Biology subjects

Ye, Y.

Publications and source records attributed to Ye, Y..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Single-cell transcriptomic atlas of human retina from Chinese donors reveals population-specific cellular diversity

The human retina exhibits complex cellular heterogeneity which is critical for visual function, yet comprehensive ethnic-specific references are scarce in ophthalmic transcriptomics. The lack of single-cell RNA sequencing (scRNA-seq) data from Asian populations particularly Chinese donors imposes significant limitations in understanding population-specific retinal biology. We constructed the first comprehensive single-cell transcriptomic atlas of the human retina from Chinese donors, generated through high-throughput scRNA-seq of [~]290,000 viable cells obtained from 18 fresh retinal specimens (living donor and post-mortem specimens). Our multi-level analysis identified 10 distinct retinal cell types, encompassing all major neuronal lineages, Muller glia, astrocytes, microglia. Detailed subcluster analyses further revealed extensive heterogeneity, identifying distinct subtypes within several cell populations such as 7 amacrine cell subtypes and 14 bipolar cell subtypes. Concurrently, through systematic analysis of delineated subtype-specific molecular programs, we mapped their associated biological signaling pathways, functions, and mechanistic processes. This analysis explained the critical involvement of these subpopulations in core biological processes including synaptic organization, neurotransmission, and phototransduction cascades, potentially governing retinal homeostatic regulation and disease mechanisms. Single-cell transcriptomic atlas of the human retina from Chinese donors describes a comprehensive cellular landscape, encompassing major cell types and subtypes including neuronal, glial, and immune populations. This ethnic-specific atlas provided an important reference for understanding retinal development, cellular interaction and disease pathogenesis in Chinese populations, addressing a longstanding gap in ophthalmic transcriptomic resources.

genomics↗

bioRxiv2025

TL1A overexpression in Crohn's Disease and mice alters Paneth cells and microbiota promoting ileal inflammation

Paneth cells regulate host-microbial homeostasis and defects in autophagy and host defense pathways have been associated with inflammatory bowel diseases (IBD). Genetic variants in TL1A (TNFSF15) and its receptor DR3 (TNFRSF25) have been associated with IBD. TL1A expression is increased in IBD patients, particularly in TL1A risk allele carriers. However, effects of TL1A on Paneth cells, resident microbiota, and development of ileitis remain unknown. TL1A overexpression in mice induces Paneth cell hyperplasia and morphological abnormalities preceding the development of ileitis. In Crohns disease (CD) patients, ileal TL1A expression was associated with abnormal Paneth cell phenotypes. We confirmed direct effects of TL1A on Paneth cells in human iPSC-derived human intestinal organoids and mouse Paneth cell-enriched organoids. Resident microbiota was required for TL1A-mediated Paneth cell dysfunction, and ileitis. Tl1a-tg mice were enriched in short chain fatty acid-producing bacteria and the metabolite acetate. Acetate supplementation in WT or Tl1a-tg mice caused ileal inflammation, suggesting that acetate is sufficient to cause ileitis. DR3-deficiency in Paneth cells resulted in Paneth cell abnormalities and microbiome composition changes. Our findings provide a mechanistic link between overexpression of TL1A in CD patients, Paneth cell dysfunction, and enrichment of acetate-producing bacteria and acetate that promotes ileal inflammation. Brief SummaryOverexpression of TL1A drives Paneth cell dysfunction in Crohns Disease and mice leading to microbial and metabolomic changes that promote small bowel inflammation.

immunology↗

bioRxiv2025

Phagosome-mediated anti-bacterial immunity is governed by the proton-activated chloride channel in peritoneal macrophages

The success of phagosome degradation relies on the ability of phagocytes to regulate the maturation of phagosomes. However, its underlying molecular mechanisms remain poorly understood. Here, we identify the proton-activated chloride (PAC) channel as a key negative regulator of phagosome maturation. PAC deletion enhanced phagosomal acidification and protease activities, leading to augmented bacterial killing in large peritoneal macrophages (LPMs) upon Escherichia coli infection in mice. Surprisingly, phagosome degradation also stimulated STING-IRF3-interferon responses and inflammasome activation in LPMs, both of which are enhanced upon PAC deletion. The increased inflammasome activation induced the release of cleaved gasdermin D, which localized to the surface of bacteria in the peritoneum and further contributed to their killing. Finally, enhanced bacterial clearance by PAC-deficient LPMs reduced proinflammatory immune cell infiltration and peritoneal inflammation, resulting in improved survival in mice. Our study thus provides new insights into the molecular mechanism of phagosome maturation and the dynamics of host defense response following phagosome-mediated bacterial degradation in peritoneal macrophages. SummaryThe PAC channel mediates phagosome maturation during bacterial infection in macrophages. PAC deletion promotes phagosome-mediated STING-interferon signaling and inflammasome-mediated gasdermin D secretion during bacterial infection in peritoneal macrophages.

immunology↗

bioRxiv2025

CHIP protects lysosomes from CLN4 mutant-induced membrane damages

Understanding how cells mitigate lysosomal damage is critical for unraveling pathogenic mechanisms of lysosome-related diseases. Here we use organelle-specific proteomics in iPSC-derived neurons (i3Neuron) and an in vitro lysosome-damaging assay to demonstrate that lysosome damage, caused by the aggregation of Ceroid Lipofuscinosis Neuronal 4 (CLN4)-linked DNAJC5 mutants on lysosomal membranes, serves as a critical pathogenic linchpin in CLN4-associated neurodegeneration. Intriguingly, in non-neuronal cells, a ubiquitin-dependent microautophagy mechanism downregulates CLN4 aggregates to counteract CLN4-associated lysotoxicity. Genome-wide CRISPR screens identify the ubiquitin ligase CHIP as a central microautophagy regulator that confers ubiquitin-dependent lysosome protection. Importantly, CHIPs lysosome protection function is transferrable, as ectopic CHIP improves lysosomal function in CLN4 i3Neurons, and effectively alleviates lipofuscin accumulation and neurodegeneration in a Drosophila CLN4 disease model. Our study establishes CHIP-mediated microautophagy as a key organelle damage guardian that preserves lysosome integrity, offering new insights into therapeutic development for CLN4 and other lysosome-related neurodegenerative diseases.

cell biology↗

bioRxiv2025

Single-Cell Transcriptomics Reveals Dynamic Microglial States and Neural-Immune Networks in Human Diabetic Retinopathy

Diabetic retinopathy (DR) is a major cause of vision loss worldwide. Here, we conduct single-cell RNA sequencing of twenty human retina samples (from living and post-mortem donors) across non-diabetic, diabetic, and DR states to create a comprehensive transcriptomic atlas. We identify two stable microglial populations--homeostatic and inflammatory--that exist along a functional continuum, plus a neutrophil cluster within C1QA+ myeloid cells with dynamic transitions occurring throughout disease progression. Module-level analysis reveals divergent transcriptional trajectories: homeostatic microglia maintain energetic programs while selectively upregulating stress elements, whereas inflammatory microglia layer additional pro-inflammatory programs onto preserved biosynthetic foundations. Eleven co-expression modules organize into two major axes: an inflammatory-stress axis, and a regulatory/metabolic-motility axis, with a stable translation module persisting across disease stages. Cell communication analysis further highlights sophisticated neural-immune interactions, particularly between photoreceptors and microglia. Our findings provide insights into the complex cellular dynamics of DR progression and suggest potential therapeutic targets for early intervention.

bioinformatics↗

bioRxiv2025

SynSeg: Generating Synthetic Datasets for Accurate Subcellular Segmentation with U-net

Accurate segmentation of subcellular components is crucial for understanding cellular processes, but traditional methods struggle with noise and complex structures. Convolutional neural networks improve accuracy but require large, time-consuming, and biased manually annotated datasets. Here, we developed SynSeg, a pipeline that generates synthetic training data to train a U-net model for subcellular structure segmentation, eliminating the need for manual annotation. SynSeg leverages synthetic datasets with variations in intensity, morphology, and signal distribution to deliver context-aware segmentations, even in challenging imaging conditions. We demonstrate SynSegs superior performance in segmenting vesicles and cytoskeletal filaments from culture cells and live C. elegans, outperforming traditional methods such as Otsus thresholding, ILEE, and FilamentSensor 2.0. Additionally, SynSeg effectively quantified disease-associated microtubule morphology in live cells, uncovering structural defects caused by mutant Tau proteins linked to neurodegenerative diseases. These results highlight the potential of synthetic data-driven approaches to advance biological segmentation and enhance microscopy techniques. Significance StatementThis study introduces a novel approach for accurately segmenting cellular structures, such as microtubules and vesicles, using synthetic datasets and advanced deep learning techniques. By leveraging a U-Net model trained on thousands of artificially generated images, our method eliminates the need for labor-intensive experimental data and simplifies the data creation process. Importantly, it incorporates noise and variability into the training datasets to make the model more robust and biologically relevant. Our findings demonstrate that the model can successfully identify cellular components, paving the way for its application in real-world microscopy images. This innovation has the potential to accelerate discoveries in cell biology by providing an efficient, scalable tool for analyzing complex cellular structures, even in challenging imaging conditions.

bioinformatics↗

bioRxiv2025

Confounder-free Predictive Models for Microbiome-based Host Phenotype Prediction

As in many fields, the presence of confounding effects (or biases) presents a significant challenge in micro-biome research, including using microbiome data to predict host phenotypes. If not properly addressed, confounders can lead to spurious associations, biased predictions and misleading interpretations. One notable example is the medication metformin, which is commonly prescribed to treat type 2 diabetes (T2D) and is known to influence the gut microbiome. In this study, we propose confounder-free predictive models for human phenotype prediction using microbiome data. These models utilize an end-to-end approach within an adversarial min-max optimization framework to derive features that are invariant to confounding factors, while accounting for the intrinsic correlations between confounders and prediction outcomes. We implemented two versions of confounder-free predictors using different network architectures: one based on a fully connected network (referred as FNN CF) and another incorporating prior biological knowledge (referred as MicroKPNN CF). We evaluated our models on microbiome datasets associated with T2D, where metformin acts as a confounder. Our results demonstrate that confounder-free predictors achieve higher accuracy compared to models that do not account for confounders and more effectively identify microbial markers associated with the phenotype, rather than markers influenced by metformin. Between the two confounder-free models, although the prior-knowledge-guided approach showed slightly lower prediction accuracy compared to the fully connected model, it offered greater interpretability, providing additional insights into the underlying biological mechanisms.

bioinformatics↗

bioRxiv2024

Time-resolved fluorescent proteins towards fluorescence microscopy in the temporal and spectral domains

Fluorescence microscopy has been widely applied in life sciences. While steady-state fluorescence intensity is mostly used, the time-resolved detection mode relying on fluorescence lifetime remains underexplored. Herein, we present a family of time-resolved fluorescent proteins (TRFP). Using a strategy that regulates lifetime without affecting spectra of FPs, we have developed different TRFPs that cover the visible spectrum and a wide range of lifetime. TRFPs are employed in the temporal-spectral resolved microscopy, allowing the simultaneous imaging of 9 different proteins in live cells and correlation of multiple activities to cell cycles. Finally, TRFPs are integrated into multiplexing super-resolution microscopy to concurrently visualize 4 proteins in live cells, acquiring a remarkable 50 nm spatial resolution using lifetime as signal. TRFPs represent a transformative toolset towards fluorescence microscopy in both the temporal and spectral domains. Beyond the multiplexing imaging, TRFPs could introduce unprecedented opportunities of system complexity and quantitative accuracy into biological research.

biochemistry↗

bioRxiv2024

Unique nigral and cortical pathways implicated by epigenomic and transcriptional analyses in a rotenone rat model of Parkinson's disease

Pesticide exposure is increasingly recognised as a potential environmental factor contributing to the onset of idiopathic Parkinsons disease, yet the molecular mechanisms underlying this connection remain unclear. This study aims to explore how pesticide exposure disrupts key brain regions involved in Parkinsons disease pathology by reshaping gene regulatory landscapes. Using the well-established rotenone rat model of the disease, we performed H3K27ac ChIP-sequencing to profile active regulatory elements in the substantia nigra and cortex. In this model, rotenone distributes uniformly throughout the brain, and the degree of complex I inhibition is equivalent in cortical and substantia nigra neurons. Despite the uniformity of complex I inhibition, we identified widespread epigenomic differences, with brain region specific acetylation patterns associated with rotenone exposure. We showed consistent changes in transcriptomic activity by RNA-sequencing. Our results indicate there is a strong immune response to rotenone localised to the substantia nigra and highlight an enrichment of immune-related motifs in this brain region, suggesting that the immune response is at least partially driven by gene regulatory mechanisms. We also noted an increase in C1q complement pathway activity in the substantia nigra. In contrast, we identified widespread dysregulation of synaptic function at the gene regulatory level in the cortex of these same rats. Our results highlight a role for gene regulatory mechanisms potentially mediating the effects of pesticide exposure, driving region-specific functional responses in the brain that may contribute to the pathology and selective vulnerability that characterise Parkinsons disease.

genomics↗

bioRxiv2024

FIDDLE: a deep learning method for chemical formulas prediction from tandem mass spectra

Molecular identification through tandem mass spectrometry is fundamental in small molecule analysis, with formula identification serving as an initial step in the process. Current computational methods often struggle with accuracy, speed, and scalability for relatively larger molecules, limiting high-throughput workflows. We present FIDDLE (Formula IDentification by Deep LEarning), a deep learning-based method trained on over 38,000 molecules and 1 million MS/MS spectra from various Quadrupole Time-of-Flight (Q-TOF) and Orbitrap instruments. FIDDLE accelerates formula identification by more than 10-fold and achieves top-1 and top-5 accuracies of 88.3% and 93.6%, respectively, outperforming state-of-the-art methods based on top-down (SIRIUS) and bottom-up (BUDDY) approaches by over 10%. On external metabolomics datasets, FIDDLE achieves top-5 accuracies of 75.1% (positive ion mode) and 66.2% (negative ion mode), with further improvements to 80.0% and 73.8% when combined with SIRIUS and BUDDY.

bioinformatics↗

bioRxiv2024

Leveraging the Human Panproteome to Enhance Peptide and Protein Identification in Proteomics and Metaproteomics

In this paper, we developed a novel approach to utilize the human pangenome to improve peptide and protein identification from proteomic data (MS/MS spectra). We propose a new data structure called panproteome graph (PPG), in which nodes are tryptic peptides, to represent the human pangenome. The PPG can be built in linear time and can be utilized via graph traversal using a depth-first search algorithm to generate potential peptides for peptide identification in proteomics. The PPG built using the 47 human proteomes from the Human Pangenome Reference Consortium (HPRC) coupled with UniProt human proteins resulted in more than 4.2M tryptic peptides, a 26% increase as compared to when only the UniProt proteins were included. Graph-based analysis of the PPG revealed a giant disconnected component with about 3M nodes, suggesting substantial sharing of tryptic peptides among proteins. We applied tryptic peptides derived from PPG to characterize three collections of human proteomic and metaproteomic datasets, and our results showed that by exploiting the human pangenome, we were able to increase the number of identified peptides on all datasets we tested (about 8% increase across all three collections). We also showed that using more complete human proteome would be useful for reducing potential misidentification of human peptides as microbial peptides, a problem that was previously studied but based on genomic sequencing data. Our tool for building PPG is available in a GitHub repo PPGpep, and PPG-derived tryptic peptides can be utilized by MetaProD, a pipeline for both human and bacterial peptide and protein identification from (meta)proteomics datasets.

bioinformatics↗

bioRxiv2024

Systematic screen of RNA binding proteins that enhance circular RNA translation

Translatable circular RNAs (circRNAs) have emerged as a promising alternative to linear mRNA as new therapeutics due to its improved stability. The translation of circRNAs is mainly driving by internal ribosome entry site (IRES) or IRES-like elements, which is under regulation by various trans-acting RNA binding proteins (RBPs). Here we designed a cell-based system to systematically screen RBPs that enhance translation of circRNAs, and identified a total of 68 proteins as putative activators of noncanonical translation. These translation activators mainly involved in the functions of RNA processing, ribosomal biogenesis and translation initiation. Furthermore, we developed a machine learning algorithm to extract common sequence features of these activators, which predicted more potential RBPs with translation activator activities. The newly identified and predicted activators were subsequently demonstrated to promote the IRES-mediated circRNA translation in a context-dependent fashion. This investigation provides new insights to discover functions for IRES trans-acting factors and to expand the toolbox for engineered RBPs in RNA synthetic biology.

molecular biology↗

bioRxiv2024

Embryonic Mast Cells Arise from Cpa3-expressing Precursors Independent of Granulocyte-Monocyte Progenitors

Most of the mast cells (MCs) in connective tissues, such as skin, are long-lived embryonic-derived immune cells that play important roles in host defense and various immunological diseases, including allergies. Their embryonic origin and ontogeny remain to be fully studied since several overlapping waves of embryonic hematopoiesis have been shown to give rise to these cells. Here, combining single-cell RNA sequencing and new genetic fate mapping models, we identified a Cpa3-expressing population sequentially appearing in the yolk sac, fetal liver, and peripheral tissues which gives rise to dermal MCs during embryonic days 11.5 to 14.5. Using in vitro differentiation and in vivo transplant methods, we identified a Ter119-F4/80- CD45+CD117+CD16/32+CD135-CD115-Ly6C-CD34lo population as potential fetal liver MC precursors. Fate mapping with Cpa3CreERT2and Zbtb16CreERT2 models, as well as the granulocyte-monocyte progenitor (GMP) models Ms4a3Cre and ElaneCre, demonstrated that MCs arise from Cpa3+ progenitors rather than Ms4a3+ or Elane+ GMPs. A corresponding population with a similar developmental trajectory was also identified in human early yolk sac and fetal liver, suggesting a conserved MC developmental program across species. These findings delineate the detailed developmental path of MCs in embryos, permitting future functional studies in immunity and development. HighlightsO_LICpa3-expressing cells in the yolk sac and fetal liver contain mast cell precursors C_LIO_LICpa3CreERT2 labels embryonic mast cells and their precursors C_LIO_LIEmbryonic mast cells arise through Cpa3+ mast cell precursors, but not Elane+/Ms4a3+ GMPs C_LIO_LIThe seeding of MCPs to embryonic skin slows down after E14.5 C_LI

immunology↗

bioRxiv2024

Structural Characterization of mRNA Lipid Nanoparticles in the Presence of Intrinsic Drug-free Lipid Nanoparticles

Lipid nanoparticles (LNPs) have emerged as a versatile platform for mRNA delivery across a range of applications, including disease prevention, cancer immunotherapy, and gene editing. Structural models of mRNA-containing lipid nanoparticles (mRNA-LNPs) have also been proposed based on characterization of samples by using various advanced techniques. Among these, small angle neutron scattering (SANS) has proven essential for elucidating the lipid distribution within mRNA-LNPs, a factor crucial to both their preparation and efficacy. However, recent findings suggest that the mRNA-LNP samples prepared via commercial microfluidic techniques may contain a substantial fraction of drug-free LNPs, casting doubt on the validity of earlier structural models. In this study, we employed contrast variation SANS to characterize both drug-free LNPs and our mRNA-LNP sample, and quantified the proportion of drug-free LNPs present to be [~]30% in our mRNA-LNP sample using nano flow cytometry. By removing the contributions of drug-free LNPs from the SANS data of our mRNA-LNP sample, we were able to precisely characterize the structure of mRNA-LNPs. Consequently, we proposed structural models for both drug-free LNPs and mRNA-LNPs. Notably, our analysis revealed similar lipid distributions and shell thicknesses between the two particle types, while the solvent content in mRNA-LNPs was significantly higher, leading to a larger core size. This work not only offers a method for accurately characterizing the structure of mRNA-LNPs, but also establishes criteria for selecting appropriate analytical techniques based on the structural parameters of interest. Therefore, our findings hold significant implications for the mechanistic understanding and quality control of mRNA-based vaccines. SignificancePrecise structural determination of mRNA-containing lipid nanoparticles (mRNA-LNPs) is vital for mechanistic insights into their preparation, delivery, immunogenicity, and storage, which are critical to the development of mRNA-based vaccines. However, most previous studies overlooked the substantial presence of drug-free LNPs within these samples. Here, we identified that approximately 30% of the nanoparticles in our mRNA-LNP sample were drug-free. By integrating contrast variation small angle neutron scattering (SANS) data from both drug-free LNPs and mRNA-LNPs, we developed structural models for both particle types, and provided a guidance for characterization technique selection based on concerned structural features. Beyond mechanistic insight on structure, our approach offers a robust method for quality assessment and process monitoring in mRNA-based vaccine production.

biophysics↗

bioRxiv2024

Fresh Human Retinal scRNA-seq Atlas Reveals a Novel Cone Subtype and Cellular Diversity

BackgroundCurrent human retina studies predominantly utilize post-mortem tissue, and the sample accessibility constraints make the characterization of the living human retina at single-cell resolution a challenge. Although single-nucleus RNA-seq expands the utility of frozen samples, it provides a nuclear-centric view, potentially missing key cytoplasmic information and transient biological processes. Thus, it is important to generate resources directly from living human retinal tissue to complement existing datasets. MethodsWe profiled 106,829 single cells from nine unfrozen human retina samples. Living samples were collected withinLJ10LJmin of therapeutic enucleation and four postmortem samples were collected within 6LJh. After standardized dissociation, single-cell transcriptomes were generated using 10x Genomics 3 RNA-seq and applied scVI to generate batch-corrected integrated atlas. Major cell types and subtypes were annotated through iterative Leiden clustering, canonical markers. Subsequent analyses included differential expression comparisons between cell states and regulon activity profiling to further characterize cellular identities and regulatory networks. Transcriptional dynamics were assessed using RNA velocity, and cell-cell signaling pathways were inferred with CellChat. Key findings were validated in independent samples from two additional donors (four samples) using the identical workflow. ResultsWe contribute to establishing a reference for retinal cell type proportions and cellular states. Our analysis revealed ELF1-mlCone, a distinct cluster of mlCone photoreceptors identified by distinct transcriptional features. The presence and transcriptional features of this cluster were validated in independent samples. Additionally, by comparing living and post-mortem samples, our study highlights differences in transcriptional dynamics: living tissue preserved coherent RNA velocity streams, enabling clear dynamic state transitions, while post-mortem tissue exhibited disorganized patterns. These findings suggest that using living tissue can improve the capture of active cellular states and transitions. ConclusionsOur atlas provides a single-cell reference contrasting living versus early post-mortem human retina, integrating cell type composition, transcriptional diversity, and functional insights. It may serve as a useful resource for retinal research and for understanding aspects of human retinal biology, particularly given its inclusion of living tissue and diverse pathological states.

bioinformatics↗

bioRxiv2024

NEMF-mediated CAT-tailing defines distinct branches of translocation-associated quality control

Ribosome stalling during co-translational translocation at the endoplasmic reticulum (ER) causes translocon clogging and impairs ER protein biogenesis. Mammalian cells resolve translocon clogging vial a poorly characterized translocation-associated quality control (TAQC) process. Here, we combine genome-wide CRISPR screen with live cell imaging to dissect the molecular linchpin of TAQC. We show that substrates translated from mRNAs bearing a ribosome stalling poly(A) sequence are degraded by lysosomes and the proteasome, while substrates encoded by non-stop mRNAs are degraded by an unconventional ER-associated degradation (ERAD) mechanism involving ER-to-Golgi trafficking and KDEL-dependent substrate retrieval. The triaging diversity appears to result from the heterogeneity of NEMF-mediated CATylation, because a systematic characterization of representative CAT-tail mimetics establishes an AT-rich tail as a "degron" for ERAD, whereas an AG-rich tail can direct a secretory protein to the lysosome. Our study reveals an unexpected protein sorting function for CAT-tailing that safeguards ER protein biogenesis.

cell biology↗

bioRxiv2024

Physical constraints and biological regulations underlie universal osmoresponses

Microorganisms constantly transition between environments with dramatically different external osmolarities. However, theories of microbial osmoresponse integrating physical constraints and biological regulations are lacking. Here, we propose such a theory, utilizing the separation of timescales for passive responses and active regulations. We demonstrate that regulations of osmolyte production and cell-wall synthesis assist cells in coping with intracellular crowding effects and adapting to a broad range of external osmolarity. Furthermore, we predict a threshold value above which cells cannot grow, ubiquitous across bacteria and yeast. Intriguingly, the theory predicts a dramatic speedup of cell growth after an abrupt decrease in external osmolarity due to cell-wall synthesis regulation. Our theory rationalizes the unusually fast growth observed in fission yeast after an oscillatory osmotic perturbation, and the predicted growth rate peaks match quantitatively with experimental measurements. Our study reveals the physical basis of osmoresponse, yielding farreaching implications for microbial physiology.

biophysics↗

bioRxiv2024

Depletion of TDP-43 exacerbates tauopathy-dependent brain atrophy by sensitizing vulnerable neurons to caspase 3-mediated endoproteolysis of tau in a mouse model of Multiple Etiology Dementia

TDP-43 proteinopathy, initially disclosed in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), coexists with tauopathy in a variety of neurodegenerative disorders, termed multiple etiology dementias (MEDs), including Alzheimers Disease (AD). While such co-pathology of TDP-43 is strongly associated with worsened neurodegeneration and steeper cognitive decline, the pathogenic mechanism underlying the exacerbated neuron loss remains elusive. The loss of TDP-43 splicing repression that occurs in presymptomatic ALS-FTD individuals suggests that such early loss could facilitate the pathological conversion of tau to accelerate neuron loss. Here, we report that the loss of TDP-43 repression of cryptic exons in forebrain neurons (CaMKII-CreER;Tardbpf/f mice) is necessary to exacerbate tauopathy-dependent brain atrophy by sensitizing vulnerable neurons to caspase 3-dependent cleavage of endogenous tau to promote tauopathy. Corroborating this finding within the human context, we demonstrate that loss of TDP-43 function in iPSC-derived cortical neurons promotes early cryptic exon inclusion and subsequent caspase 3-mediated endoproteolysis of tau. Using a genetic approach to seed tauopathy in CaMKII-CreER;Tardbpf/fmice by expressing a four-repeat microtubule binding domain of human tau, we show that the amount of tau seed positively correlates with levels of caspase 3-cleaved tau. Importantly, we found that the vulnerability of hippocampal neurons to TDP-43 depletion is dependent on the amount of caspase 3-cleaved tau: from most vulnerable neurons in the CA2/3, followed by those in the dentate gyrus, to the least in CA1. Taken together, our findings strongly support the view that TDP-43 loss-of-function exacerbates tauopathy-dependent brain atrophy by increasing the sensitivity of vulnerable neurons to caspase 3-mediated endoproteolysis of tau, resulting in a greater degree of neurodegeneration in human disorders with co-pathologies of tau and TDP-43. Our work thus discloses novel mechanistic insights and therapeutic targets for human tauopathies harboring co-pathology of TDP-43 and provides a new MED model for testing therapeutic strategies. HighlightsO_LILoss of TDP-43 repression of cryptic exons is necessary for caspase 3-dependent endoproteolysis of tau at D421 in the mouse brain and human iPSC-derived cortical neurons. C_LIO_LIThe level of caspase 3-dependent cleavage of tau is a major determinant of the vulnerability of mouse brain neurons lacking TDP-43. C_LIO_LIIn a novel mouse model of multiple etiology dementia, TDP-43 loss-of-function exacerbates tauopathy-dependent brain atrophy by sensitizing vulnerable neurons to caspase 3-mediated endoproteolysis of tau to drive tauopathy. C_LIO_LIIn human tauopathies with co-pathology of TDP-43, dysfunction of TDP-43 may promote caspase 3-dependent cleavage of endogenous tau in vulnerable neurons and exacerbate tauopathy-dependent neurodegeneration. C_LI SummaryThe pathogenic mechanism by which TDP-43 loss of repression function exacerbates tauopathy-dependent neurodegeneration in multiple etiology dementia (MED) with co-pathology of TDP-43 is unknown. In a novel mouse model of MED, loss of TDP-43 function exacerbates tauopathy-dependent brain atrophy by sensitizing vulnerable neurons to caspase 3-dependent cleavage of endogenous tau to drive tauopathy. This mechanistic insight informs novel targets and therapeutic strategies for MEDs harboring the co-pathologies of tau and TDP-43, which can be validated using this mouse model of MED.

neuroscience↗