Biology subjects

Shree, A.

Publications and source records attributed to Shree, A..

6 recordsLinked to original sources

bioRxiv2026

A Comprehensive Benchmarking of Spatial Deconvolution andDomain Detection Methods across Diverse Tissues and SpatialTranscriptomic Technologies

Spatial transcriptomic technologies enable high-resolution characterization of gene expression patterns and reconstruction of cellular architecture within tissue contexts. Two key computational problems have emerged for analyzing these datasets: spatial deconvolution, for disentangling cell-type compositions at spatial locations, and spatial domain detection, for identifying spatially coherent regions within a tissue section. Although numerous methods have been developed for each task, a comprehensive and unified benchmarking study spanning diverse tissue types, spatial resolutions, and technological platforms remains lacking, hindering informed method selection by end users and impeding future methodological advancements. Here, we present spDDB (https://github.com/Zafar-Lab/spDDB), a comprehensive benchmarking framework for spatial deconvolution and domain detection methods across a large and diverse collection of datasets spanning multiple tissues, technologies, and biological conditions. We evaluated 21 deconvolution methods, including seven recently-developed approaches, across 37 datasets curated from brain, cancer, and organ tissues encompassing four distinct technologies. To enable rigorous evaluation, we introduced SynthST, a deep graph attention autoencoder-based simulator that generates realistic spatial cell-type distributions from spatial transcriptomic data, and employed a suite of spatial bivariate metrics including a novel bivariate Gearys C metric, alongside rare cell-type, and cell-shape characterization metrics, for multidimensional performance assessment. While Cell2location, RCTD and SONAR emerged as top-performing methods for spatial deconvolution across tissue types, deconvolution performance varied substantially based on tissue architecture, spatial technology, dataset scale, and cell type diversity. For domain detection, we benchmarked 18 methods across 36 datasets spanning six spatial technologies, identifying PROST, BASS, and SpaceFlow as the leading approaches, while revealing notable limitations of existing methods in handling large-scale datasets. Finally, we provide practical guidelines to assist end users in selecting optimal methods for both tasks across diverse experimental settings.

bioinformatics↗

bioRxiv2026

Comprehensive identification and characterization of candidate effector proteins in Puccinia triticina reveals insights into the wheat leaf rust pathogenesis

The biotrophic pathogen Puccinia triticina is the causative agent of the most vulnerable foliar disease, namely leaf rust disease of wheat. The pathogen-secreted effectors are essential in modulating fungal virulence and host immune responses. Despite their significance, potential effectors and their underlying mechanisms governing host susceptibility remain elusive. In the present study, we employed an in silico approach to identify and characterise effector proteins from the P. triticina proteome. Later, performed temporal expression profiling to prioritise effector candidates associated with rust disease. Here, a total of 273 high-confidence effector candidates were identified and analysed their physicochemical properties, domains, motifs, and functional annotations, to assess their conservation and dynamics. Although most of the effectors were uncharacterised, the conserved motif virulence-associated [YFW]xC was notably enriched in the effector repertoire. Comparative PHI-base annotation highlighted similarities with known fungal virulence factors involved in host susceptibility. Effectors harbouring CAZyme activity indicate involvement in host cell wall modification. Promoter analysis identified multiple stress- and defence-related transcription factor binding sites, suggesting regulated expression during infection. Transcriptome analysis revealed that 20 effector genes were significantly upregulated during P. triticina infection. qRT-PCR validated the expression of 4 highly induced effector transcripts following P. triticina infection in susceptible wheat variety. Specifically, two of these candidates demonstrated biphasic expression pattern that aligns contrasting PTI- and ETI-mediated defense mechanisms critical for sustained virulence. Overall, this study provides a comprehensive framework for identifying functionally relevant P. triticina effectors and offers insight for future effector-target studies and effector-based leaf rust management strategies.

plant biology↗

bioRxiv2025

A Temporal Single-Cell Multi-Omics Atlas of Murine Pancreatic Islet Remodeling During Hyperglycaemia Progression

Pancreatic islets undergo coordinated cellular remodeling during obesity-induced insulin resistance (IR). However, the associated molecular changes across endocrine and non-endocrine compartments remain largely unexplored. Here, using longitudinal single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) on islets from C57BL/6 mice subjected to high-fat diet (HFD) feeding for 8, 16, and 24 weeks, along with age-matched controls on regular chow, we mapped dynamic changes in islet cell composition and transcriptional states. Beta cells demonstrated pronounced stress-induced reprogramming, with the emergence of proliferative and dysfunctional subsets. Alpha and delta cell fractions declined under HFD, despite increased polyhormonal biosynthesis, suggesting functional rather than numerical adaptation. Immune profiling showed robust expansion of proinflammatory M1 macrophages and upregulation of NF-{kappa}B and chemotaxis pathways, particularly at 16 weeks. Notably, cell-cell communication analyses revealed diet-specific disruption in signaling networks. Under HFD conditions, intercellular communication among beta cells, macrophages, and delta cells was markedly altered, leading to the disruption of key signaling pathways such as the gastric inhibitory polypeptide receptor (GIPR) and major histocompatibility complex-I (MHC-I). Notably, C-C motif chemokine ligand 27A (Ccl27a) expression and chromatin accessibility were significantly altered in a distinct subpopulation of beta cells under HFD condition, indicative of a niche-specific regulatory mechanism. Integration with human islet datasets from obese and type 2 diabetes (T2D) donors confirmed conserved shifts in beta cell identity and immune activation. This study presents a comprehensive high-resolution atlas of islet remodeling under metabolic stress, identifying key communication nodes and transcriptional programs pertinent to T2D pathogenesis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/656754v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@64aee0org.highwire.dtl.DTLVardef@150beborg.highwire.dtl.DTLVardef@1c19c6dorg.highwire.dtl.DTLVardef@4d1a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2022

scDREAMER: atlas-level integration of single-cell datasets using deep generative model paired with adversarial classifier

Integration of heterogeneous single-cell sequencing datasets generated across multiple tissue locations, time and conditions is essential for a comprehensive understanding of the cellular states and expression programs underlying complex biological systems. Here, we present scDREAMER (https://github.com/Zafar-Lab/scDREAMER), a novel data integration framework that employs a novel adversarial variational autoencoder for learning lower-dimensional cellular embeddings and a batch classifier neural network for the removal of batch effects. Using five real benchmarking datasets, we demonstrated that scDREAMER can overcome critical challenges including the presence of skewed cell types among batches, nested batch effects, large number of batches and conservation of development trajectory across different batches. Moreover, our benchmarking demonstrated that scDREAMER outperformed state-of-the-art methods in batch-correction and conservation of biological variation. Using a 1 million cells dataset, we further showed that scDREAMER is scalable and can perform atlas-level integration across species (e.g., human and mouse) while being faster than other deep-learning-based methods.

bioinformatics↗

bioRxiv2021

The nuclear effector ArPEC25 from the necrotrophic fungus Ascochyta rabiei targets the chickpea transcription factor CaβLIM1a and negatively modulates lignin biosynthesis for host susceptibility

Fungal pathogens deploy a barrage of secreted effectors to subvert host immunity, often by evading, disrupting, or altering key components of transcription, defense signaling, and metabolic pathways. However, the underlying mechanisms of effectors and their host targets are largely unexplored in necrotrophic fungal pathogens. Here, we describe the effector protein ArPEC25, which is secreted by the necrotroph Ascochyta rabiei, the causal agent of Ascochyta blight disease in chickpea (Cicer arietinum), and is indispensable for virulence. After entering host cells, ArPEC25 localizes to the nucleus and targets the host LIM transcription factor Ca{beta}LIM1a. Ca{beta}LIM1a is a transcriptional regulator of CaPAL1, which encodes phenylalanine ammonia lyase, the regulatory, gatekeeping enzyme of the phenylpropanoid pathway. ArPEC25 inhibits the transactivation of Ca{beta}LIM1a by interfering with its DNA binding ability. This results in negative regulation of the phenylpropanoid pathway and decreased levels of intermediates of lignin biosynthesis, thereby suppressing lignin production. Our findings illustrate the role of fungal effectors in enhancing virulence by targeting a key defense pathway that leads to the biosynthesis of various secondary metabolites and antifungal compounds. This study provides a template for the study of less explored necrotrophic effectors and their host target functions. One-sentence summaryThe Ascochyta rabiei effector ArPEC25 enters the host nucleus and targets the transcription factor Ca{beta}LIM1a to manipulate phenylpropanoid pathway for negative modulation of chickpea lignin biosynthesis.

plant biology↗

bioRxiv2020

Modulation of fungal virulence through CRZ1 regulated F-BAR-dependent actin remodeling and endocytosis in chickpea infecting phytopathogen Ascochyta rabiei

Polarized hyphal growth of filamentous pathogenic fungi is an essential event for host penetration and colonization. The long-range early endosomal trafficking during the hyphal growth is crucial for nutrient uptake, sensing of host-specific cues, and regulation of effector production. Bin1/Amphiphysin/Rvs167 (BAR) domain-containing proteins mediate fundamental cellular processes, including membrane remodeling and endocytosis. Here, we identified an F-BAR domain protein (ArF-BAR) in the necrotrophic fungus Ascochyta rabiei and demonstrate its involvement in endosome-dependent fungal virulence on the host plant, Cicer arietinum. We show that ArF-BAR regulates endocytosis at the hyphal tip, localizes to the early endosomes, and is involved in actin dynamics. Functional studies involving gene knockout and complementation experiments reveal that ArF-BAR is essential for virulence. The loss-of-function of ArF-BAR results in delayed formation of first septa from the hyphal tip, crucial for host penetration and proliferation. ArF-BAR was induced in response to oxidative stress and infection and localized to endocytic vesicles within the fungal hyphae. We also show that ArF-BAR is able to tubulate synthetic liposomes, suggesting the functional role of F-BAR domain in membrane tubule formation in vivo. Further, our studies identified a stress-induced transcription factor, ArCRZ1 (Calcineurin-responsive zinc finger 1) as key regulator for transcriptional reprogramming of ArF-BAR. We propose a model in which ArCRZ1 functions upstream of ArF-BAR to regulate fungal pathogenesis through a mechanism that involves membrane remodeling and actin cytoskeleton regulation. Author summaryBAR-domain superfamily is known to mold amorphous lipid bilayer into defined tubular shapes and critical for endosome formation and trafficking. Although these processes are studied earlier in the context of their structural and biochemical properties, there is limited evidence on the direct role of F-BAR domain proteins in the pathophysiological development of other economically important fungi. Our study assumes functional significance for plant infection as we identified an F-BAR domain-containing protein that is regulated by a distinct transcriptional network. We characterized F-BAR in a necrotrophic fungal pathogen, Ascochyta rabiei that causes the Ascochyta blight (AB) disease in chickpea plants. Additionally, we have also identified a calcium-regulated CRZ1 transcription factor that regulates the transcription of ArF-BAR. Our study will help to understand the complex interplay underlying the endosome formation required for fungal virulence.

plant biology↗