Biology subjects

Liu, X.

Publications and source records attributed to Liu, X..

At least 721 records · Page 40Linked to original sources

bioRxiv2024

GlyTrait Brings Insights into Functional Glycosylation

Glycomics research often grapples with the interpretability and biological relevance of glycomics data. Using glycosylation derived traits are promising methods for more in-depth biological insights, yet no such bioinformatic tool exists for such task. Here, we developed GlyTrait, a Python-based framework designed to enhance glycomics analysis through the innovative calculation and interpretation of derived traits from N-glycome data. GlyTrait automates the derivation of biologically significant traits, shifting focus from mere glycan abundances to functional glycan properties such as branching and fucosylation. GlyTrait extends the well-established nomenclatures and definitions of derived traits in the N-glycomics community, allowing for fast exploration and analysis of N-glycome data effortlessly. Furthermore, with the well-designed formula grammar, custom derived traits could be materialized without any knowledge of coding. Besides, a two-step post-filtering process reduces information redundancy, maintaining only the most informative traits. Finally, subsequent statistical and interpretable machine learning analysis provide robust insights into the glycosylation patterns associated with disease states. This comprehensive approach not only improves the statistical power and sensitivity compared to traditional methods, but also enhances the interpretability of glycomics data. GlyTraits efficacy is demonstrated through the re-analysis of published glycoengineered CHO cell lines and visceral leishmaniasis patient data, alongside a newly conducted pilot study for hepatocellular carcinoma (HCC) N-glycan biomarker discovery. We are confident in GlyTraits potential to become an indispensable tool for the glycomics community. Significance StatementGlycomics data is often challenging to interpret and analyze for biological relevance. GlyTrait, a Python-based tool, addresses this by automatically calculating biologically significant traits from N-glycome data, focusing on functional properties like glycan branching and fucosylation rather than mere abundance. This tool enhances data interpretability, reduces redundancy through post-filtering, and employs statistical methods to uncover glycosylation patterns linked to diseases. Demonstrated on various published datasets, as well as a newly conducted pilot study with 165 samples for hepatocellular carcinoma N-glycan biomarker discovery, GlyTrait proves to be a powerful tool. It improves the understanding of glycosylation changes in conditions like cancer, thereby benefiting the glycomics community.

bioinformatics↗

bioRxiv2024

Transient Naive Treatment (TNT) iPS cells do not feature Sendai virus expression: Response to Sendai virus persistence questions the transient naive reprogramming method for iPSC generation

SummaryThe Transient Naive Treatment (TNT) reprogramming method involves a brief period of culturing in naive media early in the reprogramming process. Through conducting extensive molecular, epigenetic, and functional analyses on numerous induced pluripotent stem cell lines, we have demonstrated that TNT reprogramming facilitates epigenetic memory erasure and produces induced pluripotent stem (iPS) cells more similar to embryonic stem (ES) cells than conventional reprogramming methods1. In 2024, De Los Angeles et al. posted a contradictory results preprint on bioRxiv titled Sendai virus persistence questions the transient naive reprogramming method for iPSC generation2. Their claims include: 1) that Sendai virus expression in naive cultured cells questions the TNT reprogramming method, 2) the possible selection of cells (clonal expansion) with Sendai virus expression during TNT reprogramming, 3) Sendai virus genes being expressed in control samples implying a potential sample mix-up. Here, we demonstrate these claims are not directly supported by the data, and emphasize that we assessed the possibility of cell sub-population selection experimentally in Buckberry et al. (2023). Moreover, our re-analyses of the data in the context of Sendai virus expression during reprogramming actually highlight the advantages of TNT reprogramming concerning the timing of the naive media treatment and the absence of detectable Sendai virus gene expression.

developmental biology↗

bioRxiv2024

VirID: Beyond Virus Discovery - An Integrated Platform for Comprehensive RNA Virus Characterization

RNA viruses exhibit vast phylogenetic diversity and can significantly impact public health and agriculture. However, current bioinformatics tools for viral discovery from metagenomic data frequently generate false positive virus results, overestimate viral diversity, and misclassify virus sequences. Additionally, current tools often fail to determine virus-host associations, which hampers investigation of the potential threat posed by a newly detected virus. To address these issues we developed VirID, a software tool specifically designed for the discovery and characterization of RNA viruses from metagenomic data. The basis of VirID is a comprehensive RNA-dependent RNA polymerase (RdRP) database to enhance a workflow that includes RNA virus discovery, phylogenetic analysis, and phylogeny-based virus characterization. Benchmark tests on a simulated data set demonstrated that VirID had high accuracy in profiling viruses and estimating viral richness. In evaluations with real-world samples, VirID was able to identity RNA viruses of all type, but also provided accurate estimations of viral genetic diversity and virus classification, as well as comprehensive insights into virus associations with humans, animals, and plants. VirID therefore offers a robust tool for virus discovery and serves as a valuable resource in basic virological studies, pathogen surveillance, and early warning systems for infectious disease outbreaks.

bioinformatics↗

bioRxiv2024

Clathrin-associated carriers enable recycling through a kiss-and-run mechanism

Endocytosis and recycling control the uptake and retrieval of various materials, including membrane proteins and lipids, in all eukaryotic cells. These processes are crucial for cell growth, organization, function, and environmental communication. However, the mechanisms underlying efficient, fast endocytic recycling remain poorly understood. Here, by utilizing a biosensor and imaged-based screening, we uncover a novel recycling mechanism that couples endocytosis and fast recycling, which we name the clathrin-associated fast endosomal recycling pathway (CARP). Clathrin-associated tubulovesicular carriers containing clathrin, AP1, Arf1, Rab1, and Rab11, while lacking the multimeric retrieval complexes, are generated at subdomains of early endosomes, and then transported along actin to cell surfaces. Unexpectedly, the clathrin-associated recycling carriers undergo partial fusion with the plasma membrane. Subsequently, they are released from the membrane by dynamin and reenter cells. Multiple receptors utilize and modulate CARP for fast recycling following endocytosis. Thus, CARP represents a novel endocytic recycling mechanism with kiss-and-run membrane fusion.

cell biology↗

bioRxiv2024

Pan-cancer subclonal mutation analysis of 7,827 tumors predicts clinical outcome

Intra-tumor heterogeneity is characterized by a diverse population of tumor clones and subclones which are important drivers of tumor evolution and therapeutic response. However, accurate subclonal reconstruction at scale remains challenging. We developed a machine learning tool, CliPP, and surveyed 9,972 tumors from 32 cancer types. We found that high subclonal mutation load (sML), the fraction of subclonal single nucleotide variants (SNVs) to all SNVs in the coding region, was prognostic of survival (progression free survival or overall survival) in 18 cancer types. In 14 cancers with low to moderate tumor mutation burden (TMB), high sML was associated with better prognosis. In immunotherapy trials for 42 metastatic prostate cancer (mCRPC), high sML was predictive of favorable response to ipilimumab and associated with increased CD8+ T-cell infiltration and decreased macrophage population. A validation using 613 whole-genomes of esophageal adenocarcinoma confirms the favorable effect of high sML and the observed tumor-associated macrophage. Our study identifies sML as a key feature of cancer, suggesting a biphasic relationship between evolutionary dynamics and differential immune environments. Finally, sML may serve as an orthogonal approach to identify likely responders of immune checkpoint blockade in low to moderate TMB tumors.

genomics↗

bioRxiv2024

Dynamics and Regulatory Roles of RNA m6A Methylation in Unbalanced Genomes

N6-methyladenosine (m6A) in eukaryotic RNA is an epigenetic modification that is critical for RNA metabolism, gene expression regulation, and the development of organisms. Aberrant expression of m6A components appears in a variety of human diseases. RNA m6A modification in Drosophila has proven to be involved in sex determination regulated by Sxl and may affect X chromosome expression through the MSL complex. The dosage-related effects under the condition of genomic imbalance (i.e., aneuploidy) are related to various epigenetic regulatory mechanisms. Here, we investigated the roles of RNA m6A modification in unbalanced genomes using aneuploid Drosophila. The results showed that the expression of m6A components changed significantly under genomic imbalance, and affected the abundance and genome-wide distribution of m6A, which may be related to the developmental abnormalities of aneuploids. The relationships between methylation status and classical dosage effect, dosage compensation, and inverse dosage effect were also studied. In addition, we demonstrated that RNA m6A methylation may affect dosage-dependent gene regulation through dosage-sensitive modifiers, alternative splicing, the MSL complex, and other processes. More interestingly, there seems to be a closely relationship between MSL complex and RNA m6A modification. It is found that ectopically overexpressed MSL complex, especially the levels of H4K16Ac through MOF could influence the expression levels of m6A modification and genomic imbalance may be involved in this interaction. We found that m6A could affect the levels of H4K16Ac through MOF, a component of the MSL complex, and that genomic imbalance may be involved in this interaction. Altogether, our work reveals the dynamic and regulatory role of RNA m6A modification in unbalanced genomes, and may shed new light on the mechanisms of aneuploidy-related developmental abnormalities and diseases.

genomics↗

bioRxiv2024

Unravelling the progression of the zebrafish primary body axis with reconstructed spatiotemporal transcriptomics

Elucidating the spatiotemporal dynamics of gene expression is essential for understanding complex physiological and pathological processes. Traditional technologies like in situ hybridization (ISH) and immunostaining have been restricted to analyzing expression patterns of a limited number of genes. Spatial transcriptomics (ST) has emerged as a robust alternative, enabling the investigation of spatial patterns of thousands of genes simultaneously. However, current ST methods are hindered by low read depths and limited gene detection capabilities. Here, we introduce Palette, a pipeline that infers detailed spatial gene expression patterns from bulk RNA-seq data, utilizing existing ST data as only reference. This method identifies more precise expression patterns by smoothing, imputing and adjusting gene expressions. We applied Palette to construct the Danio rerio SpatioTemporal Expression Profiles (DreSTEP) by integrating 53-slice serial bulk RNA-seq data from three developmental stages with existing ST references and 3D zebrafish embryo images. DreSTEP provides a comprehensive cartographic resource for examining gene expression and spatial cell-cell interactions within zebrafish embryos. Utilizing machine learning-based screening, we identified key morphogens and transcription factors (TFs) essential for anteroposterior (AP) axis development and characterized their dynamic distribution throughout embryogenesis. In addition, among these TFs, Hox family genes were found to be pivotal in AP axis refinement. Their expression was closely correlated with cellular AP identities, and hoxb genes may act as central regulators in this process.

developmental biology↗

bioRxiv2024

RNA-ligand interaction scoring via data perturbation and augmentation modeling

RNA-targeting drug discovery is undergoing an unprecedented revolution. Despite recent advances in this field, developing data-driven deep learning models remains challenging due to the limited availability of validated RNA-small molecule interactions and the scarcity of known RNA structures. In this context, we introduce RNAsmol, a novel sequence-based deep learning framework that incorporates data perturbation with augmentation, graph-based molecular feature representation and attention-based feature fusion modules to predict RNA-small molecule interactions. RNAsmol employs perturbation strategies to balance the bias between true negative and unknown interaction space thereby elucidating the intrinsic binding patterns between RNA and small molecules. The resulting model demonstrates accurate predictions of the binding between RNA and small molecules, outperforming other methods with average improvements of [~]8% (AUROC) in 10-fold cross-validation, [~]16% (AUROC) in cold evaluation (on unseen datasets), and [~]30% (ranking score) in decoy evaluation. Moreover, we use case studies to validate molecular binding hotspots in the prediction of RNAsmol, proving the models interpretability. In particular, we demonstrate that RNAsmol, without requiring structural input, can generate reliable predictions and be adapted to many RNA-targeting drug design scenarios.

bioinformatics↗

bioRxiv2024

BEACON: Benchmark for Comprehensive RNA Tasks and Language Models

RNA plays a pivotal role in translating genetic instructions into functional outcomes, underscoring its importance in biological processes and disease mechanisms. Despite the emergence of numerous deep learning approaches for RNA, particularly universal RNA language models, there remains a significant lack of standardized benchmarks to assess the effectiveness of these methods. In this study, we introduce the first comprehensive RNA benchmark BEACON (BEnchmArk for COmprehensive RNA Task and Language Models). First, BEACON comprises 13 distinct tasks derived from extensive previous work covering structural analysis, functional studies, and engineering applications, enabling a comprehensive assessment of the performance of methods on various RNA understanding tasks. Second, we examine a range of models, including traditional approaches like CNNs, as well as advanced RNA foundation models based on language models, offering valuable insights into the task-specific performances of these models. Third, we investigate the vital RNA language model components from the tokenizer and positional encoding aspects. Notably, our findings emphasize the superiority of single nucleotide tokenization and the effectiveness of Attention with Linear Biases (ALiBi) over traditional positional encoding methods. Based on these insights, a simple yet strong baseline called BEACON-B is proposed, which can achieve outstanding performance with limited data and computational resources. The datasets and source code of our benchmark are available at https://github.com/terry-r123/RNABenchmark.

bioinformatics↗

bioRxiv2024

Propagating cortical waves coordinate sensory encoding and memory retrieval in the human brain

Complex behavior entails a balance between taking in sensory information from the environment and utilizing previously learned internal information. Experiments in behaving mice have demonstrated that the brain continually alternates between outward and inward modes of cognition, switching its mode of operation every few seconds. Further, each state transition is marked by a stereotyped cascade of neuronal spiking that pervades most forebrain structures. Here we analyzed large fMRI datasets to demonstrate that a similar switching mechanism governs the operation of the human brain. We found that human brain activity was punctuated every several seconds by coherent, propagating waves emerging in the exteroceptive sensorimotor regions and terminating in the interoceptive default mode network. As in the mouse, the issuance of such events coincided with fluctuations in pupil size, indicating a tight relationship with arousal fluctuations, and this phenomenon occurred across behavioral states. Strikingly, concurrent measurement of human performance in a visual memory task indicated that each cycle of propagating fMRI waves sequentially promoted the encoding of semantic information and self-directed retrieval of memories. Together, these findings indicate that human cognitive performance is governed by autonomous switching between exteroceptive and interoceptive states. This apparently conserved feature of mammalian brain physiology bears directly on the integration of sensory and mnemonic information during everyday behavior.

neuroscience↗

bioRxiv2024

Make-or-break prime editing for bacterial genome engineering

CRISPR-Cas9 has revolutionized genome engineering by allowing precise introductions of DNA double-strand breaks (DSBs). However, genome engineering in bacteria is still a complex, multi-step process requiring a donor DNA template for repair of DSBs. Prime editing circumvents this need as the repair template is indirectly provided within the prime editing guide RNA (pegRNA). Here, we developed make-or-break Prime Editing (mbPE) that allows for precise and effective genetic engineering in the opportunistic human pathogen Streptococcus pneumoniae. In contrast to traditional prime editing in which a nicking Cas9 is employed, mbPE harnesses wild type Cas9 in combination with a pegRNA that destroys the seed region or protospacer adjacent motif. Since most bacteria poorly perform template-independent end joining, correctly genome-edited clones are selectively enriched during mbPE. We show that mbPE is RecA-independent and can be used to introduce point mutations, deletions and targeted insertions, including protein tags such as a split luciferase, at selection efficiencies of over 93%. mbPE enables sequential genome editing, is scalable, and can be used to generate pools of mutants in a high-throughput manner. The mbPE system and pegRNA design guidelines described here will ameliorate future bacterial genome editing endeavors.

microbiology↗

bioRxiv2024

Decoding the anti-aging effect of retinol in reshaping the human skin microbiome niches

Retinol has been widely added to skincare products due to its ability to promote the proliferation of skin keratinocytes and regulate skin cell collagen expression. While it is known the skin harbors a myriad of commensal bacteria, the impact of retinol on the skin microbiome, as well as the role of the skin microbiome in mediating the anti-aging properties of retinol, remains poorly understood. In this study, we incorporated phenomics, metagenomics and metabolomics to explore the human skin alterations during the anti-aging process mediated by retinol, and potential interactions between retinol, skin microbiome and metabolites. Topical retinol significantly improved skin conditions, including enhancing skin hydration, acidifying the epidermis, strengthening the skin barrier, and reducing the number and volume of wrinkles. Furthermore, retinol also reshaped the skin microecology by altering the structure and function of the skin microbiome as well as the host and microbial metabolites. Through GEM construction, we identified 2 skin microorganism, Sericytochromatia sp. and Corynebacterium kefirresidentii capable of oxidizing retinol to retinal. Over 10 skin microbes can utilize UDP-glucose as a carbon source, potentially accelerating RAG hydrolysis and increasing glucuronic acid consumption. The retinoic acid and retinol generated by RAG hydrolysis are reused by skin cells and microbes, enhancing retinol metabolism and its effective duration. This combined effect between the skin microbiome and retinol improves skin condition and anti-aging efficacy.

microbiology↗

bioRxiv2024

Mapping Individual Differences in the Topological Landscape of Naturalistic Brain Dynamics

Psychiatry seeks to unravel brain dysfunction and individual differences in real-world contexts. Naturalistic stimuli, like movie watching, are increasingly recognized for eliciting complex, context-dependent neural activity with high ecological validity. Yet, current methods often rely on standard paradigms that average data across time, limiting the full potential of such stimuli. Here, we present STIM, a Topological Data Analysis-based framework designed to dynamically track how individuals integrate complex contexts in real time. Applied to large-sample fMRI data from movie watching, STIM constructs a robust low-dimensional dynamical landscape that reflects group consensus while probing individual variations at both global (spanning narratives) and local (within specific narratives) levels. At the global level, individual differences emerge along a center-periphery gradient in the dynamical landscape, which significantly predicts fluid intelligence, underscoring the importance of neural adaptability and diversity. At finer scales, local geometric features correlate with context-specific psychological traits beyond cognition. STIM also captures developmental changes in the dynamical landscape and reveals abnormalities in conditions such as autism. These findings demonstrate that STIM leverages the rich information from movie stimuli and fMRI recordings as neural probes to assess individual differences in cognition and mental health.

neuroscience↗

bioRxiv2024

Structure of the E3 ligase CRL2-ZYG11B with substrates reveals the molecular basis for N-degron recognition and ubiquitination

ZYG11B is a substrate specificity factor for Cullin-RING ubiquitin ligase (CRL2) involved in many biological processes, including Gly/N-degron pathways. Yet how the binding of ZYG11B with CRL2 is coupled to substrate recognition and ubiquitination is unknown. We present the Cryo-EM structures of the CRL2-ZYG11B holoenzyme alone and in complex with a Gly/N-peptide from the inflammasome-forming pathogen sensor NLRP1. The structures indicate ZYG11B folds into a Leucine-Rich Repeat followed by two armadillo repeat domains that promote assembly with CRL2 and recognition of NLRP1 Gly/N-degron. ZYG11B promotes activation of the NLRP1 inflammasome through recognition and subsequent ubiquitination of the NLRP1 Gly/N-degron revealed by viral protease cleavage. Our structural and functional data indicate that blocking ZYG11B recognition of the NLRP1 Gly/N-degron inhibits NLRP1 inflammasome activation by a viral protease. Overall, we show how the CRL2-ZYG11B E3 ligase complex recognizes Gly/N-degron substrates, including those that are involved in viral protease-mediated activation of the NLRP1 inflammasome.

molecular biology↗

bioRxiv2024

Multiomics mapping and characterization of cellular senescence in aging human muscle uncovers novel senotherapeutics for sarcopenia

Cellular senescence is recognized as a hallmark of organismal aging but how it drives aging particularly in human tissues is not fully understood, partly due to the complex heterogeneous nature of senescence. Here in this study, we leverage single-nucleus multiomics to profile senescence in mononucleated cells of human skeletal muscle and provide the first senescence atlas. We demonstrate the intra-and inter-populational transcriptomic and epigenomic heterogeneity and dynamics of senescence in the cells. We also identify commonalities and variations in senescence-associated secretory phenotypes (SASPs) among the cells and elucidate the function of SASPs in mediating cellular interactions and niche deregulation. Furthermore, we identify targetable SASP factors and demonstrate the possibility of using Maraviroc as a pharmacological senotherapeutic for treating age-associated sarcopenia in muscle. Lastly, we define transcription factors that govern senescence state and SASP induction in aging muscle and elucidate the key function and the underlying mechanism of JUNB in regulating SASP activation in senescent cells. Altogether, our findings demonstrate the prevalence and function of cellular senescence in skeletal muscle and identify a novel pharmacological intervention for sarcopenia.

cell biology↗

bioRxiv2024

Os-circANK negatively regulates resistance to bacterial blight in rice via Osa-miR398b/OsCSD1/OsCSD2 pathways

CircRNAs are widely present in plants, yet there have been no reports on the role of circRNA in the regulatory mechanisms of interactions between rice and pathogenic bacteria. As the sequence of circRNAs matches the parent gene except for the back splicing site, there is no feasible way to specifically knockdown circRNAs in plants. We identified a circRNA, named Os-circANK, derived from an ankyrin repeat protein, which was significantly downregulated post Xanthomonas oryzae pv. oryzae (Xoo) inoculation. We have created a CRISPR-Cas13d system to specifically knockdown a plant circular RNA, resulting in genetically edited rice with a targeted decrease in Os-circANK expression. Os-circANK was found to function as a sponge for Osa-miR398b, suppressing the cleavage of OsCSD1/OsCSD2 by Osa-miR398b, leading to a reduction in ROS levels following Xoo infection and a negative regulation of resistance to bacterial blight in rice. Our findings demonstrate that Os-circANK inhibits the resistance to bacterial blight in rice via the Osa-miR398b/OsCSD1/OsCSD2 pathways.

microbiology↗

bioRxiv2024

Mealtime alters daily rhythm in nuclear O-GlcNAcome to regulate hepatic gene expression

The liver circadian clock and hepatic transcriptome are highly responsive to metabolic signals generated from feeding-fasting rhythm. Previous studies have identified a number of nutrient-sensitive signaling pathways that could interpret metabolic input to regulate rhythmic hepatic biology. Here, we investigated the role of O-GlcNAcylation, a nutrient-sensitive post-translational modification (PTM) in mediating metabolic regulation of rhythmic biology in the liver. We observe daily oscillation of global nuclear protein O-GlcNAcylation in the liver of mice subjected to night-restricted feeding (NRF) using label-free global O-GlcNAc proteomics. Additional site-specific O-GlcNAc analysis by tandem mass tag mass spectrometry further supports temporal differences in O-GlcNAcylation by revealing day-night differences. Proteins involved in gene expression are enriched among rhythmically O-GlcNAcylated proteins, suggesting rhythmic O-GlcNAcylation may directly regulate the daily rhythmicity of the hepatic transcriptome. We show that rhythmic O-GlcNAcylation can also indirectly modulate the hepatic transcriptome by interacting with phosphorylation. Several proteins harboring O-GlcNAcylation-phosphorylation interplay motif exhibit rhythmic O-GlcNAcylation and phosphorylation. Specifically, we show that O-GlcNAcylation occurs at a phospho-degron of a key circadian transcriptional activator, circadian locomotor output cycles kaput (CLOCK), thus regulating its stability and transcriptional output. Finally, we report that day-restricted feeding (DRF) in the nocturnal mouse significantly alters O-GlcNAcylation rhythm. Whereas global O-GlcNAcylation analysis indicates dampening of global O-GlcNAcylation rhythm in mice fed under DRF, site-specific analysis reveals differential responses of O-GlcNAc sites when timing of food intake is altered. Notably, a substantial number of O-GlcNAcylation sites exhibit inverted day-night profiles when mice are subjected to DRF. This suggests the dysregulation of daily nuclear protein O-GlcNAcylation rhythm may contribute to the disruption in liver transcriptomic rhythm previously observed in DRF condition. In summary, our results provide new mechanistic insights into metabolic regulation of daily hepatic transcriptomic rhythm via interplay between O-GlcNAcylation and phosphorylation and shed light on the deleterious effects of improper mealtimes.

physiology↗

bioRxiv2024

Calorie Restriction Induces Degeneration of Neurons with Mitochondrial DNA Depletion by Altering ER-Mitochondria Calcium Transfer

Mitochondrial DNA (mtDNA) mutations and/or depletion are implicated in epilepsy and many neurodegenerative diseases. However, systematic investigation into how mtDNA alterations relate to epilepsy and neural degeneration is needed. Here, we established a mouse model where in mtDNA depletion induced by Herpes Simplex Virus Type 1 (HSV-1) protein-UL12.5 in the brain led to an epileptic phenotype characterized by abnormal electroencephalography (EEG) patterns and increased neural excitability in hippocampus. We also found that UL12.5 mediated mtDNA depletion in neurons in vitro (rho-) causes epilepsy-like abnormal EEG. Caloric restriction (CR) is a strategy proven to reduce epileptic activity, however CR mimetic 2-deoxy-D-glucose (2-DG), induced degeneration in mtDNA depleted neurons. Mechanistically, mtDNA depletion increased mitochondria-endoplasmic reticulum (ER) contacts, facilitating CR-induced mitochondrial calcium overload. Rho- neurons did not show changes in mitochondrial motility or membrane potential. Our study revealed an unexpected axis of mtDNA depletion, ER-mitochondrial contacts, and calcium overload in the rho- neuron model. This is the first description of animal and neuronal models of mitochondrial epilepsy. Our findings with these models suggest that CR may not be a viable clinical intervention in patients with mtDNA depletion.

cell biology↗