Biology subjects

Khan, A.

Publications and source records attributed to Khan, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

The serine protease homolog Skanda modulates Toll-Phenoloxidase-mediated immunity in Drosophila

Extracellular serine protease (SP) cascades are central regulators of insect innate immunity. These cascades are negatively controlled by serine protease inhibitors (serpins) and fine-tuned by serine protease homologs (SPHs), which resemble SPs but lack catalytic activity. In Drosophila, a key SP cascade--the Toll-phenoloxidase (PO) pathway--governs both the melanization response and Toll-dependent antimicrobial peptide production. This cascade is triggered by secreted pattern-recognition receptors or microbial proteases and converges on two clip-domain SPs, Persephone and Hayan, which activate the Toll ligand Spatzle via the Spatzle-Processing Enzyme (SPE) and process prophenoloxidases. Here, we characterize the SPH Skanda and uncover its role in the Toll-PO cascade. skanda is genomically clustered with hayan and persephone and is transcriptionally induced upon infection. Skanda is unusual among SPHs, containing a long serine/threonine-rich region, two clip domains, and atypical disulfide bonds. Skanda is unstable and subject to cleavage by Grass. Functional assays show that Skanda dampens activation of Hayan, and to a lesser extent Persephone, within the Toll-PO cascade. Notably, skanda-deficient flies are highly susceptible to Staphylococcus aureus despite displaying normal Toll signaling and cuticular melanization. Moreover, compound mutants lacking two members of the hayan-psh-skanda cluster reveal a hidden contribution of Skanda to Toll activation in the absence of Persephone. Together, our results identify Skanda as a modulatory SPH that fine-tunes Toll pathway activity in concert with Persephone and Hayan.

immunology↗

bioRxiv2025

Editing-independent effects of Adar in Drosophila melanogaster

Vertebrate ADAR RNA editing enzymes prevent cellular dsRNA from aberrantly activating antiviral dsRNA sensors. ADARs inhibit antiviral sensor activation by deaminating selected adenosines to inosines in dsRNA and by engaging in inhibitory protein interactions with sensors on dsRNA. ADARs interact with Dicers and, in the Drosophila Adar5G1 null mutant Dicer 2 acts as the antiviral dsRNA sensor mediating aberrant innate immune induction. We overexpressed active Adar isoforms or a catalytically-inactive Adar E374A protein from UAS-Adar constructs under the control of a temperature-regulated Act5Cts-GAL4 driver. Overexpression of the edited AdarG isoform or AdarEA cause larval lethality with aberrant innate immune induction. Some escaper pupae are formed with head eversion defects. AdarS overexpression is also lethal with no progeny pupae. Ecdysone signaling gene and innate immune gene expression are aberrantly elevated in the AdarG overexpressing pupae. RNAi knockdown of Ecdysone Receptor A (EcR A) or increasing expression of HP1 partially rescue AdarG overexpression defects and normalize gene expression in progeny flies, indicating that aberrant epigenetic silencing is also involved. The structure of an ADAR2 dimer on dsRNA shows the the glycine in AdarG is suitably positioned for Adar contacts with other proteins on dsRNA.

developmental biology↗

bioRxiv2025

Polyclonal origins of human premalignant colorectal lesions

Cancer is generally thought to be caused by expansion of a single mutant cell1. However, analyses of early colorectal cancer lesions suggest that tumors may instead originate from multiple, genetically distinct cell populations2,3. Detecting polyclonal tumor initiation is challenging in patients, as it requires profiling early-stage lesions before clonal sweeps obscure diversity. To investigate this, we analyzed normal colorectal mucosa, benign and dysplastic premalignant polyps, and malignant adenocarcinomas (123 samples) from six individuals with familial adenomatous polyposis (FAP). Individuals with FAP have a germline heterozygous APC mutation, predisposing them to colorectal cancer and numerous premalignant polyps by early adulthood4. Whole-genome and/or whole-exome sequencing revealed that many premalignant polyps--40% with benign histology and 28% with dysplasia--were composed of multiple genetic lineages that diverged early, consistent with polyclonal origins. This conclusion was reinforced by whole-genome sequencing of single crypts from multiple polyps in additional patients which showed limited sharing of mutations among crypts within the same lesion. In some cases, multiple distinct APC mutations co-existed in different lineages of a single polyp, consistent with polyclonality. These findings reshape our understanding of early neoplastic events, demonstrating that tumor initiation can arise from the convergence of diverse mutant clones. They also suggest that cell-intrinsic growth advantages alone may not fully explain tumor initiation, highlighting the importance of microenvironmental and tissue-level factors in early cancer evolution.

cancer biology↗

bioRxiv2025

Saturation, Task Error, and Feedback Timing Shape Early Implicit Adaptation

Motor adaptation is essential for maintaining coordination and precision in daily activities. Implicit motor adaptation--adaptation that occurs without conscious awareness--is thought to be primarily driven by sensory prediction errors. Here, we investigated how rapidly these unconscious changes in reaching behavior emerge as a function of error magnitude and the availability of task error signals. To this end, we employed a single-trial learning (STL) paradigm within a classical visuomotor rotation task. Participants made center-out reaching movements to either small (dot) or large (arc) targets while experiencing single perturbation trials with cursor rotations ranging from 1{degrees} to 90{degrees}, each followed by an aligned washout trial. By manipulating target size, we systematically modulated the presence of task error while holding sensory prediction error constant. We further compared these early implicit changes with those observed during standard prolonged adaptation to a fixed 20{degrees} rotation across >100 trials. Our results show that implicit adaptation emerges rapidly, even after a single exposure to small perturbations, and follows a saturating, fixed-rate response profile. Importantly, the magnitude of single-trial adaptation was greater when task error was present (small targets) compared with conditions in which only sensory prediction error was available (large targets). Moreover, STL-derived parameters moderately predicted the initial phase of adaptation during prolonged learning, suggesting that STL captures core dynamics of early implicit processes. These findings provide new insight into the mechanistic principles governing implicit motor adaptation. By identifying the parameters that drive early-stage error-based learning, this work refines current models of sensorimotor learning and highlights potential strategies for designing targeted training or rehabilitation protocols that leverage rapid adaptation processes to enhance motor performance and recovery.

neuroscience↗

bioRxiv2025

Peripheral Neuropathy After Chronic Alcohol Exposure in Mice: Impact of sex, total intake and duration and alcohol metabolism.

Alcohol induced peripheral neuropathy (AIPN) is a neurodegenerative disease caused by chronic alcohol intake and is associated with peripheral nerve damage and somatosensory symptoms, such as allodynia. Current treatments lack efficacy and do not target underlying pathology emphasizing the need for preclinical models of AIPN to elucidate mechanisms and novel targets. Thus, we performed a detailed characterization of a mouse model of AIPN and candidate mechanistic associations including the role of neuroinflammation and acetaldehyde. Our studies showed chronic alcohol induced mechanical and cold hypersensitivity and deficits in spontaneous behaviors in EtOH concentration-, time- and sex-dependent manners. Female mice drank more alcohol and developed more rapid and severe hypersensitivity but less robust deficits of spontaneous behaviors. The grimace test demonstrated chronic alcohol promoted spontaneous pain independent of sex. Duration of intake impacted alcohol-induced deficits in peripheral nerve electrophysiology amplitude and intra-epidermal nerve fiber density. We characterized an extensive time-course of chronic alcohol-induced neuroinflammation in the DRG and spinal cord and found significant time, sex and tissue effects. Polymorphisms of ALDH2 have been associated with alcohol-induced neuroinflammation, alcohol-related pain, and alcohol-induced peripheral neuropathy. We investigated the role of acetaldehyde, via inhibition of ALDH2, in the development of AIPN and showed that ALDH2 inhibition accelerated and exacerbated development of chronic alcohol-induced hypersensitivity in male and female mice. Overall, our studies in a well-controlled model of AIPN strongly point to neuroinflammation and inflammatory modulators such as acetaldehyde as important mechanistic targets for possible intervention in AIPN.

pharmacology and toxicology↗

bioRxiv2025

DLRNA-BERTa: A transformer approach for RNA-drug binding affinity prediction

RNA-based therapies are a rapidly expanding field, offering treatments for a wide range of diseases, including many rare conditions. To date, 24 RNA therapeutics have received FDA approval, with 131 more in clinical trials, underscoring RNAs growing role in modern medicine. In this context, Bidirectional Encoder Representations from Transformers (BERT) models provide a cost-effective and accurate virtual screening strategy for accelerating RNA-targeted drug discovery. These models take RNA FASTA sequences and compound SMILES strings as inputs and generate predicted binding affinities in nanomolar units. In this study, we introduce DLRNA-BERTa, a RoBERTa-based framework combining RNA-BERTa, pretrained on 9.76 million RNA sequences, with ChemBERTa-v2 for predicting small molecule-RNA interactions. The framework includes six class-specific models, aptamers, repeats, ribosomal RNAs, riboswitches, microRNAs (miRNAs), and viral RNAs, plus a general model for cases where the RNA class is unknown. Proposed DLRNA-BERTa consistently outperforms existing RNA-drug interaction prediction methods. Pearson correlation coefficients achieved are: 0.94 (aptamers), 0.95 (repeats), 0.93 (ribosomal RNAs), 0.94 (riboswitches), 0.95 (viral RNAs), 0.98 (miRNAs), and 0.92 (general model), demonstrating robust performance across RNA classes. Benchmarking against four independent datasets from the ROBIN repository further confirms generalizability. Application of DLRNA-BERTa to 3,492 approved drugs from the ChEMBL database identified 2,859 compounds with predicted affinities (pKd [≥] 6) across 294 RNA targets. As proof of concept, bleomycin is highlighted, supported by literature evidence of RNA-binding activity. A publicly accessible web application is available at https://huggingface.co/spaces/IlPakoZ/DLRNA-BERTa, in alignment with FAIR principles.

molecular biology↗

bioRxiv2025

Accurate and robust classification of Mycobacterium bovis-infected cattle using peripheral blood RNA-seq data

Bovine tuberculosis (bTB) remains recalcitrant to eradication in many endemic countries where current diagnostics are suboptimal. Mycobacterium bovis causes bTB and is closely related to Mycobacterium tuberculosis, which causes human tuberculosis (hTB). Although blood-based mRNA biomarkers identified through machine learning can discriminate hTB-positive from hTB-negative individuals, similar approaches have not been explored for bTB. Here, we use RNA-seq and machine learning to investigate the utility of blood mRNA as a host-response biomarker for bTB. We identify a 30-gene signature and a 273-gene elastic net classifier that differentiate bTB-positive from bTB-negative cattle, achieving area under the curve (AUC) values of 0.986/0.900 for the former and 0.968/0.938 for the latter in training and testing, respectively. Additionally, we show that these classifiers distinguish bTB-positive cattle from cattle infected with other microbial pathogens (AUC [≥] 0.819). These mRNA-based classifiers represent a promising tool for augmenting current diagnostics to advance global bTB eradication efforts.

genomics↗

bioRxiv2025

Asymmetric Social Representations in the Prefrontal Cortex for Cooperative Behavior

Cooperation is a hallmark of social species, enabling individuals to achieve goals that are unattainable alone. Across species, cooperative behaviors are often organized by distinct social roles such as leaders and followers, yet the neural mechanisms supporting such role-based coordination remain elusive. Here we introduce a new paradigm for studying cooperation in mice, where pairs of animals engage in a joint spatial foraging task that naturally gives rise to stable leader-follower roles predictive of learning speed. Disruption of medial prefrontal cortex (mPFC) activity, particularly in followers, impairs cooperation and induces reciprocal shifts in how animals weigh self- and partner-related cues for decision-making. Calcium imaging reveals that mPFC encodes both leadership dynamics and an egocentric social value map of the partners position, each in an asymmetric, role-specific manner. Combining this behavior with a novel multi-agent inverse reinforcement learning framework, we identify latent value functions that guide cooperative decisions and are decodable from mPFC activity. These findings uncover fundamental neural computations that support cooperation, revealing how social roles shape decision-making in real time. Our work opens new avenues for investigating the cellular and circuit basis of social cognition and collective behavior.

neuroscience↗

bioRxiv2025

Data-driven strategies for drug repurposing

Drug discovery is a complex, time-intensive, and costly process, often requiring more than a decade and substantial financial investment to bring a single therapeutic to market. Drug repurposing, the systematic identification of new indications for existing approved drugs, offers a cost-effective and expedited alternative to traditional pipelines, with the potential to address unmet clinical needs. In this study, we present a comparative analysis of drug-target interaction data from three extensively curated resources: ChEMBL, BindingDB, and GtoPdb, evaluating their release histories, curation methodologies, and coverage of approved and investigational compounds and targets. To facilitate therapeutic interpretation, we manually classified ChEMBL targets into 12 high-level biological families and mapped 817 clinically approved drug indications into 28 broader therapeutic groups. This structured framework enabled a systematic profiling of physicochemical properties among approved drugs across therapeutic categories. Our analyses revealed associations between physicochemical characteristics and therapeutic groups, providing practical guidance for indication-specific compound prioritization and refining the repurposing studies. We also examined cross-indication drug approvals to identify areas with high repurposing potential. Finally, we implemented a pathway-based computational pipeline to predict repositioning opportunities for FDA-approved drugs across ten major cancer types, demonstrating its adaptability to other disease contexts. Overall, this work consolidates drug-target data and computational repurposing into a data-driven framework that advances drug discovery and translational applications.

molecular biology↗

bioRxiv2025

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

Accurate cancer subtyping with accompanying molecular characterization is critical for precision oncology. While machine learning approaches have been applied to both digital pathology and cancer genomics, previous work has been limited in sample size and has typically aggregated granular cancer subtypes into coarse groupings, likely obfuscating informative molecular and prognostic associations and phenotypic variation of more detailed tumor subtypes. Accordingly, we collated 378,123 hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) with matched targeted DNA clinical sequencing results and OncoTree detailed cancer subtypes from a real-world cohort of 71,142 patients. Using this scaled, granular dataset and a cancer subtype knowledge graph, we developed Mosaic: a family of calibrated machine learning models using H&E WSI embeddings to classify tumors and identify molecular phenotypes across 163 detailed subtypes. The cancer subtyping module (Aeon) achieved an area under the receiver operating characteristic curve (AUROC) of 0.992 overall, with 161/163 subtypes reaching an AUROC [≥] 0.90 and improved performance over a state-of-the-art genomics-based classifier. The genomic inference module (Paladin) achieved an AUROC [≥] 0.80 for 167 pairs of detailed subtypes and genomic targets. We further used the learned histopathologic representations to i) identify key associations of the histopathologic embeddings with clinical biomarkers; ii) identify unsupervised sub-clusters of tumors with genomic determinants of tumor phenotype; iii) specify granular diagnoses for cancers of unknown primary, evaluated by genomic associations and expected clinical outcome distributions; iv) annotate functional significance for variants of uncertain significance (VUS); and v) identify cases that mimic the phenotypic effect of known DNA variants on H&E in the absence of detectable DNA alterations. Taken together, this work advances our understanding of phenotypic variation of granular tumor subtypes, their relevance to enhanced diagnostics, and their potential utility in risk stratification with multimodal machine learning in cancer.

cancer biology↗

bioRxiv2025

Ceramide transfer protein regulates G-protein coupled phospholipase signalling in Drosophila photoreceptors.

The non-vesicular transfer of lipids between organelles at membrane contact sites (MCS) has been proposed as a key principle in the regulation of cell physiology. While several proteins with lipid transfer activity have been identified and localized to MCS, their functional significance for supporting physiology is poorly understood. Ceramide transfer protein (CERT) is one such molecule that can transfer ceramide between membranes in vitro. However, evidence for the mechanism and in vivo significance of CERT function is limited. In this study, we have analyzed the function of the only gene (dcert) encoding CERT in Drosophila. We find that loss of function alleles of dcert (dcert1), show elevated levels of short chain ceramide species along with a reduction in the levels of its metabolite phosphatidyl ethanolamine ceramide. Physiological analysis of dcert1 mutant alleles showed reduced electrical responses in the eye to light stimulation although photoreceptors did not undergo retinal degeneration, and this phenotype could be rescued by reconstitution of dcert1 with the wild type gene. The altered light response in dcert1 was associated with a reduction in the rate of phosphatidylinositol 4,5 bisphosphate (PIP2) resynthesis following light induced phospholipase C (PLC) stimulation. The reduced electrical response of dcert1 could be suppressed by reducing ceramide synthesis at the ER. Taken together, our findings suggest that ceramide synthesized at the ER and transferred to the Golgi by CERT regulates G-protein coupled phospholipase C signaling in vivo.

cell biology↗

bioRxiv2025

Multifunctional Roles of Brr6 and Brl1 in Nuclear Envelope Fusion During Nuclear Pore Complex Biogenesis

Brl1 and Brr6 are essential, paralogous integral membrane proteins of the yeast nuclear envelope (NE) that transiently associate with nuclear pore complexes (NPCs) during their assembly to promote fusion of the inner (INM) and outer nuclear membranes (ONM). An amphipathic -helix (AH) in Brl1 is critical for mediating this fusion during NPC biogenesis. However, the exact roles of Brl1 and Brr6 in the molecular mechanisms of NPC assembly are still unclear. Here, we demonstrate that Brr6 operates at both early and late stages of NPC assembly. Its early function is supported by AH mutants that fail to permit nucleoporin recruitment and INM deformation, while mutations in conserved cysteine residues lead to NE herniations and defective membrane fusion. Additionally, the N-terminus of Brl1 interacts with Nic96, likely promoting its recruitment to nascent NPC assembly sites. We further provide evidence that the length of the perinuclear space-spanning region of Brl1 and Brr6 is critical for proper NE fusion during NPC formation. Artificial elongation of this region produces a toxic phenotype marked by Nup82 mislocalisation and severe NE integrity defects. This phenotype supports a model in which Brl1 and Brr6 promote NE fusion following INM deformation, when the distance between the INM and ONM is reduced--a process initiated by nucleoporin assembly on the nuclear side of the INM.

cell biology↗

bioRxiv2025

Alcohol use reduces the efficacy of anti-PD1 immunotherapy by disrupting anti-tumor immunity

Immune checkpoint inhibition (ICI) has improved clinical outcomes for certain patients with cancer. However, only a minority of patients have durable responses with underlying causes of differential immune responses across individuals often being unknown. Lifestyle exposures impact immune function and may subsequently alter the response to ICI. Alcohol use is common among cancer patients with known detrimental effects on adaptive immune function. However, its impact on ICI efficacy remains unknown. To determine if alcohol impacts ICI therapies, we performed a retrospective assessment of outcomes for patients receiving anti-PD1 ICI across tumor types and employed preclinical mouse models of ICI for lung and bladder cancer. Alcohol use reduced ICI efficacy in human patients treated with anti-PD1 for lung and bladder cancer (HR [~]2.0) as well as in murine models ICI in lung (LN4K1) and bladder (MB49) cancer. Alcohol reduced tumoral T cell numbers, promoting less productive Th2 and Th17 CD4+ phenotypes intratumorally and regulatory phenotypes in the periphery. In both rodent and ex-vivo human T cells, alcohol disrupted T cell activation and effector functions. Thus, alcohol use negatively impacts ICI efficacy warranting alcohol cessation for this patient population.

immunology↗

bioRxiv2025

Biomechanical Phenotyping Reveals Unique Mechanobiological Signatures of Early-Onset Colorectal Cancer

While both incidence and mortality of sporadic average-onset colorectal cancer (AO CRC, above 50 years of age) are in constant decline, sporadic early-onset colorectal cancer (EO CRC, under 50 years of age) is rising rapidly. Yet, the causes behind this rise remain poorly understood. Epidemiological studies indicate that lifestyle and environmental exposures may result in chronic inflammation, which is known to trigger tissue fibrosis. This study tests the hypothesis that fibrotic remodeling and biomechanical stiffening of colorectal tissues represent measurable hallmarks and potential drivers of EO CRC. Using primary human tissues, this work shows that EO CRC is associated with changes in collagen microstructure, increased stiffness and elevated viscosity of primary tumors. Spatial transcriptional profiling and immunostaining reveal pro-fibrotic signatures in stromal cells, alongside enhanced Yes-associated protein (YAP) mechanotransduction and proliferation in epithelial cells of EO CRC tissues. Mechanistically, increasing matrix stiffness in vitro promotes proliferation of epithelial cells in 2D and 3D colorectal cancer models. Together, these findings establish EO CRC as a disease marked by early and widespread biomechanical remodeling, suggesting that a fibrotic and stiffened tissue microenvironment may orchestrate EO CRC tumor initiation.

bioengineering↗

bioRxiv2025

Precision Neuromodulation with Real-Time Brain Decoding for Working Memory Enhancement

Transcranial magnetic stimulation (TMS) has transformed non-invasive brain therapies but faces challenges due to variability in outcomes, likely stemming from inter-individual differences in brain function. This study aimed to address this challenge by integrating personalized functional networks (PFNs) derived from functional magnetic resonance imaging (fMRI) with a neural network-based decoder to optimize stimulation in real time during a working memory (WM) task. After identification of individualized stimulation targets, participants completed a TMS/fMRI session, performing a WM task while receiving rTMS at randomized frequencies. Decoder outputs and behavioral data during this session guided selection of optimal and suboptimal stimulation frequencies. Participants then underwent six stimulation sessions (three optimal, three suboptimal) in a randomized crossover design, performing WM and control tasks. The optimal stimulation improved WM performance by the final session, with no improvement observed in the control task. Additionally, the decoder output predicted behavioral performance on the WM task, both during the TMS/fMRI and neuromodulation sessions. These findings show that neural network-guided closed-loop neuromodulation can improve TMS effectiveness, marking a step forward in personalized brain stimulation. HIGHLIGHTSO_LIClosed-loop TMS guided by real-time brain decoding enhances post-stimulation behavioral effects. C_LIO_LIIndividualized functional connectivity networks enable targeted neuromodulation C_LIO_LIOptimal stimulation boosted working memory performance over sub-optimal C_LIO_LIBrain decoder readouts predicted behavioral performance C_LI

neuroscience↗

bioRxiv2025

A translatable evaluation tool to study the biodistribution of clinically-available doxorubicin liposomes: PET imaging of Zr-Talidox

INTRODUCTIONDoxil/Caelyx is a PEGylated liposomal formulation of the chemotherapeutic doxorubicin used in the clinic for Kaposis sarcoma, advanced ovarian cancer, progressive multiple myeloma and metastatic breast cancer. Talidox(R), a smaller doxorubicin PEGylated liposome is undergoing clinical trials and has been proposed as an improvement on previous liposomal formulations for the treatment of advanced solid tumors. We aimed to validate an easily translatable radiolabeling method using zirconium-89 (89Zr) that enables quantitative whole-body PET imaging of these formulations to study their biodistribution and pharmacokinetics. METHODS[89Zr][Zr(oxinate)4] was produced using a kit-based approach followed by use as a direct radiolabeling agent of the liposomal formulations. DFT studies were performed to elucidate the mechanism behind the radiolabeling stability observed within the liposomes. Purified 89Zr-labelled Doxil/Talidox(R) liposomes (5 mg/kg doxorubicin dose) were administered in female BALB/c mice bearing 4T1 tumors. PET/CT imaging was acquired at 20 min, 24 h, 48 h, and 72 h, followed by post-mortem biodistribution at 72 h. RESULTS and DISCUSSIONBoth formulations were radiolabeled efficiently with high stability in serum in vitro for 72 h. In vivo, both formulations showed high tumor uptake at 72 h (18.5 {+/-} 2.4 % IA/g for Doxil and 20.2 {+/-} 2.3 % IA/g for Talidox). In general, ex vivo biodistribution showed similar uptake values for both formulations with high spleen/liver uptake and low bone uptake, confirming stability. Talidox(R) showed significantly lower spleen uptake and higher uptake in bone than Doxil. DFT studies confirmed that doxorubicin can form complexes with 89Zr that are more stable than [89Zr][Zr(oxinate)4], explaining the radiolabeling mechanism and stability results in vitro and in vivo. CONCLUSIONSClinically available PEGylated liposomes containing doxorubicin can be efficiently radiolabelled with 89Zr for PET imaging studies, using a clinically translatable radiolabelling method. HighlightsO_LIDoxorubicin-containing liposomes can be labeled with the positron-emitting radionuclide 89Zr with no impact on their original physicochemical properties. C_LIO_LIRadiolabeling is stable in vivo and enables imaging and biodistribution studies of the liposomes using positron emission tomography (PET). C_LIO_LIThe radiolabeling method is clinically translatable and would allow early assessment of existing and novel doxorubicin liposome biodistribution in humans or personalized medicine (nanotheranostic) approaches. C_LI

bioengineering↗

bioRxiv2025

Mammalian mitochondrial polyphosphate is regulated by the 5-InsP7 synthase IP6K1

Inorganic polyphosphate (polyP) is a linear polymer of varying length composed of phosphate residues linked by phosphoanhydride bonds. PolyP remains poorly understood in mammals due to its low abundance and lack of information on its synthesis and regulation. Using synthetic polyP8 as a bait, we identified polyP interacting proteins involved in RNA splicing, transcription, and mitochondrial function. We developed a DAPI fluorescence-based assay to quantify the low levels of polyP present in mammalian cell lines and tissues, and detected a higher concentration of polyP in the mitochondria compared with the nucleus and post-mitochondrial fraction. We observed that mitochondrial polyP synthesis relies on active FoF1 ATP synthase and an intact proton gradient across the inner mitochondrial membrane. Our data shows that orthophosphate (Pi) is required for the generation of mitochondrial polyP and that the presence of ATP enhances Pi-driven polyP synthesis in isolated mitochondria. We discovered that the inositol pyrophosphate 5-InsP7, synthesized by IP6K1, regulates mitochondrial polyP levels. Mice and cells deficient in IP6K1 showed a significant reduction in mitochondrial polyP synthesis compared with wild type controls. Cells lacking IP6K1 also showed impaired mitochondrial respiration and membrane potential. The expression of active IP6K1, but not its catalytically inactive form, restored mitochondrial polyP synthesis and membrane potential in IP6K1 deficient cells, but mitochondrial respiration was rescued by expression of either active or inactive IP6K1. These data show that IP6K1 regulates mitochondrial function and polyP production through both the synthesis of 5-InsP7 and via a catalytic activity-independent mechanism. Our findings uncover a link between 5-InsP7, an energy sensor, and polyP, an energy store, in the regulation of mammalian mitochondrial homeostasis.

biochemistry↗

bioRxiv2025

A pan-generic marker panel for apples to enable genetic research and breeding across Malus species

AbstractWild Malus species harbor untapped genetic diversity to advance apple breeding, particularly for disease resistance and stress tolerance. However, existing marker panels, developed mainly using Malus domestica accessions, introduce ascertainment bias and limit detecting rare variants in wild species. We developed and validated a medium-density and cost-effective pan-generic 3K apple DArTag panel optimized to capture genome-wide variation across the Malus genus. The panel was constructed using conserved, syntenic, and collinear genomic blocks identified within the core genome of 13 Malus accessions for cross-species transferability. The panel was validated across three bi-parental mapping populations totaling 593 progeny. Across these populations, 2,461-3,234 SNP markers were polymorphic and 1,482-2,620 were informative. Each population contained over 900 multiallelic micro-haplotype loci, with several hundred loci exhibiting three or four distinct haplotypes. Markers were uniformly distributed across all 17 chromosomes, each containing between 60- 230 informative SNPs. The panel was further evaluated on 174 diverse germplasm accessions from 20 Malus species. It exhibited strong cross-species transferability, exceptionally low rates of missing data (<0.5%), and clear genetic differentiation between wild and domesticated accessions. Genome-wide association studies (GWAS) identified a major locus on chromosome 4 significantly linked to fruit length, weight, and width in addition to trait-specific associations on chromosomes 1, 6, 9, and 11. The cost-effectiveness of genotyping per sample (<$15), combined with these results, underscore the panels broad utility for quantitative trait locus (QTL) mapping in bi- parental and diverse populations, marker-assisted selection in the breeding programs, and genetic diversity analysis across the Malus genus.

genetics↗