Biology subjects

Paul, S.

Publications and source records attributed to Paul, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Heterotypic Protein Interactions Modulate the Condensate Dynamics and Aggregation of α-Synuclein

Multicomponent biomolecular condensates formed by diverse multivalent proteins underlie numerous cellular processes, from ribosome biogenesis to stress response regulation, and have recently been implicated in disease-related protein aggregation. Understanding how heterotypic protein interactions modulate condensate dynamics and transitions to amyloid states remains a major challenge. Here, we combine fluorescence -based ensemble and single-molecule approaches, molecular simulations, and systematic domain deletions to investigate how charge patterning and domain structure influence co-condensation between -synuclein, a disordered neuronal protein linked to Parkinsons disease, and the SARS-CoV-2 nucleocapsid protein (NP), a structured viral RNA-binding protein. We find that co-condensation is driven by multivalent electrostatic interactions and occurs when the heterotypic affinity exceeds a threshold, resulting in restricted protein dynamics and altered condensate material properties. These changes promote the formation of dense amyloid fibrils, as confirmed by atomic force microscopy and fluorescence assays. Our results elucidate how heterotypic interactions within multiphasic condensates can modulate phase behavior and aggregation, providing insight into broader mechanisms linking condensate dysregulation with neurodegenerative diseases.

biophysics↗

bioRxiv2025

Regulated proteolysis of green fluorescent protein fusion proteins in Aspergillus fumigatus

Aspergillosis caused by Aspergillus fumigatus is a clinical issue of such severity that the World Health Organization has designated this organism as 1 of the 4 most critical fungi to study. Progress in A. fumigatus has been limited by the availability of genetic tools with which to study this filamentous fungus. Currently available means of altering the dosage of genes and gene products include construction of disruption mutants as well as regulated promoters. These are powerful techniques but somewhat limited for the analysis of essential genes. Here we describe a new method that permits regulated proteolysis of any A. fumigatus protein that can be made as a fusion protein to the well-described Green Fluorescent Protein (GFP) of Aequorea victoria. A GFP fusion protein of interest can be targeted for degradation using a single-chain antibody called a nanobody that recognizes GFP (GFPNb). This GFPNb is in turn fused to an E3 ligase protein called Rnf4 from rat that efficiently ubiquitinates target proteins. A fusion gene was constructed under control of a doxycycline-inducible promoter that produced a GFPNb-Rnf4 fusion protein in A. fumigatus. Here we show that production of this GFPNb-Rnf4 protein led to the rapid proteolysis of a variety of GFP fusion proteins. Additionally, we found that some GFP fusion proteins triggered a corresponding genomic response when their degradation was induced while others were simply degraded. These studies provide a new means to directly regulate protein levels in A. fumigatus and generate new alleles of genes exposing the underlying regulatory circuitry. ImportanceAspergillus fumigatus is the major filamentous fungal pathogen of such importance in infectious disease that it has been designated as one of the 4 most critical fungal organisms to study. One of the limiting capabilities in the analysis of A. fumigatus is the limiting genetic toolbox that can be employed in this fungus. Here we describe the first system that allows the regulated degradation of a protein of interest using a recombinant single protein chain antibody (nanobody) directed against Green Fluorescent Protein (GFP). GFP is routinely used to construct fusion proteins that in turn allow localization of the fluorescent protein and immunological detection. Here we use this nanobody to deliver a ubiquitin ligase that in turn causes rapid depletion of GFP fusion proteins. This allows direct perturbation of protein levels in A. fumigatus, a feature not previously accessible to experimentation.

molecular biology↗

bioRxiv2025

A continuum reaction-diffusion model for spread of gene silencing in chromosomal inactivation

Regulation of gene silencing in large regions of chromosomes is crucial for development and disease progression, and there has been an increasing interest in using it for new therapeutics. One example of massive gene silencing is X chromosome inactivation (XCI), a process essential for dosage compensation of X-linked genes. During XCI, most genes in the X chromosome are inactivated following the transcription of XIST, an X-linked long noncoding RNA. Recent experiments with transgenes showed that the spread of gene silencing can be induced by XIST transcription in cis, but the spread is restricted in space. The mechanism of controlling the spread remains unclear. In this work, we develop a continuum reaction-diffusion model that elucidates chromosomal inactivation through a bistable system governed by a regulatory network for XIST-mediated gene silencing. We find that the spread of XIST can be tuned by known negative feedback loops regulating its synthesis and degradation, and that the spread of gene silencing is controlled by a wave-pinning mechanism in which both global regulation of silencing complex and local variations of histone modifications can play crucial roles. In addition, we integrate the discrete three-dimensional arrangement of the X chromosome and autosomes into this continuous model. We use a 3D chromosome structure inferred from experimental data and our modeling framework to show the spatiotemporal regulation for spread of gene silencing. Our method enables the investigation for the inactivation dynamics of large regions of chromosomes with varying degrees of the spread of gene silencing. Our model provides mechanistic insights that quantitatively relate gene regulatory networks to tunability and stability of chromosomal inactivation. Author SummaryPrecise control of gene expression is a fundamental process in biology and turning off large parts of chromosomes is both common in many species and important for development and diseases. A well-known example of chromosomal scale gene silencing is X chromosome inactivation (XCI), which helps balancing gene activity between sexes. XCI is governed by the production of an RNA called XIST, leading to most genes on one X chromosome being turned off. Experiments have shown that XIST can trigger nearby genes to turn off in natural and engineered contexts, but this effect only spreads to specific regions. The exact mechanism for this limit is not very well understood. In this study, the authors created a mathematical model to explain how XIST spreads and controls gene activity. They found that feedback systems involving XIST regulations and chromatin modifications synergize and determine how far the inactivation spreads, through a process similar to a wave that gets "pinned" in place. They also included the 3D shape of chromosomes in their model to better understand how gene silencing happens over time and space. This model helps to quantitatively describe chromosome inactivation with gene regulatory networks.

systems biology↗

bioRxiv2025

A novel frameshift mutation in Phosphoinositide 3-kinase regulatory subunit 1 (PIK3R1) causes immunodeficiency and Amyotrophic Lateral Sclerosis (ALS)

Mutations in PIK3R1, a regulatory subunit of Class I PI3K, are implicated in immune disorders and neurological conditions. We identified a novel heterozygous pathogenic frameshift mutation (c.1710dup) in PIK3R1 in a patient with common variable immunodeficiency who developed slowly progressive Amyotrophic Lateral Sclerosis. Induced pluripotent stem cells (iPSCs) and iPSC-derived motor neurons (iMNs) demonstrated that this mutation resulted in PIK3R1 haploinsufficiency, with downstream activation of AKT, disruption of neuronal electrical function and increased apoptosis in iPSC-derived motor neurons. Single-cell RNA sequencing (scRNA-seq) and pathway analysis of differentially expressed genes showed apoptosis pathways were upregulated in neuronal clusters from iMNs harboring the PIK3R1c.1710 dup mutation. Mutated iPSC-derived brain organoids were smaller than matched controls. scRNA-seq of brain organoids showed more active apoptosis in neuronal clusters of patient-derived brain organoids. These findings identify a critical and novel role for PIK3R1 haploinsufficiency in neuronal function and survival.

neuroscience↗

bioRxiv2025

RNA localization to nuclear speckles follows splicing logic

Nuclear speckles are membraneless organelles implicated in multiple RNA processing steps. In this work, we systematically characterize the sequence logic determining RNA localization to nuclear speckles. We find extensive similarities between the speckle localization code and the RNA splicing code, even for transcripts that do not undergo splicing. Specifically, speckle localization is enhanced by the presence of unspliced exon-like or intron-like sequence features. We demonstrate that interactions required for early splicesomal complex assembly contribute to speckle localization. We also show that speckle localization of isolated endogenous exons is reduced by disease-associated single nucleotide variants. Finally, we find that speckle localization strongly correlates with splicing kinetics of splicing-competent constructs and is tightly linked to the decision between exon inclusion and skipping. Together, these results suggest a model in which RNA speckle localization is associated with the formation of the early spliceosomal complex and enhances the efficiency of splicing reactions. HighlightsO_LISequences containing hallmarks of pre-mRNA dictate speckle localization C_LIO_LIRNA speckle localization is coupled to early spliceosome assembly C_LIO_LIDisease-associated single nucleotide variants reduce localization of isolated exons C_LIO_LIRNA speckle localization strongly correlates with splicing kinetics C_LI O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/656493v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@1efbb02org.highwire.dtl.DTLVardef@1deb7aaorg.highwire.dtl.DTLVardef@ec1ec2org.highwire.dtl.DTLVardef@1d78b72_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

biochemistry↗

bioRxiv2025

Increased vulnerability to noise exposure of low spontaneous rate type 1C spiral ganglion neuron synapses with inner hair cells (Pre-Print)

The inner hair cells (IHCs) in the inner ear form synapses with auditory nerve fibers (ANFs) that send sound signals to the brain. ANFs have been grouped by their level of spontaneous firing rates (SRs) into high-, medium-, and low-SR ANFs. Based on their molecular profiles evaluated by RNAseq experiments, ANFs have been divided into three groups (1A, 1B, and 1C) that likely correspond to high-, medium-, and low-SR ANFs, respectively. In guinea pigs, the synapses between IHCs and low-SR ANFs have been shown to be more vulnerable to noise exposure compared to other ANF subtypes, but not in a study performed in CBA/CaJ mice, questioning if these results can be generalized. Here, an LYPD1 reporter mouse model on a C57Bl/6J background with specifically labeled group 1C, low-SR ANFs was used to examine whether LYPD1 positive ANF synapses are more vulnerable to noise exposure. Six-week-old mice were exposed to an 8-16 kHz octave band noise presented at 100 dBA for 2 hours. One week later, cochlear tissue was harvested to quantify ANF synapses and compare the percentage of LYPD1 positive ANF synapses in noise-exposed and unexposed animals. Auditory brainstem response measurements were performed to assess hearing function after noise exposure. The number of all ANF synapses and the percentage of LYPD1-positive ANF synapses were reduced following noise exposure, concurrent with increased ABR thresholds and decreased ABR wave 1 amplitudes. The reduction in the percentage of LYPD1-positive ANF synapses specifically indicates greater vulnerability of LYPD1 positive ANF synapses to noise exposure compared to other ANFs in C57Bl/6J mice.

neuroscience↗

bioRxiv2025

HUGMi: Human Uro-Genital Microbiome database and hybrid classifier for improved species level annotation of 16S rRNA amplicon sequences

The human urogenital microbiota encompasses commensal microorganisms harbouring the urinary and reproductive tracts, and has been associated with the pathophysiology of multiple urogenital disorders. Here, the Human Urogenital Microbiome (HUGMi) workflow is introduced, wherein a manually curated, niche-specific, 16S rRNA database is integrated with a novel hybrid classification algorithm to enhance amplicon-based species-level taxonomic resolution in urogenital microbiome investigations. The HUGMi database is curated through rigorous quality assessment of sequences, nomenclature correction of taxonomies and meticulous selection of bacterial species biologically significant to the human urogenital region. Quantitative evaluation of taxonomic assignment with mock communities demonstrates that HUGMi consistently achieved superior accuracy compared to conventional databases, with statistically significant improvement in F1 scores. Comparative analyses across three sets of biological data also reveal a robust and versatile performance, with both QIIME2 BLAST and sklearn-based taxonomic classifiers and with varied 16S regions. Following these outcomes the HUGMi hybrid classifier was developed that combines the specificity of BLAST-based methods with the probabilistic framework of learning-based classifiers. This approach enabled superior species-level identification through varying confidence thresholds. In contrast to the limited number of species identified in real-time studies, the integrated outcome of the HUGMi database and hybrid classifier, not just replicated the original results but simultaneously revealed a spectrum of previously unidentified species. Despite its crucial role in human health, the urogenital microbiome is comparatively understudied with respect to other body sites. The HUGMi pipeline addresses this empirical lacuna by identifying a substantially expanded range of species-level taxa. This enhanced resolution will not only augment downstream functional studies, but also aid in the investigation of specific bacterial influence on urogenital homeostasis and disease pathogenesis.

bioinformatics↗

bioRxiv2025

VGLL1 contributes to both the transcriptome and epigenome of the developing trophoblast compartment

The trophectoderm (TE), the first lineage specified during mammalian development, initiates implantation and gives rise to placental trophoblasts. While animal models have elucidated key conserved signaling pathways involved in early TE specification, including BMP, WNT, and HIPPO, species-specific differences during early development emphasize the need for human-specific models. We previously identified VGLL1, a coactivator of TEAD transcription factors, as a human-specific placental marker. In this study, we employed a pluripotent stem cell (PSC)-based model of TE induction by BMP4 to investigate chromatin remodeling and transcriptional dynamics during TE formation. BMP4-induced chromatin accessibility changes promoted a trophoblast gene expression program, while mesoderm lineage markers were only transiently expressed upon canonical WNT activation. We found that VGLL1 was expressed downstream of key TE transcription factors (GATA2/3, TFAP2A/C) but was essential for establishment of full trophoblast identity by up-regulating EGFR and reinforcing GATA3 expression through positive feedback. Notably, VGLL1 enhanced canonical WNT signaling via direct regulation of WNT receptors and effectors. We also identified KDM6B, a histone demethylase that removes H3K27me3 repressive marks, as a direct VGLL1 target. KDM6B facilitated activation of bivalent promoters associated with TE markers, linking epigenetic regulation to lineage identity. Our findings establish a mechanistic framework positioning VGLL1 as a central regulator that integrates HIPPO, BMP, and WNT signaling pathways to drive establishment of human TE. Statement of SignificanceEarly development of the human placenta is essential for pregnancy success, yet the mechanisms that guide placental lineage specification remain poorly defined. Using human stem cells, we show how signaling pathways and chromatin remodeling programs work together to direct formation of the trophectoderm, the earliest placental cell type. We identify VGLL1 as a key regulator linking multiple signaling networks to gene expression and epigenetic control. Our findings reveal a species-specific mechanism of placental initiation with broad implications for understanding reproductive disorders, pregnancy loss, and advancing stem cell-based models to study and potentially treat human placental disease.

developmental biology↗

bioRxiv2025

Spatial differentiation of proteome in cervical cancer tissues using Imaging Mass Spectrometry

Cervical cancer, which is the fourth most common gynaecological cancer across the globe, has a poorly understood molecular pathogenesis and etiology. Current methods of diagnosis are based on cytology, histology and presence of Human Papillomavirus (HPV). Shortcomings of these methods lie with poor quality of smears which is very common in Papanicolaou (pap) smears, limited sensitivity in terms of early detection, dependence on presence of HPV, etc. Due to its high sensitivity and non-targeted approach, Matrix Assisted Laser Desorption Ionization based Imaging Mass Spectrometry (MALDI-IMS) might be advantageous to understand the pathogenesis, molecular mechanism, precise identification of surgical margins and identification of novel biomarkers. Since it can also identify proteins in the extracellular matrix, it is especially beneficial for the tissue types with sparse cells and excessive extracellular matrix. Although tissue proteome profiling for cervical cancer were reported, the heterogeneous distribution of proteins across cervical cancer tissues havent been explored. In this study, we employed a non-targeted MALDI-IMS based approach to profile the spatial distribution of proteins within cervical cancer tissues. We observed overexpression of Keratin 5 and Prelamin A/C in the region of cervical cancer tissues which were categorically labelled with cancerous morphology using histopathological examination. Both these proteins have been earlier associated with progression and aggressiveness of other cancers like breast and prostate cancers. However, no such reports are available for cervical cancer. Further studies are required on a large dataset to validate and quantitate these proteins as biomarkers for early diagnosis and prognosis of cervical cancer.

cancer biology↗

bioRxiv2025

Expression and In-silico Structural analysis of N-acetylglucosamine transporter, Ngt1 in model fungal pathogen, Candida albicans

IntroductionThe commensal yeast, Candida albicans, has the enormous metabolic flexibility to utilize alternative carbon sources such as N-acetylglucosamine (GlcNAc) at the infection sites, thereby facilitating its adaptive strategies to colonize and thrive within diverse host niches. In Candia, GlcNAc specific transporter (Ngt1) imports GlcNAc at cell surface to induce signaling through the master regulator Ngs1 at the chromatin level. Thus, GlcNAc signaling is responsible for changing its habitat from commensal to pathogenic life style. ObjectiveThe current study aims at understanding the expression, structural and functional intricacies of Ngt1 that determines to GlcNAc sensitivity, specificity and its transport which is a prerogatory step in the GlcNAc signaling process in Candida. MethodThe 3-D structure of Ngt1 was predicted using AlphaFold. We have carried out docking studies using AutoDoc suite for native and Site directed mutant versions of Ngt1 with GlcNAc to determine role of critical amino acids and further, tunnel analysis to reveal the transport mechanism. These findings lead to the designing structure-based Ngt1blockers via virtual screening of natural compound libraries. ResultsOur docking studies on Ngt1 with GlcNAc revealed the useful insights in to mechanism and the role of critical amino acids (Ala 324, Ile 325, Tyr 329, and Asp 332) responsible for interaction. In our analysis, Asn 195, located within transmembrane helix and part of the UNC-93-like transmembrane regulatory protein domain, was identified as critical residue for GlcNAc interaction compared with other mutated residues. Interestingly, the tunnel analysis of Ngt1 transporter revealed presence potential pathways in Ngt1 protein for effective GlcNAc transport. ConclusionThis study provides basic insights in to the structural aspects of Ngt1 and its interaction with GlcNAc that can be further explored for the development effective therapeutic agents for control of infection caused by the Candida. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/648653v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1dbd0eforg.highwire.dtl.DTLVardef@721896org.highwire.dtl.DTLVardef@ac2742org.highwire.dtl.DTLVardef@4591b0_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract:C_FLOATNO Structural and functional analysis of Ngt1 protein. Flow chart depicting Ngt1 3D modeling (AlphaFold2), docking studies Ngt1-wild type and SDM proteins with GlcNAc ligand, tunnel analysis reflecting transport of GlcNAc, and virtual screening to identify potential inhibitors (Brucine). C_FIG

bioinformatics↗

bioRxiv2025

Deep Learning-Driven Gender Classification of Drosophila melanogaster: Advancing Real-Time Analysis with Mobile Integration

Researchers extensively use Drosophila melanogaster as a model organism in genetic research and developmental studies to better understand human diseases such as cancer and diabetes. For such investigations, it is necessary to identify and classify male and female flies. This study uses deep learning techniques for gender classification of Drosophila melanogaster via models YOLOv8, Detectron2, ResNet-50, InceptionV3, and MobileNet. Benchmarking revealed that YOLOv8 achieved a maximum accuracy of 98.0%. The classification and object detection models are integrated into a mobile application, facilitating real-time gender classification. This study demonstrates the possibility of integrating deep learning models with mobile technology while ensuring an efficient way for gender prediction, leading to better reproducibility and generating new opportunities in biological research.

scientific communication and education↗

bioRxiv2025

Examining Sleep Signals at the Cradle of Life: Can phylogenomic analysis of the Last Universal Common Ancestor (LUCA) reveal the fundamental role of sleep?

In common with most physiological activities, sleep is a highly evolutionarily conserved function. Nevertheless, the purpose of sleep remains inadequately investigated. One possible cause of this deficiency is the limitations of the traditional methods used for examining sleep. Up to this time, the mainstay tool used to look at the evolutionary basis of sleep has been phylogenetic analysis. This approach has provided many valuable insights into sleep, yet it has left many questions unanswered. The present study uses a relatively new hybrid technique at the interface of phylogenetics and genomics, known as phylogenomic analysis. This study is the first to use phylogenomic analysis to investigate the basis of sleep by evaluating the presence and conservation of sleep-related genes in the reconstructed genome of the Last Universal Common Ancestor (LUCA). Our gene set enrichment analysis of humans and LUCA indicates that the conserved sleep genes are linked to signaling, metabolism, and circadian rhythm pathways, suggesting that these genes possess primordial roles in essential physiological functions. These findings indicate that the component genes carry out essential physiological tasks that were subsequently repurposed to regulate sleep in more advanced organisms throughout evolution. This study lays the foundation for a systematic phylogenomic exploration of sleep-related genes, connecting molecular evolution with sleep science. By tracing the biological history of sleep to its deep evolutionary origins, our research presents novel insights into sleeps nature, origin, and evolutionary function, paving the way for further interdisciplinary exploration of the biology of sleep. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/644522v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@17adc89org.highwire.dtl.DTLVardef@124de86org.highwire.dtl.DTLVardef@18d3e5corg.highwire.dtl.DTLVardef@1f93b06_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

In silico discovery of nanobody binders to a G-protein coupled receptor using AlphaFold-Multimer

Antibodies are central mediators of the adaptive immune response, and they are powerful research tools and therapeutics. Antibody discovery requires substantial experimental effort, such as immunization campaigns or in vitro library screening. Predicting antibody-antigen binding a priori remains challenging. However, recent machine learning methods raise the possibility of in silico antibody discovery, bypassing or reducing initial experimental bottlenecks. Here, we report a virtual screen using AlphaFold-Multimer (AF-M) that prospectively identified nanobody binders to MRGPRX2, a G protein-coupled receptor (GPCR) and therapeutic target for the treatment of pseudoallergic inflammation and itch. Using previously reported nanobody-GPCR structures, we identified a set of AF-M outputs that effectively discriminate between interacting and non-interacting nanobody-GPCR pairs. We used these outputs to perform a prospective in silico screen, identified nanobodies that bind MRGPRX2 with high affinity, and confirmed activity in signaling and functional cellular assays. Our results provide a proof of concept for fully computational antibody discovery pipelines that can circumvent laboratory experiments.

biochemistry↗

bioRxiv2025

Promoter-centric gene regulation in drug-resistant cancer

In eukaryotic cells, gene-distal regulatory elements (REs) facilitate long-range gene regulation, ensuring cell type-specific transcriptional programs. This mechanism is frequently disrupted in cancer, often driven by transcription factors (TFs) that serve as targets for cancer therapy. However, targeting these TFs can lead to acquired resistance mechanisms that are not fully understood. We demonstrate that mesothelioma cancer cells, dependent on the oncogenic driver TF family TEAD, develop resistance to a pan-TEAD inhibitor and revert to an evolutionarily ancient, promoter-centric gene regulatory mechanism to recover gene expression following TEAD inhibition. Base-pair-resolution 3D chromatin conformation mapping reveals that RE-promoter interactions are disrupted in resistant cells, despite epigenetic and transcriptomic recovery. Mechanistically, in resistant cells, TF complexes, including resistance-specific FOSL1 and KLF4, preferentially bind and enhance promoter activity to recover gene expression, rendering distal REs dispensable. Our findings highlight promoter elements and promoter-specific TFs as potential therapeutic targets using a model of drug-resistant cancer.

cancer biology↗

bioRxiv2025

CCRL2 promotes the interferon-γ signaling response in myeloid neoplasms with erythroid differentiation and mutated TP53

Patients with myeloid neoplasms with loss-of-function TP53 mutations and erythroid differentiation have poor outcomes, and a better understanding of disease biology is required. Upregulation of interferon-{gamma} (IFN-{gamma}) signaling has been associated with acute myeloid leukemia (AML) progression and chemotherapy resistance, but its drivers remain unclear. In this study, we found that the surface receptor C-C motif chemokine receptor-like 2 (CCRL2) is overexpressed in AML with erythroid differentiation and TP53 mutations compared to other AML subtypes and healthy hematopoietic cells. The knockout (KO) of CCRL2 suppressed erythroleukemia growth in vitro and in vivo. Further proteomics and transcriptomics analysis revealed IFN-{gamma} signaling response as the top CCRL2-regulated pathway in erythroleukemia. Our mechanistic studies support direct CCRL2 driven IFN-{gamma} signaling independent of exogenous IFN-{gamma}, through phosphorylation of STAT1, via JAK2-dependent and independent mechanisms. CCRL2/IFN-{gamma} signaling is upregulated in erythroid leukemias, and TP53 mutated AML without concurrent increase of IFN-{gamma} secretion in the bone marrow microenvironment and is directly induced by TP53 KO. Finally, CCRL2/IFN-{gamma} signaling is associated with the transformation of pre-leukemic single-hit TP53 clones to multi-hit TP53 mutated AML, increased resistance to venetoclax and worse survival in AML. Overall, our findings support that CCRL2 is an essential driver of cell-autonomous IFN-{gamma} signaling response in myeloid neoplasms with erythroid differentiation and TP53 mutations and highlight CCRL2 as a relevant novel target for these neoplasms. One Sentence SummaryCCRL2 is overexpressed in AML with loss-of-function TP53 mutations and erythroid differentiation and promotes IFN-{gamma} signaling response via a cell-intrinsic mechanism.

cancer biology↗

bioRxiv2025

Unraveling the distinct motion bias of TrkA-NGF complex in NGFR100W-driven HSAN V disease

Nerve growth factor (NGF), which binds to tropomyosin-related kinase A (TrkA) receptor, plays essential roles in neuronal survival and function and is also a potent mediator of pain sensation. Mutations in NGF, particularly NGFR100W, cause hereditary sensory autonomic neuropathy V (HSAN V), which is characterized by insensitivity to pain but without impairment of neurotrophin function. Even though several studies reported the mechanism of growing HSAN V disease, the dynamic mechanisms that dictate its functional specificity remain unclear. In this study, we performed a microsecond scale molecular dynamics (MD) simulation to elucidate the changes in the structural dynamics of NGF by NGFR100W at an atomic level to dissect the distinct motion bias for specific TrkA functions. We found that the NGFR100W reduced NGF dimerization while its binding to the TrkA remained unchanged. NGFR100W enhanced the magnitude of bond formation in the different regions from TrkA, which induced different correlated and dynamic motions associated with impaired nociceptive signaling. The dynamics scenario from this study, shedding light on the deleterious role of NGFR100W, provides new structural insights into the function-oriented dynamics motion of the TrkA-NGF complex, offering potential avenues for designing new therapeutics.

neuroscience↗

bioRxiv2025

Studying sleep orthologs in Epsilonproteobacteria through an evolutionary lens: Investigating sleep mysteries through phylogenomics

The current study employed phylogenomic methods to examine the evolutionary role and significance of sleep-related genes in Sulfurimonas paralvinellae of the Epsilonproteobacteria class. This has facilitated the identification of conserved sleep orthologs, including DnaK, serine hydroxymethyltransferase, and potassium channel family proteins, exhibiting sequence similarities ranging from 39.13% to 61.45%. These findings align with prior research indicating that chaperones and ion channels are conserved during sleep. This was demonstrated by the observation that proteins with fewer domains exhibited more significant conservation than others, such as adenylate kinase, which is substantial under selective pressure. Distinct adaptations in bifunctional protein - serine/threonine kinases and phosphatases were linked to S. paralvinellae, an extremophilic organism adapted to high-pressure and/or high-temperature conditions, indicating functional divergence influenced by the organisms environment. The Gene Ontology study results indicated catalytic activity, potassium channel function, and cellular processes, underscoring the significance of ion channels in regulating the sleep-wake cycle. Furthermore, the categories not recognized as particularly significant for the over-represented genes encompassed metabolic and signal transduction categories, suggesting enhanced functional flexibility within this protein subfamily. The findings emphasize that orthologous interactions are complex and influenced by subfunctionalization and neofunctionalization of ecology and evolution. These findings enhance the existing understanding of the evolution of sleep-related genes and their association with metabolic and environmental changes, providing a foundation for subsequent experimental investigations and cross-taxonomic comparisons.

genomics↗

bioRxiv2024

Elucidating conformational alteration of human islet amyloid polypeptide by nonsynonymous substitution

Islet amyloid polypeptide (IAPP) is a peptide hormone that serves multiple essential functions, including metabolism and regulating gastric emptying and satiation through amylin receptors. However, mutations in the IAPP, notably in the amyloidogenic segment (20-29 amino acid residues), cause its aggregation and amyloid formation, which leads to {beta}-cell toxicity and death in type 2 diabetes mellitus (T2DM) and protein misfolding disorders (PMDs). The current work aims to elucidate the non-synonymous variants in the IAPP, which may adversely affect its function and rise to T2DM and PMDs. We harnessed in silico non-synonymous single-nucleotide polymorphisms (nsSNPs) assessment and molecular dynamics (MD) simulation to discover the potential deleterious mutants that cause T2DM and PMDs. Firstly, we executed nsSNPs prediction in IAPP using the NCBI dbSNP server, and then, all the predicted nsSNPs were assessed by a total of 26 in silico tools to find out which possessed the most deleterious effect in IAPP. Finally, MD simulation was carried out utilizing the most deleterious nsSNPs to check which significantly alters the conformational dynamics of IAPP. We found a total of 62 nsSNPs, among which the top 4 deleterious nsSNPs (T37P, L45P, G66R, and T69I) were selected based on the deleteriousness predictions by in silico tools and their location in the mature IAPP sequence (34-70 amino acid residues). MD simulations further confirm that three variants (T37P, L45P, and G66R) significantly alter the conformational dynamics of IAPP, suggesting a potential starting point for future research to elucidate the roles of these variants in IAPP aggregation and amyloid formation and their associations with T2DM and PMDs.

biophysics↗