Biology subjects

Vijayan, A.

Publications and source records attributed to Vijayan, A..

13 recordsLinked to original sources

bioRxiv2026

A membrane-anchored inhibitor of papain-like cysteine proteases promotes Pseudomonas root colonization

Pseudomonas species, spanning both beneficial and pathogenic lifestyles, possess conserved mechanisms to modulate plant immunity. Nevertheless, the mechanisms by which commensal bacteria establish and maintain host colonization remain poorly understood. Here, we report the characterization of a Pseudomonas chagasin-like protease inhibitor (Cpi1), conserved across pseudomonads representing a novel class of membrane-anchored PLCP inhibitor. Unlike previously described secreted protease inhibitors, P. putida Cpi1 is a lipoprotein localized to the bacterial surface and outer membrane vesicles (OMVs), positioning it to selectively inhibit immune-related papain-like cysteine proteases (PLCPs) during host interactions. Functional assays demonstrated inhibition of maize PLCP activity in the nanomolar range, while cpi1 deletion and chagasin motif mutants exhibited significantly impaired early root colonization, particularly in the meristematic and elongation zones. Besides, lack of cpi1 resulted in an altered structure of a maize root-associated synthetic community. We hypothesize that, Cpi1 may protect critical bacterial surface proteins from cleavage by inhibiting plant proteases and thereby modulate the release of MAMPs, dampening host immune responses. Moreover, the release of Cpi1 via OMVs could further extend its function within the root periphery and the apoplast. Together, our results uncover a conserved, membrane-anchored mechanism among pseudomonads for subverting plant immunity and establishing host-microbe interactions.

microbiology↗

bioRxiv2026

Sex without crossovers mimics clonal reproduction in the holocentric plant Rhynchospora tenuis

Meiotic recombination ensures accurate chromosome segregation and promotes genetic diversity by generating crossovers between homologous chromosomes1. While essential in most sexually reproducing organisms, recombination is variably regulated and can be absent in some lineages, a condition known as achiasmy2. However, obligate achiasmy in both sexes of a sexual species has not been previously documented. Here, we investigate the beak-sedge Rhynchospora tenuis, a holocentric plant with the lowest known chromosome number among flowering plants (n = 2) and inverted meiosis3. Using chromosome-scale genome assemblies from nine accessions, molecular cytogenetics, immunocytochemistry, high-throughput single-gamete sequencing and whole-genome sequencing of controlled crosses, we show that R. tenuis undergoes obligate, genome-wide achiasmy in both male and female meiosis. Despite normal early meiotic axis formation, synapsis fails, crossovers are not detected cytologically or genetically, and univalents persist at metaphase I. Extensive haplotype-specific accumulation of transposable elements (TEs) generates segregation distortion (e.g. meiotic drive), favouring the transmission of larger, TE-rich chromosomes. Remarkably, sexual reproduction is retained with fertilisation producing viable seeds only when translocation-compatible gametes meet, indicating strong post-meiotic selection that eliminates incompatible homozygous combinations. As a result, all surviving offspring are genetically identical to the maternal genotype, effectively restoring heterozygosity each generation and mimicking clonal reproduction. We propose that the combined effects of recombination loss, low chromosome number, holocentricity, inverted meiosis, and selective transmission of longer chromosomes enable faithful segregation and clonal-like inheritance despite sexual reproduction. These findings challenge the boundary between sex and clonality, revealing a unique evolutionary strategy linking genome architecture, recombination loss, and transmission bias.

evolutionary biology↗

bioRxiv2025

Orco regulates the circadian activity of pheromone-sensitive olfactory receptor neurons in hawkmoths

1The mating behavior of nocturnal Manduca sexta hawkmoths is under strict temporal control. It is orchestrated via circadian and ultradian oscillations in sex-pheromone stimuli as social Zeitgeber. The extremely sensitive pheromone-detecting olfactory receptor neurons (ORNs) that innervate the long trichoid sensilla on the males antennae are peripheral circadian clocks. They express the transcriptional-translational feedback loop (TTFL) circadian clockwork, best characterized in Drosophila melanogaster. In hawkmoths, it is still unknown whether or how the ORN TTFL clockwork regulates the daily rhythms in pheromone sensitivity and in temporal resolution of ultradian pheromone pulses as prerequisites to the temporal regulation of hawkmoth mating behavior. We hypothesize that, rather than the slow TTFL clock, a more rapidly adaptive post-translational feedback loop (PTFL) clockwork, assembled in a signalosome in the ORN plasma membrane, allows for temporal control of pheromone detection via generation of multiscale endogenous membrane potential oscillations. The potential oscillations of the PTFL clock could rapidly synchronize to oscillations of pheromone stimuli at different time scales, thus enabling the prediction of stimulus patterns as a mechanism for active sensing. With in vivo long-term tip recordings of long trichoid sensilla of male hawkmoths, we analyzed the spontaneous spiking activity indicative of the ORNs endogenous membrane potential oscillations. Consistent with our hypothesis of a multiscale PTFL clock in hawkmoth ORNs, spontaneous spiking was modulated on ultradian and circadian time scales, with maximum activity at night. When we blocked the evolutionarily conserved olfactory receptor coreceptor (Orco), the circadian modulation was abolished but the ultradian frequency modulation of the spontaneous activity remained. Consistent with PTFL control, Orco was not under the transcriptional control of the TTFL clock, but its modulation of spontaneous spiking activity was dependent on cAMP. We could replicate the experimental data in a conductance-based computational model of an ORN. In this model, Orco conductance changed as a function of fluctuating 2nd messenger levels. This study demonstrates that a PTFL clock is sufficient to impose a circadian pattern on ORN sensitivity. Future experiments are necessary to further challenge our novel hypothesis. 2. Significance statementIt is generally assumed that all circadian rhythms in an organism are driven by a transcriptional-translational feedback loop (TTFL) clock. In this study, we demonstrate with in vivo recordings of hawkmoth pheromone-sensitive olfactory receptor neurons (ORNs) that the olfactory receptor coreceptor (Orco) is the key pacemaker channel for controlling circadian rhythms in spontaneous spiking activity. Since Orco expression is not driven by the TTFL clock, we put forward the novel hypothesis that Orco is a core element of a post-translational feedback loop (PTFL) membrane clock assembled in a signalosome controlling interlinked oscillations in 2nd messengers and membrane potential. Accordingly, our computational model predicts that ORN sensitivity is tuned by circadian changes in the conductance of an Orco ion channel, which is mediated by cycling levels of cyclic nucleotides. Our novel hypothesis that highlights the contribution of feedback-controlled post-translational modifications to the generation of endogenous circadian rhythmicity should spark further challenges.

physiology↗

bioRxiv2024

A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context

We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We developed a novel approach for ground truth generation and iterative training of 3D nuclear segmentation models, which we applied to popular CellPose, PlantSeg, and StarDist algorithms. We provide two high-quality models trained on plant nuclei that enable 3D segmentation of nuclei in datasets obtained from fixed or live samples, acquired from different plant and animal tissues, and stained with various nuclear stains or fluorescent protein-based nuclear reporters. We also share a diverse high-quality training dataset of about 10,000 nuclei. Furthermore, we advanced the MorphoGraphX analysis and visualization software by, among other things, providing a method for linking 3D segmented nuclei to their surrounding cells in 3D digital organs. We found that the nuclear-to-cell volume ratio varies between different ovule tissues and during the development of a tissue. Finally, we extended the PlantSeg 3D segmentation pipeline with a proofreading script that uses 3D segmented nuclei as seeds to correct cell segmentation errors in difficult-to-segment tissues. Summary StatementWe present computational tools that allow versatile and accurate 3D nuclear segmentation in plant organs, enable the analysis of cell-nucleus geometric relationships, and improve the accuracy of 3D cell segmentation.

plant biology↗

bioRxiv2022

Blood-based transcriptomic signature panel identification for cancer diagnosis: Benchmarking of feature extraction methods

Liquid biopsy has shown promise for cancer diagnosis due to its minimally invasive nature and the potential for novel biomarker discovery. However, the low concentration of relevant blood-based biosources and the heterogeneity of samples (i.e. the variability of relative abundance of molecules identified), pose major challenges to biomarker discovery. Moreover, the number of molecular measurements or features (e.g., transcript read counts) per sample could be in the order of several thousand, whereas the number of samples is often substantially lower, leading to the curse of dimensionality. These challenges, among others, elucidate the importance of a robust biomarker panel identification or feature extraction step wherein relevant molecular measurements are identified prior to classification for cancer detection. In this work, we performed a benchmarking study on eleven feature extraction methods using transcriptomic profiles derived from different blood-based biosources. The methods were assessed both in terms of their predictive performance and the robustness of the biomarker panels in diagnosing cancer or stratifying cancer subtypes. While performing the comparison, the feature extraction methods are categorised into feature subset selection methods and transformation methods. A transformation feature extraction method, namely PLS-DA, was found to perform consistently superior in terms of classification performance, while a feature subset selection method, namely Ranger, selected feature sets that were the most robust to sub-sampling in terms of consistently selecting the same features. As part of the benchmarking study, a generic pipeline has been created and made available as an R package to ensure reproducibility of the results and allow for easy extension of this study to other datasets.

bioinformatics↗

bioRxiv2022

dSeqSb: A systems biology approach to decipher dynamics of 1 host-pathogen interactions using temporal dual RNA-seq data

Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expression in both organisms. Dual RNA-seq, the simultaneous detection of host and pathogen transcripts, has become a leading approach to unravel complex molecular interactions between the host and the pathogen and is particularly informative for intracellular organisms. The amount of in vitro and in vivo dual RNA-seq data is rapidly growing which demands computational pipelines to effectively analyse such data. In particular, holistic, systems-level, and temporal analyses of dual RNA-seq data are essential to enable further insights into the host-pathogen transcriptional dynamics and potential interactions. Here, we developed an integrative network-driven bioinformatics pipeline, dRNASb, a systems biology-based computational pipeline to analyse temporal transcriptional clusters, incorporate molecular interaction networks (e.g., protein-protein interactions), identify topologically and functionally key transcripts in host and pathogen, and associate host and pathogen temporal transcriptome to decipher potential between-species interactions. The pipeline is applicable to various dual RNA-seq data from different species and experimental conditions. As a case study, we applied dRNASb to analyse temporal dual RNA-seq data of Salmonella-infected human cells, which enabled us to uncover genes contributing to the infection process and their potential functions and to identify potential host-pathogen interactions between host and pathogen genes. Overall, dRNASb has the potential to identify key genes involved in bacterial growth or host defence mechanisms for future uses as therapeutic targets.

microbiology↗

bioRxiv2021

The annotation and analysis of complex 3D plant organs using 3DCoordX

A fundamental question in biology concerns how molecular and cellular processes become integrated during morphogenesis. In plants, characterization of 3D digital representations of organs at single-cell resolution represents a promising approach to addressing this problem. A major challenge is to provide organ-centric spatial context to cells of an organ. We developed several general rules for the annotation of cell position and embodied them in 3DCoordX, a user-interactive computer toolbox implemented in the open-source software MorphoGraphX. It enables rapid spatial annotation of cells even in highly curved biological shapes. With the help of 3DCoordX we obtained new insight by analyzing cellular growth patterns in organs of several species. For example, the data indicated the presence of a basal cell proliferation zone in the ovule primordium of Arabidopsis thaliana. Proof-of-concept analyses suggested a preferential increase in cell length associated with neck elongation in the archegonium of Marchantia polymorpha and variations in cell volume linked to central morphogenetic features of a trap of the carnivorous plant Utricularia gibba. Our work demonstrates the broad applicability of the developed strategies as they provide organ-centric spatial context to cellular features in plant organs of diverse shape complexity.

plant biology↗

bioRxiv2021

Disentangling single-cell omics representation with a power spectral density-based feature extraction

Emerging single-cell technologies provide high-resolution measurements of distinct cellular modalities opening new avenues for generating detailed cellular atlases of many and diverse tissues. The high dimensionality, sparsity, and inaccuracy of single cell sequencing measurements, however, can obscure discriminatory information, mask cellular subtype variations and complicate downstream analyses which can limit our understanding of cell function and tissue heterogeneity. Here, we present a novel pre-processing method (scPSD) inspired by power spectral density analysis that enhances the accuracy for cell subtype separation from large-scale single-cell omics data. We comprehensively benchmarked our method on a wide range of single-cell RNA-sequencing datasets and showed that scPSD pre-processing, while being fast and scalable, significantly reduces data complexity, enhances cell-type separation, and enables rare cell identification. Additionally, we applied scPSD to transcriptomics and chromatin accessibility cell atlases and demonstrated its capacity to discriminate over 100 cell types across the whole organism and across different modalities of single-cell omics data.

bioinformatics↗

bioRxiv2021

MorphoGraphX 2.0: Providing context for biological image analysis with positional information

Positional information is a central concept in developmental biology. In developing organs, positional information can be idealized as a local coordinate system that arises from morphogen gradients controlled by organizers at key locations. This offers a plausible mechanism for the integration of the molecular networks operating in individual cells into the spatially-coordinated multicellular responses necessary for the organization of emergent forms. Understanding how positional cues guide morphogenesis requires the quantification of gene expression and growth dynamics in the context of their underlying coordinate systems. Here we present recent advances in the MorphoGraphX software (Barbier de Reuille et al. eLife 2015;4:e05864) that implement a generalized framework to annotate developing organs with local coordinate systems. These coordinate systems introduce an organ-centric spatial context to microscopy data, allowing gene expression and growth to be quantified and compared in the context of the positional information thought to control them.

developmental biology↗

bioRxiv2021

An atlas of healthy and injured cell states and niches in the human kidney

Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We have applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (n = 42) and disease (n = 42) kidneys. This has provided a high resolution cellular atlas of 100 cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations for major cell types spanning the entire kidney. We further identify and define cellular states altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states affecting several segments. Molecular signatures of these states permitted their localization within injury neighborhoods using spatial transcriptomics, and large-scale 3D imaging analysis of [~]1.2 million neighborhoods provided linkages to active immune responses. These analyses further defined biological pathways relevant to injury niches, including signatures underlying the transition from reference to predicted maladaptive states that were associated with a decline in kidney function during chronic kidney disease. This human kidney cell atlas, including injury cell states and neighborhoods, will be a valuable resource for future studies.

genomics↗

bioRxiv2021

Ad26.COV2.S-elicited immunity protects against G614 spike variant SARS-CoV-2 infection in Syrian hamsters and does not enhance respiratory disease in challenged animals with breakthrough infection after sub-optimal vaccine dosing

Previously we have shown that a single dose of recombinant adenovirus serotype 26 (Ad26) vaccine expressing a prefusion stabilized SARS-CoV-2 spike antigen (Ad26.COV2.S) is immunogenic and provides protection in Syrian hamster and non-human primate SARS-CoV-2 infection models. Here, we investigated the immunogenicity, protective efficacy and potential for vaccine-associated enhanced respiratory disease (VAERD) mediated by Ad26.COV2.S in a moderate disease Syrian hamster challenge model, using the currently most prevalent G614 spike SARS-CoV-2 variant. Vaccine doses of 1x109 vp and 1x1010 vp elicited substantial neutralizing antibodies titers and completely protected over 80% of SARS-CoV-2 inoculated Syrian hamsters from lung infection and pneumonia but not upper respiratory tract infection. A second vaccine dose further increased neutralizing antibody titers which was associated with decreased infectious viral load in the upper respiratory tract after SARS-CoV-2 challenge. Suboptimal non-protective immune responses elicited by low-dose A26.COV2.S vaccination did not exacerbate respiratory disease in SARS-CoV-2-inoculated Syrian hamsters with breakthrough infection. In addition, dosing down the vaccine allowed to establish that binding and neutralizing antibody titers correlate with lower respiratory tract protection probability. Overall, these pre-clinical data confirm efficacy of a 1-dose vaccine regimen with Ad26.COV2.S in this G614 spike SARS-CoV-2 virus variant Syrian hamster model, show the added benefit of a second vaccine dose, and demonstrate that there are no signs of VAERD under conditions of suboptimal immunity.

immunology↗

bioRxiv2020

A digital 3D reference atlas reveals cellular growth patterns shaping the Arabidopsis ovule

A fundamental question in biology is how morphogenesis integrates the multitude of distinct processes that act at different scales, ranging from the molecular control of gene expression to cellular coordination in a tissue. Investigating morphogenesis of complex organs strongly benefits from three-dimensional representations of the organ under study. Here, we present a digital analysis of ovule development from Arabidopsis thaliana as a paradigm for a complex morphogenetic process. Using machine-learning-based image analysis we generated a three-dimensional atlas of ovule development with cellular resolution. It allows quantitative stage- and tissue-specific analysis of cellular patterns. Exploiting a fluorescent reporter enabled precise spatial determination of gene expression patterns, revealing subepidermal expression of WUSCHEL. Underlying the power of our approach, we found that primordium outgrowth progresses evenly, discovered a novel mode of forming a new cell layer, and detected a new function of INNER NO OUTER in restricting cell proliferation in the nucellus. Moreover, we identified two distinct subepidermal cell populations that make crucial contributions to ovule curvature. Our work demonstrates the expedience of a three-dimensional digital representation when studying the morphogenesis of an organ of complex cellular architecture and shape that eventually consists of 1,900 cells.

plant biology↗

bioRxiv2020

Accurate And Versatile 3D Segmentation Of Plant Tissues At Cellular Resolution

Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs. In the last years, deep learning has provided robust automated algorithms that approach human performance, with applications to bio-image analysis now starting to emerge. Here, we present PlantSeg, a pipeline for volumetric segmentation of plant tissues into cells. PlantSeg employs a convolutional neural network to predict cell boundaries and graph partitioning to segment cells based on the neural network predictions. PlantSeg was trained on fixed and live plant organs imaged with confocal and light sheet microscopes. PlantSeg delivers accurate results and generalizes well across different tissues, scales, and acquisition settings. We present results of PlantSeg applications in diverse developmental contexts. PlantSeg is free and open-source, with both a command line and a user-friendly graphical interface.

plant biology↗