Biology subjects

Saha, D.

Publications and source records attributed to Saha, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

An insect brain-based bioelectronic neural sensor for the systemic detection and precise classification of endometriosis

Endometriosis is a chronic inflammatory disease with limited screening options and a recognized diagnostic delay. To investigate detection potentialities, a bioelectronic sensor is realized to detect endometriotic vs endometrial models via their emitted volatile organic compounds (VOCs) by leveraging an insect olfactory system combined with computational analytical techniques for classification. Our analyses of cell culture headspace-evoked neural responses show that our sensor can distinguish multiple cell lines by their scent (i.e., emitted VOC mixture). By combining neural responses across experiments, we obtained high-dimensional population neural response templates that were used to classify unknown samples with a high accuracy. We obtained an accuracy of 89% in differentiating 4 cell lines at two growth timepoints (24 hr. and 72 hr.) and obtained an accuracy of 88% in classifying epithelial co-cultures of endometriotic and endometrial cell lines cultured at 0%, 25%, 50%, 75%, and 100% in ascending/descending ratios. Our results support the hypothesis that endometriosis is detectable via the metabolic differences found in the emitted gas mixtures or scent from various cell lines and demonstrates the effectiveness of our sensor in distinguishing the subtle changes in endometriotic vs endometrial models pertaining to durations in growth and co-cultures.

bioengineering↗

bioRxiv2025

Molecular Phenotypic Plasticity Informs Possible Adaptive Change of Triple-Negative Breast Cancer Cells In Vivo

Background and ObjectivesCancer evolves via interconnected mechanisms, including changes in extrachromosomal DNA (ecDNA), genetic instability, and interactions with the tumor microenvironment (TME). These mechanisms allow for some clones to evolve metastatic traits, evade the immune system, and resist chemotherapy. However, how cancer cells evolve in vivo remains poorly understood. This study investigates the in vivo changes in gene expression of triple-negative breast cancer (TNBC) cells implanted in BALB/c mice. MethodologyWe analyzed RNA-seq data from 4T1 TNBC cells and tumors at different growth stages (1-, 3-, and 6-week) to identify differentially expressed genes, protein-protein interactions, and ecDNA alterations. We also assessed how ecDNA and genomic instability proteins interact with anti-TNBC drugs ResultsOur results reveal early transcriptional shifts within one week of tumor implantation, showing rapid acclimation. Changes in gene expression continued over time, with significant molecular reprogramming observed at six weeks under in vivo environmental pressures, including ecDNA alterations and immune evasion. The shift from the earlier generation (1 week) to the later generation (6 weeks) suggests cumulative alterations in key oncogenic pathways related to tumor progression. Additionally, we found that mutations in ecDNA and genomic instability proteins influence drug binding affinity, suggesting that adaptive changes may impact chemotherapy response. Conclusions and ImplicationsThis study provides new insights into how TNBC tumors may evolve over time and novel ecDNA-related mechanisms of possible tumor adaptation, highlighting potential biomarkers for tumor aggression and immune evasion, which could help develop more effective therapeutic strategies against TNBC.

cancer biology↗

bioRxiv2025

DDS-E-Sim: A Transformer-Based Generative Framework for Simulating Error-Prone Sequences in DNA Data Storage

DNA has emerged as a promising medium for long-lasting data stoage due to its high information density and long-term stability. However, DNA storage is a complex process where each stage introduces noise and errors. Since running DNA data storage experiments in vitro is still expensive and time-consuming, a simulation model is quite necessary that can mimic the error patterns in the real data and simulate the experiments. Existing tools often rely on fixed error rates or are specific to certain technologies. We propose DDS-E-Sim, a transformer-based probabilistic generative framework that simulates errors in a DNA data storage channel, regardless of the process or technology. DDS-E-Sim successfully captures the error distribution of DNA storage pipelines and learns to stochastically generate erroneous DNA reads. Given oligos (DNA sequences to write), it outputs erroneous reads resembling real pipelines capturing both random and biased errors, such as k-mer and transition errors. Evaluations on two distinct technology-specific datasets show high fidelity and universality: DDS-E-SIM exhibit a total error rate deviation of only 0.1% and 0.7% respectively on the datasets processed with Illumina MiSeq and Oxford Nanopore. Additionally, our simulator generates 100,743 unique oligos from 35,329 sequences, with coverage 5 (each sequence read five times) in the test datasets, demonstrating its ability to simulate biased errors and stochastic properties simultaneously.

bioinformatics↗

bioRxiv2024

Hypometabolism in Autism Spectrum Disorder: Insights from Brain and Blood Transcriptomics

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication, repetitive behaviors, and restricted interests. Recent research has emphasized the importance of metabolic dysfunctions in the pathophysiology of ASD. This study investigates metabolic alterations associated with ASD by analyzing transcriptomic data obtained from the prefrontal cortex (bulk tissue and single-nucleus) and data from peripheral blood mononuclear cells (PBMC). We assessed the metabolic activity of each patient based on gene expression profiles, revealing significant downregulation of vital metabolic pathways, including glycolysis, the tricarboxylic acid (TCA) cycle, and oxidative phosphorylation, indicative of hypometabolism. Our analysis also highlighted dysregulation in lipid, vitamin, amino acid, and heme metabolism, which may contribute to the neurodevelopmental delays associated with ASD. Cell-specific metabolic activities in the ASD brain showed altered pathways in astrocytes, oligodendrocytes, excitatory neurons, and interneurons. Furthermore, we identified critical metabolic pathways and genes from PBMC gene expression data that distinguish ASD patients from typically developing individuals. Our findings demonstrate a consistent pattern of metabolic dysfunction across brain and blood samples. This research provides a comprehensive understanding of metabolic alterations in ASD, paving the way for exploring potential therapeutic strategies targeting metabolic dysregulation.

systems biology↗

bioRxiv2024

Genetic diversity and antimicrobial resistance of Campylobacter jejuni isolates from Gambian children under five with moderate-to-severe diarrhoea and healthy Controls

IntroductionCampylobacter is a leading cause of bacterial gastroenteritis globally, but its molecular epidemiology remains poorly understood in sub-Saharan Africa. This study investigates the genotypic population structure of Campylobacter jejuni isolates from children with moderate-to-severe diarrhoea (MSD) and healthy controls in The Gambia. Additionally, we determined the antimicrobial susceptibility levels of the isolates. MethodsAs part of the Global Enteric Multicenter Study (GEMS) in The Gambia, a total of 49 C. jejuni isolates were collected from the stools of children under 5 years old, including 22 with MSD and 27 healthy controls. These isolates were subjected to multilocus sequence typing (MLST) and antimicrobial susceptibility testing using the disc-diffusion method. ResultsThe C. jejuni isolates belonged to 22 sequence types (STs), ten of which were novel. The most common STs were ST-353 (19.1%, 9/47), ST-7784 (12.7%, 6/47), and ST-1038 (10.6%, 5/47). All isolates were fully susceptible to erythromycin, tetracycline, gentamicin and chloramphenicol, with two isolates (4.4%, 2/45) resistant to ciprofloxacin and nalidixic acid. Antimicrobial resistance or intermediate susceptibility to trimethoprim-sulfamethoxazole, cefotaxime and ampicillin was observed in 91.1% (41/45), 90.9% (40/44), and 44.4% (20/45) of the isolates, respectively. There was no strong evidence linking C. jejuni antimicrobial susceptibility or MLST genotype to MSD status. ConclusionThis study provides the first overview of the high genotypic diversity of human C. jejuni isolates in The Gambia and reveals low-level resistance among the isolates to antibiotics commonly used to treat campylobacteriosis. The study contributes to understanding the epidemiology and resistance patterns of C. jejuni in this region.

microbiology↗

bioRxiv2024

Candida glabrata maintains two Hap1 homologs, Zcf27 andZcf4, for distinct roles in ergosterol gene regulation to mediate sterol homeostasis under azole and hypoxic conditions

Candida glabrata exhibits innate resistance to azole antifungal drugs but also has the propensity to rapidly develop clinical drug resistance. Azole drugs, which target Erg11, is one of the three major classes of antifungals used to treat Candida infections. Despite their widespread use, the mechanism controlling azole-induced ERG gene expression and drug resistance in C. glabrata has primarily revolved around Upc2 and/or Pdr1. In this study, we determined the function of two zinc cluster transcription factors, Zcf27 and Zcf4, as direct but distinct regulators of ERG genes. Our phylogenetic analysis revealed C. glabrata Zcf27 and Zcf4 as the closest homologs to Saccharomyces cerevisiae Hap1. Hap1 is a known zinc cluster transcription factor in S. cerevisiae in controlling ERG gene expression under aerobic and hypoxic conditions. Interestingly, when we deleted HAP1 or ZCF27 in either S. cerevisiae or C. glabrata, respectively, both deletion strains showed altered susceptibility to azole drugs, whereas the strain deleted for ZCF4 did not exhibit azole susceptibility. We also determined that the increased azole susceptibility in a zcf27{Delta} strain is attributed to decreased azole-induced expression of ERG genes, resulting in decreased levels of total ergosterol. Surprisingly, Zcf4 protein expression is barely detected under aerobic conditions but is specifically induced under hypoxic conditions. However, under hypoxic conditions, Zcf4 but not Zcf27 was directly required for the repression of ERG genes. This study provides the first demonstration that Zcf27 and Zcf4 have evolved to serve distinct roles allowing C. glabrata to adapt to specific host and environmental conditions. IMPORTANCEInvasive and drug-resistant fungal infections pose a significant public health concern. Candida glabrata, a human fungal pathogen, is often difficult to treat due to its intrinsic resistance to azole antifungal drugs and its capacity to develop clinical drug resistance. Therefore, understanding the pathways that facilitate fungal growth and environmental adaptation may lead to novel drug targets and/or more efficacious antifungal therapies. While the mechanisms of azole resistance in Candida species have been extensively studied, the roles of zinc cluster transcription factors, such as Zcf27 and Zcf4, in C. glabrata have remained largely unexplored until now. Our research shows that these factors play distinct yet crucial roles in regulating ergosterol homeostasis under azole drug treatment and oxygen-limiting growth conditions. These findings offer new insights into how this pathogen adapts to different environmental conditions and enhances our understanding of factors that alter drug susceptibility and/or resistance.

genetics↗

bioRxiv2024

Evaluation of melanocyte stem cell population in vitiliginous skin pre- and post-narrow-band UVB phototherapy

Vitiligo vulgaris is an autoimmune disorder characterized by the destruction of epidermal melanocytes leading to white lesions devoid of pigmentation. The destruction of epidermal melanocytes. Is driven by tissue-resident and circulatory immune cells that maintain an inflammatory milieu. Two percent of the global population suffer from vitiligo vulgaris, of which, prevalence is higher in the Indian population. Narrow-band UV-B (NBUVB) phototherapy is commonly used as an economical, non-invasive, and well-tolerated treatment modality. NBUVB promotes the migration of melanocyte stem cells (MelSC) to the epidermis, thus regaining pigmentation in affected individuals. Despite the widespread use of NBUVB in secondary and tertiary clinics in India, the status of melanocyte stem cells and immune cells, pre-and post-NBUVB is not well understood. We observe that following NBUVB phototherapy, melanocyte stem cells (pax3+) re-populate the epidermis and express melanogenesis markers (Tyrosinase, Trp2, kit) concomitant with a decrease in CD3+ T-cells within the skin. Our study reaffirms the therapeutic efficacy of NBUVB in promoting re-pigmentation in an Indian cohort of vitiligo patients. Further, NBUVB is effective in reducing overall immune load, widely considered a major contributor to the pathogenesis of the disease.

cell biology↗

bioRxiv2023

Angiopoietin-like protein 2 mediates vasculopathy driven fibrogenesis in a mouse model of systemic sclerosis

Vasculopathy is a common hallmark of various fibrotic disorders including systemic sclerosis (SSc), yet its underlying etiology and contribution to fibrogenesis remain ill-defined. In SSc the vasculopathy typically precedes the onset of fibrosis and we observed that this phenomenon is recapitulated in the Snail transgenic mouse model of SSc. The vascular anomalies manifest as deformed vessels, endothelial cell dysfunction and vascular leakage. Our investigation into the underlying mechanism of this phenotype revealed that Angiopoietin-like protein 2 (Angptl2), secreted by the Snail transgenic keratinocytes, is a principal driver of fibrotic vasculopathy. In endothelial cells, Angptl2 upregulates pro-fibrotic genes, downregulates the tight junction protein Claudin 5, and prompts the acquisition of mesenchymal characteristics. Inhibiting endothelial cell junctional instability and consequently vascular leakage with a synthetic analog of the microbial metabolite Urolithin A (UAS03) effectively mitigated the vasculopathy and inhibited fibrogenesis. Thus, Angptl2 emerges as a promising early biomarker of the disease and inhibiting the vasculopathy inducing effects of this protein with agents such as UAS03 presents an appealing therapeutic avenue to reduce disease severity. These insights hold the potential to revolutionize the approach to the treatment of fibrotic diseases by targeting the vascular defects.

pathology↗

bioRxiv2023

Employing a honeybee olfactory neural circuit as a novel gas sensor for the detection of human lung cancer biomarkers

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, for the first time, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers and their mixtures at concentration ranges relevant to human breath, parts-per-billion to parts-per-trillion. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we could classify individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create synthetic lung cancer vs. synthetic healthy breath, honeybee population neuronal responses were also able to classify those complex breath mixtures successfully (100% success rate with a leave-one-trial-out method). Finally, we used separate training and testing datasets containing responses to the synthetic lung cancer and healthy breath mixtures. We identified a simple metric, the peak response of the neuronal ensemble, with the ability to distinguish synthetic lung cancer breath from the healthy breath with 86.7% success rate. This study provides proof-of-concept results that a powerful biological gas sensor, the honeybee olfactory system, can be used to detect human lung cancer biomarkers and their complex mixtures at biological concentrations.

bioengineering↗

bioRxiv2023

A gut meta-interactome map reveals modulation of human immunity by microbiome effectors

The molecular mechanisms by which the gut microbiome influences human health remain largely unknown. Pseudomonadota is the third most abundant phylum in normal gut microbiomes. Several pathogens in this phylum can inject so-called virulence effector proteins into host cells. We report the identification of intact type 3 secretion systems (T3SS) in 5 - 20% of commensal Pseudomonadota in normal human gut microbiomes. To understand their functions, we experimentally generated a high-quality protein-protein meta-interactome map consisting of 1,263 interactions between 289 bacterial effectors and 430 human proteins. Effector targets are enriched for metabolic and immune functions and for genetic variation of microbiome-influenced traits including autoimmune diseases. We demonstrate that effectors modulate NF-{kappa}B signaling, cytokine secretion, and adhesion molecule expression. Finally, effectors are enriched in metagenomes of Crohns disease, but not ulcerative colitis patients pointing toward complex contributions to the etiology of inflammatory bowel diseases. Our results suggest that effector-host protein interactions are an important regulatory layer by which the microbiome impacts human health.

microbiology↗

bioRxiv2023

Testing Adaptive Therapy Protocols using Gemcitabine and Capecitabine on a Mouse Model of Endocrine-Resistant Breast Cancer

Highly effective cancer therapies often face limitations due to acquired resistance and toxicity. Adaptive therapy, an ecologically inspired approach, seeks to control therapeutic resistance and minimize toxicity by leveraging competitive interactions between drug-sensitive and drug-resistant subclones, prioritizing patient survival and quality of life over maximum cell kill. In preparation for a clinical trial in breast cancer, we used large populations of MCF7 cells to rapidly generate endocrine-resistance breast cancer cell line. We then mimicked second line therapy in ER+ breast cancers by treating the endocrine-resistant MCF7 cells in a mouse xenograft model to test adaptive therapy with capecitabine, gemcitabine, or the combination of those two drugs. Dose-modulation adaptive therapy with capecitabine alone increased survival time relative to MTD, but not statistically significant (HR: 0.22, 95% CI 0.043-1.1 P = 0.065). However, when we alternated the drugs in both dose modulation (HR = 0.11, 95% CI: 0.024 - 0.55, P = 0.007) and intermittent adaptive therapies significantly increased survival time compared to high dose combination therapy (HR = 0.07, 95% CI: 0.013 - 0.42; P = 0.003). Overall, survival time increased with reduced dose for both single drugs (P < 0.01) and combined drugs (P < 0.001). Adaptive therapy protocols resulted in tumors with lower proportions of proliferating cells (P = 0.0026) and more apoptotic cells (P = 0.045). The results show that Adaptive therapy outperforms high-dose therapy in controlling endocrine-resistant breast cancer, favoring slower-growing tumors, and showing promise in two-drug alternating regimens.

cancer biology↗

bioRxiv2023

Partial alopecia area retains bulge hair follicle progenitor cells in Indian androgenetic alopecia patients

Androgenic alopecia (AGA) is a pathological condition characterized by the progressive decrease of scalp hair follicle density. Completely bald areas of AGA scalp still retain hair follicle stem cells but the progenitor cells are drastically decreased in number. However, it is unknown when the progenitor cells begin to diminish in number during the progression of AGA. Despite the prevalence of AGA in 58% of the Indian male population, no study to date has characterized the hair follicle stem and progenitor cell populations in AGA patients in this ethnic group. We observed that the partially bald area retains progenitor cells expressing CD34 and Sox9 but they are not present in the hair follicles in the completely bald area. Our study sheds light on the timeframe for effective therapeutic interventions based on modulating regulatory mechanisms to reinitiate the existing inactive follicle stem cells.

pathology↗

bioRxiv2023

xpanding the toolkit for genetic manipulation and discovery in Candida species using a CRISPR ribonucleoprotein-based approach

The World Health Organization recently published the first list of priority fungal pathogens highlighting multiple Candida species including C. glabrata, C. albicans, and C. auris. The use of CRISPR-Cas9 and auxotrophic C. glabrata and C. albicans strains have been instrumental in the study of these fungal pathogens. Dominant drug resistance cassettes are also critical for genetic manipulation and eliminate the concern of altered virulence when using auxotrophic strains. However, genetic manipulation has been mainly limited to the use of two drug resistance cassettes, NatMX and HphMX. Using an in vitro assembled CRISPR-Cas9 ribonucleoprotein (RNP)-based system and 130-150 bp homology regions for directed repair, we expand the drug resistance cassettes for Candida to include KanMX and BleMX, commonly used in S. cerevisiae. As a proof of principle, we demonstrated efficient deletion of ERG genes using KanMX and BleMX. We also showed the utility of the CRISPR-Cas9 RNP system for generating double deletions of genes in the ergosterol pathway and endogenous epitope tagging of ERG genes using an existing KanMX cassette. This indicates that CRISPR-Cas9 RNP can be used to repurpose the S. cerevisiae toolkit. Furthermore, we demonstrated that this method is effective at deleting ERG3 in C. auris using a codon optimized BleMX cassette and effective at deleting the epigenetic factor, SET1, in C. albicans using a recyclable SAT1. Using this expanded toolkit, we discovered new insights into fungal biology and drug resistance. IMPORTANCEThe increasing problem of drug resistance and emerging pathogens is an urgent global health problem that necessitates the development and expansion of tools for studying fungal drug resistance and pathogenesis. We have demonstrated the effectiveness of an expression-free CRISPR-Cas9 RNP-based approach employing 130-150 bp homology regions for directed repair. Our approach is robust and efficient for making gene deletions in C. glabrata, C. auris and C. albicans as well as epitope tagging in C. glabrata. Furthermore, we demonstrated that KanMX and BleMX drug resistance cassettes can be repurposed in C. glabrata and BleMX in C. auris. Overall, we have expanded the toolkit for genetic manipulation and discovery in fungal pathogens.

genetics↗

bioRxiv2023

Adaptation invariant concentration discrimination in an insect olfactory system

Neural responses evoked by a stimulus reduce upon repetition. While this adaptation allows the sensory system to attend to novel cues, does information about the recurring stimulus, particularly its intensity, get compromised? We explored this issue in the locust olfactory system. We found that locusts innate behavioral response to odorants varied with repetition and stimulus intensity. Counter-intuitively, the stimulus-intensity dependent differences became significant only after adaptation had set in. Adaptation altered responses of individual neurons in the antennal lobe (neural network downstream to insect antenna). These response variations to repetitions of the same stimulus were unpredictable and inconsistent across intensities. Although both adaptation and intensity decrements resulted in an overall reduction in spiking activities across neurons, these changes could be disentangled, and information about stimulus intensity was robustly maintained by ensemble neural responses. In sum, these results show how information about odor intensity can be preserved in an adaptation-invariant manner.

neuroscience↗

bioRxiv2023

Bacopa monnieri phytochemicals regulate fibroblast cell migration via modulation of focal adhesions

The Bacopa monnieri plant contains a large repertoire of active phytochemicals that have been used extensively in traditional medicine for the treatment of various complex diseases. More recently it has been shown to increase the wound healing rate in rats, though its mechanism of action is largely unknown. Here we investigated the cellular pathways activated by a methanol extract of Bacopa monnieri in human dermal fibroblasts, which play many critical roles in the wound healing program. Gene expression analysis revealed that Bacopa monnieri extract can enhance tissue repair by modulating multiple processes involved in the wound healing program such as migration, proliferation, and angiogenesis. We discovered that Bacopa monnieri extract can increase migration of fibroblasts via modulating the size and number of focal adhesions. Bacopa monnieri-mediated changes in focal adhesions are dependent on 5{beta}1 integrin activation and subsequent phosphorylation of Focal Adhesion Kinase (FAK). Altogether our results suggest that Bacopa monnieri extract could enhance the wound healing rate via modulating fibroblast migration in the wound bed.

cell biology↗

bioRxiv2022

Predicting and Interpreting Protein Developability via Transfer of Convolutional Sequence Representation

Engineered proteins have emerged as novel diagnostics, therapeutics, and catalysts. Often, poor protein developability - quantified by expression, solubility, and stability - hinders utility. The ability to predict protein developability from amino acid sequence would reduce the experimental burden when selecting candidates. Recent advances in screening technologies enabled a high-throughput developability dataset for 105 of 1020 possible variants of protein ligand scaffold Gp2. In this work, we evaluate the ability of neural networks to learn a developability representation from a high-throughput dataset and transfer this knowledge to predict recombinant expression beyond observed sequences. The model convolves learned amino acid properties to predict expression levels 44% closer to the experimental variance compared to a non-embedded control. Analysis of learned amino acid embeddings highlights the uniqueness of cysteine, the importance of hydrophobicity and charge, and the unimportance of aromaticity, when aiming to improve the developability of small proteins. We identify clusters of similar sequences with increased developability through nonlinear dimensionality reduction and we explore the inferred developability landscape via nested sampling. The analysis enables the first direct visualization of the fitness landscape and highlights the existence of evolutionary bottlenecks in sequence space giving rise to competing subpopulations of sequences with different developability. The work advances applied protein engineering efforts by predicting and interpreting protein scaffold developability from a limited dataset. Furthermore, our statistical mechanical treatment of the problem advances foundational efforts to characterize the structure of the protein fitness landscape and the amino acid characteristics that influence protein developability. Significance statementProtein developability prediction and understanding constitutes a critical limiting step in biologic discovery and engineering due to limited experimental throughput. We demonstrate the ability of a machine learning model to learn sequence-developability relationships first through the use of high-throughput assay data, followed by the transfer of the learned developability representation to predict the true metric of interest, recombinant yield in bacterial production. Model performance is 44% better than a model not pre-trained using the high-throughput assays. Analysis of model behavior reveals the importance of cysteine, charge, and hydrophobicity to developability, as well as of an evolutionary bottleneck that greatly limited sequence diversity above 1.3 mg/L yield. Experimental characterization of model predicted candidates confirms the benefit of this transfer learning and in-silico evolution approach.

bioinformatics↗

bioRxiv2022

WWOX P47T loss-of-function mutation induces epilepsy, progressive neuroinflammation, and cerebellar degeneration in mice phenocopying human SCAR12

WWOX gene loss-of-function (LoF) has been associated with neuropathologies resulting in developmental, epileptic, and ataxic phenotypes of varying severity based on the level of WWOX dysfunction. WWOX gene biallelic germline variant p.Pro47Thr (P47T) has been causally associated with a new form of autosomal recessive cerebellar ataxia with epilepsy and intellectual disability (SCAR12). This mutation affects the WW1 protein binding domain of WWOX, impairing its ability to interact with canonical proline-proline-X-tyrosine motifs in partner proteins. We generated a mutant knock-in mouse model of Wwox P47T that phenocopies SCAR12. WwoxP47T/P47T mice displayed epilepsy, profound social behavior and cognition deficits, and poor motor coordination, and unlike KO models that survive only for 1 month, live beyond 1 year of age. These deficits progressed with age, and mice became practically immobile, suggesting severe cerebellar dysfunction. WwoxP47T/P47T mice exhibited signs of progressive neuroinflammation with elevated astro-microgliosis that increased with age. The cerebellar cortex displayed significantly reduced molecular and granular layer thickness and a strikingly reduced number of Purkinje cells with degenerated dendrites. Transcriptome profiling from various brain regions from these Wwox LoF mice highlighted widespread changes in neuronal and glial pathways, enrichment of bioprocesses related to neuroinflammation and severe cerebellar dysfunction, activation of pathways compatible with compensatory neurogenesis along with major suppression of gene networks associated with excitability, neuronal cell differentiation and brain development. Our results show significant pathobiological effects and potential mechanisms through which WWOX LoF leads to epilepsy, cerebellar neurodegeneration, neuroinflammation, and ataxia. Additionally, the mouse model described here will be a useful tool for the study of WWOX in common neurodegenerative conditions in which it has been identified as a novel risk factor.

neuroscience↗

bioRxiv2022

An RNA binding module of SWI/SNF is required for activation of cell-type specific enhancers and super-enhancers in early development

The mammalian SWI/SNF complex is an ATP-dependent chromatin remodeler and master regulator in development that when mutated is the cause for several human diseases including cancer. Although SWI/SNF is highly enriched at enhancers and its basic chromatin remodeling activities have been studied for over 30 years, there is little known about how it regulates enhancer activity or enhancer-promoter interactions. We find a putative RNA binding module located near the C-terminus of the catalytic subunit of SWI/SNF required for SWI/SNF recruitment to cell-type specific enhancers and super-enhancers in naive and cell lineage primed pluripotent cells. The AT-hook is required for acquisition of the active histone marks H3K27ac and H3K4me1 and recruitment of the MLL3/4 co-activator to these enhancers and super-enhancers. Consistent with changes in enhancer architecture, loss of the AT-hook interferes with activation of genes involved in cell lineage priming as well as genes normally activated in naive pluripotent cells.

genomics↗