Biology subjects

Gao, J.

Publications and source records attributed to Gao, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Structural basis for the midnolin-proteasome pathway and its role in suppressing myeloma

The midnolin-proteasome pathway degrades many nuclear proteins without ubiquitination, but how it operates mechanistically remains unclear. Here, we present structures of the midnolin-proteasome complex, revealing how established proteasomal components are repurposed to enable a unique form of proteolysis. While the proteasomal subunit PSMD2/Rpn1 binds to ubiquitinated or ubiquitin-like proteins, we discover that it also interacts with the midnolin nuclear localization sequence, elucidating how midnolins activity is confined to the nucleus. Likewise, PSMD14/Rpn11, an enzyme that normally cleaves ubiquitin chains, surprisingly functions non-enzymatically as a receptor for the midnolin ubiquitin-like (Ubl) domain, positioning the substrate-binding Catch domain directly above the proteasomal entry site to guide substrates into the proteasome. Moreover, we demonstrate that midnolin downregulation is critical for the survival of myeloma cells by promoting the expression of its transcription factor substrate IRF4. Our findings uncover the mechanisms underlying the midnolin-proteasome pathway and midnolin downregulation as a driver of multiple myeloma.

cell biology↗

bioRxiv2025

Single-Cell Sequencing Identifies the Crucial Role of Mitochondrial Fission-Fusion Balance in Cardiac Hypertrophy Progression

BackgroundThe heart undergoes growth in response to both pathological and physiological stimuli. Pathological hypertrophy often leads to cardiomyocyte loss and heart failure (HF), whereas physiological hypertrophy paradoxically protects the heart and enhances cardiomyogenesis. The molecular mechanisms that distinguish these two forms of hypertrophy remain unclear. MethodsIn this study, we utilized single-cell transcriptomics from transverse aortic constriction (TAC) models at 2, 5, 8, and 11 weeks (GSE120064), along with bulk RNA sequencing from mice subjected to 12 months of exercise-induced physiological hypertrophy and cardiomyogenesis (CRA007207), to investigate the molecular differences between pathological and physiological hypertrophy. ResultsOur results reveal the following. Mitochondrial-related pathways are the primary drivers of the pathological changes that occur following TAC. The mitochondrial fission and fusion pathways exhibited increased activity at 2 weeks but decreased activity at 5, 8, and 11 weeks post TAC. The expression pattern of exercise-induced physiological hypertrophy was similar to that of 2-week TAC-induced changes, indicating that the early stage of TAC represents an adaptive physiological response or physiological hypertrophy. Notably, during HF, the fission genes Fis1 and Dnm1l increase, in contrast to the expected decrease in fusion genes. These findings were experimentally validated, indicating that the mitochondrial fission genes Fis1 and Dnm1l are key promoters of HF. ConclusionsOur data indicate that the balance between mitochondrial fission and fusion plays a critical role in the transition from physiological to pathological hypertrophy. The fission-related genes Fis1 and Dnm1l have emerged as key drivers of pathological hypertrophy and heart failure. These findings suggest that targeting fission genes, particularly Fis1 and Dnm1l, may represent promising therapeutic strategies for managing heart failure.

bioinformatics↗

bioRxiv2025

Highly efficient genome editing in Bacillus subtilis via miniature DNA nucleases IscB.

Existing CRISPR-based genome editing tools are limited in Bacillus subtilis due to the large cas gene. The recently reported DNA nuclease IscB has the potential to be developed into a novel genome editing tool due to its size being one-third of Cas9, while its application in B. subtilis remains unexplored. In this study, genome editing tools pBsuIscB/pBsuenIscB based on IscB and enIscB (enhanced IscB) were established in B. subtilis SCK6, and successfully deleted 0.6 kb to 4.3 kb genes with efficiencies up to 100%. Subsequently, the pBsuenIscB with higher deletion efficiency was used, whereby the large genomic fragment of 37.7 kb or 169.9 kb was deleted with only one {omega}RNA. Additionally, single-copy or multi-copy mCherry genes was integrated by using pBsuenIscB. Finally, the editing plasmid was eliminated and the second round of genome editing was completed. Overall, this study has successfully applied IscB to B.subtilis, expanded the genome editing toolbox of B. subtilis, and will help to construct B. subtilis chassis for production of a variety of biomolecules.

microbiology↗

bioRxiv2025

Translational activators align mRNAs at the small mitoribosomal subunit for translation initiation

Mitochondrial gene expression is essential for oxidative phosphorylation. Mitochondrial-encoded mRNAs are translated by dedicated mitochondrial ribosomes (mitoribosomes), whose regulation remains elusive. In the bakers yeast Saccharomyces cerevisiae, nuclear-encoded mitochondrial translational activators (TAs) facilitate transcript-specific translation by a yet unknown mechanism. Here, we investigated the function of TAs containing RNA-binding pentatricopeptide repeats (PPRs) using selective mitoribosome profiling and cryo-EM structural analysis. These analyses revealed that TAs exhibit strong selectivity for mitoribosomes initiating on their target transcripts. Moreover, TA-mitoribosome footprints indicated that TAs recruit mitoribosomes proximal to the start codon. Two cryo-EM structures of mRNA-TA complexes bound to post-initiation/pre-elongation-stalled mitoribosomes revealed the general mechanism of TA action. Specifically, the TAs bind to structural elements in the 5 UTR of the client mRNA as well as to the mRNA channel exit to align the mRNA in the small subunit during initiation. Our findings provide a mechanistic basis for understanding how mitochondria achieve transcript-specific translation initiation without relying on general sequence elements to position mitoribosomes at start codons.

molecular biology↗

bioRxiv2025

Potent synthetic lethality between PLK1 and EYA-family inhibitors in tumours of the central and peripheral nervous system

The Eyes Absent family of protein phosphatases (EYA1-4) are aberrantly expressed and tumour-promoting across many devastating cancers of neurological origin affecting both children and adults. It has recently been demonstrated that EYA1 and EYA4 promote tumour cell survival by increasing the active pool of Polo-like kinase 1 (PLK1) molecules. This discovery provides a rationale for the therapeutic combination of EYA inhibitors with direct, ATP-competitive, PLK1 inhibitors. Here, we demonstrate potent and synergistic effects of EYA and PLK1 inhibition in cancer cell lines that overexpress EYA1 and/or EYA4, including in neuroblastoma and glioblastoma models. We identify decreases in PLK1 activity and RAD51 foci formation, and increases in mitotic arrest and cell death, as mechanistic contributors to combination sensitivity. Combined EYA and PLK1 inhibition is also effective in glioblastoma stem cell models that overexpress EYA1/EYA4 and specifically targets the cancer stem cell state. Finally, through multi-omic correlational analysis, we identify high levels of the NuRD complex and SOX9 as contributors to combination treatment sensitivity. Overall, this work identifies a novel synthetic lethal combination therapy with potential utility across a wide range of neurological cancers.

cancer biology↗

bioRxiv2025

Charge-based fingerprinting of unlabeled full-length proteins using an aerolysin nanopore

Proteins play essential roles in cellular processes and are involved in numerous diseases, driving the need for efficient proteoform identification. While nanopore technology was highly successful for DNA sequencing, this approach has not yet delivered its full potential in protein identification. Here, we demonstrate the capabilities of an aerolysin nanopore for direct identification of a range of unlabeled full-length proteins. Combining low pH and guanidinium chloride, we generate a strong electroosmotic flow that enables an efficient capture and translocation, resulting in distinct fingerprints from single-protein translocations. Using machine learning classifier, we achieve 80% accuracy in distinguishing seven related proteins with 38%-70% pairwise sequence identities. Differences in fingerprints largely reflect the distribution of positive charges in the protein sequences, providing a rational basis for the observed sensitivity. With further development, fingerprint-predictions could allow to infer de novo protein sequence information from single-molecule data, offering a powerful tool for proteomics.

bioengineering↗

bioRxiv2024

Tumor break load quantitates structural variant-associated genomic instability with biological and clinical relevance across cancers

While structural variants (SVs) are a clear sign of genomic instability, they have not been systematically quantified per patient. Therefore, the biological and clinical impact of high numbers of SVs in patients is unknown. We introduce tumor break load (TBL), defined as the sum of unbalanced SVs, as a measure for SV-associated genomic instability. Using pan-cancer data from TCGA, PCAWG, and CCLE, we show that a high TBL is associated with significant changes in gene expression in 26/31 cancer types that consistently involve upregulation of DNA damage repair and downregulation of immune response pathways. Patients with a high TBL show a higher risk of recurrence and shorter median survival times for 5/15 cancer types. Our data demonstrate that TBL is a biologically and clinically relevant feature of genomic instability that may aid patient prognostication and treatment stratification. For the datasets analyzed in this study, TBL has been made available in cBioPortal.

cancer biology↗

bioRxiv2024

Astrocyte-specific secretome profiling reveals its correlation with neurological disorders

Secreted proteins mediate intercellular communication throughout the lives of multicellular organisms. However, due to the lack of new technology for secreted protein capturing, the progress of "secretomics lags behind. Here, we report a two-step secretome enrichment method (tsSEM) combining unnatural amino acid labeling and click chemistry-based biorthogonal reaction, which enables in vitro secretome profiling in the presence of serum. Using this novel method, we systematically investigated the secretome of human iPSCs-derived astrocytes (iAst) in different disease models and identified a panel of astrocyte-secreted proteins that are responsible for its non-cell autonomous toxicity under disease conditions. Furthermore, we validated two astrocytes-derived novel neurotrophic proteins, FAM3C and KITLG, which we identified from disease models, and found that they could boost neurite outgrowth, protect neurons, and promote neural progenitor proliferation. Our study highlights the utility of secretome profiling of iAst and demonstrates its applications in disease study and target identification and validation in drug development.

neuroscience↗

bioRxiv2024

scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity by providing gene expression data at single-cell resolution, uncovering insights into rare cell populations, cell-cell interactions, and gene regulation. Foundation models pretrained on large-scale scRNA-seq datasets have shown great promise in analyzing such data, but existing approaches are often limited to modeling a small subset of highly expressed genes and lack the integration of external genespecific knowledge. To address these limitations, we present sc-Long, a billion-parameter foundation model pretrained on 48 million cells. sc-Long performs self-attention across the entire set of 28,000 genes in the human genome. This enables the model to capture long-range dependencies between all genes, including lowly expressed ones, which often play critical roles in cellular processes but are typically excluded by existing foundation models. Additionally, sc-Long integrates gene knowledge from the Gene Ontology using a graph convolutional network, enriching its contextual understanding of gene functions and relationships. In extensive evaluations, sc-Long surpasses both stateof-the-art scRNA-seq foundation models and task-specific models across diverse tasks, including predicting transcriptional responses to genetic and chemical perturbations, forecasting cancer drug responses, and inferring gene regulatory networks.

bioinformatics↗

bioRxiv2024

Structure of the TXNL1-bound proteasome

Proteasomes degrade diverse proteins in different cellular contexts through incompletely defined regulatory mechanisms. Here, we report the cryo-EM structure of thioredoxin-like protein 1 (TXNL1) bound to the 19S regulatory particle of proteasomes via interactions with PSMD1/Rpn2, PSMD4/Rpn10, and PSMD14/Rpn11. These interactions are necessary for the ubiquitin-independent degradation of TXNL1 upon cellular exposure to metal- or metalloid-containing oxidative agents, thereby establishing a structural basis for the stress-induced degradation of TXNL1.

cell biology↗

bioRxiv2024

A PERTURBATION CELL ATLAS OF HUMAN INDUCED PLURIPOTENT STEM CELLS

Towards comprehensively investigating the genotype-phenotype relationships governing the human pluripotent stem cell state, we generated an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J human induced pluripotent stem cells (hiPSCs) mapping transcriptional and fitness phenotypes associated with 11,739 targeted genes. Using the transcriptional phenotypes, we created a minimum distortion embedding map of the pluripotent state, demonstrating rich recapitulation of protein complexes, such as strong co-clustering of MRPL, BAF, SAGA, and Ragulator family members. Additionally, we uncovered transcriptional regulators that are uncoupled from cell fitness, discovering potential novel pluripotency (JOSD1, RNF7) and metabolic factors (ZBTB41). We validated these findings via phenotypic, protein-interaction, and metabolic tracing assays. Finally, we propose a contrastive human-cell engineering framework (CHEF), a machine learning architecture that learns from perturbation cell atlases to predict perturbation recipes that achieve desired transcriptional states. Taken together, our study presents a comprehensive resource for interrogating the regulatory networks governing pluripotency.

bioengineering↗

bioRxiv2024

Extending the Coding-variant Allelic Series Test to Summary Statistics

Genes for which a dose-response relationship exists between mutational severity and phenotypic impact make for logical therapeutic targets, as the effects of pharmacological modulation can be anticipated from the natural variation present in a population. We refer to genes where such a dose-response relationship exists as harboring allelic series, and have introduced the rare coding-variant allelic series test (COAST) for their identification. The original COAST required access to individual-level data. However, such data are often unavailable due to privacy concerns or logistical challenges. Meanwhile, single-variant summary statistics of the type produced by genome-wide association studies are plentiful. Here we introduce COAST-SS, an extension of COAST that accepts summary statistics as input, namely the per-variant effect sizes and standard errors, along with estimates of the minor allele frequency and local linkage disequilibrium (LD). As a running example, we consider identifying allelic series for circulating lipid traits, drawing on data from the UK Biobank, Million Veterans Program, and Trans-Omics of Precision Medicine Program. Through extensive analyses of real and simulated data, we demonstrate that COAST-SS provides p-values effectively equivalent to those from the original COAST. Interestingly, we find that when LD is low, as is expected among rare variants, COAST-SS is robust to misspecification of the LD matrix, providing valid inference even when the LD matrix is set to the identity matrix. We explore several strategies for annotating the pathogenicity of variants supplied to COAST-SS, finding that they often yield similar power for detecting candidate allelic series. Lastly, we employ COAST-SS to screen for lipid trait allelic series in a meta-analyzed cohort of up to 840K subjects. COAST-SS has been incorporated into the publicly available AllelicSeries R package.

genetics↗

bioRxiv2024

Dietary control of peripheral adipose storage capacity through membrane lipid remodelling

Complex genetic and dietary cues contribute to the development of obesity, but how these are integrated on a molecular level is incompletely understood. Here, we show that PPAR{gamma} supports hypertrophic expansion of adipose tissue via transcriptional control of LPCAT3, a membrane-bound O-acyltransferase that enriches diet-derived omega-6 (n-6) polyunsaturated fatty acids (PUFAs) in the phospholipidome. In high-fat diet-fed mice, lowering membrane n-6 PUFA levels by adipocyte-specific Lpcat3 knockout (Lpcat3AKO) or by dietary lipid manipulation leads to dysfunctional triglyceride (TG) storage, ectopic fat deposition and insulin resistance. Aberrant lipolysis of stored TGs in Lpcat3AKO adipose tissues instigates a non-canonical adaptive response that engages a futile lipid cycle to increase energy expenditure and limit further body weight gain. Mechanistically, we find that adipocyte LPCAT3 activity promotes TG storage by selectively enriching n-6 arachidonoyl-phosphatidylethanolamine at the ER-lipid droplet interface, which in turn favours the budding of large droplets that exhibit greater resistance to ATGL-dependent hydrolysis. Thus, our study highlights the PPAR{gamma}-LPCAT3 pathway as a molecular link between dietary n-6 PUFA intake, adipose expandability and systemic energy balance.

physiology↗

bioRxiv2024

Identification of a key gain-of-function residue for effector binding by in vitro shuffling of barley Mla NLR genes

Natural plant populations maintain high resistance (R) gene diversities that provide effective pathogen resistance; however, such diversity has been reduced significantly by the genetic bottlenecks associated with plant domestication and breeding. Agricultural crops typically contain limited R gene diversity so resistance is often short-lived as pathogens evolve rapidly to evade recognition. The mildew resistance locus A (Mla) R gene family of barley and wheat represents a rich source of natural genetic variation that is ideal for mining disease resistance specificities. Mla R genes encode immune receptor proteins of the nucleotide-binding leucine-rich repeat (NLR) class that recognise unrelated plant pathogens by binding secreted virulence proteins termed effectors. The barley NLRs MLA13 and MLA7 confer resistance to different strains of the barley powdery mildew pathogen through direct interaction with the pathogen effectors AVRA13 and AVRA7 respectively. Using DNA shuffling, we generated a variant library by recombining the Mla7 and Mla13 genes in vitro. The variant library was cloned into yeast generating [~]4,000 independent clones and was screened for interaction with AVRA13 and AVRA7 using a yeast-two-hybrid (Y2H) assay. This yielded a number of clones that encode NLR proteins that interacted with AVRA13. Sequence analysis showed that the interacting MLA proteins can be clustered into three groups, all of which contain a critical residue from MLA13. While MLA13 and MLA7 differ by 30 residues across the LRR domain, the replacement of leucine to serine at this position in MLA7 facilitated interaction with AVRA13 in yeast and AVRA13-dependent immune signalling in planta. We have established a pipeline that evolves MLAs to recognise distinct pathogen effectors without the requirement for protein structural knowledge and the use of rationale design. We suggest these findings represent a step towards evolving novel recognition capabilities rapidly in vitro.

plant biology↗

bioRxiv2024

3D-UHU-TU: A Three-Dimensional Bladder Cancer Model in a Healthy Urothelial Environment

Bladder cancer cases and fatalities continue to rise worldwide with treatment outcomes not improving in the last four decades. Poor translation of potential new therapies from pre- clinical studies to the clinic could be one reason behind this. The patient-derived xenograft (PDX) mouse is the gold-standard for testing new bladder cancer therapies, but there are key physiological and molecular differences between mouse and human bladders. Thus, more human cell-based models may improve translation of treatments. Here, we introduce a bladder cancer microtissue model called 3D Urine-tolerant Human Urothelium-Tumour (3D-UHU-TU), which incorporates spheroids derived from human bladder cancer cell lines RT112 (low grade) and T24 (high grade) into the previously published 3D-UHU healthy urothelial model in a 100% urine environment. Both low- and high-grade 3D- UHU-TU models were characterised using immunofluorescence and immunohistochemistry staining with diagnostic markers (CK7, CK20 and GATA3), cadherin markers (E- and N-Cadherin), invasion and migration markers (MMP-2 and MMP-9) and a proliferation marker (Ki-67). Both models expressed the correct markers in the correct spatial areas. We also investigated the utility of both 3D-UHU-TU models as a platform to test treatments, using the conventional chemotherapeutic Mitomycin C as proof of principle. After 2 hours of treatment and 24 hours of recovery, cell lysis and nuclear damage were observed in both low- and high- grade cancer spheroids, with minimal damage to the surrounding healthy urothelium. At higher doses, cancer spheroids either disintegrated or were reduced in size, with the healthy urothelium still intact. Taken together, 3D-UHU-TU is a novel, in vitro model for testing both the safety and efficacy of new treatments. Furthermore, our work lays the foundation for testing treatments on patient-derived tumour spheroids in a personalised medicine approach.

cancer biology↗

bioRxiv2024

Characterization the gene editing with miniature nucleases TnpB, IscB and enIscB in Escherichia coli strains

DNA nucleases TnpB and IscB were regarded as new antibacterial strategy to combat the drug-resistant bacteria represented by Escherichia coli due to its specificity in targeting DNA and smallest size, but the genome-editing of TnpB/IscB in E. coli remains unclear. This study characterized the genome-editing of TnpB/IscB in E. coli strains. First, the toxicity and cleavage results showed TnpB only worked in E. coli MG1655, while IscB and enIscB could perform in ATCC9637 and BL21(DE3). Next, TnpB-based genome-editing tool was established in MG1655, while IscB/enIscB achieved in ATCC9637/BL21(DE3). The copy number of TnpB/IscB/enIscB were changed to explore the impact of editing efficiency. Moreover, the editing plasmids were successfully cured. Finally, the escaping mechanism of E. coli under editing of TnpB/IscB was revealed. Overall, this study successfully applied TnpB/IscB/enIscB to genome-editing in E. coli, which will broaden genetic manipulation toolbox in E. coli and facilitate the development of new antimicrobial drugs.

microbiology↗

bioRxiv2024

Spatiotemporal Single-Cell Roadmap of Human Skin Wound Healing

Wound healing is vital for human health, yet the details of cellular dynamics and coordination in human wound repair remain largely unexplored. To address this, we conducted single-cell and spatial transcriptomics analyses on human skin and acute wound tissues through inflammation, proliferation, and remodeling phases of wound repair from the same individuals, monitoring the cellular and molecular dynamics of human skin wound healing at an unprecedented spatiotemporal resolution. This singular roadmap reveals the cellular architecture of the wound margin and identifies FOSL1 as a critical driver of re-epithelialization. It shows that pro-inflammatory macrophages and fibroblasts sequentially support keratinocyte migration like a relay race across different healing stages. Comparison with single-cell data from venous and diabetic foot ulcers uncovers a link between failed keratinocyte migration and impaired inflammatory response in chronic wounds. Additionally, comparing human and mouse acute wound transcriptomes underscores the indispensable value of this roadmap in bridging basic research with clinical innovations. HighlightsO_LIA spatiotemporal atlas to explore human in vivo gene expression across wound healing C_LIO_LIWound margin architecture unveils a model for human re-epithelialization C_LIO_LIDistinct healing challenges in venous ulcers and diabetic foot ulcers C_LIO_LIUnique human healing traits emerge in cellular heterogeneity and gene expression C_LI

cell biology↗

bioRxiv2024

MorphLink: Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics

Multi-modal spatial omics data are invaluable for exploring complex cellular behaviors in diseases from both morphological and molecular perspectives. Current analytical methods primarily focus on clustering and classification, and do not adequately examine the relationship between cell morphology and molecular dynamics. Here, we present MorphLink, a framework designed to systematically identify disease-related morphological-molecular interplays. MorphLink has been evaluated across a wide array of datasets, showcasing its effectiveness in extracting and linking interpretable morphological features with various molecular measurements in multi-modal spatial omics analyses. These linkages provide a transparent depiction of cellular behaviors that drive transcriptomic heterogeneity and immune diversity across different regions within diseased tissues, such as cancer. Additionally, MorphLink is scalable and robust against cross-sample batch effects, making it an efficient method for integrative spatial omics data analysis across samples, cohorts, and modalities, and enhancing the interpretation of results for large-scale studies.

bioinformatics↗