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Li, B.

Publications and source records attributed to Li, B..

At least 235 records · Page 13Linked to original sources

CRISPR tiling deletion screens reveal functional enhancers of neuropsychiatric risk genes and allelic compensation effects (ACE) on transcription

Precise transcriptional regulation is critical for cellular function and development, yet the mechanism of this process remains poorly understood for many genes. To gain a deeper understanding of the regulation of neuropsychiatric disease risk genes, we identified a total of 39 functional enhancers for four dosage-sensitive genes, APP, FMR1, MECP2, and SIN3A, using CRISPR tiling deletion screening in human induced pluripotent stem cell (iPSC)-induced excitatory neurons. We found that enhancer annotation provides potential pathological insights into disease-associated copy number variants. More importantly, we discovered that allelic enhancer deletions at SIN3A could be compensated by increased transcriptional activities from the other intact allele. Such allelic compensation effects (ACE) on transcription is stably maintained during differentiation and, once established, cannot be reversed by ectopic SIN3A expression. Further, ACE at SIN3A occurs through dosage sensing by the promoter. Together, our findings unravel a regulatory compensation mechanism that ensures stable and precise transcriptional output for SIN3A, and potentially other dosage-sensitive genes.

genetics↗

3D Reconstruction Enables High-Throughput Phenotyping and Quantitative Genetic Analysis of Phyllotaxy

Differences in canopy architecture play a role in determining both the light and water use efficiency. Canopy architecture is determined by several component traits, including leaf length, width, number, angle, and phyllotaxy. Phyllotaxy may be among the most difficult of the leaf canopy traits to measure accurately across large numbers of individual plants. As a result, in simulations of the leaf canopies of grain crops such as maize and sorghum, this trait is frequently approximated as alternating 180{degrees} angles between sequential leaves. We explore the feasibility of extracting direct measurements of the phyllotaxy of sequential leaves from 3D reconstructions of individual sorghum plants generated from 2D calibrated images and test the assumption of consistently alternating phyllotaxy across a diverse set of sorghum genotypes. Using a voxel-carving-based approach, we generate 3D reconstructions from multiple calibrated 2D images of 366 sorghum plants representing 236 sorghum genotypes from the sorghum association panel. The correlation between automated and manual measurements of phyllotaxy is only modestly lower than the correlation between manual measurements of phyllotaxy generated by two different individuals. Automated phyllotaxy measurements exhibited a repeatability of R2 = 0.41 across imaging timepoints separated by a period of two days. A resampling based genome wide association study (GWAS) identified several putative genetic associations with lower-canopy phyllotaxy in sorghum. This study demonstrates the potential of 3D reconstruction to enable both quantitative genetic investigation and breeding for phyllotaxy in sorghum and other grain crops with similar plant architectures.

plant biology↗

Expression Profiles of FABP4 and FABP5 in Breast Cancer: Clinical Implications and Perspectives

The incidence of breast cancer continues to rise each year despite significant advances in diagnosis and treatment. Obesity-associated dysregulated lipid metabolism is believed to contribute to the increasing risk of breast cancer. However, the mechanisms linking lipid dysregulation to breast cancer risk and progression remain to be determined. The family of fatty acid binding proteins (FABPs) evolves to facilitate lipid transport and metabolism. As the predominant isoforms of FABP members expressed in breast tissue, adipose FABP (A-FABP, also known as FABP4) and epithelial FABP (E-FABP, FABP5) have been shown to play critical roles in breast carcinogenesis. In this study, we collected surgical breast tissue samples from 96 women with different subtypes of breast cancer and comprehensively analyzed the expression pattens of FABP4 and FABP5. We found that distinct expression profiles of FABP4 and FABP5 were associated with their unique roles in breast cancer development. FABP4, mainly expressed in breast stroma, especially in adipose tissue, supported neighboring tumor cell lymphvascular invasion through secretion from adipocytes. In contrast, FABP5, primarily expressed in epithelial-derived tumor cells, promoted tumor metastasis by enhancing lipid metabolism. Thus, elevated levels of FABP4 and FABP5 could serve as poor prognostic markers for breast cancer. Inhibiting the activity of FABP4 and/or FABP5 may offer a novel strategy for breast cancer treatment.

cancer biology↗

Mechanism of NPC1L1 mediated 27-hydroxycholesterol metabolisms in the occurrence and development of osteoporosis

Cholesterol metabolism is closely related to the occurrence and development of osteoporosis, but the exact mechanism remains unclear. Niemann-Pick C1-like 1 (NPC1L1) is one of the key cholesterol transporter proteins, however, there are few reports on the functions of NPC1L1 besides regulating cholesterol transport, let alone bone homeostasis. Our preliminary research indicated that NPC1L1 may play a negative regulatory role in osteogenic differentiation. In this study, using in vitro osteogenic differentiation experiment and mouse osteoporosis model, we showed here that NPC1L1 expression was downregulated during osteogenesis, and NPC1L1 knockdown significantly enhanced osteogenic differentiation ability of osteoblasts and delayed progress of osteoporosis. Mechanistically, through RNA sequencing, NPC1L1 was found regulate cholesterol metabolism rather than transportation. It increased 27-Hydroxycholesterol (27-OHC) level through activating 27-hydroxylase (Cyp27a1), resulting in 27-OHC accumulation in osteoblasts and inhibition of osteogenesis. Moreover, C/EBP was proved mediated NPC1L1 promotes production of 27-OHC by Cyp27a1. These findings reveal that NPC1L1 inhibits osteogenesis and promotes osteoporosis via regulate cholesterol metabolism. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/615783v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@11a62bforg.highwire.dtl.DTLVardef@148fb9aorg.highwire.dtl.DTLVardef@7e486eorg.highwire.dtl.DTLVardef@c53116_HPS_FORMAT_FIGEXP M_FIG NPC1L1 inhibits osteogenic differentiation and promotes the progression of OP through the C/EBP/Cyp27a1/27-OHC axis. C_FIG

molecular biology↗

Tumorigencity decrease in Bcl-xL deficient MDCK cells ensuring the safety for influenza vaccine production

Madin-Darby canine kidney (MDCK) cells are the recognized cell strain for influenza vaccine production. However, the tumorigenic potential of MDCK cells raises concerns about their use in biological product manufacturing. To reduce MDCK cells tumorigenicity and ensure the safety of influenza vaccine production, a B-cell lymphoma extra-large (Bcl-xL) gene, which plays a pivotal role in apoptosis regulation, was knocked-out in original MDCK cells by CRISPR-Cas9 gene editing technology, so that a homozygous MDCK-Bcl-xL-/- cell strain was acquired and named as BY-02. Compared with original MDCK cells, the proliferation and migration ability of BY-02 were significantly reduced, while apoptosis level was significantly increased, the endogenous mitochondrial apoptotic pathway were also modulated after Bcl-xL knock-out in MDCK cells. For tumor formation assays in nude mouse tests, all ten mice injected with original MDCK cells presented tumors growth in the injection site, in contrast to only one mouse injected with BY-02 cells presented tumors growth. These findings suggest that Bcl-xL knock-down is an effective strategy to inhibit tumor formation in MDCK cells, making BY-02 a promising genetically engineered cell strain for influenza vaccine production.

cell biology↗

Anti-phase clustering of regulatory factors shapes gene bursting

Stem cell self-renewal relies on finely tuned transcriptional oscillations of pluripotency genes, yet the sequence by which transcription factors (TFs) govern "on" and "off" states remains unclear. Here, we integrate trimodal single-molecule imaging - SOX2 mobility, Nanog locus diffusion, and real-time Nanog mRNA synthesis using the STREAMING-tag reporter - to visualise endogenous regulatory dynamics in living cells. We identify two SOX2 binding modes linked to transcriptional priming and termination and show coordinated temporal activity of SOX2, OCT4, BRD4, and MED22 at the Nanog locus. Live-cell and fixed-cell measurements reveal that local RNA fluctuations modulate SOX2 visiting-frequency rates. During the active elongation, high nascent enhancer and mRNA levels transiently sequester SOX2 through non-specific interactions, reducing its effective repetitive rebinding and limiting interference with elongating polymerase. After transcript release, declining RNA density permits SOX2 re-engagement, with high-visiting frequency with longer residency and increased locus mobility. These dynamics reveal RNA-dependent feedback that alternately buffers and primes transcriptional re-initiation.

molecular biology↗

Astrocyte ezrin defines resilience to stress-induced depressive behaviours in mice

Astrocyte atrophy is the main histopathological hallmark of major depressive disorder (MDD) in humans and in animal models of depression. Here we demonstrated that manipulating with ezrin expression specifically in astrocytes significantly increases the resilience of mice to chronic unpredictable mild stress (CUMS). Overexpression of ezrin in astrocytes from prefrontal cortex (PFC) rescued depressive-like behaviours induced by CUMS, whereas down-regulation of ezrin in astrocytes from PFC increased mice susceptibility to CUMS and promoted depressive-like behaviours. These behavioural changes correlated with astrocytic morphology. Astrocytes from PFC of mice sensitive to CUMS demonstrated significant atrophy; similar atrophy was found in astrocytes from animals with down-regulated ezrin expression. To the contrary morphology remains unchanged astrocytes in animals resistant to CUMS and in animals with astrocytic overexpression of ezrin. Morphological changes also correlated with ezrin immunoreactivity which was low in mice with depressive-like behaviours and high in mice resistant to stress. We conclude that Ezrin-dependent morphological remodelling of astrocytes defines the sensitivity of mice to stress: high ezrin expression renders them stress resilient, whereas low ezrin expression promotes depressive-like behaviour in response to chronic stress.

neuroscience↗

Interpretable scRNA-seq Analysis with Intelligent Gene Selection

AO_SCPLOWBSTRACTC_SCPLOWSingle-cell RNA sequencing (scRNA-seq) data analysis faces multiple challenges, including high dimensionality, significant noise, and data loss. To effectively address these issues, we introduce AIGS, a robust and transparent single-cell analysis framework. AIGS utilizes an intelligent gene selection method that systematically identifies the most informative genes for clustering based on the normalized mutual information between pre-learned pseudo-labels and quantified genes. Additionally, AIGS incorporates a scale-invariant distance metric to assess cell-to-cell similarity, enhancing connections between homogenous cells and ensuring more accurate and robust results. Through comprehensive comparisons with state-of-the-art techniques, AIGS demonstrates superior performance in both clustering accuracy and multi-resolution visualization quality. Our in-depth analysis of clustering and visualization results further reveals that AIGS can uncover complex, stage-specific gene expression patterns during the same developmental cell stage.

bioinformatics↗

Imaging the interactions of chimeric antigen receptor-expressing T-cells with colorectal cancer cells

Chimeric antigen receptor (CAR) T-cell therapy has shown unprecedented success in haematological cancers but faces challenges in solid tumours. Although carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) is differentially expressed in many solid tumours, anti-CEACAM5 CAR T-cells are ineffective. Here, we have studied the interaction of CEACAM5 targeting primary CAR T-cells with colorectal cancer (CRC) cells using fluorescence microscopy. We found that CRC cells glycocalyx is much deeper than that of the CAR T cell causing delayed activation. Oscillating calcium fluxes, indicative of non-sustained CAR T cell activation and reduced cytotoxicity, were observed when CAR T cells interacted with CRC cells, which increased with increasing cell-seeding time. Imaging revealed that this effect correlated with a progressive loss of accessible CEACAM5 antigen on the CRC cell surface, possibly due to their sequestration in the intercellular junction, rendering CAR T cell engagement less effective. Local proteolytic treatment with trypsin to disrupt the CRC cell monolayer, using a micropipette, increased CEACAM5 availability, decreased glycocalyx thickness, and restored sustained CAR T cell calcium fluxes, increasing the killing of CRC cells. Similar enhanced interaction was observed after treatment of CRC cell monolayer with hyaluronidase, approved for use in humans. We observed limited availability of CEACAM5 on human colorectal cancer tissues, whereas treatment with trypsin or hyaluronidase increased accessibility. Our results reveal why CAR T cells targeting CEACAM5 are ineffective and suggest possible routes to improved therapy for CRC.

immunology↗

Coordinated Tbx3 / Tbx5 transcriptional control of the adult ventricular conduction system

The cardiac conduction system (CCS) orchestrates the electrical impulses that enable coordinated contraction of the cardiac chambers. The T-box transcription factors TBX3 and TBX5 are required for cardiac conduction system development and associated with overlapping and distinct human cardiac conduction system diseases. We evaluated the coordinated role of Tbx3 and Tbx5 in the murine ventricular conduction system (VCS). We engineered a compound Tbx3:Tbx5 conditional knockout allele for both genes located in cis on mouse chromosome 5. Conditional deletion of both T-box transcriptional factors in the ventricular conduction system, using the VCS-specific MinK:Cre, caused loss of VCS function and molecular identity. Combined Tbx3 and Tbx5 deficiency in the adult VCS led to conduction defects, including prolonged PR and QRS intervals and elevated susceptibility to ventricular tachycardia. These electrophysiological defects occurred prior to detectable alterations in cardiac contractility or histologic morphology, indicative of a primary conduction system defect. Tbx3:Tbx5 double knockout VCS cardiomyocytes revealed a transcriptional shift towards non-CCS-specialized working myocardium, indicating a change to their cellular identity. Furthermore, optical mapping revealed a loss of VCS-specific conduction system propagation. Collectively, these findings indicate that Tbx3 and Tbx5 coordinate to control VCS molecular fate and function, with implications for understanding cardiac conduction disorders in humans.

developmental biology↗

A wheat tandem kinase and NLR pair confers resistance to multiple fungal pathogens

Recently discovered tandem kinase proteins (TKPs) are pivotal to the innate immune systems of cereal plants, yet how they initiate plant immune responses remains unclear. This report identifies the wheat protein WTN1, a non-canonical NLR receptor featuring tandem NB-ARC domains, as crucial for WTK3-mediated disease resistance. Both WTK3 and its allelic variant Rwt4, known for conferring resistance to wheat powdery mildew and blast respectively, are capable of recognizing the blast effector PWT4, and activate WTN1 to form calcium-permeable channels, akin to ZAR1 and Sr35. This study unveils a unique plant defense mechanism wherein TKPs and associated NLRs operate as "sensor-executor" pairs against fungal pathogens. Additionally, evolutionary analyses reveal a co-evolutionary trajectory of the TKP-NLR module, highlighting their synergistic role in triggering plant immunity. One Sentence SummaryAn ancient synergistic TKP-NLR pair triggers innate immunity for multiple disease resistance in wheat.

plant biology↗

Structural basis of phosphate export by human XPR1

Phosphorus is an essential element for all living organisms. While inorganic phosphate (Pi) cellular import is well documented, export is poorly characterized despite the recent discovery of the inositol pyrophosphate (PP-IP)-dependent Pi exporter XPR1. In this study, we determined the cryo-EM structures of XPR1. XPR1 forms a loose dimer, with each protomer containing 10 transmembrane helices (TMs) that can be divided into a peripheral domain (TM1, 3 and 4) and a core domain (TM2 and TM5-10) structurally related to ion-translocating rhodopsins. Bound Pi is observed in a tunnel formed by the helical bundle inside the core domain at a narrowest point that separates the tunnel into an intracellular vestibule (IV) and an extracellular vestibule (EV). This narrowest point contains a cluster of Pi-coordinating basic residues, and their substitution by mutagenesis strongly impaired phosphate export. PP-Ips stimulate XPR1 activity by binding to its SPX domain. Loss of this interaction induces a conformational change of the wide open EV (conducting state) into a collapsed EV (closed state), mainly caused by structural movements of TM9 and the bulky sidechain of Trp573 right above the Pi binding site, which are essential for the Pi export activity of XPR1. Our structural and functional characterization paves the way for further in-depth studies of XPR1.

biochemistry↗

Evaluating Methods for the Prediction of Cell Type-Specific Enhancers in the Mammalian Cortex

Identifying cell type-specific enhancers in the brain is critical to building genetic tools for investigating the mammalian brain. Computational methods for functional enhancer prediction have been proposed and validated in the fruit fly and not yet the mammalian brain. We organized the Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics to assess machine learning and feature-based methods designed to nominate enhancer DNA sequences to target cell types in the mouse cortex. Methods were evaluated based on in vivo validation data from hundreds of cortical cell type-specific enhancers that were previously packaged into individual AAV vectors and retro-orbitally injected into mice. We find that open chromatin was a key predictor of functional enhancers, and sequence models improved prediction of non-functional enhancers that can be deprioritized as opposed to pursued for in vivo testing. Sequence models also identified cell type-specific transcription factor codes that can guide designs of in silico enhancers. This community challenge establishes a benchmark for enhancer prioritization algorithms and reveals computational approaches and molecular information that are crucial for identifying functional enhancers in mammalian cortical cell types. The results of this challenge bring us closer to understanding the complex gene regulatory landscape of the mammalian cortex and to designing more efficient genetic tools to target cortical cell types.

genomics↗

Low-cost and highly efficient generation of near-complete bacterial pathogen genomes by TELL-Seq

Recent evidences suggest that de novo genome assembly can provide additional insights into genomic variation landscape beyond short-read NGS analyses. Despite the advent of longread sequencing technologies, generating high-quality bacterial genome assemblies remains expensive and requires high-quality and large quantities of DNA. TELL-Seq, an emerging linked-read technology, has been reported as a low-cost alternative for producing nearcomplete genome assembly in certain bacterial species. However, a systematic assessment of its performance and characteristics in de novo bacterial genome assembly has not yet been conducted. To address this, we benchmarked TELL-Seq using a set of clinical and standard bacterial pathogens with a wide range of genome size (2.0 6.4 Mbp), GC-content (32% - 68%), genome complexity (mappability from 0.15 to 0.60) and Gram types. Our findings indicate that, with 1/6 cost and 1/15,000 of DNA compared to PacBio HiFi, TELL-Seq could generate as high quality near-complete bacterial genome assemblies. The optimal depth for assembly is around 200x, as increased depth improves contiguity and completeness, though quality plateaus at 250x. In general, genome complexity was significantly correlated with assembly quality, but GC-content was not. Nevertheless, genomes with extreme GC-content may require higher depths for accurate assembly. Our study suggests that TELL-Seq could be a scalable method for large-scale bacterial genomic surveys. The data generated from this study could serve as a benchmark dataset for further algorithm development. Impact StatementAn increasing body of literature have shown that de novo genome assembles could provide additional insights into genomic variation beyond standard short-read technologies. Its particularly useful in clinical and epidemiological studies of bacteria, due to high variable nature of their genomes. Although great advances have been made in long-read sequencing technology, its still expensive with high requirement over sample DNAs quality and quantity, limiting its adoption in large-scale studies or surveys. Linked-read technology is an inexpensive alternative which used single molecule barcoding to mark origin of reads for better scaffolding of contigs assembled from normal short reads. TELL-Seq, as one of these promising technologies, was reported to be able to inexpensively and efficiently generate near-complete bacterial de novo genomic assemblies with low DNA inputs. Theres not yet a systematic benchmarking of this technology in bacterial pathogens. In this study, a set of clinically important bacterial pathogens with a wide spectrum of GC-content, genome size, genome complexity, and Gram Type were used to investigate the performance of TELL-Seq technology in de novo genome assembly. We found that, with about 1/6 of cost and 1/15000 of DNA quantity, it could generate comparable de novo assemblies compared to standard reference genomes or PacBio HiFi assemblies, while beating conventional short-read assemblies. We found several key factors, such as genome complexity, and sequencing depth, which would impact the quality of the assembly. Our study suggests that a sequencing depth of 200x is sufficient to achieve satisfactory results. Our study has revealed characteristics of this technology in bacterial genome assembly and paved the way for its large-scale application in clinical or epidemiological surveys. Data SummaryO_LIRaw sequencing data for all isolates have been deposited to SRA, accessible through these NCBI BioProject PRJNA1133244. C_LIO_LIA full list of SRA BioSample accession numbers are available in Tab S5. C_LIO_LIAssemblies and analyses companion this paper is available at: https://github.com/x-lab/tellseq_bacteria C_LI

bioinformatics↗

FEDKEA: Enzyme function prediction with a large pretrained protein language model and distance-weighted k-nearest neighbor

Recent advancements in sequencing technologies have led to the identification of a vast number of hypothetical proteins, surpassing current experimental capabilities for annotation. Enzymes, crucial for diverse biological functions, have garnered significant attention; however, accurately predicting enzyme EC numbers for proteins with unknown functions remains challenging. Here, we introduce FEDKEA, a novel computational method that integrates ESM-2 and distance-weighted KNN (k-nearest neighbor) to enhance enzyme function annotation. FEDKEA first employs a fine-tuned ESM-2 model with four fully connected layers to distinguish from other proteins. For predicting EC numbers, it adopts a hierarchical approach, utilizing distinct models and training strategies across the four EC number levels. Specifically, the classification of the first EC number level utilizes a fine-tuned ESM-2 model with three fully connected layers, while transfer learning with embeddings from this model supports the second and third-level tasks. The fourth-level classification employs a distance-weighted KNN model. Compared to existing tools such as CLEAN and ECRECer, two state-of-the-art computational methods, FEDKEA demonstrates superior performance. We anticipate that FEDKEA will significantly advance the prediction of enzyme functions for uncharacterized proteins, thereby impacting fields such as genomics, physiology and medicine. FEDKEA is easy to install and currently available at: https://github.com/Stevenleizheng/FEDKEA

bioinformatics↗

TFE3 fusions direct an oncogenic transcriptional program that drives OXPHOS and unveils vulnerabilities in translocation renal cell carcinoma

Translocation renal cell carcinoma (tRCC) is an aggressive subtype of kidney cancer driven by TFE3 gene fusions, which act via poorly characterized downstream mechanisms. Here we report that TFE3 fusions transcriptionally rewire tRCCs toward oxidative phosphorylation (OXPHOS), contrasting with the highly glycolytic metabolism of most other renal cancers. This TFE3 fusion-driven OXPHOS program, together with heightened glutathione levels found in renal cancers, renders tRCCs sensitive to reductive stress - a metabolic stress state induced by an imbalance of reducing equivalents. Genome-scale CRISPR screening identifies tRCC-selective vulnerabilities linked to this metabolic state, including EGLN1, which hydroxylates HIF-1 and targets it for proteolysis. Inhibition of EGLN1 compromises tRCC cell growth by stabilizing HIF-1a and promoting metabolic reprogramming away from OXPHOS, thus representing a vulnerability to OXPHOS-dependent tRCC cells. Our study defines a distinctive tRCC-essential metabolic program driven by TFE3 fusions and nominates EGLN1 inhibition as a therapeutic strategy to counteract fusion-induced metabolic rewiring.

cancer biology↗

Gene Expression Prediction from Histology Images via Hypergraph Neural Networks

Spatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing crucial insights into biological processes, disease mechanisms, and drug development. The prediction of gene expression based on cost-effective histology images is a promising yet challenging field of research. Existing methods for gene prediction from histology images exhibit two major limitations. First, they ignore the intricate relationship between cell morphological information and gene expression. Second, these methods do not fully utilize the different latent stages of features extracted from the images. To address these limitations, we propose a novel hypergraph neural network model, HGGEP, to predict gene expressions from histology images. HGGEP includes a gradient enhancement module to enhance the models perception of cell morphological information. A lightweight backbone network extracts multiple latent stage features from the image, followed by attention mechanisms to refine the representation of features at each latent stage and capture their relations with nearby features. To explore higher-order associations among multiple latent stage features, we stack them and feed into the hypergraph to establish associations among features at different scales. Experimental results on multiple datasets from disease samples including cancers and tumor disease, demonstrate the superior performance of our HGGEP model than existing methods. Key PointsWe develop a novel histology image-based gene prediction model named HGGEP, which demonstrates high accuracy and robust performance. To reveal the intricate relationship between cell morphology and gene expression in images, we propose a gradient enhancement module, which effectively improves the models capability in perceiving cell morphology in images. HGGEP includes a hypergraph module that efficiently models higher-order associations among features across multiple latent stages, resulting in significant performance improvement.

bioinformatics↗

Episodic Transport of Protein Aggregates Achieves a Positive Size Selectivity in Aggresome Formation

Eukaryotic cells direct toxic misfolded proteins to various protein quality control pathways based on their chemical features and aggregation status. Aggregated proteins are targeted to selective autophagy or specifically sequestered into the "aggresome," a perinuclear inclusion at the microtubule-organizing center (MTOC). However, the mechanism for selectively sequestering protein aggregates into the aggresome remains unclear. To investigate aggresome formation, we reconstituted MTOC-directed aggregate transport in Xenopus laevis egg extract using AgDD, a chemically inducible aggregation system. High-resolution single-particle tracking revealed that dynein-mediated transport of aggregates was highly episodic, with average velocity positively correlated with aggregate size. Our mechanistic model suggests that the recurrent formation of the dynein transport complex biases larger aggregates towards the active transport state, compensating for the slowdown due to viscosity. Both episodic transport and positive size selectivity are specifically associated with aggresome-dynein adaptors. Coupling conventional dynein-activating adaptors to the aggregates perturbs aggresome formation and reverses size selectivity.

cell biology↗