Biology subjects

Yao, S.

Publications and source records attributed to Yao, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Convergent evolution of plant prickles is drivenby repeated gene co-option over deep time

An enduring question in evolutionary biology concerns the degree to which episodes of convergent trait evolution depend on the same genetic programs, particularly over long timescales. Here we genetically dissected repeated origins and losses of prickles, sharp epidermal projections, that convergently evolved in numerous plant lineages. Mutations in a cytokinin hormone biosynthetic gene caused at least 16 independent losses of prickles in eggplants and wild relatives in the genus Solanum. Strikingly, homologs promote prickle formation across angiosperms that collectively diverged over 150 million years ago. By developing new Solanum genetic systems, we leveraged this discovery to eliminate prickles in a wild species and an indigenously foraged berry. Our findings implicate a shared hormone-activation genetic program underlying evolutionarily widespread and recurrent instances of plant morphological innovation.

evolutionary biology↗

bioRxiv2024

A self-adaptive and versatile tool for eliminating multiple undesirable variations from transcriptome

Accurate identification of true biological signals from diverse undesirable variations in large-scale transcriptomes is essential for downstream discoveries. Herein, we develop a universal deep neural network, called DeepAdapter, to eliminate various undesirable variations from transcriptomic data. The innovation of our approach lies in automatic learning of the corresponding denoising strategies to adapt to different situations. The data-driven strategies are flexible and highly attuned to the transcriptomic data that requires denoising, yielding significant improvement in reducing undesirable variation originating from batches, sequencing platforms, and bio-samples with varied purity beyond manually designed schemes. Comprehensive evaluations across multiple batches, different RNA measurement technologies and heterogeneous bio-samples demonstrate that DeepAdapter can robustly correct diverse undesirable variations and accurately preserve biological signals. Our findings indicate that DeepAdapter can act as a versatile tool for the comprehensive denoising of the large and heterogeneous transcriptome across a wide variety of application scenarios.

bioinformatics↗

bioRxiv2024

Cooperativity of c-MYC with Krüppel-Like Factor 6 Splice Variant 1 induces phenotypic plasticity and promotes prostate cancer progression and metastasis

Metastasis remains a major cause of morbidity and mortality in men with prostate cancer, and the functional impact of the genetic alterations, alone or in combination, driving metastatic disease remains incompletely understood. The proto-oncogene c-MYC, commonly deregulated in prostate cancer. Transgenic expression of c-MYC is sufficient to drive the progression to prostatic intraepithelial neoplasia and ultimately to moderately differentiated localized primary tumors, however, c-MYC-driven tumors are unable to progress through the metastatic cascade, suggesting that a "second-hit" is necessary in the milieu of aberrant c-MYC-driven signaling. Here, we identified cooperativity between c-MYC and KLF6-SV1, an oncogenic splice variant of the KLF6 gene. Transgenic mice that co-expressed KLF6-SV1 and c-MYC developed progressive and metastatic prostate cancer with a histological and molecular phenotype like human prostate cancer. Silencing c-MYC expression significantly reduced tumor burden in these mice supporting the necessity for c-MYC in tumor maintenance. Unbiased global proteomic analysis of tumors from these mice revealed significantly enriched vimentin, a dedifferentiation and pro-metastatic marker, induced by KLF6-SV1. c-MYC-positive tumors were also significantly enriched for KLF6-SV1 in human prostate cancer specimens. Our findings provide evidence that KLF6-SV1 is an enhancer of c-MYC-driven prostate cancer progression and metastasis, and a correlated genetic event in human prostate cancer with potential translational significance.

cancer biology↗

bioRxiv2024

Tractography-based automated identification of the retinogeniculate visual pathway with novel microstructure-informed supervised contrastive learning

The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and can inform the treatment of related brain diseases. Diffusion MRI (dMRI) tractography is an advanced imaging method that uniquely enables in vivo mapping of the 3D trajectory of the RGVP. Currently, identification of the RGVP from tractography data relies on expert (manual) selection of tractography streamlines, which is time-consuming, has high clinical and expert labor costs, and is affected by inter-observer variability. In this paper, we present a novel deep learning framework, DeepRGVP, to enable fast and accurate identification of the RGVP from dMRI tractography data. We design a novel microstructure-informed supervised contrastive learning method that leverages both streamline label and tissue microstructure information to determine positive and negative pairs. We propose a simple and successful streamline-level data augmentation method to address highly imbalanced training data, where the number of RGVP streamlines is much lower than that of non-RGVP streamlines. We perform comparisons with several state-of-the-art deep learning methods that were designed for tractography parcellation, and we show superior RGVP identification results using DeepRGVP. In addition, we demonstrate a good generalizability of DeepRGVP to dMRI tractography data from neurosurgical patients with pituitary tumors and we show DeepRGVP can successfully identify RGVPs despite the effect of lesions affecting the RGVPs. Overall, our study shows the high potential of using deep learning to automatically identify the RGVP.

neuroscience↗

bioRxiv2023

Deciphering the Biosynthetic Potential of Microbial Genomes Using a BGC Language Processing Neural Network Model

Microbial secondary metabolites are usually synthesized by colocalized genes termed biosynthetic gene clusters (BGCs). A large portion of BGCs remain undiscovered in microbial genomes and metagenomes, representing a pressing challenge in unlocking the full potential of natural product diversity. In this work, we propose BGC-Prophet, a language model based on the transformer encoder that captures the distant location-dependent relationships among biosynthetic genes, allows accurately and efficiently identifies known BGCs and extrapolates novel BGCs among the microbial universe. BGC-Prophet is the first ultrahigh-throughput (UHT) method that is several orders of magnitude faster than existing tools such as DeepBGC, enabling pan-phylogenetic screening and whole-metagenome screening of BGCs. By analyzing 85,203 genomes and 9,428 metagenomes, new insights have been obtained about the diversity of BGCs on genomes from the majority of bacterial and archaeal lineages. The profound enrichment of BGCs in microbes after important geological events have been revealed: Both the Great Oxidation and Cambrian Explosion events led to a surge in BGC diversity and abundance, particularly in polyketides. These findings suggest that it is a general but constantly evolving approach for microbes to produce secondary metabolites for their adaptation in the changing environment. Taken together, BGC-Prophet enables accurate and fast detection of BGCs on a large scale, holds great promise for expanding BGC knowledge, and sheds light on the evolutionary patterns of BGCs for possible applications in synthetic biology. HighlightsO_LIBGC-Prophet shows superior performance to existing tools in terms of accuracy and speed. C_LIO_LIBGC-Prophet is the first ultrahigh-throughput (UHT) method that enables pan-phylogenetic screening and whole-metagenome screening of BGCs. C_LIO_LIBGC-Prophet builds the comprehensive profile of BGCs on 85,203 genomes and 9,428 metagenomes from the majority of bacterial and archaeal lineages. C_LIO_LIBGC-Prophet reveals the profound enrichment pattern of BGCs after important geological events. C_LI

bioinformatics↗

bioRxiv2023

Millimeter-scale magnetic implants paired with a fully integrated wearable device for wireless biophysical and biochemical sensing

Implantable sensors can directly interface with various organs for precise evaluation of health status. However, extracting signals from such sensors must rely on transcutaneous wires, integrated circuit chips, or cumbersome readout equipment, which increases the risks of infection, reduces the biocompatibility, or limits the portability. Here, we develop a set of millimeter-scale, chip-less and battery-less magnetic implants that can measure biophysical and biochemical signals wirelessly. In particular, the implants form two-way communications with a fully integrated wearable device, where the wearable device can induce a large-amplitude damped vibration of the magnetic implants and capture their subsequent motions in a wireless manner. Such damped vibrations reflect not only the biophysical conditions surrounding the implants movements, but also the concentration of a specific biochemical depending on the surface modification. Experiments in rat models demonstrate the capabilities in measuring cerebrospinal fluid (CSF) viscosity, intracranial pressure (ICP), and CSF glucose levels. This miniaturized system opens possibility for continuous, wireless monitoring of a wide range of biophysical and biochemical conditions within the living organism.

bioengineering↗

bioRxiv2023

The microbial community of rust layer biofilm was driven by seawater microbial community

Microbiologically influenced corrosion (MIC) accounts for approximately 20% of the total corrosion-related losses worldwide, causing significant economic damage each year, particularly in Marine environments. However, there are still no truly effective and eco-friendly protection solutions against MIC, among which the incomplete understanding of the microbial biofilm development on metallic surface is a key limitation. Using 16S rRNA and ITS sequencing, we studied bacterial and fungal communities in rust layer biofilm and seawater. The results showed that Proteobacteria, Cyanobacteria and Bacteroidota were the dominant bacterial phyla, and Ascomycota and Basidiomycota were the dominant fungal phyla both in the rust layer biofilm and seawater. Bacteria like Erythrobacter and Aquimarina, as well as fungi like Aspergillus and Acremonium were were notable microorganisms in the rust layer biofilm. Source analysis revealed differences between biofilm and seawater communities, with 23.08% bacterial and 21.48% fungal communities originating from seawater. Stochastic processes governed biofilm and seawater microbial communities, and network analysis showed coexistence and interaction among bacteria and fungi. IMPORTANCEThe composition and source analysis of bacterial and fungal communities in the rust layer and seawater were studied, and the interaction of bacteria and fungi in the rust layer was discussed for the first time. Based on these findings, we provided a framework to explain the observed characteristics of microbial communities in rust layer biofilm and presented key evidence supporting the relationship between different microbial structures and interactions with metal corrosion. These findings, from the perspective of microbial ecology, provide a theoretical foundation for studying microbial corrosion in marine environments.

microbiology↗

bioRxiv2023

Alternating Polarity as a Novel Strategy for Cultivating Electro-Methanogenic Microbial Communities Capable of Robust Biogas Production

Electro-methanogenic microbial communities can produce biogas with high efficiency. Extensive efforts have been made to cultivate these communities in engineered systems. Conventional cultivation strategies can select electrotrophic methanogens but not their electron-donating partners, resulting in communities that are sensitive to perturbations. Herein, we developed an alternating polarity strategy to simultaneously select both microbial populations. In two-chamber bioelectrochemical systems amended with activated carbon, the electrode potential was alternated between +0.8 V and -0.4 V vs. standard hydrogen electrode every three days. After eight alternating cycles, cultivated activated carbon was transferred into new bioreactors, and the enrichment procedure was repeated four times. Cumulative biogas production under alternating polarity increased from 45 L/L/kg-activated carbon after start-up to 125 L/L/kg after the 4th enrichment, significantly higher than that under intermittent cathode (-0.4 V/open circuit), continuous cathode (-0.4 V), and open circuit. The communities cultivated under alternating polarity were electroactive and structurally different from those cultivated under other conditions. One Methanobacterium population and two Geobacter populations were consistently abundant and active in the communities. Their 16S rRNA was upregulated by electrode potentials. Bayesian networks inferred close associations between these populations. The cultivation strategy can enhance biogas production, and the cultivated communities may serve as a model system for elucidating the mechanisms of extracellular electron uptake. SynopsisAn alternating polarity strategy was developed in this study to cultivate electro-methanogenic microbial communities. The cultivated communities can produce biogas more efficiently and help us understand the ecophysiology of the key microbial populations.

ecology↗

bioRxiv2023

Capturing dynamic fear experiences in naturalistic contexts: An ecologically valid fMRI signature integrating brain activation and connectivity

Enhancing our understanding of how the brain constructs conscious emotional experiences within dynamic real-life contexts necessitates ecologically valid neural models. Here, we present evidence delineating the constraints of current fMRI activation models in capturing naturalistic fear dynamics. To address this challenge, we fuse naturalistic fMRI with predictive modeling techniques to develop an ecologically valid fear signature that integrates activation and connectivity profiles, allowing for accurate prediction of subjective fear experience under highly dynamic close-to-real-life conditions. This signature arises from insights into the crucial role of distributed brain networks and their interactions in emotion modulation, and the potential of network-level information to improve predictions in dynamic contexts. Across a series of investigations, we demonstrate that this signature predicts stable and dynamic fear experiences across naturalistic scenarios with heightened sensitivity and specificity, surpassing traditional activation- and connectivity-based signatures. Notably, the integration of affective connectivity profiles enables accurate real-time predictions of fear fluctuations in naturalistic settings. Additionally, we unearth a distributed yet redundant brain-wide representation of fear experiences. Subjective fear is encoded not only by distributed cortical and subcortical regions but also by their interactions, with no single brain system conveying substantial unique information. Our study establishes a comprehensive and ecologically valid functional brain architecture for subjective fear in dynamic environments and bridges the gap between experimental neuroscience and real-life emotional experience.

neuroscience↗

bioRxiv2023

Unveiling targeted cell-free DNA methylation regions through paired methylome analysis of tumor and normal tissues

Liquid biopsy analysis of cell-free DNA (cfDNA) has revolutionized cancer research by enabling non-invasive assessment of tumor-derived genetic and epigenetic changes. In this study, we conducted a comprehensive paired-sample differential methylation analysis (psDMR) on reprocessed methylation data from two large datasets, CPTAC and TCGA, to identify and validate differentially methylated regions (DMRs) as potential cfDNA biomarkers for head and neck squamous cell carcinoma (HNSC). Our hypothesis is that the paired sample test provides a more suitable and powerful approach for the analysis of heterogeneous cancers like HNSC. The psDMR analysis revealed a significant number of overlapped hypermethylated DMRs between two datasets, indicating the reliability and relevance of these regions for cfDNA methylation biomarker discovery. We identified several candidate genes, including CALCA, ALX4, and HOXD9, which have been previously established as liquid biopsy methylation biomarkers in various cancer types. Furthermore, we demonstrated the efficacy of targeted region analysis using cfDNA methylation data from oral cavity squamous cell carcinoma and nasopharyngeal carcinoma patients, further validating the utility of psDMR analysis in prioritizing cfDNA methylation biomarkers. Overall, our study contributes to the development of cfDNA-based approaches for early cancer detection and monitoring, expanding our understanding of the epigenetic landscape of HNSC, and providing valuable insights for liquid biopsy biomarker discovery not only in HNSC and other cancer types.

genomics↗

bioRxiv2023

Prolonging lung cancer response to EGFR inhibition by targeting the selective advantage of resistant cells

Non-small cell lung cancers (NSCLCs) treated with tyrosine kinase inhibitors (TKIs) of the epidermal growth factor receptor (EGFR) almost invariably relapse in the long term, due to the emergence of subpopulations of resistant cells. Here we show that the lack of sensitivity of these cells to EGFR-TKIs constitutes a vulnerability that can be potentially targeted. Through a DNA barcoding approach, we demonstrate that the clinically approved drug sorafenib specifically abolishes the selective advantage of EGFR-TKI-resistant cells, while preserving the response of EGFR-TKI-sensitive cells, thus resulting in overall inhibition of clonal evolution within the tumor cell mass population. Sorafenib is active against multiple mechanisms of resistance/tolerance to EGFR-TKIs and its effects depend on early inhibition of MAPK interacting kinase (MNK) activity and signal transducer and activator of transcription 3 (STAT3) phosphorylation, and later down-regulation of MCL1 and EGFR. Using several xenograft and allograft models to recapitulate different mechanisms and kinetics of acquired resistance, we show that the sorafenib-EGFR-TKI combination can substantially delay tumor growth and promote the recruitment of inflammatory cells. Together, our findings indicate that sorafenib can substantially prolong the response to EGFR-TKIs by targeting NSCLC capacity to adapt to treatment through the emergence of resistant cells.

cancer biology↗

bioRxiv2023

Targeting CD301+ macrophage inhibits endometrial fibrosis and improves pregnancy outcome

Macrophages are a key and heterogeneous cell population involved in endometrial repair and regeneration during the menstrual cycle, but their role in the development of intrauterine adhesion (IUA) and sequential endometrial fibrosis remains unclear. Here, we reported that CD301+ macrophages were significantly increased and showed their most active interaction with profibrotic cells in the endometria of IUA patients compared with the normal endometria by single-cell RNA sequencing, bulk RNA sequencing and experimental verification. Increasing CD301+ macrophages promoted the differentiation of endometrial stromal cells into myofibroblasts and resulted in extracellular matrix accumulation, which destroyed the physiological architecture of endometrial tissue, drove endometrial fibrosis and ultimately led to female infertility or adverse pregnancy outcomes. Mechanistically, CD301+ macrophages secreted GAS6 to activate the AXL/NF-{kappa}B pathway, up-regulating the profibrotic protein synthesis. Targeted deletion of CD301+ macrophages or inhibition of AXL by Bemcentinib blunted the pathology and improved the outcomes of pregnancy in mice, supporting the therapeutic potential of targeting CD301+ macrophages for treating endometrial fibrosis.

immunology↗

bioRxiv2023

Transcriptional profiling of mucus production and modification in rhesus macaque endocervical cells under hormonal regulation

ObjectiveEndocervical mucus production is a key regulator of fertility throughout the menstrual cycle. With cycle-dependent variability in mucus quality and quantity, cervical mucus can either facilitate or block sperm ascension into the upper female reproductive tract. This study seeks to identify genes involved in the hormonal regulation of mucus production, modification, and regulation through profiling the transcriptome of endocervical cells from the non-human primate, the Rhesus Macaque (Macaca mulatta). DesignExperimental. SettingTranslational science laboratory. InterventionWe treated differentiated primary endocervical cultures with estradiol (E2) and progesterone (P4) to mimic peri-ovulatory and luteal-phase hormonal changes. Using RNA-sequencing, we identified differential expression of gene pathways and mucus producing and modifying genes in cells treated with E2 compared to hormone-free conditions and E2 compared to E2-primed cells treated with P4. Main Outcome MeasuresWe pursued differential gene expression analysis on RNA-sequenced cells. Sequence validation was done using qPCR. ResultsOur study identified 158 genes that show significant differential expression in E2-only conditions compared to hormone-free control, and 250 genes that show significant differential expression in P4-treated conditions compared to E2-only conditions. From this list, we found hormone-induced changes in transcriptional profiles for genes across several classes of mucus production, including ion channels and enzymes involved in post-translational mucin modification that have not previously been described as hormonally regulated. ConclusionOur study is the first to use an in vitro culture system to create an epithelial-cell specific transcriptome of the endocervix. As a result, our study identifies new genes and pathways that are altered by sex-steroids in cervical mucus production.

molecular biology↗

bioRxiv2023

Rabies virus-based barcoded neuroanatomy resolved by single-cell RNA and in situ sequencing

Mapping the connectivity of diverse neuronal types provides the foundation for understanding the structure and function of neural circuits. High-throughput and low-cost neuroanatomical techniques based on RNA barcode sequencing have the potential to map circuits at cellular resolution and a brain-wide scale, but existing Sindbis virus-based techniques can only map long-range projections using anterograde tracing approaches. Rabies virus can complement anterograde tracing approaches by enabling either retrograde labeling of projection neurons or monosynaptic tracing of direct inputs to genetically targeted postsynaptic neurons. However, barcoded rabies virus has so far been only used to map non-neuronal cellular interactions in vivo and synaptic connectivity of cultured neurons. Here we combine barcoded rabies virus with single-cell and in situ sequencing to perform retrograde labeling and transsynaptic labeling in the mouse brain. We sequenced 96 retrogradely labeled cells and 295 transsynaptically labeled cells using single-cell RNA-seq, and 4,130 retrogradely labeled cells and 2,914 transsynaptically labeled cells in situ. We found that the transcriptomic identities of rabies virus-infected cells can be robustly identified using both single-cell RNA-seq and in situ sequencing. By associating gene expression with connectivity inferred from barcode sequencing, we distinguished long-range projecting cortical cell types from multiple cortical areas and identified cell types with converging or diverging synaptic connectivity. Combining in situ sequencing with barcoded rabies virus complements existing sequencing-based neuroanatomical techniques and provides a potential path for mapping synaptic connectivity of neuronal types at scale.

neuroscience↗

bioRxiv2023

A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge

Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional nearinfrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural selfregulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.

neuroscience↗

bioRxiv2023

Title: Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease

Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

genomics↗

bioRxiv2022

Alterations in intestinal Proteobacteria and antimicrobial resistance gene burden in individuals administered microbial ecosystem therapeutic (MET-2) for recurrent Clostridioides difficile infection

Intestinal colonisation with pathogens and antimicrobial resistant organisms (AROs) is associated with increased risk of infection. Fecal microbiota transplant (FMT) has successfully been used to cure recurrent Clostridioides difficile infection (rCDI) and to decolonise intestinal AROs. However, FMT has significant practical barriers to implementation. A microbial consortium, microbial ecosystem therapeutic (MET)-2, is an alternative to FMT for the treatment of rCDI. It is unknown whether MET-2 is associated with decreases in pathogens and antimicrobial resistance genes (ARGs). We conducted a post-hoc metagenomic analysis of stool collected from two interventional studies of MET-2 (published) and FMT (unpublished) for rCDI treatment to understand if MET-2 had similar effects to FMT for decreasing pathogens and ARGs as well as increasing anaerobes. Patients were included in the current study if baseline stool had Proteobacteria relative abundance [≥]10% by metagenomic sequencing. We assessed pre- and post-treatment Proteobacteria, obligate anaerobe and butyrate-producer relative abundances and total ARGs. MET-2 and FMT were associated with decreases in Proteobacteria relative abundance as well as increases in obligate anaerobe and butyrate-producer relative abundances. The microbiota response remained stable over 4 or 6 months for MET-2 and FMT, respectively. MET-2, but not FMT, was associated with a decrease in the total number of ARGs. MET-2 is a potential therapeutic strategy for ARO/ARG decolonisation and anaerobe repletion.

microbiology↗

bioRxiv2022

Mechanical force induces DRP1-dependent asymmetrical mitochondrial fission for quality control

Mitochondria are membrane-bound organelles that perform diverse critical biological functions. They undergo constant fission and fusion, which are important for mitochondrial inheritance, functions, and quality control. While tremendous efforts have identified many factors governing mitochondria dynamics, emerging evidence indicates the involvement of various intracellular or extracellular mechanical cues. However, how mechanical stress directly modulates mitochondrial dynamics remains largely unknown. Here utilizing an optogenetic mitochondria-specific mechanostimulator to apply pulling forces to intracellular mitochondria, we find that mechanostimulation can promote mitochondrial fission, with sustained mechanostimulation triggering fission more effectively than transient one. Asymmetrical fission can occur at different sub-mitochondrial sites after force-induced mitochondrial elongation. Such force-induced fission is dependent on DRP1 and involves the wrapping of ER tubules. Moreover, mechanical force generates mitochondrial fragments without mtDNA which recruit Parkin proteins. Our results prove the mechanosensitivity and mechanoresponsiveness of mitochondria and reveal the role of mechanical cues in directly regulating mitochondrial dynamics.

cell biology↗