Biology subjects

Ahmad, S.

Publications and source records attributed to Ahmad, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Transcriptome-based lead generation, ligand- and structure-based prioritization and experimental validation of TLR5-activating molecules

Current in silico drug discovery protocols ubiquitously depend on lead generation using a ligand-based approach in which novel leads are generated by fragment-signature matching or by a structure-based search involving molecular docking and conformational dynamics. None of them incorporates cellular contexts in which these drugs ultimately operate, leaving the task to a later stage of optimization leading to a high failure rate. Incorporating systems-level responses of drugs in an early stage of lead generation can significantly address this concern but has not been sufficiently explored. In this work, we employ a systems-level approach using connectivity map (CMAP) library to generate leads against a challenging system of a TLR pathway. Starting with gene expression data of TLR5 activation by its natural ligand, we generated molecular leads using CMAP and rigorously analyzed their validity using ligand and structure-based approaches, and helping to prioritize top hits. Experimental validation using ELISA-based antibody assay confirmed the activation of TLR5 by each of the top nine prioritized leads with their dose-dependent patterns suggesting that some of them may actually interact with the TLR signaling pathway in a complex manner. Although, demonstrated on TLR5, the proposed framework is intuitively scalable to other lead generation and optimization tasks.

bioinformatics↗

bioRxiv2026

Sex shapes the human genitourinary microbiome, including many species recognized as uropathogens: urine profiles from a population-level shotgun metagenomics study

Background: The urinary tract was long considered sterile. The discovery of the urinary microbiome has attracted interest in its role in urinary health and disease. Population-level urinary microbiome composition remains poorly defined and previous studies relied on selected populations and low-resolution sequencing. We characterized the microbial composition of voided urine from adults without urinary symptoms in a large Swedish population cohort to establish a population-based reference for microorganisms detected in voided urine using shotgun metagenomics. Methods: We performed shotgun metagenomic sequencing of voided urine samples from 2,062 participants of the population-based Swedish CArdioPulmonary bioImage Study (SCAPIS; 55% women, 50-65 years). Results: Among 3,668 identified species, 90% were classified at the species level. Microbial profiles differed substantially between sexes, with lactobacilli and bifidobacteria enriched in females, while Cutibacterium acnes, Enterococcus and Propionimicrobium lymphophilum were enriched in males. Recognized uropathogens, including Enterococcus faecalis and Escherichia coli, were frequently detected despite participants having no urinary symptoms. Males showed higher alpha diversity (Shannon and inverse Simpson indices), whereas richness did not differ by sex. Age showed only modest associations with alpha diversity, and beta diversity differed by sex but showed minimal age-related variation. Conclusions: This study provides a population-based reference for interpreting microorganisms detected in routine voided urine samples. Biological sex was the principal determinant of microbial composition, supporting routine consideration of sex in future studies of the urogenital microbiota using routine voided urine samples.

microbiology↗

bioRxiv2025

The urinary pathobiont Actinobaculum massiliense generates androgens via the dirAB pathway

While overlooked during the Human Microbiome Project, characterizing the urinary microbiota in health and disease is a new frontier in microbiome science. Recent studies have associated differential abundance of bacterial taxa including Propionimicrobium lymphophilum and Actinobaculum/Actinotignum spp. with prostate cancer. In this study, we collected urine from subjects prior to prostate biopsy and applied a novel Human Sterolbiome Discovery High-throughput (HSDH) assay to identify culturable urinary bacteria with the ability to generate androgens. Application of the HSDH assay to urine samples led to the isolation of eight P. lymphophilum strains positive for cortisol side-chain cleavage (steroid-17,20-desmolase), 17{beta}-HSDH activity, or both. In addition, we isolated three strains of Actinobaculum massiliense that encode DHEA isomerase reductase (dir) genes. The dirA gene encodes a novel 3{beta}/17{beta}-hydroxysteroid dehydrogenase/{Delta}4,5-isomerase and the dirB gene encodes a novel 17{beta}-hydroxysteroid dehydrogenase isoform. Structural prediction and molecular dynamics reveal probable catalytic mechanisms based on the shared catalytic triad but distinct binding pocket geometries of the DirA and DirB that describe their respective reactions. Phylogenetic analysis of DirA and DirB revealed homologs in urinary tract commensals as well as bacteria associated with steroid degradation found in aquatic and terrestrial environments. Taken together, the development of the HSDH assay and the identification of the dir pathway genes is a significant advance in microbial endocrinology, laying the methodological foundation and providing the molecular basis for understanding the role of urinary tract bacteria in host endocrine physiology.

microbiology↗

bioRxiv2025

Targeting Ogt in ADPKD mitigates metabolic reprogramming and renal cystogenesis, extending survival

Aberrant cell metabolism drives autosomal dominant polycystic kidney disease (ADPKD). O-GlcNAcylation, a metabolically regulated post-translational modification, is elevated in ADPKD kidneys. Using rapidly and slowly progressive ADPKD mouse models, we demonstrate that deleting O-GlcNAc transferase (Ogt) reduces renal cystogenesis and extends survival in a rapidly progressive model from postnatal day 21 to over a year. Pharmacological OGT inhibition similarly reduced cyst formation of patient-derived renal epithelial cells in vitro. In Pkd1 conditional knockout kidneys, Ogt deletion maintained phosphorylated AMPK and mitochondrial respiratory chain complex levels, preserving cellular energy sensing and production. Further, metabolomic analysis revealed normalization of glycolysis and of the hexosamine and hyaluronic acid biosynthesis pathways. In contrast, dysregulation of these pathways in Pkd1 conditional knockout kidneys culminated in increased tricarboxylic acid cycle entry, increased O-GlcNAc, and increased hyaluronic acid in the extracellular matrix, respectively. These findings identify Ogt as a central metabolic regulator and therapeutic target, linking metabolism to intracellular and extracellular mechanisms of cyst formation.

cell biology↗

bioRxiv2025

Emergence and spread of outbreak-adapted Candidozyma auris harboring mutations in RBA1

Candidozyma auris is an emerging healthcare-associated fungal pathogen, increasingly isolated from clinical outbreaks, with a high propensity to colonize patients and the medical environment. Here, we leveraged C. auris isolates from multi-facility clinical outbreaks to identify genomic patho-adaptations promoting persistence and dissemination in the healthcare environment. Genomic and phylogenetic analyses revealed loss-of-function mutations in the uncharacterized C. auris transcription factor gene RBA1 to have independently emerged multiple times within these outbreaks. We demonstrate loss of RBA1 increases C. auris adhesion to plastic and human keratinocytes, enhances biofilm formation, and exacerbates fungal burden in a mouse model of catheter-associated urinary tract infection. Finally, we uncover mutations in RBA1 have emerged during multiple C. auris outbreaks across the globe, and that RBA1 mutant lineages are present among large ongoing clinical outbreaks. These results reveal loss-of-function mutations in C. auris RBA1 as a novel and clinically relevant genetic determinant of enhanced outbreak characteristics.

microbiology↗

bioRxiv2025

Local extraction of predatory fish may initiate behaviourally mediated trophic cascades in coral reefs in the Andaman Islands.

Humans disproportionately target predators due to their higher economic and social value. This has led to widespread declines of predators in ecosystems worldwide leading to far-reaching effects on ecosystem processes. We investigate how the loss of predators from nearshore ecosystems due to fishing affects individual prey behaviour using a gradient of protection as a natural experiment. We collected data on piscivorous predator assemblages, reef habitats and prey behaviour within and outside two marine protected areas (MPAs) in the South Andaman Islands, India. As expected, predator abundance was significantly greater within MPAs. Similarly, we found greater coral cover and reduced algal cover within MPAs. In response, prey species, which included herbivorous and invertivorous fish, exhibited reduced movement and heightened vigilance inside MPAs. Additionally, prey individuals foraged at higher rates within MPAs. Habitat complexity and resource availability had complex effects on prey behaviours that varied across guilds. Our findings suggest that fishing directly alters the seascape of fear through the removal of predators. Fishing may also shape prey behaviour and ecological interactions indirectly through habitat degradation. Overall, this study highlights the need to study both direct and indirect consequences of human interactions with wild animals to understand their combined impacts on ecosystems.

ecology↗

bioRxiv2025

Cell clusters are programmed towards a reductive metabolic 1 state by adherence junctions

Solitary cells form stable clusters via cell-cell adhesion using adherens junctions. The role of these junctions in early cell-state changes as cells form clusters is unclear. Here, we uncover that the formation of cadherin junctions as cells cluster drives a ubiquitous metabolic reprogramming. This reprogramming enhances the pentose phosphate pathway (PPP) and NADPH production to augment a reductive state. Consequently, cell clusters stabilized by cadherin junctions have reduced intracellular reactive oxygen species (ROS), are resistant to exogenous ROS-inducing agents, and have reduced apoptotic markers. Mechanistically, this metabolic reprogramming is driven by the cadherin-dependent activation of NRF2. Blocking the cadherin junction-dependent metabolic program reverses clustered cells to resemble the solitary cell state, increasing cell death and enhancing sensitivity to exogenous ROS. These insights suggest a biochemical basis for adherens junctions mediating a reductive metabolic program as solitary cells form clusters, with implications for understanding multicellular organization and collective cell behavior.

cell biology↗

bioRxiv2025

Co-circulation of distinct high pathogenicity avian influenza virus (HPAIV) subtypes in a mass mortality event in wild seabirds and co-location with dead seals

H5Nx clade 2.3.4.4b high pathogenicity avian influenza viruses (HPAIV) have been detected repeatedly in Great Britain (GB) since autumn 2020, with H5N1 dominating detections but with low level detection of H5N5 during 2025. Globally, these viruses have caused mass mortalities in captive and wild avian and mammalian populations, including terrestrial and marine mammals. H5N1 has been the dominant subtype, and whilst incursions have overlapped temporally, occurrences have often been spatially distinct. Here, we report the detection of a mortality event in wild birds on the Norfolk coastline in the east of England, where H5N1 HPAIV was detected in five Great Black-backed Gulls (Larus marinus) and a Northern Fulmar (Fulmarus glacialis). Interestingly, at the same site, and as part of the same mortality event, a total of 17 Great Black-backed Gulls, one Herring Gull (Larus argentatus), one Atlantic Puffin (Fratercula arctica) and one Northern Fulmar tested positive for H5N5 HPAIV. Additionally, H5N5 was also detected in 17 co-located Grey Seal carcases (Halichoerus grypus). The H5N1 HPAIV from an infected bird belonged to genotype DI.2, closely related to contemporaneous detections in GB wild birds and poultry. In contrast, all H5N5 HPAIVs from birds and seals were genotype I with a 22-amino acid stalk deletion in NA and the 627K polymorphism in PB2. This represents the first recorded instance in GB of two subtypes being detected within the same avian population at the same location. It is also the first mass detection of HPAIV H5N5 in mammals within GB. Potential infection mechanisms are discussed.

genetics↗

bioRxiv2025

An increased excitation and inhibition onto CA1 pyramidal cells sets the path to Alzheimer s disease

Synapses are critical targets of Alzheimers disease (AD), a highly prevalent neurodegenerative disease associated with accumulation of extracellular amyloid-{beta} peptides. Although amyloidosis and aggregation of the 42-amino acid amyloid-{beta} (A{beta}42) have long been considered pathogenic triggers for AD, clinical evidence linking high levels of A{beta}42 with normal cognition challenges this hypothesis. To resolve this conundrum on the role of A{beta}42 in regulating synaptic activity, we used an adeno-associated viral vector approach that triggers extracellular accumulation of A{beta}42 and spatial memory impairment. We show that A{beta}42 leads to an early increase in excitatory and proximal inhibitory synaptic transmission onto hippocampal CA1 pyramidal cells, and an increased expression of the glutamate transporter GLT-1 in these cells. A{beta}42 accumulation does not cause early cognitive deficits unless accompanied by an increased neuronal GLT-1 expression, suggesting this transporter is a critical mediator of A{beta}42s effects. These findings unveil key molecular and cellular mechanisms implicated with AD pathogenesis.

neuroscience↗

bioRxiv2025

From Shadows to Data: A Robust Population Assessment of Snow Leopards in the Highland Crossroads

The snow leopard (Panthera uncia) is a flagship species of the greater Himalayan region - referred to as the Third Pole - and symbolizes integrity of this ecological system. Within the greater Himalayas, Pakistan holds special significance as the north of the country represents a confluence of four major mountain ranges (Hindu Kush, Pamir, Karakoram, and Himalaya). However, robustly surveying and monitoring elusive, low-density species such as snow leopards has historically been difficult in the region. As a result, our understanding of the spatial patterns in density and overall population size of snow leopards has remained conjectural in the highland crossroads of northern Pakistan. This lack of objective information is an obstacle to realizing effective conservation planning for the species in Pakistan, as well as the broader ecosystem within which it plays a key role. This study aimed to empirically derive population estimates for snow leopards in Pakistan, based on robust camera trapping. Extensive camera trapping was conducted covering about 39% of the snow leopard range in Pakistan from 2010 to 2019, spread across the four major mountain ranges in the north of the country. A total of 828 cameras were placed over 26,540 trap days, resulting in 4,712 photos of snow leopards obtained from 65 different locations. Among the 53 unique individuals identified, the majority (53%) were detected only once, with an overall recapture frequency of 2.28 times per individual. Spatial capture-recapture (SCR) was employed for population and density estimation. Model selection strongly favored a model in which density was positively associated with elevation, and camera type influenced baseline encounter rates. The estimated population size for snow leopards in this highland crossroads was 127 (95% CI 88-182) adult animals, with a mean density of 0.13 (95% CI 0.09-0.19) animals per 100 km{superscript 2}. Examination of the density predictions revealed that higher density areas were associated with protected areas and greater prey biomass, highlighting the importance of these two key factors. This research provides the first robust population estimate for snow leopards in this region, establishing a foundation for long-term population monitoring and assessing the effectiveness of conservation measures. We recommend the integration of complementary approaches, such as non-invasive genetic methods, to validate and refine population estimates.

ecology↗

bioRxiv2025

Spatial statistics of submicron size clusters of activating and inhibitory Natural Killer cell receptors in the resting state regulate early time signal discrimination

Natural Killer (NK) cells are lymphocytes of the innate immunity and sense healthy or diseased target cells with activating and inhibitory NK cell receptor (NKR) molecules expressed on the cell surface. The protection provided by NK cells against viral infections and tumors critically depends on their ability to distinguish healthy cells from diseased target cells that express 100- fold more activating ligands. NK cell signaling and activation depend on integrating opposing signals initiated by activating and inhibitory NKRs interacting with the cognate ligands expressed on target cells. A wide range of imaging experiments have demonstrated aggregation of both activating and inhibitory NKRs in the plasma membrane on submicron scales in resting NK cells. How do these submicron size NKR clusters formed in the resting state affect signal discrimination? Using in silico mechanistic signaling modeling with information theory and published superresolution imaging data for two well-studied human NKRs, activating NKG2D and inhibitory KIR2DL1, we show that early time signal discrimination by NK cells depends on the spatial statistics of these clusters. When NKG2D and KIR2DL1 clusters are disjoint in the resting state, these clusters help NK cells to discriminate between target cells expressing low and high doses of the activating cognate ligand, whereas, when the NKR clusters fully overlap the NK cells are unable to distinguish between healthy and diseased target cells. Therefore, the spatial statistics of submicron scale clusters of activating and inhibitory NKRs at the resting state provides an additional layer of control for signal discrimination in NK cells. SignificanceSignal integration of opposing signals initiated by activating and inhibitory NK cell receptors (NKRs) in a noisy environment determine an NK cells response to healthy and diseased target cells. Superresolution microscopy imaging revealed aggregation of NKRs in submicron scales in resting NK cells. Using computational modeling, information theory, and published imaging data, we show when these clusters of the opposing NKRs are disjoint, the NK cells can separate healthy from diseased target cells but fail to do so when the clusters overlap. Thus, spatial statistics of submicron-sized NKR clusters in the resting state provide a lever for distinguishing self from non-self. The results suggest spatial organization of receptors in the resting state in may modulate signal discrimination in immune cells.

immunology↗

bioRxiv2025

Visualizing the transcription and replication of influenza A viral RNAs in cells by multiple direct RNA padlock probing and in-situ sequencing (mudRapp-seq)

Influenza A viruses (IAV) contain eight negative-sense single-stranded viral RNA (vRNA) molecules, which are transcribed into mRNA and replicated via complementary RNA (cRNA). These processes are tightly regulated, but the precise molecular mechanisms governing the switch from transcription to replication remain elusive. Here, we introduce multiple direct-RNA assisted padlock probing in combination with in situ sequencing (mudRapp-seq) to visualize the transcription and replication of all eight IAV vRNA and mRNA molecules at the single-cell level. We demonstrate that direct RNA padlock probing is three times more efficient than conventional probes that target cDNA. Individual probes showed variations in efficiency, partly due to the RNA structure of the target, which was mitigated by employing multiple padlock probes per target. Applying mudRapp-seq to an infection time course, we observed early mRNA expression, followed by vRNA accumulation approximately 3 hours later. Individual viral segments exhibited differential expression, particularly in the mRNA population. Both bulk and single-cell analyses revealed a correlation between the expression of M mRNA and the onset of the transcription-to-replication switch. Our findings demonstrate that mudRapp-seq offers significant potential for elucidating viral replication mechanisms and may be applicable to studying other RNA viruses and cellular RNA processes.

microbiology↗

bioRxiv2025

Biophysical characterization of Eag chaperones suggests the mechanism of effector transmembrane domain release

The type VI secretion system (T6SS) is a dynamic protein nanomachine found in Gram- negative bacteria that secretes toxic effectors into prey-cells. For secretion, effectors require chaperones or adaptors for proper loading onto the T6SS. Effector associated genes (Eags) are a family of T6SS chaperones that stabilize N-terminal transmembrane domains (TMDs) found in thousands of effectors. Eags are essential for secretion and inhibit effector TMDs from prematurely adopting a membrane-penetrative conformation. However, the mechanism of TMD release from its cognate Eag chaperone is unknown. Here, we take a biochemical and biophysical approach to probe the mechanism of TMD binding and dissociation from Eag chaperones. Using steady-state fluorescence, stopped-flow measurements, and bacterial competition assays, we compare the thermodynamics, kinetics, and in vivo chaperone function of wild-type and point-variant Eag-TMD complexes. Additionally, we solve an X-ray crystal structure of an Eag-TMD point-variant complex that captures an intermediate state of TMD release. Our data reveals the molecular features and specific residue contacts necessary for TMD binding and demonstrates the Eag conformational change required to initiate rapid release of the TMD. Overall, our work details the stability of Eag-TMD complexes and the energetic pathway for the dissociation of effector TMDs from their Eag chaperones.

biochemistry↗

bioRxiv2025

A Pan-Cancer, Pan-Treatment (PCPT) Model For Predicting Drug Responses From Patient-Derived Xenografts With Application To Cancer Types With Sparse Training Data

Predicting personalized treatment-specific responses in cancer patients requires not only robust experimental models such as PDX, which generate accurate training data on different treatment responses for the same model, but also computational models that can translate this knowledge into decisions for real patients in a timely manner. The translatability of PDX data into patient-specific outcomes is limited by the challenges in the data size requirements for training machine learning models. Previously, ML models have been developed for the two most abundant cancer types, viz. BRCA and CRC, but the same could not be scaled up to other cancer types with a smaller number of PDX samples. Here, we provide an ML framework to train a single pan-cancer, pan-treatment model for predicting treatment outcomes. We show that such models give promising results for all cancer types considered and reproduce the accuracy levels of individually trained cancer types. In the proposed model, all PDX genomic profiles from all cancer types are used as the training data, and instead of partitioning them into cancer types for each model, the cancer type and treatment name are appended as the input features of the training model. Using genomic-only and treatment-only embeddings and combining them with PCA-based dimensionality reduction, our models show promising results and provide a framework for further improvements and real-time use for best treatment selections for cancer patients. Data and Code AvailabilityAll raw and processed data, along with analysis scripts, are available at: https://github.com/Sciwhylab/pcpt

bioinformatics↗

bioRxiv2025

Enantioselective Protein Affinity Selection Mass Spectrometry (EAS-MS)

We report an enantioselective protein affinity selection mass spectrometry screening approach (E-ASMS) that enables the detection of weak binders, informs on selectivity, and generates orthogonal confirmation of binding. After method development with control proteins, we screened 31 human proteins against a designed library of 8,210 chiral compounds. 16 binders to 12 targets, including many proteins predicted to be "challenging to ligand", were discovered and confirmed in orthogonal biophysical assays. 7 binders to 6 targets bound in an enantioselective manner, with KD values ranging from 3 to 20 {micro}M. Binders for four targets (DDB1, WDR91, WDR55, and HAT1) were selected for in-depth characterization using X-ray crystallography. In all four cases, the mechanism for enantioselectivity was readily explained. We conclude E-ASMS can be used to identify and characterize selective and weakly-binding ligands for novel protein targets with unprecedented throughput and sensitivity.

pharmacology and toxicology↗

bioRxiv2025

Predicting Personalised Therapeutic Combinations in Non-Small Cell Lung Cancer Using In Silico Modelling

The disease burden from non-small cell lung cancer (NSCLC) adenocarcinoma is substantial, with around a million new cases diagnosed globally each year, and a 5-year survival rate of less than 20%. A lack of therapeutic options personalized to individual patient genetics, and the targeted therapies that exist quickly succumbing to resistance, leads to high variation in survival. Patient stratification combined with greater personalisation of therapies have the potential to improve outcomes, however, the wide variation in mutations found in NSCLC adenocarcinoma patients mean that experimentally determining suitable treatment combinations is time-consuming and expensive. Here we present an in silico model encompassing tumour intrinsic key oncogenic signalling pathways, including EGFR, AKT, JAK/STAT and WNT for efficiently predicting rational drug-drug and drug-radiotherapy combination therapies in NSCLC. Using this model, we simulate diverse genetic profiles and test over 10,000 therapeutic combinations to identify optimal strategies to overcome resistance mechanisms specific to genetic profiles and p53 status. Our in silico model reproduces drug additivity experiments, predicts radio-sensitising genes validated in a CRISPR screen and identifies 53BP1 as a potential drug target that improves the therapeutic window during radiotherapy, as well as potential to use ATM inhibitors to overcome p53 loss-of-function driven radiotherapy resistance. We further use the in silico model to identify a 19-gene signature to stratify patients most likely to benefit from radiotherapy and validated this using TCGA data. These results further demonstrate the utility of in silico mechanistic modelling and present a bespoke computational resource for large-scale screening of personalised therapies applied to NSCLC.

cancer biology↗

bioRxiv2025

A framework integrating multiscale in-silico modeling and experimental data predicts CD33 CAR-NK cytotoxicity across target cell types

Uncovering mechanisms and predicting tumor cell responses to CAR-NK cytotoxicity is essential for improving therapeutic efficacy. Currently, the complexity of these effector-target interactions and the donor-to-donor variations in NK cell receptor (NKR) repertoire require functional assays to be performed experimentally for each manufactured CAR-NK cell product and target combination. Here, we developed a computational mechanistic multiscale model which considers heterogenous expression of CARs, NKRs, adhesion receptors and their cognate ligands, signal transduction, and NK cell-target cell population kinetics. The model trained with quantitative flow cytometry and in vitro cytotoxicity data accurately predicts the short- and long- term cytotoxicity of CD33CAR-NK cells against leukemia cell lines across multiple CAR designs. Furthermore, using Pareto optimization we explored the effect of CAR proportion and NK cell signaling on the differential cytotoxicity of CD33CAR-NK cells to cancer and healthy cells. This model can be extended to predict CAR-NK cytotoxicity across many antigens and tumor targets.

cancer biology↗

bioRxiv2024

Replication stress increases de novo CNVs across the malaria parasite genome

Changes in the copy number of large genomic regions, termed copy number variations (CNVs), contribute to important phenotypes. CNVs are readily identified using conventional approaches when present in a large fraction of the cell population. However, CNVs in only a few genomes are often overlooked but important; if beneficial, a de novo CNV that arises in a single genome can expand during selection to create a population of cells with novel characteristics. While single cell methods for studying de novo CNVs are increasing, we continue to lack information about CNV dynamics in rapidly evolving microbial populations. Here, we investigated de novo CNVs in the genome of the Plasmodium parasite that causes human malaria. The highly AT-rich P. falciparum genome readily accumulates CNVs that facilitate rapid adaptation. We employed low-input genomics and specialized computational tools to evaluate the impact of sub-lethal stress on the de novo CNV rate. We observed a significant increase in genome-wide de novo CNVs following treatment with an antimalarial compound that inhibits replication. De novo CNVs encompassed genes from various cellular pathways participating in human infection. This snapshot of CNV dynamics emphasizes the connection between replication stress, DNA repair, and CNV generation in this important microbial pathogen.

genomics↗