Biology subjects

Paul, S.

Publications and source records attributed to Paul, S..

At least 145 records · Page 8Linked to original sources

bioRxiv2021

Aspergillus fumigatus ffmA encodes a C2H2-containing transcriptional regulator that modulates azole resistance and is required for normal growth

The production of a collection of disruption mutant strains corresponding to a large number of transcription factors from the filamentous fungal pathogen Aspergillus fumigatus has permitted rapid identification of transcriptional regulators involved in a range of different processes. Here we characterize a gene designated ffmA (favors fermentative metabolism) as an C2H2-containing transcription factor that is required for azole drug resistance and normal growth. Loss of ffmA caused cells to exhibit significant defects in growth, either under untreated or azole-challenged conditions. Loss of FfmA caused a reduction in expression of the AbcG1 ATP-binding cassette transporter, previousy shown to contribute to azole resistance. Strikingly, overproduction of the AtrR transcription factor gene restored a wild-type growth phenotype to a ffmA{Delta} strain. Overexpression of AtrR also suppressed the defect in AbcG1 expression caused by loss of FfmA. Replacement of the ffmA promoter with a doxycycline-repressible promoter restored near normal growth in the absence of doxycycline. Finally, chromatin immunoprecipitation experiments indicated that FfmA bound to its own promoter as well as to the abcG1 promoter. These data imply that FfmA and AtrR interact both with respect to abcG1 expression and also more broadly to regulate hyphal growth. ImportanceInfections associated with azole-resistant forms of the primary human pathogen, Aspergillus fumigatus, are associated with poor outcomes in patient populations. This makes analysis of the mechanisms underlying azole resistance of A. fumigatus a high priority. In this work, we describe characterization of a gene designated ffmA that encodes a sequence-specific transcriptional regulator. We identified ffmA in a screen of a collection of gene disruption mutant strains made in A. fumigatus. Loss of ffmA caused sensitivity to azole drugs and also a large reduction in normal growth. We found that overproduction of the AtrR transcription factor was able to restore growth to ffmA null cells. We provide evidence that FfmA can recognize promoters of genes involved in azole resistance as well as the ffmA promoter itself. Our data indicate that FfmA and AtrR interact to support azole resistance and normal growth.

microbiology↗

bioRxiv2021

CDK5 mediated phosphorylation of cytosolic phospholipase A2 regulates its activity and neuroinflammation in Parkinsons Disease

Hyperactivation of cyclin-dependent kinase 5 (CDK5) by p25, contributes to neuroinflammation causing neurodegeneration in Parkinsons Disease (PD) and Alzheimer diseases (AD). However, the mechanism by which CDK5 induces neuroinflammation in the PD brain is largely unexplored. Here, we show that CDK5 phosphorylates cytosolic phospholipase A2 (cPLA2) at Thr-268 and Ser-505 sites lead to its activation and generation of eicosanoid products. Mutational studies using site-directed mutagenesis and molecular simulations show that the architecture of the protein changes upon each single-point mutation. Interestingly, double-mutations also led to severe decline in the activity of cPLA2 and disruption of its translocation to the plasma membrane. Further, the brain lysates of transgenic PD mouse models show hyperactivation of CDK5 resulting in enhanced phosphorylation of Thr-268 and Ser-505 of cPLA2 and its heightened activity confirming the findings observed in the cell culture model of PD. These phosphorylation sites of cPLA2 and CDK5 could be explored as the future therapeutic targets against neuroinflammation in PD. Further, conjoint transcriptomic analysis of the publicly available human PD datasets strengthens the hypothesis that genes of the arachidonic acid, prostaglandin synthesis and inflammatory pathways are significantly upregulated in case of the PD patients as compared to that of healthy controls.

neuroscience↗

bioRxiv2021

Waning grasslands: a quantitative temporal evaluation of the grassland habitats across human-dominated upper Gangetic Plains, north India

Grassland habitats currently face severe anthropogenic exploitations leading to cascading effects on the survival of grassland-dependent biodiversity globally, particularly in non-protected areas. Significant amount of such biodiversity-rich grasslands in India are found outside protected areas but lack quantitative information on their status. We evaluated the current and historical (30 years) status of the grasslands using a combination of intensive field surveys and GIS tools across one of the most fertile, human-dominated region: the upper Gangetic Plains of north India. On-ground mapping and visual classifications revealed 57% decline in grassland habitats between 1985 (418 km2) and 2015 (178km2), mostly driven by conversion to croplands (74% contribution). Radio-telemetry data from the largest endemic cervid swamp deer (n=2) showed grassland-dominated average home range (50% BBMM) size of 1.02 km2. The animals highly preferred these patches (average Ivlevs index- 0.85) and showed highest temporal continuity (88%) compared to other LULC classes. Camera trapping within the core habitats suggests critical use of these patches as fawning/breeding grounds. Habitat suitability analysis indicates only [~]18% of the entire area along Ganges is suitable for swamp deer. Accurate mapping (86% accuracy) and characterization of four major grass species revealed a total 144.04 km{superscript 2} vegetation area, dominted by Saccharum sp. (35%). We recommend protection and recovery of these critical grassland patches to maintain dynamic corridors and other appropriate management strategies involving multiple stakeholders to ensure survival of this critical ecosystem. Such evaluations, if spatially expanded, would be critical to restore this rapidly vanishing ecosystem worldwide.

ecology↗

bioRxiv2021

The organization of individually mapped structural and functional semantic networks in aging adults

Language function in the brain, once thought to be highly localized, is now appreciated as relying on a connected but distributed network. The semantic system is of particular interest in the language domain because of its hypothesized integration of information across multiple cortical regions. Previous work in healthy individuals has focused on group-level functional connectivity (FC) analyses of the semantic system, which may obscure interindividual differences driving variance in performance. These studies also overlook the contributions of white matter networks to semantic function. Here, we identified semantic network nodes with a semantic decision fMRI task in 53 typically-aging adults, characterized network organization using structural connectivity (SC), and quantified the segregation and integration of the network using FC. Hub regions were identified in left inferior frontal gyrus. The individualized semantic network was composed of three interacting modules: 1) default-mode module characterized by bilateral medial prefrontal and posterior cingulate regions and also including right-hemisphere homotopes of language regions; 2) left frontal module extending dorsally from inferior frontal gyrus to pre-motor area; and 3) left temporoparietal module extending from temporal pole to inferior parietal lobule. FC within Module3 and integration of the entire network related to a semantic verbal fluency task, but not a matched phonological task. These results support and extend the tri-network semantic model (Xu et al., 2017) and the controlled semantic cognition model (Chiou et al., 2018) of semantic function.

neuroscience↗

bioRxiv2021

Gut microbiota and age shape susceptibility to clostridial enteritis in lorikeets under human care

BackgroundEnteritis is a common cause of morbidity and mortality in lorikeets that can be challenging to diagnose and treat. In this study, we examine gut microbiota in two lorikeet flocks with enteritis (Columbus Zoo and Aquarium - CZA; Denver Zoo - DZ). Since 2012, the CZA flock has experienced repeated outbreaks of enteritis despite extensive diet, husbandry, and clinical modifications. In 2018, both CZA and DZ observed a spike in enteritis. Recent research has revealed that the gut microbiota can influence susceptibility to enteropathogens. We hypothesized that a dysbiosis, or alteration in the gut microbial community, was making some lorikeets more susceptible to enteritis, and our goal was to characterize this dysbiosis and determine the features that predicted susceptibility. ResultsWe employed 16S rRNA sequencing to characterize the cloacal microbiota in lorikeets (CZA n = 67, DZ n = 24) over time. We compared the microbiota of healthy lorikeets, to lorikeets with enteritis, and lorikeets susceptible to enteritis, with "susceptible" being defined as healthy birds that subsequently developed enteritis. Based on sequencing data, culture, and toxin gene detection in intestinal contents, we identified Clostridium perfringens type A (CZA and DZ) and C. colinum (CZA only) at increased relative abundances in birds with enteritis. Histopathology and immunohistochemistry further identified the presence of gram-positive bacilli and C. perfringens, respectively, in the necrotizing intestinal lesions. Finally, using Random Forests and LASSO models, we identified several features (young age and the presence of Rhodococcus fascians and Pseudomonas umsongensis) associated with susceptibility to clostridial enteritis. ConclusionsWe identified C. perfringens type A and C. colinum associated with lorikeet necrohemorrhagic enteritis at CZA and DZ. Susceptibility testing of isolates lead to an updated clinical treatment plan which ultimately resolved the outbreaks at both institutions. This work provides a foundation for understanding gut microbiota features that are permissive to clostridial colonization and host factors (e.g. age, prior infection) that shape responses to infection.

microbiology↗

bioRxiv2021

A machine learning model for screening of body fluid cytology smears

IntroductionBody fluid cytology is one of the commonest investigations performed in indoor patients, both for diagnosis of suspected carcinoma as well as staging of known carcinoma. Carcinoma is diagnosed in body fluids by the pathologist through microscopic examination and searching for malignant epithelial cell clusters. The process of screening body fluid smears is a time consuming and error prone process. AimWe have attempted to construct a machine learning model which can screen body fluid cytology smears for malignant cells. Materials and methodsMGG stained Ascitic / pleural fluid cytology smears were included from 21 cases (14 malignant, 07 benign) in this study. A total of 693 microphotographs were taken at 40x magnification at the same illumination and after correction of white balance. A Magnus Microphotography system was used for photography. The images were split into the training set (195 images), test set (120 images) and validation set (378 images). A machine learning model, a convolutional neural network, was developed in the Python programming language using the Keras deep learning library. The model was trained with the images of the training set. After completion of training, the model was evaluated on the test set of images. ResultsEvaluation of the model on the test set produced a sensitivity of 97.87%, specificity 85.26%, PPV 95.18%, NPV 93.10% In 06 images, the model has failed to detect singly scattered malignant cells/ clusters. 14 (3.7%) false positives was reported by the model. The machine learning model shows potential utility as a screening tool. However, it needs improvement in detecting singly scattered malignant cells and filtering inflammatory infiltrate.

pathology↗

bioRxiv2021

Glutathione regulates subcellular iron homeostasis via transcriptional activation of iron responsive genes in Arabidopsis

While glutathione (GSH) is known to regulate iron (Fe) deficiency response in plants, its involvement in modulating subcellular Fe homeostasis remained elusive. In this study, we report that the GSH depleted mutants, cad2-1 and pad2-1 displayed increased sensitivity to Fe deficiency with significant down-regulation of the vacuolar Fe exporters, AtNRAMP3 and AtNRAMP4 and the chloroplast Fe importer, AtPIC1. Moreover, the pad2-1 mutant accumulated higher Fe content in vacuoles and lower in chloroplasts compared with Col-0 under Fe limited condition. Exogenous GSH treatment could enhance the chloroplast Fe content in Col-0 plants but failed to do so in the nramp3nramp4 double mutant demonstrating the role of GSH in modulating subcellular Fe homeostasis. Pharmacological experiments, mutant analysis and promoter assay revealed that this regulation involved transcriptional activation of the transporter genes by a GSH-GSNO module. The Fe responsive bHLH transcription factors (TFs), AtbHLH29, AtbHLH38 and AtbHLH101 were identified to interact with the promoters of these genes which were in turn activated via S-nitrosylation. Together, the present study delineates the role of GSH-GSNO module in regulating subcellular Fe homeostasis by transcriptional activation of the Fe transporters AtNRAMP3, AtNRAMP4 and AtPIC1 via S-nitrosylation of the bHLH TFs during Fe deficiency. Summary statementGlutathione regulates subcellular iron homeostasis under iron deficiency via GSNO dependent transcriptional activation of AtNRAMP3, AtNRAMP4 and AtPIC1 genes by S-nitrosylation of the iron responsive bHLH transcription factors, AtbHLH29, AtbHLH38 and AtbHLH101.

plant biology↗

bioRxiv2021

Genomic surveillance and phylodynamic analyses reveal emergence of novel mutation and co-mutation patterns within SARS-CoV2 variants prevalent in India

Emergence of distinct viral clades has been observed in SARS-CoV2 variants across the world and India. Identification of the genomic diversity and the phylodynamic profiles of the prevalent strains of the country are critical to understand the evolution and spread of the variants. We performed whole-genome sequencing of 54 SARS-CoV2 strains collected from COVID-19 patients in Kolkata, West Bengal during August to October 2020. Phylogeographic and phylodynamic analyses were performed using these 54 and other sequences from India and abroad available in GISAID database. Spatio-temporal evolutionary dynamics of the pathogen across various regions and states of India over three different time periods in the year 2020 were analyzed. We estimated the clade dynamics of the Indian strains and compared the clade specific mutations and the co-mutation patterns across states and union territories of India over the time course. We observed that GR, GH and G (GISAID) or 20B and 20A (Nextstrain) clades were the prevalent clades in India during middle and later half of the year 2020. However, frequent mutations and co-mutations observed within the major clades across time periods do not show much overlap, indicating emergence of newer mutations in the viral population prevailing in the country. Further, we explored the possible association of specific mutations and co-mutations with the infection outcomes manifested within the Indian patients.

genomics↗

bioRxiv2021

Lithium ions display weak interaction with amyloid-beta (Aβ) peptides and have minor effects on their aggregation

Alzheimers disease (AD) is an incurable disease and the main cause of age-related dementia worldwide, despite decades of research. Treatment of AD with lithium (Li) has showed promising results, but the underlying mechanism is unclear. The pathological hallmark of AD brains is deposition of amyloid plaques, consisting mainly of amyloid-{beta} (A{beta}) peptides aggregated into amyloid fibrils. The plaques contain also metal ions of e.g. Cu, Fe, and Zn, and such ions are known to interact with A{beta} peptides and modulate their aggregation and toxicity. The interactions between A{beta} peptides and Li+ ions have however not been well investigated. Here, we use a range of biophysical techniques to characterize in vitro interactions between A{beta} peptides and Li+ ions. We show that Li+ ions display weak and non-specific interactions with A{beta} peptides, and have minor effects on A{beta} aggregation. These results indicate that possible beneficial effects of Li on AD pathology are not likely caused by direct interactions between A{beta} peptides and Li+ ions.

biochemistry↗

bioRxiv2021

6-gingerol interferes with amyloid-beta (Aβ) peptide aggregation

Alzheimers disease (AD) is the most prevalent age-related cause of dementia. AD affects millions of people worldwide, and to date there is no cure. The pathological hallmark of AD brains is deposition of amyloid plaques, which mainly consist of amyloid-{beta} (A{beta}) peptides, commonly 40 or 42 residues long, that have aggregated into amyloid fibrils. Intermediate aggregates in the form of soluble A{beta} oligomers appear to be highly neurotoxic. Cell and animal studies have previously demonstrated positive effects of the molecule 6-gingerol on AD pathology. Gingerols are the main active constituents of the ginger root, which in many cultures is a traditional nutritional supplement for memory enhancement. Here, we use biophysical experiments to characterize in vitro interactions between 6-gingerol and A{beta}40 peptides. Our experiments with atomic force microscopy imaging, and nuclear magnetic resonance and Thioflavin-T fluorescence spectroscopy, show that the hydrophobic 6-gingerol molecule interferes with formation of A{beta}40 aggregates, but does not interact with A{beta}40 monomers. Thus, together with its favourable toxicity profile, 6-gingerol appears to display many of the desired properties of an anti-AD compound.

biochemistry↗

bioRxiv2020

Incorporation of Heterogeneity in a Case-Control Study Through a Mixture Model

Most common human diseases and complex traits are etiologically heterogeneous. Genome-wide Association Studies (GWAS) aim to discover common genetic variants that are associated with complex traits, typically without considering heterogeneity. Heterogeneity, as well as im-precise phenotyping, significantly reduces the power to find genetic variants associated with human diseases and complex traits. Disease subtyping through unsupervised clustering techniques such as latent class analysis can explain some of the heterogeneity; however, subtyping methods do not typically incorporate heterogeneity into the association framework. Here, we use a finite mixture model with logistic regression to incorporate heterogeneity into the association testing framework for a case-control study. In the proposed method, the disease outcome is modeled as a mixture of two binomial distributions. One of the component distributions refers to the subgroup of the population for which the genetic variant is not associated with the disease outcome and another component distribution corresponds to the subgroup for which the genetic variant is associated with the disease outcome. The mixing parameter corresponds to the proportion of the population for which the genetic variant is associated with the disease outcome. A simulation study of a trait with differing levels of prevalence, SNP minor allele frequency, and odds ratio was performed, and effect size estimates compared between the models with and without incorporating heterogeneity. The proposed mixture model yields lower bias of odds ratios while having comparable power compared to classical logistic regression.

genetics↗

bioRxiv2020

Global Importance Analysis: A Method to QuantifyImportance of Genomic Features in Deep NeuralNetworks

Deep neural networks have demonstrated improved performance at predicting the sequence specificities of DNA- and RNA-binding proteins compared to previous methods that rely on k-mers and position weight matrices. To gain insights into why a DNN makes a given prediction, model interpretability methods, such as attribution methods, can be employed to identify motif-like representations along a given sequence. Because explanations are given on an individual sequence basis and can vary substantially across sequences, deducing generalizable trends across the dataset and quantifying their effect size remains a challenge. Here we introduce global importance analysis (GIA), a model interpretability method that quantifies the population-level effect size that putative patterns have on model predictions. GIA provides an avenue to quantitatively test hypotheses of putative patterns and their interactions with other patterns, as well as map out specific functions the network has learned. As a case study, we demonstrate the utility of GIA on the computational task of predicting RNA-protein interactions from sequence. We first introduce a convolutional network, we call ResidualBind, and benchmark its performance against previous methods on RNAcompete data. Using GIA, we then demonstrate that in addition to sequence motifs, ResidualBind learns a model that considers the number of motifs, their spacing, and sequence context, such as RNA secondary structure and GC-bias.

genomics↗

bioRxiv2020

Identification of a polymorphism in the N gene of SARS-CoV-2 that adversely impacts detection by a widely-used RT-PCR assay

We identify a mutation in the N gene of SARS-CoV-2 that adversely affects annealing of a commonly used RT-PCR primer; epidemiologic evidence suggests the virus retains pathogenicity and competence for spread. This reinforces the importance of using multiple targets, preferably in at least 2 genes, for robust SARS-CoV-2 detection. Article Summary LineA SARS-CoV-2 variant that occurs worldwide and has spread in California significantly affects diagnostic sensitivity of an N gene assay, highlighting the need to employ multiple viral targets for detection.

molecular biology↗

bioRxiv2020

Body size and food plants drive local extinction risk in butterflies

Lepidoptera, butterflies and moths, are significant pollinators and ecosystem health indicators. Therefore, monitoring their diversity, distribution, and extinction risks are of critical importance. We aim to understand the drivers of the local extinction risks of the butterflies in Bangladesh. We conducted a systematic review to extract the diversity, distribution and local extinction risks of the butterflies of Bangladesh, and possible drivers of their extinction, e.g., body size, host plants and nectar plants. We updated the current checklist, which now consists of 463 species. We provided distribution and extinctions risk atlas showing both the diversity and extinction risks were highest in the eastern region of Bangladesh. We tested whether body size and host plants contribute to the local extinction risks of butterflies. We predicted butterflies with larger body size and fewer host plants and nectar plants would be in greater extinction risk. Accordingly, we showed that extinction risk was higher in larger butterflies than smaller butterflies, and in butterflies with a fewer number of host plants and nectar plants than the butterflies with higher number host plants. Our study highlights the contribution of body size and host plants as potential drivers of the local extinction risks of butterflies.

ecology↗

bioRxiv2020

ImmunoPET-informed sequence for focused ultrasound-targeted mCD47 blockade controls glioma

Phagocytic immunotherapies such as CD47 blockade have emerged as promising strategies for glioblastoma (GB) therapy, but the blood brain/tumor barriers (BBB/BTB) pose a persistent challenge for mCD47 delivery that can be overcome by focused ultrasound (FUS)-mediated BBB/BTB disruption. We here leverage immuno-PET imaging to determine how timing of [89Zr]-mCD47 injection relative to FUS impacts antibody penetrance into orthotopic murine gliomas. We then design and implement a rational paradigm for combining FUS and mCD47 for glioma therapy. We demonstrate that timing of antibody injection relative to FUS BBB/BTB disruption is a critical determinant of mCD47 access, with post-FUS injection conferring superlative antibody delivery to gliomas. We also show that mCD47 delivery across the BBB/BTB with repeat sessions of FUS can significantly constrain tumor outgrowth and extend survival in glioma-bearing mice. This study generates provocative insights for ongoing pre-clinical and clinical evaluations of FUS-mediated antibody delivery to brain tumors. Moreover, our results confirm that mCD47 delivery with FUS is a promising therapeutic strategy for GB therapy.

bioengineering↗

bioRxiv2020

Direct energy transfer from photosystem II to photosystem I is the major regulator of winter sustainability of Scots pine

Evergreen conifers in boreal forests can survive extremely cold (freezing) temperatures during the long dark winter and fully recover during the summer. A phenomenon called sustained quenching putatively provides photoprotection and enables their survival, but its precise molecular and physiological mechanisms are not understood. To unveil them, we have analyzed the seasonal adaptation of the photosynthetic machinery of Scots pine (Pinus sylvestris) trees by monitoring multi-year changes in weather, chlorophyll fluorescence, chloroplast ultrastructure, and changes in pigment-protein composition. Recorded Photosystem II and Photosystem I performance parameters indicate that highly dynamic structural and functional seasonal rearrangements of the photosynthetic apparatus occur. Although several mechanisms might contribute to sustained quenching of winter/early spring pine needles, time-resolved fluorescence analysis shows that extreme down-regulation of photosystem II activity along with direct energy transfer from photosystem II to photosystem I plays a major role. This mechanism is enabled by extensive thylakoid destacking allowing for mixing of PSII with PSI complexes. These two linked phenomena play crucial roles in winter acclimation and protection. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/144170v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@b9d757org.highwire.dtl.DTLVardef@e8ba28org.highwire.dtl.DTLVardef@115c5b2org.highwire.dtl.DTLVardef@6634f5_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

bioRxiv2020

Using a bistable animal opsin for switchable and scalable optogenetic inhibition of neurons

There is no consensus on the best optogenetic tool for neuronal inhibition. Lamprey parapinopsin ( Lamplight) is a Gi/o-coupled bistable animal opsin that can be activated and deactivated by short and long wavelength light, respectively. Since native mechanisms of neuronal inhibition frequently employ Gi/o signalling, we asked here whether Lamplight could be used for optogenetic silencing. We show that short (405nm) and long (525nm) wavelength pulses repeatedly switch Lamplight between stable signalling active and inactive states, and that combining these wavelengths can be used to achieve intermediate levels of activity. We demonstrate that these properties can be applied to produce switchable and scalable neuronal hyperpolarisation, and suppression of spontaneous spike firing in the mouse hypothalamic suprachiasmatic nucleus. We show that expressing Lamplight in (predominantly) ON bipolar cells can photosensitise retinas following advanced photoreceptor degeneration, and that 405 and 525nm stimuli can produce responses of opposite sign in output neurons of the retina. Lamplight-driven responses to both activating (405nm) and deactivating (525nm) light can occur within 500ms and be elicited by intensities at least 10x below threshold for available inhibitory optogenetic tools. We conclude that Lamplight can co-opt endogenous signalling mechanisms to allow optogenetic inhibition that is scalable, sustained and rapidly reversible.

neuroscience↗

bioRxiv2020

Spatial distribution of the lectin protein Osr40g3 determines its dual regulatory function in imparting salinity tolerance while impeding seed development in rice

Under changing environmental conditions, salt stress has posed a severe threat to agriculture. Although the R40 family lectins are known to be associated with osmotic stress response, their mechanism of action remains elusive. Among them, Osr40g3 displays the highest expression under salt stress. Here, we report that the constitutive overexpression of Osr40g3 imparts salt tolerance but displays pollen sterility and poor seed development in rice. Promoter analysis and gene expression studies revealed that the gene follows a precise tissue-specific expression pattern, which is essential for proper seed development. Overexpressing the gene under the control of its native promoter rescued the pollen-sterile phenotype while significantly improving salt tolerance. Protein-protein interaction studies demonstrated that Osr40g3 positively regulates an expansin protein, OsEG45, while decreasing the stability of a 14-3-3 protein, OsGF14e. Correspondingly, the OsEG45 overexpression and OsGF14e silencing lines display a salt-tolerant phenotype. Again, silencing OsEG45 in the background of OsGF14e silencing lines resulted in a salt-sensitive phenotype, indicating that salt tolerance of the OsGF14e silencing lines is OsEG45-dependent. Notably, the OsGF14e gene displays early salt responsiveness, while Osr40g3 and OsEG45 display a late response, indicating a spatio-temporal regulation of these genes. Interestingly, constitutive overexpression of Osr40g3 or silencing of OsGF14e leads to diminished gibberellic acid (GA) accumulation that activates the OsEG45 gene. Together, our study demonstrates that during salt stress, Osr40g3, a late salt-responsive gene, confers salt tolerance by negatively regulating OsGF14e while positively regulating OsEG45 via a GA-mediated pathway. This mechanistic insight broadens our understanding of lectin-mediated regulation of salt tolerance.

plant biology↗