Biology subjects

Lv, W.

Publications and source records attributed to Lv, W..

At least 19 recordsLinked to original sources

bioRxiv2026

The tongue-brain axis mediates a hidden amino acid appetite

Selecting a diet containing all essential amino acids (EAAs) is critical for health. Following EAA deprivation, animals can select a nutritiously complete food source; however, the underlying mechanisms in vertebrates remain unclear. In mice, we show that leucine deficiency activates hypothalamic agouti-related protein (AgRP) neurons, which project to the paraventricular thalamus (PVT) via {gamma}-aminobutyric acid and are required for EAA deficiency-induced leucine appetite in mice. Furthermore, the peripheral tongue amino acid sensor general control nonderepressive-2 (GCN2) mediates acute EAA appetite via AgRP neurons. Together, these findings identify a tongue-AgRP-PVT circuit underlying EAA appetite, which is important for the rapid and accurate selection of essential nutrients.

neuroscience↗

bioRxiv2026

Pan-cancer circular genomics identifies intratumoral Staphylococcus lugdunensis as a metabolic driver in bladder cancer

Intratumoral microbiota play key roles in cancer but are challenging to profile due to low biomass. We developed CIRCMIP, an enzymatic pipeline that eliminates linear DNA to enrich bacterial genomes, achieving 100-fold higher sensitivity than standard metagenomics. Applied to 312 pan-cancer specimens, CIRCMIP identified Staphylococcus lugdunensis as a signature bacterium enriched in early-stage bladder cancer (BLCA), where its presence predicts poor survival. Integrated modeling and lipidomics revealed that Staphylococcus lugdunensis colonization drives aberrant lipid metabolism with secretion of LPC14:0. Both Staphylococcus lugdunensis and LPC14:0 drive BLCA progression by promoting fatty acid uptake and {beta}-oxidation. Mechanistically, chemical proteomics revealed LPC14:0 as a direct PPAR{delta} ligand, binding via hydrogen bonds with Thr292/Thr289. This activation upregulates fatty acid transporters (CD36, FABP4) and metabolic enzymes (ACOX2), fueling malignant proliferation. Furthermore, CIRCMIP-derived biomarkers show robust diagnostic accuracy, establishing a new research paradigm and revealing the Staphylococcus lugdunensis-LPC14:0-PPAR{delta} axis as a therapeutic target in bladder cancer. HIGHLIGHTO_LICIRCMIP leverages DNA circularity to achieve 100-fold sensitivity in pan-cancer bacteriome profiling. C_LIO_LIStaphylococcus lugdunensis is a bacterial signature in early-stage bladder cancer that predicts poor patient survival. C_LIO_LIBacteria-derived LPC14:0 acts as a direct ligand for PPAR{delta} to drive host malignant metabolic reprogramming. C_LIO_LITargeting the Staphylococcus lugdunensis-LPC14:0-PPAR{delta} axis abrogates malignant progression in bladder cancer. C_LI

cancer biology↗

bioRxiv2025

The Critical and Unexpected Role of a Methyl Group in Interleukin-17A Inhibitors

Interleukin-17 (IL-17) is a pro-inflammatory cytokine primarily secreted by Th17 cells. It plays a crucial role in the bodys immune defense against fungal and bacterial pathogens. However, an imbalance in IL-17 production can contribute to the development of autoimmune and inflammatory disorders. Therapeutic strategies targeting IL-17, such as blocking antibodies like secukinumab (Cosentyx), have been successfully developed. These antibodies are currently employed in the treatment of various conditions, including psoriasis, psoriatic arthritis, and ankylosing spondylitis. More recently, a small molecule inhibitor of IL-17, LY3509754, progressed to clinical trials but was halted during Phase 1 due to unfavorable hepatotoxicity. Two derivatives, compounds 7 and 8, did not advance to clinical trials due to safety concerns. These three compounds (7, 8, and the original lead compound, presumably implied) share a common difluoro substituent, which was hypothesized to be the cause of the observed safety issues. In subsequent structure-activity relationship (SAR) studies, replacing the difluoro substituent with a single methyl group (resulting in compound 9) unexpectedly led to a significant improvement in cellular activity. Furthermore, compound 9 exhibited a very low unbound fraction and reduced liver distribution, ultimately translating to high in vivo efficacy with a sufficient safety margin. This seemingly minor methyl substitution transformed the compound into a highly promising preclinical candidate (compound 9), now slated for further development. Co-development inquiries are welcome. Please contact us at enan1@dcpc.com. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/680113v2_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@3f31adorg.highwire.dtl.DTLVardef@d6873forg.highwire.dtl.DTLVardef@494af7org.highwire.dtl.DTLVardef@1d8b7eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Mechanism of Sanliangsan Lipid-Lowering in treating hyperlipidemia: insights from network pharmacology and molecular docking

Background and ObjectiveThis study aimed to identify the active ingredients, key targets, and signaling pathways of Sanliangsan Lipid-Lowering (SLL) in the treatment of hyperlipidemia (HLP) using network pharmacology, and to further clarify the material basis and mechanism responsible for its lipid-lowering efficacy. MethodsAll active ingredients of SLL were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), followed by the identification of target proteins corresponding to each active ingredient. Target genes associated with these target proteins were obtained from the Uniprot database, with duplicate genes excluded to generate the predicted targets of the active ingredients.Cytoscape was utilized to construct the "Herb-Active Ingredient-Predicted Target" network for SLL. Targets related to hyperlipidemia (HLP) were retrieved from the GeneCards, OMIM, and DrugBank databases using "hyperlipidemia" as the keyword. The intersection of the predicted targets of SLL active ingredients and HLP-related targets was defined as the potential therapeutic targets of SLL for HLP. Utilizing Cytoscape 3.9.1 software, the top 20 targets with the highest Degree values were selected to construct the "Herb-Active Ingredient-Target-Disease" network, (esignated as the "Herb-Active Ingredient-Target Network of SLL against HLP." The STRING database was employed to build a protein-protein interaction (PPI) network of the potential therapeutic targets, which was subsequently analyzed using the Network Analysis, CytoNCA, and CytoHubba plugins in Cytoscape to identify the top 10 key targets. The Metascape platform was used for Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the key targets, and the Bioinformatics online tool was applied to visualize the analytical results. Furthermore, AutoDock Tools 1.5 software was utilized to perform molecular docking between the active ingredients and key targets, thereby validating the results of the network pharmacology analysis. ResultsA total of 115 active ingredients and 255 corresponding predicted targets of SLL were screened from the TCMSP database. Additionally, 2106 HLP-related targets were retrieved from the aforementioned databases, and 140 common targets (potential therapeutic targets) were identified through intersection analysis. From these common targets, the top 20 with the highest Degree values were selected for the construction of the "Active Ingredient-Potential Target-Disease" network. Network analysis revealed that kaempferol, quercetin, and formononetin were the top three active ingredients in terms of content, while tumor necrosis factor (TNF), interleukin-6 (IL6), protein kinase B1 (AKT1), interleukin-1{beta} (IL1B), prostaglandin-endoperoxide synthase 2 (PTGS2), peroxisome proliferator-activated receptor {gamma} (PPARG), caspase 3 (CASP3), and hypoxia-inducible factor 1 (HIF1A) were the targets associated with the largest number of active ingredients. The PPI network consisted of 140 nodes and 3,207 edges. By using the CytoHubba plugin for analysis, six key targets were identified: AKT1, TNF-, IL-1 {beta}, IL6, PPARG and PTGS2. The GO functional enrichment analysis revealed 30 entries, which encompassed 10 biological processes (such as positive regulation of transcription by RNA polymerase II), 10 cellular components (such as extracellular space), and 10 molecular functions (such as transcription coactivator binding). Additionally, 10 KEGG signaling pathways were identified, including Lipid and atherosclerosis, the AGE-RAGE signaling pathway in diabetic complications, and Fluid shear stress and atherosclerosis. The findings indicated that SLL exerts a therapeutic effect on HLP by regulating multiple signaling pathways. Molecular docking results demonstrated that the binding energies of the three core ingredients--kaempferol, quercetin, and formononetin--with all key targets were less than -5.0 kJ/mol, with the lowest binding energy (-10.1 kJ/mol) observed between formononetin and PTGS2, indicating a strong binding affinity between these two molecules. ConclusionThis study identified the potential active ingredients, key targets, and core signaling pathways of SLL in treating HLP, confirming that SLL exerts its lipid-lowering effect through a synergistic "multi-component, multi-target, multi-pathway" mechanism. It provides a theoretical basis for further experimental validation and clinical application of SLL in managing HLP.

molecular biology↗

bioRxiv2025

A Benchmark of Evo2 Genomic AI Models for Efficient and Practical Deployment

The rapid advancement of DNA foundation language models has brought about a transformative shift in genomics, allowing for the deciphering of intricate patterns and regulatory mechanisms embedded within DNA sequences. The genomic foundation model Evo2 demonstrates remarkable capabilities in decoding DNA functional patterns through cross-species pretraining. However, despite the great potential of Evo2 in basic genomics research, there is currently no clear and systematic guidance on its specific application scenarios, performance, and optimization directions in the field of tumor genomics, and its performance dependency on specialized hardware (such as FP8 precision on H800 GPUs) has not been empirically benchmarked. Here, we present a focused validation of Evo2 using two independent cancer genomic datasets (Bladder Urothelial Carcinoma and Ovarian Cancer), we tested the downstream tasks of Evo2, including the prediction of tumor pathogenic variants and the prediction of mutational effects, and compared its performance on A100 and H800 GPUs. The results show that critical importance of FP8 precision, enabling the H800 to achieve a 4x faster inference speed than the A100 with stable accuracy (AUC 0.88-0.95). The 7B-parameter model emerged as the top performer, whereas the 40B model experienced a severe performance drop (AUC to 0.48) on non-FP8 hardware like the A100. These findings empirically validated Evo2s hardware specifications and provided practical insights for researchers implementing the model with similar computational resources. Futhermore, our findings provide a framework for the application and optimization of downstream tasks of the DNA language model Evo2 in cancer, and can guide researchers in effectively applying it in genomic studies. Key PointsO_LIHardware Precision Impact: FP8 precision on H800 GPUs is critical for Evo 2s performance, enabling 4x faster inference than A100 (without FP8 support) while maintaining high accuracy (AUC 0.88-0.95). C_LIO_LIModel Scale Optimization: The 7B-parameter model outperformed larger variants (e.g., 40B), which suffered severe accuracy drops (AUC as low as 0.48) on non-FP8 hardware, highlighting a balance between efficiency and performance. C_LIO_LIPractical Guidelines: We provide a framework for deploying Evo 2 in cancer genomics, including hardware recommendations, dataset curation, and downstream task optimization--valuable for researchers with varied computational resources. C_LI

genomics↗

bioRxiv2025

Housekeeping genes are enriched in rheumatoid arthritis-related genes

Housekeeping genes are often considered to be stably expressed in any tissue, cell, or disease state, and the relationship between housekeeping genes and rheumatoid arthritis (RA) has never been systematically analyzed. Therefore we aimed to explore whether housekeeping genes are abnormally expressed in RA by analyzing 15 datasets that were filtered from 140 gene expression profiles. By cumulative hypergeometric test, for 73.3% (11/15) of the datasets, housekeeping genes were significantly (p < 0.05) enriched in differentially expressed genes (DEGs) between RA patients and healthy controls. Using the relative enrichment factor (Re) as an effect size, a Meta-analysis strategy was adopted to integrate the individual results. The logarithmic Re estimation for multiple studies was 0.48 with the 95% confidence interval ranging from 0.17 to 0.80. The combined effect size was significantly higher than that of the randomized case (p = 0.0012) suggesting a consistent result with the hypergeometric test. The robustness of results was verified by sensitivity and subgroup analyses. Furthermore, the expression fluctuation of housekeeping genes was higher in RA patients than healthy controls and the correlation between DNA methylation and gene expression of housekeeping genes was significantly higher than that of non-housekeeping genes, which indicates the potential epigenetic regulation relationship between housekeeping genes and the pathogenesis of RA. This study identified for the first time a significant enrichment of housekeeping genes in DEGs of RA, which might provide new perspectives for understanding the potential role of housekeeping genes in RA.

bioinformatics↗

bioRxiv2024

Discovery and Biosynthesis of Sulfenicin and Its New-to-Nature Acylsulfenic Acid Functional Group

Lifes organic molecules are built with diverse functional groups that enable biology by fine tuning intimate connections through time and space. As such, the discovery of new-to-nature functional groups can expand our understanding of the natural world and motivate new applications in biotechnology and biomedicine. Herein we report the genome-aided discovery of sulfenicin, a novel polyketide-nonribosomal peptide hybrid natural product from a marine Streptomyces bacterium bearing a unique acylsulfenic acid functionality. Through a series of heterologous biosynthesis, functional genetics, and enzymatic reconstitution experiments, we show that this previously described synthetic functional group is biologically assembled by a set of enzymes from both primary and secondary metabolism, including a novel flavin-dependent S-hydroxylase that hydroxylates a thiocarboxylic acids sulfur atom. While the sulfenicin biosynthetic gene cluster is presently without parallel in public databases, acylsulfenic acid-encoding enzymes are widely distributed in bacterial genomes, implying that this labile functional group may similarly have a broad distribution among specialized metabolites.

biochemistry↗

bioRxiv2024

Chromosome-level genome assembly of autotetraploid Selenicereus megalanthus and gaining genomic insights into the evolution of trait patterning in diploid and polyploid pitaya species

Yellow pitaya (Selenicereus megalanthus, 2n=4x=44) breeding remains severely hindered due to lacking a reference genome. Here we report yellow pitayas high-quality chromosome-level genome assembly and link the phenotypic trait with genomic data, based on Hi-C, ATAC, and RNA-seq data of specific tissues. We declared yellow pitaya as an autotetraploid with a 7.16 Gb genome size (harboring 27,246 high confidence genes) and majorly evolved from diploid ancestors, which remains unknown. Beyond generating the genome assembly, we explored the 3D chromatin organization which revealed insights into the genome, compartments A (648 and 519), compartments B (728 and 1064), topologically associated domains-TADs (3376 and 2031), and varying numbers of structural variations (SVs) in diploid and polyploid pitaya species, respectively. Overall, TAD boundaries were enriched with the motifs of AP2, WRKY18/60/75, MYB63/116, PHL2, and GATA8 in both pitaya species. By linking the open chromatin genomic structure to function, we identified the major changes in betalains biosynthesis pathway in diploid and polyploid pitaya. Moreover, the higher genetic expression of SmeADH1 [Chr11, Compartment A (135400000 - 135500000), genes inside the TAD region (135480000 - 135520000)], and lower expression of HuDOPA [Chr11, Compartment A (87100000 - 87200000), genes inside the TAD region (87160000-87200000)] acts as a key regulator of yellow and red color on the pericarp of polyploid and diploid pitaya, respectively. In addition, higher expression of HuCYP76AD1 genes in diploid pitaya and lower expression of SmeCYP76AD1 in polyploid pitaya potentially created the difference in the oxidase process that led to the production of betacyanin and betaxanthin, respectively. Furthermore, our results revealed not only the type of motifs that play a potential role in trait patterning but we also further uncovered that motif count in TAD-boundaries may impact the gene expression within the TAD regions of diploid and polyploid pitaya. Our valuable genomic resource and comparison of 3D euchromatin architecture of diploid and polyploid pitaya species will not only aid in the advancement of molecular breeding efforts but also offer insights into the organization of genomes, SVs, compartmentalization (A and B), and TADs, which have the potential to strengthen the idea of TADs-based trait improvement to achieve global food security.

plant biology↗

bioRxiv2024

Generative Modelling of Oncogene-carrying Extrachromosomal Circular DNA Biogenesis and Dynamics in Cells

Extrachromosomal circular DNAs (ecDNA) are focal gene amplifications frequently associated with cancer development and often indicating a poor prognosis. To understand the early dynamics of oncogene-carrying ecDNAs, we previously developed CRISPR-C, a tool for precise ecDNA generation by deleting specific chromosomal regions. Here, we adapted CRISPR-C to recreate tumor ecDNAs. This method also allowed us to enhance ecDNA generation efficiency by directly delivering Cas9 protein and sgRNAs as a ribonucleoprotein complex. By using the modified CRISPR-C, we successfully generated ecDNAs carrying oncogenes (EGFR, CDK4, MDM2, MYC, MYCN, FGFR2, ABCB1, and DHFR) in various human cell types. Furthermore, we demonstrated that our method could generate chimeric ecDNAs composed of target sequences from distant intra or inter-chromosomal regions. Using these generative ecDNA cell models, we studied the oncogene ecDNA expression and stability. The MDM2 expression was increased after CRISPR-C, while CDK4 was decreased indicating genomic-context dependent effect. The copy number of CRISPR-C generated CDK4 was ecDNA increased in cells after a long period of treatment with the CDK4 inhibitor palbociclib. Unlike CDK4, the CRISPR-C generated ABCB1 ecDNA was unstable in cells under normal growth conditions, but is stably retained when the cells were treated with colcemid, a recognized substrate for ABCB1. We thus provide valuable tools and an attractive platform for studying ecDNA biogenesisy and in vitro drug screening on ecDNA stability.

cancer biology↗

bioRxiv2024

SHP2-triggered endothelium activation fuels estradiol-independent endometrial sterile inflammation

Endometrial hyperplasia (EH) is a common gynecological disease primarily driven by excess estrogen. How endometrial sterile inflammation regulates EH remains unclear. First, we found the upregulation of SHP2 in endometrial endothelial cells from patients with EH by scRNA-Seq. SHP2 promoted inflammatory activation of endothelial cells, which promoted macrophage transendothelial migration. Subsequently, IL1{beta} and TNF from macrophages gave a feedforward loop to enhance endothelial cell activation and result in more IGF1 secretion, thereby sustaining sterile endometrial inflammation and facilitating endometrial epithelial cell proliferation even after estradiol withdrawal. Mechanistically, results of bulk RNA-Seq and phosphoproteomic analyses showed that endothelial SHP2 dephosphorylated RIPK1Y380 after estradiol stimulation. This event promoted activator protein 1 (AP-1) activation, instigating inflammation and increased CXCL10, CXCL13, COX2 and IGF1 secretion. Furthermore, targeting SHP2 by SHP099 or endothelial-specific SHP2 deletion alleviated EH progression in mice. Collectively, our findings demonstrate that SHP2 mediates the transition of endothelial activation, from estradiol-driven short inflammation to macrophage-amplified continuous sterile inflammation. Targeting chronic sterile inflammation mediated by endothelial cell activation is a promising strategy for non-hormonal intervention in EH.

molecular biology↗

bioRxiv2023

The essential genome of Xanthomonas citri

Citrus canker, caused by the bacterium Xanthomonas citri subsp. citri, is a devastating disease with significant economic implications for the citrus industry worldwide. Understanding the molecular basis of Xanthomonas cell cycle and identifying therapeutic targets is crucial for effective disease management. In this study, we employed hyper-saturated transposon mutagenesis combined with high-throughput sequencing to determine the essential features of the Xanthomonas citri genome at [~]7-bp resolution. Our analysis revealed 525 essential genes, 181 high fitness cost genes, 7 small non-coding RNAs, 25 transfer RNAs, 4 ribosomal RNAs, and the origin of replication. Notably, the use of a newly designed Tn5 transposon with an outward pointing lac promoter significantly reduced false positives caused by polar effects associated with conventional transposons. Functional enrichment analysis showed that essential genes were significantly enriched in processes related to ribosome biogenesis, energy production and conversion, and membrane metabolism. Interestingly, the distribution of essential genes in X. citri showed similarities to that of the model organism E. coli, suggesting a conserved mode of genome organization that influences transposon accessibility. Our comprehensive analysis provides valuable target genes for potential therapeutic interventions against citrus canker and other related plant diseases.

microbiology↗

bioRxiv2023

Predicting Gene Spatial Expression and Cancer Prognosis: An Integrated Graph and Image Deep Learning Approach Based on HE Slides

Interpreting the tumor microenvironment (TME) heterogeneity within solid tumors presents a cornerstone for precise disease diagnosis and prognosis. However, while spatial transcriptomics offers a wealth of data, ranging from gene expression and spatial location to corresponding Hematoxylin and Eosin (HE) images, to explore the TME of various cancers, its high cost and demanding infrastructural needs significantly limit its clinical application, highlighting the need for more accessible alternatives. To bridge this gap, we introduce the Integrated Graph and Image Deep Learning (IGI-DL) model. This innovation, a fusion of Convolutional Neural Networks and Graph Neural Networks, is designed to predict gene spatial expression using HE images. The IGI-DL model outperforms its predecessors in analyzing colorectal cancer (CRC), breast cancer, and cutaneous squamous cell carcinoma (cSCC) by leveraging both pixel intensity and structural features in images. Significantly, across all cancer types, the IGI-DL model enhances the mean correlation of the top five genes by an average of 0.125 in internal and external test sets, rising from 0.306 to 0.431, surpassing existing state-of-the-art (SOTA) models. We further present a novel risk score derived from a super-patch graph, where gene expression predicted by IGI-DL serves as node features. Demonstrating superior prognostic accuracy, this risk score, with a C-index of 0.713 and 0.741 for CRC and breast cancer, supersedes traditional HE-based risk scores. In summary, the approach augments our understanding of the TME from the aspect of histological images, portending a transformation in cancer prognostics and treatment planning and ushering in a new era of personalized and precision oncology.

bioinformatics↗

bioRxiv2023

A Resource of Gene Expression Data from a Multiethnic Population Cohort of Induced Pluripotent Cell-Derived Cardiomyocytes

Induced pluripotent stem cells (iPSCs), upon differentiation into somatic cell types, offer the ability to model the genetic states of tissues in the individuals from whom the iPSCs were derived.1 A prior study used a multiethnic cohort of healthy individuals to derive iPSCs and iPSC-hepatocytes and perform gene expression and expression quantitative trait locus (eQTL) analyses, identifying causal genes and variants linked to blood lipid levels.2 We sought to use this cohort of iPSC lines to generate a similar resource with iPSC-cardiomyocytes (iPSC-CMs) and make the results available to the community.

genomics↗

bioRxiv2022

Comparison of DNA targeting CRISPR editors in human cells

Profiling and comparing the performance of current widely used DNA targeting CRISPR systems provide the basic information for the gene-editing toolkit and can be a useful resource for this field. Herein we made a parallel comparison between the recently reported miniature Cas12f1 and the widely used Cas12a and Cas9 nucleases in mammalian cells. The results revealed that as a CRISPRa activator, Un1Cas12f1 could induce gene expression with a comparable level to these of Cas12a and Cas9, while as a cleaving editor, Cas12f1 exhibited similar properties to Cas12a, like high specificity and dominantly induced deletions over insertions, but with less activity. In contrast, wild-type SpCas9 showed the highest activity, lowest specificity, and induced balanced deletions over insertions. Thus, Cas12f1 is recommended for gene-activation-based applications, Cas12a is for therapy applications, and wild-type Cas9 is for in vitro and animal investigations. The comparison provided the editing properties of current widely used DNA-targeting CRISPR systems for the gene-editing field.

synthetic biology↗

bioRxiv2022

"Double-Effect" strategy against Triple-Negative Breast Cancer via a synergistic therapy of Magneto-mechanical Force enhancing NIR-II Hypothermal Ablation

Triple-negative breast cancer (TNBC) is a form of breast cancer that is more aggressive and harder to treat than others, with a higher probability of relapse. Its highly efficient capabilities for migrating and invading other parts of the body together with the current lack of clinically established effective therapies account for a low survival rate. Thus, we propose the in-tandem use of two complementary therapeutic routes to effectively combat TNBC. Herein, a versatile magnetic-photothermal converter (MPC) is elaborately designed via integrating zinc-doped ferrite nanoparticles and polyethene glycol, synergistically enhanced through magneto-mechanical force (MMF) and near-infrared-II (NIR-II) hypothermal ablation, thereby displaying excellent therapeutic efficiency. Their combined use, which is less aggressive to the human body compared to conventional chemotherapeutic approaches, results in the splendid suppression of TNBC migration and invasion. Remotely controlling the MPCs by an external magnetic stimulus, results in cellular MMF effects that cause direct mechanical destruction to the cancer cell membrane, leading to its necrosis. Furthermore, the MMF disrupts intracellular lysosomes, thereby triggering the release of large amounts of protein hydrolases, which induce intracellular oxidative stress, and accelerate the induction of apoptosis. Complementing the therapeutic approach based on MMF, the excellent photothermal performance of the MPC in the NIR-II region (1064nm) is exploited to enable effective hypothermal ablation of the tumours, which can be achieved in deep tissue layers. The proposed multifunctional nanocomposites, together with the demonstrated "double effect" therapeutic approach, hold significant potential to pave the way for future cutting-edge weapons against the dreadful TNBC.

cancer biology↗

bioRxiv2022

CRISPR/Cas9 screens implicate RARA and SPNS1 in doxorubicin cardiotoxicity

Doxorubicin (DOX) is an efficacious chemotherapy compound used to treat various cancers which elicits severe side effects, including heart failure. Uptake of DOX by cardiomyocytes causes metabolic dysfunction and cell death but causal mechanisms remain largely undefined. We applied genome-wide CRISPR/Cas9 knockout screens to discover genetic modifiers of DOX-induced cardiomyocyte cell death, and independently, DOX uptake and clearance. Both screens discovered known and novel factors. In cell death screens and validation studies, loss of retinoic acid receptor- (RARA) predisposed cardiomyocytes to DOX-mediated cell death. Conversely, RARA activation reduced DOX cytotoxicity in wild type cardiomyocytes. RNA-Seq analysis revealed that whilst DOX caused large-scale suppression of metabolic and mitochondrial gene expression, RARA activation mitigated this effect. In DOX accumulation screens, an essential role for lysosomes in DOX clearance was observed. Loss of Sphingolipid Transporter 1 (SPNS1) led to DOX hyperaccumulation, suppression of autophagy, increased DNA damage, and increased cell death. Hence, SPNS1 plays a key role in buffering against DOX accumulation and toxicity. Collectively, our study nominated hundreds of drug-gene interactions, providing a springboard for exploration of causal mechanisms, and a technical framework for future screening campaigns.

cell biology↗

bioRxiv2022

Multiple omic investigations of freeze tolerance adaptation in the aquatic ectothermic vertebrate, the Amur sleeper

Freeze tolerance is an amazing overwintering strategy that enables ectotherms to occupy new niches and survive in cold climates. However, the genetic basis underpinning this ecologically relevant adaptation is largely unknown. Amur sleeper is the only known freeze-tolerant fish species that can overwinter with its entire body frozen in ice. Here, we sequenced the chromosome-level genome of the Amur sleeper and performed comparative genomic, transcriptomic, and metabolomic analyses to investigate this remarkable adaptation. Phylogenetic analyses showed that the Amur sleeper diverged from its close relative with no cold hardiness about 15.07 million years ago and revealed two unusual population expansions during the glacial epochs. Integrative omics data identified a synchronous regulation of genes and metabolites involved in hypometabolism and cellular stress response, and several related genes showed strong evidence of accelerated evolution and positive selection. Potential evolutionary innovations that might aid in freezing survival were found to be associated with the dynamic rearrangement of the cytoskeleton to maintain cell viability, redistribution of water and cryoprotectants to limit cell volume reduction, and inhibition in nerve activity to facilitate dormancy, demonstrating a coordinated evolution for this complex adaptation. Overall, our work provides valuable resources and opportunities to unveil the genetic basis of freeze tolerance adaptation in ectothermic vertebrates.

evolutionary biology↗

bioRxiv2021

Cell free extrachromosomal circular DNA is common in human urine

Cell free extrachromosomal circular DNA (eccDNA) is evolving as a potential biomarker in liquid biopsies for disease diagnosis. In this study, an optimized next generation sequencing-based Circle-Seq method was developed to investigate urinary cell free eccDNA (ucf-eccDNA) from 28 adult healthy volunteers (mean age = 28, 19 males/ 9 females). The genomic distributions and sequence compositions of ucf-eccDNAs were comprehensively characterized. Approximately 1.2 million unique ucf-eccDNAs are identified, covering 14.9% of the human genome. Comprehensive characterization of ucf-eccDNAs show that ucf-eccDNAs contain higher GC content than flanking genomic regions. Most eccDNAs are less than 1000 bp and present four pronounced peaks at 203, 361, 550 and 728 bp, indicating the association between eccDNAs and the numbers of intact nucleosomes. Analysis of genomic distribution of ucf-eccDNAs show that eccDNAs are found in all chromosomes but enriched in chromosomes i.e. chr.17, 19 and 20 with high density of protein-codding genes, CpG islands, SINE and simple repeat elements. Lastly, analysis of sequence motif signatures at eccDNA junction sites reveal that direct repeats (DRs) are commonly found, indicating a potential role of DRs in eccDNA biogenesis. This work underscores the deep sequencing analysis of ucf-eccDNAs and provides a valuable reference resource for exploring potential applications of ucf-eccDNA as diagnostic biomarkers of urogenital disorders in the future. Significance StatementExtrachromosomal circular DNA (eccDNA) is an important genetic element and a biomarker for disease diagnosis and treatment. In this study, we conduct a comprehensive characterization of urinary cell free eccDNA (ucf-eccDNA) in 28 heathy subjects. Over one million ucf-eccDNAs are identified. Ucf-eccDNAs are characterized as high GC content. The size of most ucf-eccDNAs is less than 1000 bp and enriched in four peaks resembling the size of single, double, triple, and quadruple nucleosomes. The genomic distribution of ucf-eccDNAs is enriched in generic regions, protein-coding genes, Alu, CpG islands, SINE and simple repeats. Sequence motif analysis of ucf-eccDNA junctions identified simple direct repeats (DRs) commonly presented in most eccDNAs, suggesting potential roles of DRs in eccDNA biogenesis.

genomics↗