by transmission electron microscopy, nanoparticle tracking analysis, and zeta potential. Gastrointestinal stability was evaluated in simulated digestion model. Source specific phytometabolites were profiled by untargeted LC MS MS metabolomics. Functionally validated in ammonia stressed epithelial cells and steatotic hepatocytes. PDEVs exhibited characteristic cup shaped morphology with particle sizes ranging from 60 to 214 nm and zeta potentials of -6.0 to -49.0 mV. PDEVs retained colloidal stability, supporting their suitability for oral delivery. We identified 572 phytometabolites with distinct source specific signatures, including lignin and quercetin in carrot EVs, [6] gingerol and silymarin in ginger EVs, diosgenin in garlic EVs, and curcumin in turmeric EVs. These metabolites found associated to antioxidant, anti inflammatory, epithelial barrier, lipid metabolic, and apoptotic pathways. Functional validation demonstrated carrot EVs significantly enhanced epithelial barrier integrity by increasing claudin (>8-fold, p<0.05), occludin (>2-fold, p<0.05). Ginger EVs restored ZO 1 while suppressing cyclin D1 and MMP9(p<0.05). Garlic and turmeric EVs attenuated inflammatory signaling by reducing STAT3, AKT1, and TNF , whereas turmeric EVs additionally decreased caspase 3 and PTGS2(p<0.01). In steatotic hepatocytes, garlic EVs significantly reduced PNPLA3 (p<0.001) and SREBP 1c while increasing PPAR- (p=0.002). Hence, our results indicate that edible PDEVs are gastrointestinally stable, phytometabolite enriched nanocarriers with distinct source specific functional properties, supporting their potential as orally deliverable nutraceuticals for improving gut liver functions.

pharmacology and toxicology↗

bioRxiv2026

Gene regulatory co-expression networks decipher potential lncRNA-miRNA-mRNA interactions modulating transcription regulation in neurodegeneration

Neurodegenerative diseases are complex disorders characterised by progressive neuronal loss and widespread transcriptomic dysregulation; however, the coordinated interactions among coding and non-coding RNAs that contribute to disease progression remain incompletely understood. In this study, RNA-seq datasets from disease-relevant neuronal populations and brain regions representing Alzheimers disease (AD), Parkinsons disease (PD) and amyotrophic lateral sclerosis (ALS) were analysed using an integrative network-based framework. Differential expression analysis coupled with weighted gene co-expression network analysis identified modules significantly correlated with disease and prioritised highly connected hub genes. Integration of these hub genes with curated RNA interaction database enabled the construction of candidate lncRNA-miRNA-mRNA regulatory networks. Functional enrichment analysis revealed Gene Ontology biological processes associated with synaptic signalling, mitochondrial function, RNA metabolism and neuroinflammatory responses across neurodegenerative conditions. The inferred regulatory networks suggested both disease-specific and shared post-transcriptional regulatory modules involving key hub genes and non-coding RNAs. Additionally, putative sequence variants were identified within untranslated regions of selected hub genes, suggesting potential alterations in miRNA-mediated regulations. Therefore, this study provides a systems-level view of transcriptomic dysregulation across major neurodegenerative diseases and identifies candidate regulatory interactions and molecular targets for future functional investigation.

bioinformatics↗

bioRxiv2026

Time-Resolved Neuronal Network Dynamics Distinguish Pathological States in Organoid Models

Human brain assembloids offer a powerful platform for modeling neurological diseases, yet comprehensive methods for analyzing their complex network dynamics are lacking. Here, we developed a time-resolved network analysis pipeline that extracts quantitative biomarkers from two-photon calcium imaging, enabling the detection of subtle differences between disease and control models. We applied this pipeline to assembloids containing a pathogenic MAPT p.R406W variant--clinically associated with an Alzheimers disease-like phenotype--and their isogenic controls. Our analysis revealed that mutant networks exhibit significantly increased degree variance and clustering. This indicates a "hub-like", interconnected topology prone to hypersynchrony, a finding that parallels the network hyperexcitability and seizure-like features observed in in-vivo models of Alzheimers disease. Furthermore, a Random Forest classifier trained on these dynamic network features distinguished between diseased and control states with high accuracy (F1 score = 0.90). These results establish that dynamic network properties can serve as potent biomarkers for identifying pathological states in assembloid models, providing a quantitative framework to investigate disease mechanisms and potential therapeutic interventions.

neuroscience↗

bioRxiv2026

Dynamic Antigen Expression and Intrinsic CTL Resistance in HIV Reservoir Clones

Reservoirs of clonally expanded CD4+ T-cells harboring rebound-competent HIV proviruses persist lifelong during ART. Latency is considered the principal barrier to viral eradication and has resisted pharmacological reversal, yet it appears that sustained immune pressure may still erode reservoirs. Recent advances have yielded glimpses into these exceptionally rare reservoir-harboring cells, implicating intrinsic pro-survival properties in their persistence. Here, we isolate and characterize populations of authentic reservoir clones (ARCs) that robustly proliferate and accumulate while producing infectious virus, without overtly succumbing to viral cytopathic effects. At any given moment, only small fractions of ARCs expressed HIV proteins, a state remarkably unperturbed by potent TCR or mitogenic stimulation. Nevertheless, sustained co-culture with cytotoxic T-lymphocytes (CTL) revealed extensive time-integrated antigenic vulnerability, culling clonal expansion of some ARCs by >90%. Notably, a regulatory T-cell ARC displayed pronounced cell-intrinsic resistance to CTL - a longstanding hypothesis we now directly demonstrate - linked to low oxidative stress and reversed with desferoxamine, a hypoxic stress inducer and FDA-approved therapeutic. Overall, we provide novel insights into the vulnerabilities of reservoir clones to potent, sustained CTL pressure and highlight intrinsic resistance pathways as actionable therapeutic targets, opening opportunities for advancing immune-based HIV cure strategies.

immunology↗

bioRxiv2025

HIV Nef amplifies mechanical heterogeneity to promote immune evasion

Intracellular pathogens must evade cytotoxic immunity to establish persistent infection. Although immune escape is typically viewed through a biochemical lens, the ability of certain pathogens to alter the mechanical properties of infected cells suggests that biophysical mechanisms may also contribute to the process. Here, we show that a subset of CD4+ T cells infected with the human immunodeficiency virus (HIV) resist elimination through a soft phenotype that inhibits killing by mechanosensitive cytotoxic T lymphocytes (CTLs). This phenotype arises from the combined effects of the HIV virulence factor Nef, which remodels the actin cytoskeleton, and intrinsic heterogeneity in the basal cytoskeletal properties of infected T cells. Pharmacological or genetic perturbations that reverse Nef signaling to the cytoskeleton or that stiffen the filamentous-actin cortex sensitize infected cells to CTL-mediated lysis. Taken together, these findings define a novel, biophysical paradigm of immune evasion with implications for HIV cure strategies.

immunology↗

bioRxiv2025

DR5 CAR-T cells target solid tumors and suppress MDSCs with minimal toxicity

Chimeric antigen receptor (CAR) T cell therapies have poor efficacy in solid tumors due to limited target specificity and an immunosuppressive tumor microenvironment. We investigated death receptor 5 (DR5) as a CAR target based on its high expression in both solid tumors and myeloid- derived suppressor cells (MDSCs). We engineered agonistic DR5-specific CAR constructs and evaluated their activity in multiple models, demonstrating DR5-expression-dependent tumor killing, confirmed by knockout and overexpression experiments. DR5-targeting single-chain variable fragments retained their pro-apoptotic activity when expressed on non-effector cells or extracellular vesicles. Among multiple CAR designs, we identified a construct with optimized binding affinity that maintained T cell viability while preserving strong tumor and MDSC-killing potency. To assess safety and efficacy in an immunocompetent setting, we also developed a murine DR5-targeted CAR. In multiple xenograft and syngeneic mouse models, DR5 CAR-T cells reduced tumor growth, prolonged survival, and did not cause detectable toxicity. In patient- derived organoids and tissue slices, DR5 CAR-T cells infiltrated tumor tissues, reduced MDSCs, boosted CD8+ T cell activity, and inhibited tumor growth. These findings support DR5-targeted CAR-T therapy as a promising strategy for treating solid tumors, which combines direct tumor cytotoxicity with immune activation and minimizes off-target effects. TeaserDR5 CAR-T cells eliminate tumor cells and MDSCs and activate tumor-resident CD8+ T cells within the TME.

cancer biology↗

bioRxiv2025

Epstein-Barr virus and Helicobacter pylori Coinfection Drives Gut and Brain Barrier Dysfunction

Biological barriers, including blood-brain barrier (BBB) and gut epithelial barrier, are essential to maintain homeostasis and provide protection against pathogenic stress. Here, we investigated the impact of Helicobacter pylori-Epstein Barr Virus coinfection on gut-brain axis integrity. Our results demonstrate that coinfection induces significant disruptions in tight and adherens junction (TJ and AJ respectively) proteins in gastric epithelial cells, including downregulation of ZO-1 and E-cadherin. The secretome from these coinfected cells significantly compromises the integrity of BBB-derived endothelial cells, including cleavage of VE-cadherin, loss of TJ proteins such as Claudin-5, and enhanced permeability. Furthermore, the sole exposure of mice to coinfected secretome lead to the loss of cerebral VE-cadherin and ZO-1 and the induction of neuroinflammation, characterized by elevated pro-inflammatory cytokines, TNF-, amyloidogenic accumulation, and neurocognitive deficits. The secretome driving such forces potentially carries pathogenic metabolites, host inflammatory cytokines and metabolites that might contribute to disease pathogenesis as observed in this study. Together, our current study provides novel insights into how coinfections contribute to gut-brain axis dysregulation and neurological pathogenesis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/655045v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@138ca23org.highwire.dtl.DTLVardef@15eccc4org.highwire.dtl.DTLVardef@d588c6org.highwire.dtl.DTLVardef@106a485_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

microbiology↗

bioRxiv2025

Future flooding tolerant rice germplasm: resilience afforded beyond Sub1A gene

Developing high-yielding, flood-tolerant rice varieties is essential for enhancing productivity and livelihoods in flood-prone ecologies. We explored genetic avenues beyond the well-known SUB1A gene to improve flood resilience in rice. We screened a collection of 6,274 elite genotypes from IRRIs germplasm repository for submergence and stagnant flooding tolerance over multiple seasons and years. This rigorous screening identified 89 outstanding elite genotypes, among which thirty-seven exhibited high submergence tolerance, surpassing the survival rate of SUB1A introgression genotypes by 40-50%. Thirty-five genotypes showed significant tolerance to stagnant flooding, and 17 demonstrated dual tolerance capabilities, highlighting their adaptability to varying flood conditions. The genotypes identified have a broader genetic diversity and harbor 86 key QTLs and genes related to traits such as grain quality, grain yield, herbicide resistance, and various biotic and abiotic traits, highlighting the richness of the identified elite collection. Besides germplasm, we introduce an innovative breeding approach called Transition from Trait to Environment (TTE). TTE leverages a parental pool of high-performing genotypes with complete submergence tolerance to drive population improvement and enable genomic selection in the flood breeding program. Our approach of TTE achieved a remarkable 65% increase in genetic gain for submergence tolerance, with the resulting fixed breeding genotypes demonstrating exceptional performance in flood-prone environments of India and Bangladesh. The elite genotypes identified herein represent invaluable genetic resources for the global rice research community. By adopting the TTE approach, which is trait agonistic, we establish a robust framework for developing more resilient genotypes using advanced breeding tools. Plain Language SummaryTo address climate challenges, an urgent focus is necessary to identify and develop flood-tolerant rice varieties, particularly for flood-prone ecosystems across Asia and Africa. We screened 6,274 elite genotypes from IRRIs germplasm and identified 89 promising lines with improved tolerance to submergence and stagnant flooding. Among these, 37 demonstrated 40-50% greater submergence tolerance than SUB1A introgression lines, 35 exhibited stagnant flooding tolerance, and 17 showed dual tolerance. These genotypes contain 86 key QTLs and genes associated with yield, grain quality, and biotic and abiotic tolerance traits. A new breeding strategy, the Transition from Trait to Environment (TTE) approach, was developed. We achieved a genetic gain of 65% for submergence tolerance in rice using this method. The newly identified germplasm provides invaluable genetic resources for the global rice research community to develop flood-tolerant rice genotypes. Core ideas The SUB1A gene, enabling rice to survive underwater for 14 days, marked a significant breakthrough. We have identified elite genotypes with submergence tolerance significantly surpassing the SUB1A gene-mediated tolerance. The diverse elite genotypes identified harbor 86 key genes and QTLs that affect various traits positively. Developed a unique breeding strategy for implementing population improvement in challenging environments. The new breeding strategy demonstrated a genetic gain of 65% for submergence tolerance.

plant biology↗

bioRxiv2024

Gray matter abnormalities in sight deprivation and sight restoration

Blindness provides a unique model for investigating brain plasticity in response to sensory deprivation. While structural changes in both gray and white matter have been widely documented, particularly in cases of early or congenital visual deprivation, gray matter studies have traditionally focused on cortical thickness, often finding cortical thickening in posterior regions. However, other aspects of gray matter integrity, such as cortical myelin content, remain underexplored. In this study, we examined the effects of visual deprivation on cortical structure in a cohort of congenitally blind individuals who received eye surgery during adolescence, expanding beyond conventional measures to include cortical thickness, curvature, and T1-weighted signal intensity. This multi-faceted approach offers a more comprehensive view of cortical adaptations to congenital sensory deprivation. While blindness offers valuable insights into sensory-driven brain plasticity, an intriguing and unresolved question is whether structural plasticity reverses after sight restoration, enabling typical visual processing circuits to develop despite the initial period of deprivation. To address this, we assessed the effect of sight-recovering eye surgery on gray matter changes. Critically, individuals in this cohort received surgery after the closure of the sensitive period for visual development. We did not find evidence of gray matter changes after surgery. However, in a previous study conducted on the same cohort, we reported that notable plasticity in white matter emerged in this same population. These results suggest that white matter alterations, rather than gray matter changes, may potentially serve as a biomarker of structural plasticity following sight restoration, even beyond the sensitive developmental window.

neuroscience↗

bioRxiv2024

Connecting Transcriptomics with Computational Modeling to Reveal Developmental Adaptations in the Human Pediatric Myocardium

BackgroundNearly 1% or 1.3 million babies are born with congenital heart disease (CHD) globally each year - many of whom will require palliative or corrective heart surgery within the first few years of life. A detailed understanding of cardiac maturation can help to expand our knowledge on cardiac diseases that develop during gestation, identify age-appropriate cardiovascular drug therapies, and inform clinical care decisions related to surgical repair, myocardial preservation, or postoperative management. Yet, to date, our knowledge of the temporal changes that cardiomyocytes undergo during postnatal development is largely limited to animal models. MethodsRight atrial tissue samples were collected from n=117 neonatal, infant, and pediatric patients undergoing correct surgery due to (acyanotic) CHD. Patients were stratified into five age groups: neonate (0-30 days), infant (31-364 days), toddler to preschool (1-5 years), school age (6-11 years), and adolescent to young adults (12-32 years). We measured age-dependent adaptations in cardiac gene expression, and used computational modeling to simulate action potential and calcium transients. ResultsEnrichment of differentially expressed genes (DEG) was explored, revealing age-dependent changes in several key biological processes (cell cycle, cell division, mitosis), cardiac ion channels, and calcium handling genes. Gene-associated changes in ionic currents exhibited both linear trends and sudden shifts across developmental stages, with changes in calcium handling (INCX) and repolarization (IK1) most strongly associated with an age-dependent decrease in the action potential plateau potential and increase in triangulation, respectively. We also note a shift in repolarization reserve, with lower IKr expression in younger patients, a finding likely tied to the increased amplitude of IKs triggered by elevated sympathetic activation in pediatric patients. ConclusionThis study provides valuable insights into age-dependent changes in human cardiac gene expression and electrophysiology among patients with CHD, shedding light on molecular mechanisms underlying cardiac development and function across different developmental stages.

cell biology↗

bioRxiv2023

Analysis of the Cross-Study Replicability of Tuberculosis Gene Signatures Using 49 Curated Transcriptomic Datasets

BackgroundTuberculosis (TB) is the leading cause of infectious disease mortality worldwide. Numerous blood-based gene expression signatures have been proposed in the literature as alternative tools for diagnosing TB infection. Ongoing efforts are actively focused on developing additional signatures in other TB-related contexts. However, the generalizability of these signatures to different patient contexts is not well-characterized. There is a pressing need for a well-curated database of TB gene expression studies for the systematic assessment of existing and newly developed TB gene signatures. ResultsWe built the curatedTBData, a manually-curated database of 49 TB transcriptomic studies. This data resource is freely available through GitHub and as an R Bioconductor package that allows users to validate new and existing biomarkers without the challenges of harmonizing heterogeneous studies. We also demonstrate the use of this data resource with cross-study comparisons for 72 TB gene signatures. For the comparison of subjects with active TB from healthy controls, 19 gene signatures had weighted mean AUC of 0.90 or greater, with the highest result of 0.94. In active TB disease versus latent TB infection, 7 gene signatures had weighted mean AUC of 0.90 or greater, with a maximum of 0.93. We also explore ensembling methods for averaging predictions from multiple gene signatures to significantly improve diagnostic ability beyond any single signature. ConclusionsThe curatedTBData data package offers a comprehensive resource of curated gene expression and clinically annotated data. It could be used to identify robust new TB gene signatures, to perform comparative analysis of existing TB gene signatures, and to develop alternative gene set scoring or ensembling methods, among other things. This resource will also facilitate the development of new signatures that are generalizable across cohorts or more applicable to specific subsets of patients (e.g. with rare comorbid conditions, etc.). We demonstrated that these blood-based gene signatures could distinguish patients with distinct TB outcomes; moreover, the combination of multiple gene signatures could improve the overall predictive accuracy in differentiating these subtypes, which point out an important aspect for the translation of genomics to clinical implementation.

genomics↗

bioRxiv2023

Distance v.s. Resolution: Neuromapping of Effective Resolution onto Physical Distance

The main focus of this work is on determining the effective resolution of a face image on the retina when the face is at a particular distance from the eye. Despite its straightforward articulation, arriving at a satisfactory solution might be unexpectedly challenging. The relationship between viewing distance and effective resolution cannot be easily obtained through Snellen acuity, contrast sensitivity, photoreceptor packing density or ganglion cell convergence rate in the retina. We used theoretical modelling to establish preliminary guidelines and then tested them empirically. We showed participants a 2 x 2 array of images in different resolutions at various viewing distances. At each distance, participants were expected to perform an "odd one out" task, identifying the image that was blurrier than the other three. As the study progressed, viewing distance was gradually reduced. The data collected enabled us to determine the upper and lower limits of the available effective resolution for human vision under normal conditions, as a function of viewing distance. Notably, human performance in blur detection is superior to what a theoretical model based on projected image size, cone density, and foveal extent predicts, especially at close ranges. Therefore, we propose that future theoretical models must account for non-uniform in-fovea density and the less pronounced decline in acuity outside the fovea to establish a reliable relationship between viewing distance and perceived image characteristics. The mapping allows for a direct comparison of human face recognition performance across different levels of blur and viewing distance. It also enables us to systematically compare human performance to that of machine vision systems using resolution as a common factor.

neuroscience↗

bioRxiv2023

DeepMap: A deep learning-based model with four-line code for prediction-based breeding in crops

Prediction of phenotype through genotyping data using the emerging machine or deep learning technology has been proven successful in genomic prediction. We present here a graphical processing unit (GPU) enabled DeepMap configurable deep learning-based python package for the genomic prediction of quantitative phenotype traits. We found that deep learning captures non-linear patterns more efficiently than conventional statistical methods. Furthermore, we suggest an additional module inclusion of epistasis interactions and training of the model on Graphical Processing Units (GPUs) in addition to Central Processing Unit (CPU) to enhance efficiency and increase the models performance. We developed and demonstrated the application of DeepMap using a 3K rice genome panel and 1K-Rice Custom Amplicon (1kRiCA) data for several phenotypic traits including days to 50% flowering (DTF), number of productive tillers (NPT), panicle length (PL), plant height (PH), and plot yield (PY). We have found that DeepMap outperformed the best existing state-of-the-art models by giving higher predictive correlation and low mean squared error for the datasets studied. This prediction performance was higher than other compared models in the range of 13-31%. Similarly for Dataset-2, significantly higher predictions were observed than the compared models (16-20% higher prediction ability). On Dataset-3, we have also shown the better and versatile performance of our model across crops (wheat, maize, and soybean) for yield and yield-related traits. This demonstrates the potentiality of the framework and ease of use for future research in crop improvement. The DeepMap is accessible at https://test.pypi.org/project/DeepMap-1.0/. Short SummaryDeepMap is a deep learning-based breeder-friendly python package to perform genomic prediction. It utilizes epistatic interactions for data augmentation and outperforms the existing state-of-the-art machine/deep learning models such as Bayesian LASSO, GBLUP, DeepGS, and dualCNN. DeepMap developed for rice and tested across crops such as maize, wheat, soybean etc.

genomics↗

bioRxiv2023

Identification of PS1/gamma-secretase and glutamate transporter GLT-1 interaction sites

The recently discovered interaction between Presenilin 1 (PS1), a catalytic subunit of {gamma}-secretase responsible for generating amyloid-{beta} (A{beta}) peptides, and GLT-1, a major glutamate transporter in the brain (EAAT2) provides a mechanistic link between these two key factors involved in Alzheimers disease (AD) pathology. Modulating this interaction can be crucial to understand the consequence of such crosstalk in AD context and beyond. However, the interaction sites between these two proteins are unknown. Herein, we utilized an alanine scanning approach coupled with FRET-based fluorescence lifetime imaging microscopy (FLIM) to identify the interaction sites between PS1 and GLT-1 in their native environment within intact cells. We found that GLT-1 residues at position 276 to 279 (TM5) and PS1 residues at position 249 to 252 (TM6) are crucial for GLT-1/PS1 interaction. These results have been cross validated using AlphaFold Multimer prediction. To further investigate whether this interaction of endogenously expressed GLT-1 and PS1 can be prevented in primary neurons, we designed PS1/GLT-1 cell-permeable peptides (CPPs) targeting the PS1 or GLT-1 binding site. We used HIV TAT domain to allow for cell penetration which was assayed in neurons. First, we assessed the toxicity and penetration of CPPs by confocal microscopy. Next, to ensure the efficiency of CPPs, we monitored the modulation of GLT-1/PS1 interaction in intact neurons by FLIM. We saw significantly less interaction between PS1 and GLT-1 with both CPPs. Our study establishes a new tool to study the functional aspect of GLT-1/PS1 interaction and its relevance in normal physiology and AD models.

biochemistry↗

bioRxiv2022

Dynein functions in galectin-3 mediated processes of clathrin-independent endocytosis

Multiple endocytic processes operate in cells in tandem for the uptake of multiple cargoes, metabolites, and signaling molecules that are involved in diverse cellular functions including cell adhesion and migration. The best studied endocytic process involves the formation of a well-defined cytoplasmic coat at sites of uptake made of clathrin and its interacting partners. Galectin-3 (Gal3), an endogenous lectin, binds to glycosylated membrane receptors and glycosphingolipids (GSLs) to drive membrane bending, leading to the formation of tubular membrane invaginations which undergo scission to form a morphologically distinct class of uptake structures, termed clathrin-independent carriers (CLICs). This mechanism has been termed the GlycoLipid-Lectin (GL-Lect) hypothesis. Which components from cytoskeletal machinery are involved in the scission of CLICs remains yet to be explored. In this study, we propose that dynein, a retrograde motor protein, is recruited onto Gal3-induced tubular endocytic pits and provides the pulling force to for friction driven scission. Uptake of Gal3 and its cargoes (CD98/CD147) is significantly dependent on dynein activity, whereas the uptake of transferrin (a marker for clathrin-mediated endocytosis) is only slightly affected upon dynein inhibition. Dynein inhibition also affects cellular organelle distribution, 3D cell invasion and wound healing. Our study thereby reveals functions of dynein in individual and collective cell migration in 2D and 3D that are tightly coupled to endocytic processes in cells.

cell biology↗