Biology subjects

Ding, S.

Publications and source records attributed to Ding, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Abnormal shear stress induces ferroptosis in endothelial cells via KLF6 downregulation

Stable laminar flow maintains vascular tone regulation, while abnormal blood flow, such as disturbed flow or extreme shear stress, causes endothelial dysfunction, but the underlying mechanism is yet to be explored. We used a microfluidic device to deform flat microchannel into tunnel-like macrochannel. The cross-sectional area of this macrochannel varies with the flow rate and the thickness of the deformable layer, creating three levels of shear stress: low (0.99 dyn/cm2, LSS), medium (4.78 dyn/cm2, MSS), and high (24 dyn/cm2, HSS). Comparing different shear stress exposure to endothelial cells for 24 h, prominent ferroptosis features emerged under either LSS or HSS compared to MSS. These features included increased C11 BODIPY-labeled lipid peroxidation and 4-hydroxynonenal accumulation, CoQ10 depletion, reduced SLC7A11 protein expression, and diminished cell death with Ferrostatin-1 treatment. RNA-seq analysis (LSS/MSS) showed that LSS significantly downregulated transcription of cholesterol homeostasis and unfolded protein response (UPR). Compared to MSS, Western blot results showed that both LSS and HSS reduced the expression of two key enzymes (MVD and IDI1) in the mevalonate pathway, as well as the expression of two main UPR signaling regulators (PERK and BiP). Based on the binding prediction between transcription factors and gene promoters from differentially expressed genes identified through RNA-seq, we found KLF6 to be a key transcription factor. It regulates the PERK-mediated UPR and the mevalonate pathway, which are associated with SLC7A11 expression and CoQ10 synthesis, respectively. The overexpression of KLF6 restored SLC7A11 and CoQ10 levels under both LSS and HSS, significantly reducing foam cell formation, monocyte adhesion, and lipid peroxidation. Our findings reveal KLF6 as a crucial regulator of atherosclerosis induced by abnormal shear stress.

cell biology↗

bioRxiv2025

Novel single-domain AA12 pyrroloquinoline quinone-dependent oxidoreductases directly and co-operatively drive lytic polysaccharide monooxygenase activity with AA8 module

The single-domain auxiliary activity family 12 (AA12) pyrroloquinoline quinone-dependent oxidoreductases and free AA8 modules are prevalent in cellulolytic fungi, however, their function in polysaccharide biodegradation is still confused. Here, we characterized three single-domain AA12 oxidoreductases and one free AA8 module from Thermothelomyces thermophilus and Thermothielavioides terrestris. All three single-domain AA12 oxidoreductases are restrict dehydrogenases with trace oxidase activity. All three single-domain AA12 enzymes could directly transfer electrons to lytic polysaccharide monooxygenase (LPMO) and drive NcLPMO9C activity. Furthermore, inter-protein electron transfer between single-domain AA12 enzymes and the AA8 module was observed. The AA12 enzyme-driven NcLPMO9C efficiency could be significantly enhanced by the addition of free AA8 module TthAA8B, probably attributing to the acceleration of electron transfer from AA12 enzymes to NcLPMO9C and the attenuation of H2O2 accumulation mediated by TthAA8B. Our findings highlight the potential role of single-domain AA12 enzyme and free AA8 modules in the biodegradation system of LPMOs. IMPORTANCEThis study reveals the directly electron transferring and driving capability of single-domain AA12 PQQ-dependent enzyme for the oxidative reaction of lytic polysaccharide monooxygenase (LPMO). This funding is quite distinct from the AA8 cytochrome domain-dependent driving pattern of the previous characterized multi-domain CcPDH. We also demonstrated that this priming capability could be facilitated by the free AA8 cytochrome module, providing new insight on the interactions and functions of single-domain AA12 enzymes and free AA8 modules in fueling LPMO activity during fungal lignocellulose biodegradation process. These findings collectively provide evidence for the potential function of widespread single-domain AA12 PQQ-dependent enzymes and free AA8 cytochrome modules as unique enzyme redox partners in cellulolytic fungi.

biochemistry↗

bioRxiv2025

BIN1 deficiency leads to DNA damage and neuronal insulin resistance through ATM dysregulation

The major neuronal isoform of the AD risk gene BIN1 is specifically reduced in patients. In the present work, we demonstrate that BIN1 is necessary for intact insulin signaling and its loss leads to cellular-level insulin resistance. Persistently activated mTORC1 feedback inhibits the insulin signaling; meanwhile, ATM-dependent DNA Damage Response decreases the expression of multiple insulin signaling pathway members. Unexpectedly, nuclear ATM activation is accompanied by autophagic degradation of the cytoplasmic ATM, rendering neurons susceptible to oxidative stress, which predisposes oxidative DNA damage, DNA strand breaks, and ATM-dependent DNA Damage Response. Treating BIN1-deficient mice with rapamycin or liraglutide to improve the insulin response, or with the natural antioxidant alpha-lipoic acid to attenuate oxidative stress, both effectively preserved the spatial cognitive ability. Lastly, we reanalyzed a single-cell transcriptomic dataset from human neurons and identified positive correlations between levels of BIN1 and the insulin signaling, as well as neuronal activity. Together, this work revealed an ATM-centered mechanism that globally damages neuronal health in BIN1-deficient pyramidal neurons, which could be a driving force in the AD disease course.

cell biology↗

bioRxiv2025

Auto-MedCalc: Automated Biomarkers Discovery and Risk Score Generation with AI Agents

Reproducible biomarker identification and transplant rejection risk prediction remain fundamental yet unsolved challenges in transplantation medicine. Traditional approaches rely on hypothesis-driven analyses and domain expertise, limiting scalability and generalizability across diverse populations. We introduce Transplant-Agents, a data-driven multi-agent AI framework integrating large language models (LLMs) with machine learning algorithms for automated biomarker identification and rejection risk prediction. Agents interact through structured, iterative dialogue governed by predefined rules and criteria, converging on optimal biomarker sets reproducible across multiple iterations. We evaluated three multicenter clinical trial transplant datasets from ImmPort, comprising 683 patients across kidney, liver, and heart transplant cohorts. Transplant-Agents achieve AUROC scores of 0.93, 0.88, and 0.88. Feature importance analysis further confirms the stability, interpretability and potential generalizability of identified biomarkers. This work demonstrates that AI-agent frameworks can reliably reproduce established transplant biomarkers while enabling transparent, validated, and standardized risk prediction pipelines.

bioinformatics↗

bioRxiv2025

Dissecting Molecular Origins of the Mechano-Adaptive Behaviors of Actomyosin Bundles

Actomyosin bundles, composed mainly of actin filaments, myosin II filaments, and actin cross-linking proteins, are central to force generation and maintenance in non-striated muscle cells. Actomyosin bundles exhibit diverse mechano-adaptive responses to external mechanical cues. However, the molecular mechanisms underlying such adaptability remain poorly understood. In this study, we employed experiments and agent-based simulations to illuminate how actomyosin bundles adapt to complex mechanical perturbations. Our experiments revealed that individual stress fibers isolated from cells, and thus operating independently of cellular regulation, exhibited buckling in response to rapid compressions following stretch, accompanied by gradual recovery to a straight configuration. Such buckling was not observed under slow compression, indicating that the bundles exhibit rate-dependent adaptive responses. These findings demonstrate that mechano-adaptive behavior is an intrinsic property of actomyosin bundles. Simulations successfully reproduced these rate-dependent behaviors intrinsic to actomyosin bundles and identified key factors determining the dependence. Bundle stiffness influenced the buckling-induced curvature but had little effect on the time required for recovery to straight configuration. Motor density did not alter the recovery time but significantly influenced the magnitude of tensile forces developed after full recovery. The recovery time was primarily governed by the motor walking rate and the applied compressive strain rate. This work reveals how intrinsic mechanics and motor activity drive actomyosin bundle behavior in cellular mechano-adaptation.

biophysics↗

bioRxiv2025

ImmuneFM: Pre-training Foundation Model from Cytometry Data for Immunology Research

Immunology is an essential field in the biomedicine domain, which plays an important role in oncology, vaccines, infection, etc. With the increasing amount of data available in immunology and artificial intelligence technique development, there is a need to develop data-driven AI methods in the field. However, the data from various immunology studies is very hard to integrate into an AI-ready dataset due to the lack of a standard. Moreover, independent immunology studies data lacks enough labels to train the supervised model. Motivated by these challenges, we curated a large-scale AI-ready cytometry dataset for immunology from the publicly available ImmPort portal. We design the framework to pre-train a foundation model, ImmuneFM, on the cytometry dataset. ImmuneFM can be applied to a wide range of downstream immunology diseases with fine-tuning on a limited number of labeled samples. The experiment results on eight downstream tasks demonstrate the superior performance of ImmuneFM compared to baseline deep learning and traditional methods.

immunology↗

bioRxiv2025

Human myelocyte and metamyelocyte-stage neutrophils suppress tumor immunity and promote cancer progression

Tumor-infiltrating neutrophils (TINs) are highly heterogeneous and mostly immunosuppressive in the tumor immune microenvironment (TIME). Current biomarkers of TINs and treatment strategies targeting TINs have not yielded optimal responses in patients across cancer types. Here, we separated human and mouse neutrophils into three developmental stages, including promyelocyte (PM), myelocyte & metamyelocyte (MC & MM), and banded & segmented (BD & SC) neutrophils. Based on this separation, we observed the predominance of human but not mouse MC & MM-stage neutrophils in bone marrow (BM), which exhibit potent immunosuppressive and tumor-promoting properties. MCs & MMs also occupy the majority of TINs among patients with 17 cancer types. Moreover, through the creation of a NCG-Gfi1-/- human immune system (HIS) mouse model, which supports efficient reconstitution of human TIN, we found a significant increase of BM MCs & MMs in tumor-bearing mice. By comparing the scRNA-seq analysis results of human neutrophils from both BM and tumors, we found CD63 and Galectin-3 distinguish MC & MM from neutrophil populations in cancer patients. Furthermore, we proposed a strategy with Flt3L to specifically induce the trans-differentiation of MCs & MMs into monocytic cells, and trigger tumor control in NCG-Gfi1-/- HIS mice. Thus, our findings establish an essential role of human MC & MM-stage neutrophils in promoting cancer progression, and suggest their potential as targets for developing potential biomarkers and immunotherapies for cancer.

immunology↗

bioRxiv2025

UniCure: A Foundation Model for Predicting Personalized Cancer Therapy Response

Predicting drug efficacy across diverse patient contexts remains a major challenge in oncology, as models trained on cancer cell lines often fail to capture patient-specific biology. Emerging biological foundation models and patient-derived technologies offer a promising solution. Here, we present UniCure, the first pre-trained foundation model integrating both omics and chemical foundation models (UCE and Uni-mol) to predict transcriptomic responses to drugs across diverse cellular and tissue contexts, enabling personalized cancer therapy and drug prioritization at the individual level. Rather than encoder/decoder used in traditional models, UniCure utilizes parameter-efficient fine-tuning (PEFT) techniques for optimizing the training process, a novel FlexPert module for modeling flexible drug-cell interactions, and a Maximum Mean Discrepancy (MMD) loss for learning unpaired data. Trained on over 1.8 million perturbation RNA-seq profiles over 22,000 compounds, 166 cell types, and 24 tissues, UniCure achieves high accuracy in predicting both dose-dependent responses and drug combination effects, demonstrating strong generalization across bulk and single-cell transcriptomic data. In particular, fine-tuning on our patient-derived tumor-like clusters and real-world data of 800 profiles enables UniCure to generate individualized therapeutic predictions on patients tissue samples. In addition, UniCure enables patient stratification based on the predicted drug responses, providing a new way for subtyping patients. UniCures drug prioritization was validated across over 1000 patients from pan-cancer cohorts and supported by experiments of candidate therapeutics. By enabling the potential to screen millions of compounds per patient at scale, UniCure represents a biologically grounded tool that could advance personalized precision oncology and accelerate drug discovery.

bioinformatics↗

bioRxiv2025

RNA-seq reveals transcriptomic differences in circadian-related genes of the choroid plexus in a preclinical chronic migraine model.

BackgroundMigraine patients show choroid plexus (CP) changes, impairing the blood-CSF barrier. The CP regulates circadian rhythms, but links between CP circadian genes and migraine are unexplored. ObjectiveThis study examined CP circadian gene transcriptome changes in a chronic migraine rat model versus controls to identify migraine-related pathways. DesignChronic migraine model: Sprague Dawley rats (3 females, 3 males) received nitroglycerine (NTG) every other day for 9 days; controls (3 females, 3 males) got saline. CP from the 4th ventricle was collected 2 hours post-final injection for RNAseq. MethodsMigraine Behavior: Von Frey hair tests on days 1, 5, and 9, pre- and 2 hours post-NTG/saline injection, assessed basal and NTG-induced pain thresholds. RNAseq & Analysis: Differentially expressed genes (p < 0.05, fold change > 1) were identified. GO, KEGG, and Reactome enrichment analyses evaluated circadian gene expression changes. ResultsO_LINTG group showed reduced basal and NTG-induced pain thresholds on days 1, 5, and 9. C_LIO_LIFemales had more upregulated genes (MT2A, SLC7A11), males upregulated ZBTB16, S100A8. SLC7A11, SCG2, GRIA1 showed inverse regulation (up in females, down in males). C_LIO_LICircadian gene expression altered: 10 genes upregulated (e.g., SERPINE1, MAPK9, ATF4), 13 downregulated (e.g., PER2, DBP, EZH2). Sex-specific differences: females (FBXL12, GPR157), males (NKX2-1, ATF4, CLOCK). C_LIO_LIGO/KEGG analyses revealed significant enrichment of circadian rhythm-related pathways, insulin resistance, and inflammatory response processes, with sex-specific differences: females showed HIF-1 signaling and hemoglobin-related pathways, while males exhibited arachidonic acid and leukotriene production. C_LI ConclusionCP transcriptomics in the rat migraine model revealed sex-specific gene regulation, with females upregulating antioxidant genes (MT2A, SLC7A11) and males upregulating inflammatory factors (ZBTB16, S100A8), alongside circadian disruption (e.g., SERPINE1 upregulated, PER2 downregulated). Pathway analyses indicate enriched circadian rhythms, HIF-1 signaling (females), inflammatory processes (males), lipid metabolism (PPAR), and heme signaling, highlighting sex-specific and circadian targets for migraine therapy.

neuroscience↗

bioRxiv2025

Fluorescence recovery in the Super-Resolution regime reveals subcompartments of 53BP1 foci

We combine Lattice Structured Illumination Microscopy (diSIM with [~]60 nm resolution), Lattice Light-sheet microscopy and Fluorescence Recovery After Photobleaching (FRAP) to explore 53BP1 dynamics in Retinal Pigment Epithelial cells. 53BP1 forms liquid condensates during double-strand DNA repair, long-range DNA end-joining and heterochromatin maintenance. Our super-resolution movies reveal differences in 53BP1 foci contour: some foci are compact and stationary while others appear amorphous, dynamically changing shapes. To explore them, we developed FRAP in the Super-Resolution regime (FRAP-SR). 53BP1 foci with an amorphous loose contour display subcompartments that recover 53BP1-eGFP signals rapidly, indicating differential protein mobilities and 53BP1 functions within a single foci. In contrast, 53BP1-eGFP foci with a compact contour recover uniformly as single foci but show higher heterogeneity in 53BP1-eGFP recovery rates compared to foci that recover as multiple subcompartments. In cells released from aphidicolin, amorphous foci show faster 53BP1 recovery compared to compact foci. We discuss the conceptual implications of different 53BP1 mobilities, and how the FRAP-SR method transforms studies of dynamic 60-100 nm structures.

cell biology↗

bioRxiv2025

ArchLips: A comprehensive in silico database for high-throughput identification of archaeal lipids

Archaeal membrane lipids are markedly distinct from those in bacteria and eukaryotes, serving as unique biomarkers for unraveling their ecological and biogeochemical roles. Recent advancements in lipidomics have facilitated detailed cellular-level characterizations of lipid compounds. However, the lack of a comprehensive and dedicated database has severely limited large-scale, high-throughput investigations of archaeal lipids. We present ArchLips, a comprehensive database containing 218,868 in silico molecular structures and tandem mass spectra of 199,248 corresponding archaeal lipids. ArchLips enables the rapid and accurate identification of characterized archaeal lipid compounds from both pure cultures and environmental samples, serving as a transformative tool for enhancing our understanding of archaeal diversity and their ecological and evolutionary significance within global ecosystems.

biochemistry↗

bioRxiv2025

Cell type-specific epigenomic variation and its association with genotype in the human breast

BackgroundUnderstanding the interplay between genomic variation and the epigenome is fundamental to the study of development and mechanisms of disease. Previous studies have leveraged population-scale genotype surveys to associate alleles with epigenomic states in heterogenous tissue types. However, epigenomes are inherently cell type-specific, giving rise to unique genome-epigenome interactions that can influence distinct functional states and susceptibility to disease. Moreover, the extent of individual variation in cell type-specific epigenotypes remains poorly understood, posing additional challenges to accurately link genotypes with epigenomic features. ResultsWe generated comprehensive genomic and epigenomic profiles of four functionally defined human breast epithelial cell types from eight healthy individuals. To quantify inter-individual epigenomic variation, we developed a statistical framework that measures variability in histone modification landscapes across individuals. This analysis revealed substantially greater variation in repressive chromatin marked by H3K27me3 than in active chromatin marked by H3K27ac and H3K4me3. Integrative chromatin state analysis further identified enhancer elements as the principal source of epigenomic divergence between individuals. Stable enhancer states corresponded to high-confidence cis-regulatory elements that underpin cell type-specific transcriptional programs, whereas variable enhancer states were enriched for environmentally responsive regulatory circuits. Mapping genetic variants associated with chromatin state variation uncovered extensive cell type-specificity, with nearly 90% of regulatory variants detected in only a single cell type. These associations were strongly enriched within active regulatory chromatin and, when integrated with gene expression, enabled the prioritization of functional regulatory variants. We experimentally validated one such variant, rs75071948, demonstrating allele-specific regulation of ANXA1 expression using CRISPR/Cas9 genome editing. ConclusionsOur study defines the landscape of normal epigenomic variation across the major human breast epithelial cell types and demonstrates that genome-epigenome interactions are highly cell type-specific. These findings establish cell type as a critical determinant of the functional interpretation of regulatory genetic variation and provide a framework for understanding how inherited genetic variation shapes normal breast biology and disease susceptibility.

genomics↗

bioRxiv2025

Structural Basis of CSN-mediated SCF Deneddylation

Cullin-RING ligases (CRLs) are the largest family of E3 ligases, with their ubiquitination activity dynamically regulated by neddylation and deneddylation by the COP9 signalosome (CSN). CSN-mediated deneddylation not only deactivates CRLs but also enables substrate receptor exchange, fine-tuning CRL specificity. CSN has emerged as a promising drug target, yet the structural basis underlying its catalytic mechanism remains insufficiently understood. To address this, we used cryo-electron microscopy (cryo-EM) analysis of CSN-CRL1 (SCF) complexes to uncover distinct functional states, capturing key intermediates of the deneddylation cycle. The earliest state represents an initial docking step in which CSN remains autoinhibited. In contrast, the catalytic intermediate reveals the fully engaged state, with the CSN5 Ins-1 loop, RBX1 RING, and neddylated Cullin WHB domains repositioned for isopeptide bond cleavage. We further resolve four dissociation intermediates that define the stepwise release of CSN from its deneddylated product, highlighting a central role for RBX1RING in stabilising key interactions throughout this process. Additionally, our structures reveal the previously uncharacterised position of CSNAP, which integrates into the CSN scaffold at a groove formed by CSN3 and CSN8. Together, our study provides a comprehensive mechanistic model of CSN function, linking CRL recognition, catalytic activation, and stepwise disengagement. These insights lay the groundwork for the rational design of CSN inhibitors, offering new opportunities to modulate CRL activity for therapeutic applications. Key TakeawaysO_LIHigh-resolution cryo-EM structures capture key intermediates of the CSN-mediated SCF deneddylation cycle C_LIO_LIStructural identification of CSNAP places it within a previously uncharacterized groove at the interface of CSN3 and CSN8. C_LIO_LIPre-catalytic and catalytic states define the conformational transitions of CSN5Ins-1, RBX1RING, and N8WHB that enable isopeptide bond cleavage. C_LIO_LIFour dissociation intermediates reveal a sequential pathway for CSN disengagement, with RBX1RING playing a central role in stabilising key interactions. C_LI

biochemistry↗

bioRxiv2025

Optimized upstream analytical workflow for single-nucleus transcriptomics in main metabolic tissues

Single-nucleus RNA sequencing (snRNA-seq) has emerged as a powerful approach for studying cellular heterogeneity in metabolic tissues. However, snRNA-seq analysis remains challenging due to low gene expression and data complexity. Here, we introduce an optimized analytical workflow for snRNA-seq data from 67 samples across white adipose tissue, muscle, liver and the hypothalamus. We emphasized the importance of key steps including ambient RNA removal, doublet identification and data integration to ensure accurate downstream analysis. This workflow offers a valuable resource for researchers in metabolism, facilitating deeper insights into cellular diversity and metabolic function through rigorous snRNA-seq analysis.

bioinformatics↗

bioRxiv2025

Substantial contribution of in-situ produced bacterial lipids to the sedimentary lipidome

The sedimentary lipid pool is comprised of a myriad of individual components. Due to their importance for organic carbon sequestration and their application in paleoclimatic and geobiological reconstructions, its composition has been studied for many decades with targeted approaches but an overall view on its composition is still lacking. In part this uncertainty relates to the different sources of sedimentary lipids, they can be both delivered from the overlying water column by sedimentation, but also produced in-situ by sediment dwelling organisms. Another uncertainty relates to the differing degree of preservation, both between lipid groups and relative to other organic matters. Here we conduct an untargeted analysis of the sedimentary lipidome in the Black Sea using high resolution mass spectrometry. Besides commonly reported phytoplankton-derived fossil lipids, a diverse and abundant set of sphingolipids was discovered, accounting for [~]20% of the sedimentary lipidome. These sphingolipids are produced in situ by sedimentary anaerobic bacteria, which probably used sphingolipids instead of phospholipids, likely because of the deficiency of phosphate in the anoxic sediments. Our results suggest that while phytoplankton-derived lipids contribute 50-60% of the sedimentary lipidome, the importance of bacterial lipids, particularly in-situ produced sphingolipids, may have been overlooked.

microbiology↗

bioRxiv2025

Dissecting Force Transmission across SUN Proteins Using Nuclear Tension Sensors

Forces on the linker of the nucleoskeleton and cytoskeleton (LINC) complex control nuclear mechano-sensing and mechano-adaptation. However, the force transmission dynamics across the LINC complex are not fully understood, mainly because of the lack of imaging tools. We developed a set of genetically-encoded fluorescence resonance energy transfer (FRET)-based nuclear tension sensors (NuTS) that measure tension forces across SUN1/2 proteins in living cells with high sensitivity. SUN2-based NuTS (NuTS2) responded rapidly to mechanical changes in cell contractility and matrix stiffness. Notably, NuTS2 dynamically showed force transmission with high spatiotemporal resolution during cell adhesion, migration and squeeze. We also used NuTS2 to monitor tension force changes as the notochord matures in zebrafish development. NuTS2 detected a gradient tension force that increased from the posterior tail buds to the anterior as vacuoles expanded in notochord cells. Force reduction affected notochord maturation and zebrafish embryo development. Our results provide a biophysical cue for dissecting how force transmission on SUN2 protein regulates embryo development. TeaserNuclear tension sensor (NuTS) was developed for direct force measurement across SUN proteins in living cells and zebrafish.

biophysics↗

bioRxiv2025

A dWDR45 knock-out Drosophila model to decipher the role of autophagy in BPAN

Beta-propeller protein-associated neurodegeneration (BPAN) is a rare neurological disorder characterized by severe cognitive and motor impairments. BPAN is caused by de novo pathogenic variants in the WDR45 gene on the X chromosome. WDR45 gene encodes the protein WDR45/WIPI4, a known regulator of autophagy. A defective autophagy has been observed in cellular models of BPAN disease and is associated with neurological dysfunctions in wdr45 knockout (KO) mice. However, it remains unclear whether the autophagic defect directly contributes to all WDR45 loss-induced phenotypes or whether other WDR45-dependent cellular functions are involved. To investigate this, we generated a CRISPR/Cas9-mediated KO of CG11975 (dwdr45 KO), the Drosophila homolog of WDR45. Our analysis revealed that dwdr45 KO flies display BPAN-like phenotypes, including impaired locomotor function, seizure-like behavior, autophagy dysregulation and iron dyshomeostasis. Additionally, dwdr45 KO flies exhibit shortened lifespan compared to control flies. These findings demonstrate that dwdr45 KO fly is a relevant in-vivo model for investigating the key cellular and molecular mechanisms underlying BPAN-associated phenotypes. Here we showed that induction of autophagy in dwdr45 KO flies improved both the shortened lifespan and the seizure-like behavior, but did not restore locomotor function. This suggests that defective autophagy contributes to some, but not all, aspects of the phenotypes resulting from loss of dWdr45 function.

cell biology↗

bioRxiv2024

Wafer-scale integration of alpha-quartz thin films towards super high frequency piezoelectric bioNEMS for arbovirus detection

Micro and nanoelectromechanical systems (MEMS/NEMS), especially piezoelectric resonators, offer a promising strategy for the manufacturing of point-of-care devices providing rapid, sensitive, and field-deployable tests with minimal user training for the diagnostic of viral infections. High-frequency (HF) MEMS/NEMS have the potential for ultrasensible mass-loading devices. Yet, their use for biomedical applications requires challenging manufacturing qualities. Here, we develop a large-scale chemical integration of epitaxial -quartz (100) thin films on silicon wafers up to 4-inches. This methodology allows the microfabrication of wafer-scale piezoelectric -quartz/silicon bioMEMS using a recognition layer capable of selectively detecting emerging arboviruses over other viral loads. Using contact-free vibrometry, we show a mass sensitivity of the bioMEMS device of 22.4 pg/Hz in liquid conditions and a Chikungunya virus limit of detection of 9 ng/ml. To reach piezoelectric transduction for compact quartz sensor devices, we develop NEMS resonators at super HF, i.e., 17.8 GHz with a quality factor of 280 which represents a QxF product of 4.98{middle dot}1012. These -quartz NEMS can reach thicknesses between 100 and 800 nm and lateral dimensions up to 9 mm2. Our work opens the door for cost-efficient single-chip epitaxial piezoelectric -quartz/Si ultrasensitive NEMS sensors manufactured exclusively by soft-chemistry for biomedical applications and many other fields.

bioengineering↗