Biology subjects

Aggarwal, D.

Publications and source records attributed to Aggarwal, D..

10 recordsLinked to original sources

bioRxiv2026

Molecular anatomy of the entorhinal cortex

The entorhinal cortex (EC) is critical for episodic memory formation and is the epicenter of neurofibrillary tangle formation in Alzheimer's disease. Its cytoarchitectonic and functional heterogeneity has been recognized for decades, but the molecular underpinnings of this heterogeneity are still relatively uncharted. While many features of the region appear to be conserved between rodents and primates, very little is known about the conservation of the molecular identity of EC neurons. Here we perform single-nucleus RNAseq (snRNAseq) of the mouse EC and use in situ hybridization, as well as publicly available transcriptomics data, to enhance the understanding of the heterogeneity of neuron types present in the area. While the well-known dichotomy between lateral and medial EC is evident in superficial layers of EC, we highlight that the medioventral region of EC forms a different population from the caudomedial section. We identify molecular correlates for the previously described parcellation of lateral EC, and show that, at least in layer IIa, subterritories of EC are not separated by abrupt borders but rather form smooth gradients. Lastly, we show that both lateral vs. medial ECIIa markers, and markers that reveal finer grain heterogeneity within ECIIa have conserved patterns of expression in macaque, highlighting the high degree of homology between the two species. Overall this molecular atlas of the mouse EC with some comparative elements is a resource for anatomically-informed molecular studies of the EC and lays the groundwork for mechanistic studies of selective neuronal vulnerability of the region in the context of AD.

neuroscience↗

bioRxiv2026

Structural Insights into the Expanded Substrate Scope of a Cysteine-Dependent Hydrolase from Rhodococcus opacus for Polyethylene, Polypropylene, and Polystyrene Biodegradation

Microplastic pollution from homopolymers such as polypropylene (PP), polystyrene (PS), and polyethylene (PE) poses growing health and environmental concerns, highlighting the need for robust polymer-degrading biocatalysts. We previously identified a naturally occurring cysteine-dependent hydrolase (CsdH) from Rhodococcus opacus, featuring a unique Cys160-Lys127-Asp39 catalytic triad and providing a novel mechanism for polyethylene terephthalate (PET) degradation. In this study, we have determined crystal structures of CsdH in complex with PP, PS, PE, and styrene and demonstrated the potential of the enzyme to directly degrade these homopolymers into their respective low molecular weight degradation products using LC-MS. Structural analysis reveals that the enzyme retains a conserved principal access tunnel while undergoing subtle substrate-dependent changes to accommodate different substrates. The enzyme exhibited broad plastic degradation activity with the highest weight loss observed for PE, followed by PP and PS. SEM analysis reveals surface roughness, cracks and grooves, confirming polymer degradation. Further, these results corroborate through FTIR and TGA analysis. These findings establish a strong foundation for enzyme engineering and aim at developing efficient microplastic degradation.

biophysics↗

bioRxiv2026

Utilization of cyanobacterial siderophore cyanochelin B by phylogenetically distant heterotrophs suggest its role in mediating microbial interactions

Cyanobacteria are key prokaryotic primary producers in diverse ecosystems, yet the role of cyanobacterial siderophores in shaping their associated microbiomes remains unexplored. Our study demonstrates the benefits provided to the heterotrophic co-habitants of filamentous cyanobacteria in terrestrial microbial biofilms, focusing on the recently discovered widespread siderophores cyanochelins. To address the acceptance of cyanochelin B (CychB) across multiple bacterial classes, we first investigated its role in providing iron to a model siderophore producer P. aeruginosa PAO1 and selected Pseudomonas natural isolates, which were found to utilize CychB under iron limiting conditions while downregulating endogenous siderophore production. In response to CychB, PAO1 expresses a siderophore internalization cluster, which is localized in multiple Pseudomonas natural isolates. Using metagenome analysis, we characterized the bacterial community recruited along with CychB producing Phormidesmis cyanobacteria under long-term iron starvation. Potential CychB acceptor bacteria associated with the CychB producer were predominantly lacking endogenous siderophore machineries. Using siderophore selective pressure, we isolated a genuine CychB acceptor, gram-negative bacterium Methyloversatilis sp. S146 and demonstrated that its genome hosts an iron processing cluster overexpressed after CychB feeding, recognizing Methyloversatilis as a candidate for further mechanistic investigation of iron acquisition-driven microbial interactions. Our results indicate that CychB supports a specific subset of co-habiting heterotrophic bacteria during iron starvation, further emphasizing the role of cyanobacteria as key drivers of nutrient flows within globally important microbial soil crust ecosystems, supporting microbial life in nutrient-limited environments. These findings provide a mechanistic foundation to elucidate the role of cyanochelins as a public good in these communities.

microbiology↗

bioRxiv2026

Patient-derived organoid xenografts reveal the multifaceted role of the lncRNA MALAT1 in breast cancer progression

Long non-coding RNAs (lncRNAs) have emerged as key regulators of tumor biology, however, thus far none have translated to cancer therapies. The lncRNA MALAT1 is overexpressed in more than 20 cancers, including breast cancer and has been shown to function via various mechanisms in a context-dependent manner, in 2D cell lines and mouse models. However, its functional role and therapeutic potential have not been evaluated in clinically relevant patient-derived models. We investigated the therapeutic potential of MALAT1-targeting antisense oligonucleotides (ASOs) for breast cancer, using clinically relevant 3D human patient-derived organoids (PDOs) and PDO-xenograft (PDO-X) models. We systematically evaluated the efficiency of MALAT1-targeting ASOs using a biobank of 28 PDO models. Across three independent PDO-X models of triple negative breast cancer (TNBC), MALAT1 depletion reproducibly drove widespread alternative splicing changes across all event types, with an enrichment of intron retention. Differentially spliced transcripts were enriched for targets of shared cancer-associated transcription factors, and MALAT1 knockdown specifically altered the relative abundance of previously unannotated splicing isoforms. Beyond tumor-intrinsic effects, tumor-specific MALAT1 depletion induced a consistent reduction in macrophage-associated gene signatures and reduced lung metastatic burden. Our data defines MALAT1s multifaceted role in TNBC, coordinating alternative splicing, tumor-stroma crosstalk, and metastatic progression. Our study provides strong preclinical evidence supporting MALAT1-targeted ASO therapy and establishes PDO-X models as a clinically relevant platform for functional interrogation of TNBC therapies. SignificanceUsing clinically relevant human PDO-X models, we show that MALAT1 influences alternative splicing, metastatic potential and the tumor microenvironment. These data support the potential of oncogenic lncRNA MALAT1 as a therapeutic target.

cancer biology↗

bioRxiv2025

Unveiling the PET plastics degradation potential of the thermostable EstS1 esterase through integrated biochemical, structural, and morphological analyses

Enzymatic polyethylene terephthalate (PET) plastic degradation is a promising approach to combat the exploding plastic pollution. EstS1, a pH-tolerant, thermostable esterase, has been previously recognized for its degradation potential against phthalate diester plasticizers. The present study elucidates the exceptional potential of this enzyme to degrade crystalline PET plastic and its primary intermediate, bis(2-hydroxyethyl)terephthalate (BHET), into terephthalate. Kinetic analyses revealed that EstS1 degrades 75% of BHET in 1h, liberating mono(2-hydroxyethyl) terephthalate (MHET) and terephthalate as end products. The co-crystal structure of wild-type EstS1 with BHET exhibited the electron density of BHET, MHET, and ethylene glycol, including MHET bound at the active site, in a canonical tetrahedral intermediate conformation. The complex structure of BHET with the Ser154Ala mutant of EstS1 further accommodated two BHET molecules, one interacting directly with the catalytic triad and the oxyanion hole. MD simulation analysis revealed highly stable interactions of BHET at the active site of EstS1. Moreover, SEM imaging displayed significant degradation of the crystalline PET plastic film by EstS1 esterase over a period of 15 days, both under controlled and soil-based fluctuating environmental conditions, highlighting its versatility to varying environmental conditions. XPS analysis discovered the increase in -C-O-, -C-N-, -N-H-, and -N=O- bonds at the surface of EstS1-treated PET film, indicating effective degradation. Consequently, this comprehensive kinetic, structural, and morphology-based analysis of the PET-degrading potential of EstS1 esterase encourages further enzyme engineering studies to exploit the dual potential of EstS1 esterase to degrade both plastic and plasticizers.

biophysics↗

bioRxiv2025

Paraventricular Thalamus Hyperactivity Mediates Stress-Induced Sensitization of Unlearned Fear but Not Stress-Enhanced Fear Learning (SEFL)

Exposure to stress can cause long-lasting enhancement of fear and other defensive responses that extend beyond the cues or contexts associated with the original traumatic event. These nonassociative consequences of stress, referred to as fear sensitization, are thought to underlie some symptoms of trauma-related disorders. Fear sensitization has been predominately studied using the Stress-Enhanced Fear Learning (SEFL) paradigm, which models the stress-induced amplification of fear learning. Less is known about the mechanisms through which unlearned fear responses are sensitized by stress. Here, we investigated the neural mechanisms for sensitization of unlearned fear responses using a paradigm we termed Stress-Enhanced Fear Responding (SEFR). In this model, mice exposed to a single session of footshock stress exhibit enhanced freezing to a novel tone stimulus. To investigate brain regions that might mediate SEFR, we first used c-Fos mapping to identify neural activity changes associated with stress-induced enhancement of unlearned fear. Our c-Fos screen identified the posterior paraventricular thalamus (pPVT) as a region that was persistently hyperactive after footshock stress and whose activity correlated with behavioral expression of SEFR. Using fiber photometry, we observed that SEFR, but not SEFL, was associated with increased activity in the pPVT. Next, we found that chemogenetic inhibition of the pPVT blocked both the induction of SEFR during stress and its later expression, while artificial stimulation of pPVT in stress-naive mice was sufficient to recapitulate SEFR. Interestingly, pPVT inhibition or stimulation did not affect acquisition or expression of SEFL. In conclusion, our results indicate that sensitization of fear learning (SEFL) and sensitization of unlearned fear (SEFR) have distinct neural mechanisms. Our results identify pPVT hyperactivity as a mechanism for stress-induced sensitization of unlearned fear and highlight pPVT as a potential target for treating arousal and reactivity symptoms of trauma- and stressor-related disorders.

neuroscience↗

bioRxiv2025

BaGPipe: an automated, reproducible, and flexible pipeline for bacterial genome-wide association studies

Microbial genome-wide association study (GWAS) tools often require manual data processing steps, lack comprehensive workflows, and are limited by scalability issues, thus hindering the exploration of bacterial genetic traits. To address these challenges, we developed BaGPipe, an automated and flexible bacterial GWAS pipeline built using Nextflow and incorporating Pyseer for association analysis. BaGPipe integrates all essential components of a bacterial GWAS--spanning pre-processing, statistical analysis, and downstream visualisation--into a unified workflow that is reproducible and easy to deploy across diverse computational environments. BaGPipe was validated on a publicly available dataset of Streptococcus pneumoniae whole-genome sequences, and reproduced published findings with improved computational efficiency. BaGPipe was then applied to a dataset of Staphylococcus aureus whole-genome sequences, successfully identifying known and novel antibiotic resistance associations. By offering an accessible, efficient, and reproducible platform, BaGPipe accelerates bacterial GWAS and facilitates deeper exploration into the genetic underpinnings of phenotypic traits. Impact StatementThe increasing availability of bacterial genome sequences has created an opportunity for robust, reproducible tools to facilitate the discovery of novel genotype-phenotype associations. Despite the demonstrated utility of genome-wide association studies (GWAS) in identifying genetic determinants of disease, toxicity and antibiotic resistance, existing tools for bacterial GWAS often involve fragmented workflows requiring extensive manual intervention, limiting their adoption and reproducibility. Here, we introduce BaGPipe, a fully integrated bacterial GWAS pipeline that automates pre-processing, statistical analysis, and visualisation, thereby streamlining the entire workflow. With its flexibility, scalability, and ease of use, BaGPipe makes bacterial GWAS more accessible to researchers, enabling faster and more reliable insights into microbial genetics. This is an important step towards overcoming the computational and logistical barriers that have constrained bacterial GWAS, ultimately accelerating research into microbial evolution, resistance mechanisms, and the genetic basis of other key phenotypic traits. Data SummaryBaGPipe is freely available at https://github.com/sanger-pathogens/BaGPipe. The Streptococcus pneumoniae input dataset is available from the Pyseer tutorial (https://pyseer.readthedocs.io/en/master/tutorial.html#). The Staphylococcus aureus sequencing assemblies can be sourced from their ERS accession numbers provided in supplementary data. The reference assemblies, listed in the supplementary, can be sourced from NCBI.

bioinformatics↗

bioRxiv2024

MARK2/MARK3 kinases are catalytic co-dependencies of YAP/TAZ in human cancer

The Hippo signaling pathway is commonly dysregulated in human cancer, which leads to a powerful tumor dependency on the YAP/TAZ transcriptional coactivators. Here, we used paralog co-targeting CRISPR screens to identify the kinases MARK2/3 as absolute catalytic requirements for YAP/TAZ function in diverse carcinoma and sarcoma contexts. Underlying this observation is direct MARK2/3-dependent phosphorylation of NF2 and YAP/TAZ, which effectively reverses the tumor suppressive activity of the Hippo module kinases LATS1/2. To simulate targeting of MARK2/3, we adapted the CagA protein from H. pylori as a catalytic inhibitor of MARK2/3, which we show exerts anti-tumor activity in vivo. Together, these findings reveal MARK2/3 as powerful co-dependencies of YAP/TAZ in human cancer; targets that may allow for pharmacology that restores Hippo pathway-mediated tumor suppression.

cancer biology↗

bioRxiv2022

The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK

The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.

evolutionary biology↗

bioRxiv2020

Genetic differences between extreme and composite constitution types from whole exome sequences reveal actionable variations

Personalized medicine relies on successful identification of genome-wide variations that governs inter-individual differences in phenotypes and system level outcomes. In Ayurveda, assessment of composite constitution types "Prakriti" forms the basis for risk stratification, predicting health and disease trajectories and personalized recommendations. Here, we report a novel method for identifying pleiotropic genes and variants that associate with healthy individuals of three extreme and contrasting "Prakriti" constitutions through exome sequencing and state-of-the-art computational methods. Exome Seq of three extreme Prakriti types from 108 healthy individuals 54 each from genetically homogeneous populations of North India (NI, Discovery cohort) and Western India (VADU, Replication cohort) were evaluated. Fishers Exact Test was applied between Prakriti types in both cohorts and further permutation based p-value was used for selection of exonic variants. To investigate the effect of sample size per genetic association test, we performed power analysis. Functional impact of differentiating genes and variations were inferred using diverse resources -Toppfun, GTEx, GWAS, PheWAS, UK Biobank and mouse knockdown/knockout phenotype (MGI). We also applied supervised machine learning approach to evaluate the association of exonic variants with multisystem phenotypes of Prakriti. Our targeted investigation into exome sequencing from NI (discovery) and VADU (validation) cohorts datasets provide ~7,000 differentiating SNPs. Closer inspection further identified a subset of SNPs (2407 (NI) and 2393 (VADU)), that mapped to an overlapping set of 1181 genes. This set can robustly stratify the Prakriti groups into three distinct clusters with distinct gene ontological (GO) enrichments. Functional analysis further strengthens the potential pleiotropic effects of these differentiating genes/variants and multisystem phenotypic consequences. Replicated SNPs map to some very prominent genes like FIG4, EDNRA, ANKLE1, BCKDHA, ATP5SL, EXOCS5, IFIT5, ZNF502, PNPLA3 and IL6R. Lastly, multivariate analysis using random forest uncovered rs7244213 within urea transporter SLC14A2, that associate with an ensemble of features linked to distinct constitutions. Our results reinforce the concept of integration of Prakriti based deep phenotypes for risk stratification of healthy individuals and provides markers for early actionable interventions.

genomics↗