Biology subjects

Mishra, P.

Publications and source records attributed to Mishra, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Male youth BMI is associated with epigenetic ageing of female descendants but not blood or sperm DNA methylation

Studies based on harvest records indicate that grandparental nutrition in youth is associated with the health traits of grandchildren in a sex-specific lineage. We investigated whether male early adulthood anthropometrics associate with epigenetic age, a measure of general well-being, and DNA methylation, a potential molecular inheritance mechanism, in three generations of descendants. Data on weight, height, BMI and chest circumference measured at military draft examinations (at age 18-24 yrs.) were retrieved from national archives for 1,013 men, herein referred to as Generation Archives (GA). The genome-wide DNA methylation of their descendants participating in the Young Finns Study (YFS) was measured from the blood and sperm from the children (59-80 yrs., nblood = 362, nsperm = 51), grandchildren (34-49 yrs., nblood = 421, nsperm = 98) and great-grandchildren (7-30 yrs., nblood = 200). The men's (GA) BMI had an inverse association with the epigenetic pace of ageing (DunedinPACE) of their daughters ({beta} = -0.01, p = 0.002, n = 169) and the daughters' daughters ({beta} = -0.01, p = 0.049, n = 126) but not with that of their male descendants. From within the YFS cohort, maternal, but not paternal, BMI at ages 13-34 also had an inverse association with the DunedinPACE of the immediate offspring. However, robust evidence for the inheritance mechanism was not found in the analyses between the anthropometric measurements of the GA men and the DNA methylation profiles in the blood and sperm of their descendants.

molecular biology↗

bioRxiv2026

Identification of Novel Inhibitors of JEV RdRp as Potent Antiviral Drugs: Targeting NS5-NS3 Protein Interaction

Japanese Encephalitis Virus (JEV) belongs to the Flavivirus family, and the RNA dependent RNA polymerase (RdRp) domain located at the C terminus of non structural protein 5 (NS5) regulates de novo viral genome synthesis. The conserved priming loop inserted in the thumb domain of RDRP initiates de novo genome synthesis. Interestingly, the reported replication process initiates with an interaction between NS5 (methyltransferase/RDRP) and NS3 (protease/helicase), and inhibiting this interaction directly correlates with the inhibition of viral replication. The function of the priming loop in the context of the NS5 NS3 interaction is not yet known. In this study, we studied the priming loop function in the NS5 NS3 interaction and viral replication. Using a structure based drug design approach, we screened the Maybridge compound library against the RdRp priming loop and identified 15 candidate compounds based on binding energy. Among them, DSHS00151 showed significant dose dependent inhibition of the NS5 NS3 interaction with an IC50 of 3.5 micromolar in the mammalian two hybrid assay, inhibited viral infectivity with an IC50 of 2.54 micromolar, and reduced viral RNA load with an IC50 of 2.9 micromolar, compared to CD10712. Molecular Dynamics (MD) simulations revealed that DSHS00151 exhibits stronger and more stable binding with the priming loop residues (790 to 812) compared to CD10712. The molecular mechanism suggested by the docking of the NS5 and NS3 proteins showed that the priming loop tends to rotate toward the NS3 protein to stabilize the complex, and compound binding restricts this loop rotation, thus compromising the stability of the NS5 and NS3 complex and affecting viral replication. Overall, our study validated the function of the NS5 priming loop as an allosteric site, and compounds binding to this allosteric site belong to the Non Nucleoside Reverse Transcriptase Inhibitors (NNRTI) class of inhibitors, which disrupt the NS5 and NS3 interaction and could be developed as novel anti JEV therapeutics.

pathology↗

bioRxiv2026

Seizure-related gene 6 (SEZ6) encodes a Cancer stem cell-specific proangiogenic molecule: A novel glioma therapeutic target

Cancer stem-like cells (CSCs) not only initiate tumors but also orchestrate angiogenesis through multiple mechanisms, thereby sustaining vascularization and promoting tumor growth. In glioblastoma (GBM; WHO grade IV glioma), the most aggressive adult brain tumor, glioma stem-like cells (GSCs; glioma CSCs) are the main drivers of tumor progression, drug resistance, and recurrence. An interrogated multi-omic secretome analysis identified Wnt-{beta}-catenin signaling-regulated, membrane-localized Seizure Related 6 Homolog (SEZ6) as a patient-derived GSC-specific proangiogenic molecule. Silencing of SEZ6 inhibited the ability of the GSC secretome to induce angiogenic network formation by brain- and lung-derived endothelial cells, but not GSC growth as neurospheres in vitro. SEZ6 silencing also suppressed patient-derived GSC-initiated glioma tumors, resulting in reduced tumor vasculature in an orthotopic mouse model. We also found that SEZ6 induces TGF{beta}-dependent IL-8 expression in endothelial cells to promote angiogenesis. Coimmunoprecipitation and molecular dynamics simulation experiments determined that the Sushi 3 domain of SEZ6 mediates the interaction with TGF{beta} RII to activate the TGF{beta} pathway. Pharmacological inhibition of BACE1 with an in-house-developed small molecule, or blockade of the SEZ6-TGF{beta} RII interaction using a rationally designed peptide, markedly attenuated SEZ6-driven TGF{beta} signaling, and suppressed angiogenesis. Thus, our findings identify SEZ6 as a novel CSC-specific therapeutic target for GBM.

cancer biology↗

bioRxiv2026

AGPI: An AI-Powered Genomic Pathogen Intelligence Platform for Integrated Classification, Visualization, and Therapeutic Targeting

Rapid and accurate pathogen detection remains a major challenge in modern bioinformatics, as existing tools are often fragmented and require multiple specialized workflows. We present AGPI (AI-powered Genomic Pathogen Intelligence), an integrated platform that combines genomic sequence classification, biological enrichment, three-dimensional structural visualization, and AI-guided therapeutic prioritization within a single interpretable pipeline. AGPI employs a hybrid convolutional-Bidirectional Gated Recurrent Unit (BiGRU) architecture trained on DNA sequences from 40 pathogen classes spanning viruses, bacteria, fungi, and protozoan pathogens. The model achieved 99.61% validation accuracy and 94.90% accuracy on an independent held-out evaluation of 600 pathogen sequences following iterative refinement. As a proof of concept, AGPI correctly classified a Zika virus genome with 96.14% confidence, retrieved curated biological context from 245 peer-reviewed studies, and identified Ribavirin as a leading therapeutic candidate against the Zika NS5 polymerase through AI-guided molecular docking. Multi-metric ligand similarity analysis further differentiated candidate compounds according to their structural and pharmacological properties. These results demonstrate that integrated AI-driven genomic pipelines can accelerate pathogen characterization and therapeutic hypothesis generation while providing an accessible and interpretable framework for infectious disease surveillance and computational drug repurposing.

bioinformatics↗

bioRxiv2026

Autoantibodies Drive Fc Gamma Receptor-Dependent Colon Inflammation During Immune Checkpoint Blockade

Immune checkpoint inhibitor (ICI)-associated colitis limits effective cancer immunotherapy, yet host determinants of severe toxicity remain undefined. We investigated whether humoral immunity is associated with subsequent severe immune-related colitis (irC). In melanoma patients, baseline serum autoantibody (AAb) profiling identified a composite antigen signature - a signature-level association rather than validated functional specificities - associated with severe irC, marked by retained reactivity to tumor-associated antigens and relative depletion of antibodies recognizing immune- and mucosal-regulatory proteins. To assess functional relevance, we transferred polyclonal IgG from severe- or non-severe-irC patients into wild-type or humanized Fc{gamma} receptor (hFc{gamma}R) mice treated with anti-PD-1 or anti-CTLA-4. IgG alone did not induce inflammation; however, severe-irC IgG amplified checkpoint-driven colonic inflammation in hFc{gamma}R mice, but not in wild-type mice, with checkpoint-specific remodeling of myeloid, lymphoid, and innate lymphoid compartments. These findings suggest that pretreatment humoral immunity conditions susceptibility to irC via the IgG-Fc{gamma}R axis.

cancer biology↗

bioRxiv2026

AE-PocketMiner Uses Attention to Simultaneously Predict Cryptic Pockets and Their Allosteric Coupling

Finding and targeting cryptic pockets could dramatically expand the druggable proteome. However, discovering these sites remains challenging since they are only open a fraction of the time. It is also difficult to predict the functional relevance of a cryptic site as this often requires insight into allostery. Here we introduce attention enabled (AE-)PocketMiner, an artificial intelligence (AI) method that uses a graph neural network with an attention mechanism to simultaneously predict the locations of cryptic pockets and their allosteric coupling to the rest of the protein from a single input structure. We show that AE-PocketMiner outperforms past methods for identifying cryptic pockets and recapitulates known allosteric interactions. Moreover, we experimentally confirm newly predicted cryptic pockets and mutations that allosterically control pocket opening. AE-PocketMiner thus provides a powerful framework for multiple steps of the drug discovery process--including pocket identification, prioritization, and assay design--that will help expand the druggable proteome.

biophysics↗

bioRxiv2026

Residue-specific dominant-negative mutant of ubiquitin reveals functional selectivity as Ubp14 deubiquitinase inhibitor

Multifunctional proteins encode specificity through nuanced molecular interactions that operate in the presence of abundant wild-type molecules. Previous studies on multifunctional proteins have shown how certain regulated interactions parse complex biological activities into discrete functional modules. Discrete interaction edges can function as regulatory nodes whose perturbations selectively remodel proteostasis output, especially under disease conditions. However, whether such interaction specificity can be harnessed to selectively manipulate functional modules and reveal residue-level control principles, remains largely unexplored. Here, we screened for dominant negative mutations that impact partner-selective functions linked to Leu8, a critical binding residue on ubiquitin. Our results reveal that the Leu8Ala mutation specifically leads to accumulation of polyubiquitinated proteins and decreased levels of free ubiquitin suggesting loss of deubiquitinase function in yeast cells. Cellular and biochemical analyses establish that the Leu8Ala variant of ubiquitin specifically inhibits the yeast deubiquitinase, Ubp14, and its human homolog, USP5. We further demonstrate remodelling of the binding interface with increased interface contacts for the variant and Ubp14 complex. The variant shows a higher inhibitory potency compared to the wild-type ubiquitin and can inhibit Ubp14 both as unconjugated and as conjugated ubiquitin chain indicating the strength of its inhibitory function. Our results provide mechanistic insight into how edge perturbations in ubiquitin can reveal critical nodes that impact selective functions and thus fine-tune the cellular proteostasis network for therapeutic benefit.

biochemistry↗

bioRxiv2026

Classification of Smartphone Interaction Using Multimodal Physiological Signals with a Brain-Body Spatio-Temporal Transformer

Distinct smartphone interaction behaviors, like short-form video scrolling and mobile gaming, elicit qualitatively different cognitive and physiological responses. However, such distinctions is often overlooked by approaches that treat smart-phone use as a monolithic behavior. This paper presents Brain-Body Spatio-Temporal Transformer (BB-STT), a unified deep learning framework for classifying interaction-specific physiological signatures from multimodal signals, including EEG, EDA, PPG, and eye-tracking. BB-STT achieves 83.51% accuracy in distinguishing smartphone from non-smartphone activity and 74.13% accuracy in three-class classification of short-form video, gaming, and baseline viewing. The model demonstrates strong generalization with leave-one-subject-out (LOSO) performance that is also comparable to 5-fold cross-validation accuracy. Cross-modal attention emerges as the key component, improving three-class accuracy by 16.74 points through dynamic integration of multimodal signals. Interpretability analysis indicates a hierarchical organization of physiological responses. Eye-tracking features, particularly gaze depth, enable coarse separation between smartphone and non-smartphone activity. In contrast, finer discrimination between passive video viewing and active gaming on smartphones relies on the joint contribution of bilateral pupil dilation and central EEG features. Together, these results demonstrate the potential of multimodal physiological signals for objective, real-time assessment of digital engagement in naturalistic settings.

neuroscience↗

bioRxiv2026

Genome-wide architecture of prolonged starvation adaptation in experimentally evolved Drosophila and comparative enrichment in human orthologs

Long-term starvation stress represents a strong evolutionary constraint across taxa, yet the genetic architecture underlying adaptation to sustained nutrient deprivation remains poorly resolved. We experimentally evolved Drosophila melanogaster under starvation stress for 60 generations, maintaining four starvation-selected populations and four matched controls, and then performed whole-genome resequencing. Starvation-selected populations exhibited extended survival and pronounced genome-wide restructuring, including the expansion of low-heterozygosity regions, reduced nucleotide diversity, and recurrent sweep signatures across replicates. Drift-aware allele-frequency modeling identified 3,578 single-nucleotide polymorphisms (SNPs) whose shifts exceeded neutral expectations, indicating widespread, parallel responses to sustained starvation. Mitochondrial pathways emerged as prominent targets: nuclear-encoded mitochondrial genes were significantly enriched among low-diversity, sweep-associated, and drift-exceeding loci, and the mitochondrial origin of replication harbored a sharply differentiated variant, suggesting a mito-nuclear component of starvation adaptation. Comparative analyses further showed that human orthologs of starvation-responsive fly genes were enriched for highly differentiated variants in selected 1000 Genomes populations, with regulators of TOR/S6K signaling recurring among loci in the extreme tails of population differentiation. Together, these results define a replicate-convergent and functionally coherent genomic response to prolonged starvation in Drosophila, comprising regional signatures of linked selection and distributed allele-frequency shifts exceeding neutral expectations, and connect laboratory selection in flies to population differentiation in human orthologs.

evolutionary biology↗

bioRxiv2026

Evolutionary turnover of protein structural disorder drives aberrant proteome remodelling in naked mole rat

The naked mole rat is an evolutionary outlier among mammals, exhibiting extreme longevity, cancer resistance, hypoxia tolerance, pain insensitivity, eusociality, poikilothermy and other distinctive physiological traits, most of which likely resulted from its adaptation to highly adverse subterranean habitat. Despite accumulating data, the genetic and molecular basis underlying these traits remain poorly understood. Through analyses of 18 distinct protein attributes and allied datasets across hystricomorphs, myomorphs, carnivores, and primates, we observed lineage-specific evolutionary divergence in intrinsic protein disorder in the naked mole rat. The disorder turnover exhibited functional dichotomy. The gain of disorder preferentially associated with proteostasis, immune regulation, neurodevelopment, skeletal growth and tumour suppressive properties, while loss of disorder modulated mostly the cardiac development. The proteins that gained disorder in NMR exhibited lower degradation rates, consistent with stabilization through phase-separation, while the proteins losing disorder show pronounced divergence in gene expression. The disorder turnover was primarily driven by indels affecting functional regions including Pfam domains, ANCHOR-predicted binding sites, short linear motifs, stress induced modifications of Tyr, Met, and Cys residues. Notably, the gained disordered regions were inferred to be redox-sensitive, aligning to exceptional stress tolerance in naked mole rats. Collectively, our results highlight an unusual and previously overlooked large-scale proteome remodelling that drives the molecular evolution of extraordinary traits of naked mole rat. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/720964v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@644d1dorg.highwire.dtl.DTLVardef@102c9e4org.highwire.dtl.DTLVardef@14c770org.highwire.dtl.DTLVardef@31bc5e_HPS_FORMAT_FIGEXP M_FIG C_FIG

evolutionary biology↗

bioRxiv2026

A multimodal dataset of EEG, eye-tracking, and physiological signals during naturalistic smartphone interactions

Smartphones have become pervasive tools for communication, information consumption, and digital interaction, yet the neurophysiological dynamics associated with naturalistic smartphone use remain insufficiently characterized. Here, we present a multimodal physiological dataset collected during ecologically valid smartphone interaction and a subsequent standardized low-engagement baseline condition. Twenty-three participants engaged with their most frequently used smartphone application (primarily gaming or short form video) for ten minutes, followed by a five-minute passive viewing of a standardized nature video. Simultaneous recordings were obtained from electroencephalography (EEG; 64 channels), wearable eye-tracking, photoplethysmography (PPG), and galvanic skin response (GSR) sensors. Questionnaire-based assessments, including the smartphone addiction scale (SAS) and the mobile phone problematic use scale (MPPUS), are also collected to characterize individual differences in smartphone-related behavioral traits. All data streams are synchronized using transistor-transistor logic (TTL) trigger signals to ensure precise temporal alignment across modalities. The dataset is organized according to the Brain Imaging Data Structure (BIDS) specification and is publicly available on OpenNeuro (Accession Number: ds007537). This dataset enables the investigation of neural, ocular, and autonomic responses during smartphone interaction and supports multimodal analysis of diverse smartphone behaviors while preserving ecological validity.

neuroscience↗

bioRxiv2026

HMCVelo: A Deterministic Model for Hydroxymethylation Velocity in Single Cells

I present hydroxymethylation velocity (HMCVelo), the first velocity framework for DNA methylation dynamics. HMCVelo is a deterministic ordinary differential equation (ODE) model that computes the time derivative of hydroxymethylation state for individual cells and genes. The model exploits a recent advance in single-cell epigenomics--Joint single-nucleus hydroxymethylcytosine and methylcytosine sequencing (Joint-snhmC-seq)--which enables subtraction-free quantification of 5-hydroxymethylcytosine (5hmC) and 5-methylcytosine (5mC) at single-cell resolution, resolving temporal methylation dynamics from static molecular snapshots. HM-CVelo models the methylation-demethylation cycle as three coupled processes--methylation, hydroxymethylation, and demethylation--governed by gene-specific rate parameters estimated at steady state via constrained least-squares regression. Scale invariance reduces the parameter space from three to two free parameters per gene. Applied to murine cortical cells (n = 519 and n = 545), HMCVelo infers cellular trajectories with velocity confidence scores exceeding 0.89 across all cell types, compared to confidence scores below 0.45 when RNA velocity is repurposed on the same data. I further prove that in any closed biochemical system with a conservation law, the complement variable cannot resolve trajectory bifurcations--a result with implications for embedding basis selection in all future velocity frameworks applied to cyclic biochemical systems. This work provides a foundation for multi-omic trajectory inference integrating epigenetic and transcriptomic measurements.

bioinformatics↗

bioRxiv2026

Integration of QTL Mapping, Transcriptomics, and Genome Resequencing Identifies Yield-Associated Genes for Salt Stress in Rice

Salinity and sodicity stresses adversely affect rice growth and yield. To overcome yield losses, suitable tolerant rice cultivars can be developed through a marker-assisted breeding (MAB) program. In the present study, genomic regions associated with sodicity stress tolerance at the reproductive stage were identified using a high-density 50kSNP array in a recombinant inbred line (RIL) population derived from the contrasting rice genotypes CSR11 and MI48. A total of 50 QTLs were detected for various yield-related traits; further, 19 QTLs with [≥]15% of phenotypic variance were selected for integrated (omics) analysis. RNA sequencing of leaves and panicles at the reproductive stage under sodic stress conditions was employed to find differentially expressed genes. A total of 1368 and 1410 SNPs; 104 and 144 indels were found for MI48 and CSR11, respectively, within the QTL regions from resequencing. At chromosomes 1 and 6, colocalized QTLs (qPH1-1/qGP1-1 and qGP6-2/qSSI6-2) were discovered. Differentially expressed genes (DEGs) were mapped over the QTL regions selected, and SNP variations and indels were screened for colocalized QTLs. Potential candidate genes, namely Os-pGlcT1 (Os01g0133400), OsHKT2;1 (Os06g0701600) and OsHKT2;4 (Os06g0701700), OsANTH12 (Os06g0699800), and OsPTR2 (Os06g0706400), were identified as being responsible for glucose transport, ion homeostasis, pollen germination, and nitrogen use efficiency, respectively, under salt stress. Finally, our study provides important insights into the genes and potential mechanisms affecting grain yield under sodic stress in rice, which will contribute to the development of molecular markers for rice breeding programs.

plant biology↗

bioRxiv2026

Microbial Signal Recognition & Neuronal Mimicry (SRNM) axis in IBD

Inflammatory bowel disease (IBD), encompassing Crohns disease (CD) and ulcerative colitis (UC), is a chronic inflammatory disorder whose pathogenesis involves intricate host-microbiome interactions. Molecular mimicry (the structural or functional resemblance between microbial and host proteins) represents a plausible mechanism by which gut microbiota may trigger or perpetuate autoimmune responses. Here we present a comprehensive, multi-layered molecular mimicry in silico pipeline (MMIP) analysis of 39 baseline shotgun metagenomic samples from Human Microbiome Project 2 (HMP2/IBDMDB). Using DIAMOND-based homology search against the SwissProt followed by UniProt Retrieve/ID Mapping (URIM), we characterized microbial protein functional space through three complementary frameworks: (i) normalized GO term frequency comparison across diagnostic groups, (ii) protein family (PFAM) domain enrichment analysis, and (iii) sequence-level mimicry analysis identifying microbial proteins with direct homology to human proteins. Taxonomic profiling using MetaPhlAn3 pre-computed abundance profiles provided further biological context. CD microbiomes exhibited greater enrichment of immune-relevant biological processes and a higher per-sample sequence-level mimicry rate than UC. CD and UC also showed distinct pathobiont profiles, with CD enriched for oral-origin taxa including Haemophilus parainfluenzae and UC enriched for Fusobacterium nucleatum and Prevotella species. Notably, healthy gut microbiome maintains coordinated mimicry of host neuronal, signal-recognition-particle-associated, and antimicrobial peptide machinery, a repertoire dismantled in IBD and replaced by disease-subtype-specific signatures, alongside a candidate mimicry link between CD-enriched bacteria and NOD2. These results represent the first metagenome-wide characterization of molecular mimicry across IBD subtypes using shotgun metagenomic data, offering new mechanistic insight into how microbial dysbiosis may contribute to immune dysregulation in IBD.

bioinformatics↗

bioRxiv2026

UFMylation of Pyruvate Dehydrogenase Regulates Mitochondrial Metabolism

The ubiquitin-fold modifier 1 (UFM1) post-translational modification (PTM), or UFMylation, regulates protein homeostasis and is essential for human development. Yet the roles of the de-UFMylase, UFM1-specific peptidase 2 (UFSP2), which removes UFM1 from UFMylated proteins, remain poorly characterized. Here, we demonstrate that UFMylation and UFSP2 regulate mitochondrial metabolism. Quantitative proteomics in UFSP2-deficient cells revealed the accumulation of many proteins previously unknown to be impacted by UFMylation. These included components of the mitochondrial ribosome, electron transport chain (ETC), and pyruvate dehydrogenase (PDH) complex. Functional analyses demonstrated that excessive UFMylation in UFSP2-deficient cells increases mitochondrial respiration, glucose oxidation in the tricarboxylic acid (TCA) cycle, and PDH enzymatic activity. We identified dihydrolipoamide S-acetyltransferase (DLAT), the E2 component of PDH, as a direct UFMylation substrate, with lysine 118 (K118) as the primary conjugation site. Mutating K118 to arginine (K118R) abolished DLAT UFMylation and reduced pyruvate oxidation, identifying this modification as an activator of PDH. These findings reveal a UFMylation-based regulatory mechanism that controls mitochondrial function by inducing utilization of pyruvate as a TCA cycle fuel.

biochemistry↗

bioRxiv2026

Miniprotein inhibitors of the Staphylococcus aureus efflux transporter NorA

Multidrug efflux pumps transport antibiotics across the cellular membrane resulting in resistance conferred to the host organism. Efflux pump inhibitors (EPIs) potentiate the efficacy of antibiotics by blocking drug efflux and hold promise as adjuvant therapeutics in the fight against multidrug resistant pathogenic bacteria. A hurdle in the field has been the lack of selectivity of small molecule EPIs which often display off-target toxicity due to non-specific binding. To tackle this specificity challenge, we aimed to maximize an inhibitors binding surface area to efflux pumps by designing miniprotein EPIs using computational protein design and an E. coli co-expression assay to screen inhibition in cells. We used S. aureus NorA as a model efflux transporter since it confers drug resistance to fluoroquinolones, puromycin, and other cytotoxic compounds. Starting from a focused miniprotein library of only 86 members, we identified inhibitors in the screen that blocked NorA transport under active efflux conditions in vitro. Our most promising inhibitor I-23 was validated by solving a cryo-EM structure of the miniprotein in complex with NorA, which stabilized the transporter in the outward-open conformation. I-23 has a ferredoxin-like fold with one of its {beta}-hairpins inserted into the substrate binding pocket of NorA and other parts of the globular fold occupying the shallow pocket and making extensive intermolecular contacts with NorA. An arginine residue on the tip of the hairpin loop was positioned near an anionic patch required for NorA antibiotic efflux. The identified structural motifs in this work could be employed to explore the molecular properties of peptidoglycan penetration; full realization of the therapeutic potential of the designed miniprotein inhibitors will require determining the principles for facilitating passage of [~]7 to 8 kDa miniproteins across the peptidoglycan bacterial cell wall.

biochemistry↗

bioRxiv2026

A distal CTCF-binding site drives MYC expression plasticity in a negative feed-forward loop

Oncogene expression heterogeneity systemically diversifies cancer cell phenotypes, enabling selection and cancer evolution. Here we document that the level of MYC expression variation is coordinated by a negative feed-forward loop involving the non-coding CCAT1 eRNA and the MYC gating process. While CCAT1 eRNA indirectly antagonizes MYC gating by promoting MYC transcriptional initiation and elongation, the MYC protein promotes gated MYC expression in a feedback loop by inhibiting both MYC transcription and CCAT1 expression. This entire process is coordinated by a CTCF binding site positioned within CCAT1 at a distal, oncogenic super-enhancer, which functions as a master switch by coordinating both CCAT1 and gated MYC expression to diversify cells toward both low and high MYC levels, as determined by heterogeneity metrics. As hallmarks of this principle are frequent in breast cancer and colorectal tumors, the dynamics of this new principle may underlie transitions between therapy-resistant low-MYC, and proliferative high-MYC tumor cells. Highlights- Transcriptional rate regulates MYC gating frequency - CCAT1 expression indirectly inhibits MYC gating by promoting MYC transcription - High MYC protein levels promote gated expression by inhibiting both MYC transcription and CCAT1 expression - These features are controlled by a single CTCF binding in the distant super-enhancer to drive expression plasticity in colorectal cancer cells

cancer biology↗

bioRxiv2026

Personalized smartphone notifications bias auditory salience across processing stages

Modern digital environments expose the brain to a dense stream of personally meaningful cues that differ markedly from the conditions under which sensory systems evolved. Understanding how the brain responds and adapts to such environments is increasingly relevant for cognitive and mental well-being. In this study, we used auditory event-related potentials (ERPs) recorded during a task-irrelevant auditory oddball paradigm to obtain a time-resolved account of neural responses to smartphone notifications. We dissociated the effects of generic notification sounds from the learning-related effects of personalized notification sounds, and examined how these responses varied across levels of smartphone use. Among early stages of processing, generic tones exhibited experience-dependent strengthening of auditory representations, whereas personalized tones engaged stable, pre-learned representations, as reflected in P2 dynamics. The strongest stimulus-dependent modulation was observed in pre-attentive salience detection, reflected in the mismatch negativity (MMN), which was earlier and larger for personalized tones compared to generic ones. At later stages, attentional orienting and extended evaluative processing showed distinct patterns that were differentially sensitive to stimulus identity and smartphone use. Notably, smartphone usage levels modulated later attentional and evaluative stages (P3a and LPP) without altering early pre-attentive prediction-error signaling. Overall, our findings demonstrate that personalized smartphone notifications do not uniformly increase neural distraction. Instead, they engage robust and rapid pre-attentive prediction-error signaling that is largely independent of usage, while habitual smartphone use selectively shapes later attentional orienting and evaluative dynamics. Significance statementModern digital environments are saturated with personalized cues, such as smartphone notifications, that are known to disrupt ongoing behavior. A common assumption in discussions of digital distraction is that repeated exposure to such cues progressively amplifies their sensory salience, rendering habitual users increasingly reactive. Here, we challenge this assumption using an ecologically grounded neural paradigm with personalized notification sounds. We show that personalized notifications engage robust early salience detection that is shared across users, while habitual smartphone use selectively modulates later attentional and evaluative processing. These findings place important constraints on how repeated exposure to personalized digital cues shapes neural processing, indicating that usage-related effects emerge downstream rather than at early sensory stages.

neuroscience↗