Biology subjects

Zheng, G.

Publications and source records attributed to Zheng, G..

At least 19 recordsLinked to original sources

bioRxiv2026

DNA methylation reveals molecular heterogeneity and urate excretion-associated subtypes of gout

Background: The molecular heterogeneity among gout patients remains largely unexplored, hindered the precise treatment for gout. Common indices for gout subtyping are cumbersome to measure, resulting in poor patient compliance. Methods: We elucidated the molecular heterogeneity of gout and developed a simple, reliable classification method for gout subtypes based on genome-wide DNA methylation, to facilitate individualized treatment. Genome-wide DNA methylation profiling was conducted in two independent cohorts, comprising a discovery cohort (n = 108) and a validation cohort (n = 100) representing four clinical gout subtypes. Results: We identified two gout subgroups associated with the fractional excretion of uric acid (FEUA) but not with 24-hour urinary uric acid levels (UUE) based on unsupervised clustering of whole-genome DNA methylation profiles, highlighting the contribution of epigenetic regulation to molecular heterogeneity in urate metabolism. Enrichment analysis links FEUA-associated subtypes to renal cell types, calcium related pathways and extended to the circulating immune compartment, with neutrophil- versus memory B cell-skewed leukocyte composition. A methylation-based classification model using 18 LASSO-selected CpGs with an XGBoost classifier effectively distinguished patients with high and low uric acid excretion, achieving excellent predictive performance (training cohort: AUC = 0.96, AP = 0.91; validation cohort: AUC = 0.86, AP = 0.85), outperforming the published model with clinical characteristics and SNPs. The signature site-associated genes NEK1 and TRPS1 display significant expression differences among urate-stratified patients and immune cells groups. TRPS1 may affect the AP-1/NF-{kappa}B inflammatory programme. Conclusions: These findings reveal distinct DNA methylation signatures underlying gout heterogeneity and demonstrate the feasibility of DNA methylation markers for gout subtype classification. The proposed methylation-based model provides a promising approach for personalized management of gout.

bioinformatics↗

bioRxiv2026

Click alginate cryogel for real-time gastric pH monitoring

Gastric acidity shapes mucosal injury in reflux disease, peptic ulcer, and gastritis, yet is almost never measured. Acid-suppressive therapy, taken by approximately 40% of elderly adults, is therefore titrated on symptoms alone. A gastric sensor must hold onto its reporter in a highly acidic protease-rich environment, conditions that destabilize ionically crosslinked hydrogels and leach physically entrapped dyes. Click alginates, established in biomechanics and drug delivery but not as sensors, meet this requirement with a single chemistry: bioorthogonal tetrazine-norbornene crosslinks are inert to acid and proteases, and excess norbornene from crosslinking become the anchoring site for the pH-sensitive reporter, so network and reporter are installed by the same mechanism. Cryogelation adds macroporosity for rapid gastric fluid influx. A screen identifies IRDye 680RD as the only near-infrared dye responsive across the targeted pH 2-5. Dye release stays below 1.5% in simulated gastric and intestinal fluids, and the pH response remains active after nine months of storage. In rats, the orally administered NIR fluorescent cryogel resolves pH 2.0 from pH 5.0 transabdominally, and discriminates esomeprazole- from saline-treated animals, without plasma fluorescence. Photoacoustic imaging points toward detection at translationally relevant depths, establishing covalently functionalized cryogels as a general sensing platform for hostile physiological environments.

bioengineering↗

bioRxiv2026

Multi-parametric NIR-II fluorescence perfusion imaging towards quantitative stroke evaluation

Preclinical stroke research is severely hampered by the lack of high-throughput, quantitative perfusion imaging tools capable of bridging the gap between functional hemodynamics and structural injury. The emerging second near-infrared (NIR-II) fluorescence imaging offers superior spatial resolution and tissue penetration, but its utility remains restricted by a lack of standardized analysis protocols and inability to resolve in-depth infarct regions. Here, we introduce FIMPA, an integrated analytical framework for standardized, multi-parametric stroke evaluation based on NIR-II fluorescence perfusion imaging. FIMPA systematically processes the image sequence through motion correction and atlas registration to generate an anatomically aligned library of 125 vascular and hemodynamic parameters. Statistical screening identifies 67 stroke-correlated features, enabling objective, data-driven quantification of perfusion deficits. To resolve spatial infarct boundaries, we developed FIMPA-SI (FIMPA Stroke Index), a deep learning-based index utilizing a ViT-UNETR framework. By leveraging self-supervised pre-training with MRI data, FIMPA-SI suppresses dominant vascular signals to translate multi-parametric dynamics into anatomically precise stroke severity maps. Validated in tMCAO mice, FIMPA-SI achieves high spatial concordance with MRI and significantly outperforms conventional laser speckle contrast imaging and single-parameter metrics. FIMPA provides a robust solution for accelerating preclinical therapeutics and advancing optical neuroimaging.

bioengineering↗

bioRxiv2026

Targeting cellular senescence alleviates bone marrow aging

Aging of the hematopoietic system impairs hematopoietic stem cell (HSC) function and alters bone marrow niche behavior, increasing susceptibility to anemia, infections, and hematologic malignancies. Here, pharmacologic clearance of senescent cells with the PROTAC compound 753b simultaneously targeting BCL-xL and BCL-2 reverses key secretory, transcriptional, and functional hallmarks of hematopoietic aging with low toxicity, restoring balanced lineage output. Single-cell RNA sequencing further demonstrates that 753b treatment attenuates aging-associated transcriptional signatures in HSCs, while selectively eliminating senescent, pro-survival niche cells without grossly perturbing niche composition. Functionally, 753b suppresses pro-inflammatory cues from both niche and hematopoietic cells including those emanating from neutrophil progenitors, rebalancing global bone marrow secretory ecosystem across stromal and hematopoietic compartments. Collectively, we identify 753b-induced senescent cell clearance as a powerful strategy to rejuvenate aged hematopoiesis and re-establish homeostatic communication between HSCs and their microenvironment, with implications for mitigating age-related hematologic dysfunction and improving hematologic health in older individuals.

cell biology↗

bioRxiv2026

Polystyrene microplastics uptake drives Inflammatory, Epitranscriptomic, and Metabolic Reprogramming in Human aortic endothelial cells

Microplastics (MPLs) are pervasive environmental pollutants increasingly linked to adverse human health outcomes, including atherosclerosis. However, the underlying mechanisms remain poorly understood. Human aortic endothelial cells (HAECs), which line the inner surface of blood vessels, play a critical role in maintaining vascular homeostasis and in the development of atherosclerosis. This study demonstrates that polystyrene microplastics enter HAECs through clathrin-mediated endocytosis and macropinocytosis and subsequently co-localize with mitochondria and lysosomes. Exposure to MPLs induced coordinated transcriptional, epitranscriptomic, and metabolomic reprogramming in HAECs. Transcriptomic analysis revealed disruption of mitochondrial genes and activation of inflammatory pathways with the response of the NF-{kappa}B pathway being particularly prominent. Mass spectrometry analysis of RNA modification further identified significant remodeling of the epitranscriptomic landscape, highlighted by increased 1-methyladenosine (m1A) modification and reciprocal regulation of its associated enzymes (TRMT61A upregulation and ALKBH3 suppression), along with alterations in other RNA modifications such as m3C, pseudouridine ({Psi}), m5C, and m7G. Comparative analysis of transcriptomic profiles from human atherosclerotic plaques revealed shared dysregulated pathways in vascular regulation and cellular signaling. Metabolomic profiling further showed extensive remodeling of lipid metabolic networks associated with oxidative stress and inflammation. Together, these findings suggest that MPLs exposure may disrupt endothelial function and pose a potential risk to human cardiovascular health. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/737624v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@2ad601org.highwire.dtl.DTLVardef@47f041org.highwire.dtl.DTLVardef@ee45cdorg.highwire.dtl.DTLVardef@128d6d5_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2026

Exposure to perfluorooctanoic acid accelerates Drosophila melanogaster juvenile development and disrupts mitochondrial metabolism

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with poorly understood sublethal effects on insects. Perfluorooctanoic acid (PFOA), one of the most widely distributed legacy PFAS is increasingly recognized for altering organismal physiology beyond traditional toxicity endpoints. Here, we use the fruit fly Drosophila melanogaster as a model to examine how PFOA exposure during larval (juvenile) development reshapes insect life-history progression and metabolic homeostasis. Our studies reveal that at environmentally relevant concentrations (nM to low {micro}M), PFOA induces precocious expression of developmentally-regulated genes and leads to metabolic changes that persist into adulthood. At higher concentrations used to probe mechanism, PFOA accelerates larval development, disrupts mitochondrial membrane potential, and increases whole-organism metabolic heat production - results that suggest altered mitochondrial energetic efficiency. Consistent with this tradeoff, PFOA-exposed larvae that develop faster under permissive conditions exhibit heightened sensitivity to environmental stressors, including elevated temperature and reduced food hydration. Together, these findings demonstrate that PFOA disrupts metabolic and developmental processes in a dose- and context-dependent manner, highlighting sublethal effects that may influence insect resilience under environmental stress. SYNOPSIS STATEMENTHere we describe how PFOA alters the growth, development, and metabolism of the fruit fly Drosophila melanogaster. Specifically, we find that PFOA accelerates Drosophila juvenile growth while also rendering exposed larvae sensitive to environmental stress. These observations suggest that widespread PFOA contamination may impair the developmental fitness of insect populations.

pharmacology and toxicology↗

bioRxiv2026

VarDCL: A Multimodal PLM-Enhanced Framework for Missense Variant Effect Prediction via Self-distilled Contrastive Learning

Missense variants are a common type of genetic mutation that can alter the structure and function of proteins, thereby affecting the normal physiological processes of organisms. Accurately distinguishing damaging missense variants from benign ones is of great significance for clinical genetic diagnosis, treatment strategy development, and protein engineering. Here, we propose the VarDCL method, which ingeniously integrates multimodal protein language model embeddings and self-distilled contrastive learning to identify subtle sequence and structural differences before and after protein mutations, thereby accurately predicting pathogenic missense variants. First, leveraging sequence and structural information before and after mutations, VarDCL generates sequence-structural multimodal features via different language models. It incorporates both global and local perspectives of feature embeddings to provide the model with dynamic, multimodal, and multi-view input data. Additionally, a Self-distilled Contrastive Learning (SDCL) module was proposed to enable more effective information integration and feature learning, enhancing the models ability to detect sequence and structural changes induced by mutations. Within this module, the multi-level contrastive learning framework excels at capturing information differences before and after mutations within the same modality; meanwhile, the feature self-distillation mechanism effectively utilizes high-level fused features to guide the learning of low-level differential features, facilitating information interaction across different modalities. The VarDCL framework not only ensures the models capacity to learn dynamic changes pre- and post-mutation but also significantly improves cross-modal information interaction between sequence and structure, thereby remarkably boosting the models performance in distinguishing pathogenic mutations from benign ones. To validate the effectiveness of VarDCL, extensive experiments were conducted. The ablation study demonstrates that all key components of VarDCL contribute significantly. On an independent test set containing 18,731 clinical variants, VarDCL achieved an AUC of 0.917, an AUPR of 0.876, an MCC of 0.690, and an F1-score of 0.789, outperforming 21 state-of-the-art existing methods. Benchmark analysis shows that VarDCL can be utilized as an accurate and potent tool for predicting missense variant effects.

bioinformatics↗

bioRxiv2026

Endocrine-metabolic decoupling drives stress vulnerability in dystrophin deficiency

Skeletal muscle orchestrates systemic metabolism, dynamically coordinating glucose uptake and fuel use to match energy demand. In Duchenne muscular dystrophy, loss of dystrophin is associated with altered metabolic regulation. In the mdx mouse, we show that physiological stress reveals impaired coordination between insulin and stress responses: glucocorticoid signalling increases without a proportional rise in insulin secretion, resulting in systemic hyperglycaemia despite preserved capacity for muscle glucose uptake. These data support a multi-tissue dystrophinopathy associated with altered endocrine-metabolic coordination. Skeletal muscle glycogen is elevated and incompletely mobilised under stress. The heart maintains high glucose uptake, whereas the brain exhibits reduced uptake, highlighting tissue specific differences in metabolic response. Acute insulin supplementation improves systemic glucose control and restores stress-induced behavioural deficits. Likewise, empagliflozin-mediated glucose offloading reduces stress-associated blood glucose spikes and is associated with improved muscle function to levels comparable with standard care prednisolone. These findings identify impaired coordination of endocrine and metabolic responses during stress as a contributor to metabolic vulnerability in DMD and suggest that modulating insulin availability or glucose flux can improve systemic metabolic control.

systems biology↗

bioRxiv2026

The combination of BCL-xL PROTAC and mTOR inhibitor sensitizes pancreatic ductal adenocarcinoma to KRASG12D inhibitor treatment by enhancing apoptosis induction

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a five-year survival rate of approximately 13%, partly because of limited treatment options and resistance to therapies. Although the recently discovered KRAS G12D inhibitor MRTX1133 has shown promise for PDAC treatment in preclinical studies, its clinical efficacy as a single agent is expected to be limited, as is the case with KRAS G12C inhibitors. Therefore, in this study, we evaluated potential combination strategies to enhance the therapeutic effect of MRTX1133. We rationally combined MRTX1133 with the BCL-xL proteolysis-targeting chimera (PROTAC) DT2216 and the mTOR inhibitor everolimus, which significantly potentiated the anti-tumor activity of MRTX1133 in multiple G12D-mutated PDAC cells in vitro by enhancing apoptosis induction. Mechanistically, MRTX1133 treatment increased BIM and decreased NOXA levels, while the combination of DT2216/everolimus was shown to simultaneously enhance BIM release and stabilize NOXA. In vivo, DT2216/everolimus combination significantly potentiated the anti-tumor activity of MRTX1133 in AsPC1 PDAC xenograft model. Furthermore, the triple combination of MRTX1133, DT2216, and everolimus effectively overcame acquired resistance to MRTX1133 in AsPC1 cells in vitro and in xenograft model. Collectively, our findings suggest that the single-agent efficacy of MRTX1133 is limited by apoptosis inhibition, and that its combination with DT2216/everolimus can enhance apoptosis and potentially overcome resistance in KRAS G12D-mutated PDAC. SIGNIFICANCEKRAS inhibitors, including KRAS G12D inhibitor MRTX1133, are promising therapeutics against KRAS-mutated pancreatic ductal adenocarcinoma (PDAC), but drug resistance limits their efficacy. Our study reveals that robust induction of apoptosis using a combination of BCL-xL PROTAC degrader and an mTOR inhibitor, significantly enhances MRTX1133 efficacy in PDAC models without increasing toxicity to normal tissues.

cancer biology↗

bioRxiv2025

DINOcell: Learning Generalizable Perturbation Effects through Self-Distillation

AO_SCPLOWBSTRACTC_SCPLOWPredicting cellular responses to therapeutics is a promising approach for novel target discovery. However, state-of-the-art computational models designed to predict perturbation effects struggle to generalize and outperform simple baselines. We present DINOcell, a weakly supervised framework that adapts self-distillation to single-cell transcriptomics for predicting perturbation effects. We demonstrate that DINOcell outperforms baselines in predicting the effects of single gene perturbations. Furthermore, DINOcell accurately predicts non-additive effects of combination perturbations, indicating its capacity to model complex genetic interactions. Finally, we show that DINOcell learns representations that capture biological signals and is a promising, generalizable approach for in silico perturbation modeling, providing a valuable tool for accelerating therapeutic target discovery.

bioinformatics↗

bioRxiv2025

Atacformer: A transformer-based foundation model for analysis and interpretation of ATAC-seq data

IntroductionChromatin accessibility profiling is an important tool for understanding gene regulation and cellular function. While public repositories house nearly 10,000 scATAC-seq experiments, unifying this data for meaningful analysis remains challenging. Existing tools struggle with the scale and complexity of scATAC-seq datasets, limiting tasks like clustering, cell-type annotation, and reference mapping. A promising solution is using foundation models adapted to specific tasks via transfer learning. While transfer learning has been applied to scRNA-seq, its potential for scATAC-seq remains underexplored. MethodsWe introduce Atacformer, a transformer-based foundation model for scATAC-seq data analysis. Unlike other models that only produce cell-level representations, Atacformer generates embeddings for individual cis-regulatory elements. Pre-trained on a large atlas of scATAC-seq experiments, Atacformer learns robust representations of genomic regulatory regions for downstream use. After pretraining, the model is fine-tuned for cell-type prediction and batch correction. We also integrated Atacformer with RNA-seq data to build a Contrastive RNA-ATAC Fine Tuning (CRAFT) model capable of cross-modal alignment and RNA imputation from ATAC data. ResultsAtacformer matches or exceeds leading scATAC-seq clustering tools in adjusted rand index and runtime, with fine-tuned models achieving top performance across datasets. It processes raw fragment files end-to-end 80% faster than existing tools while preserving biological structure. Fine-tuned on bulk BED files, it recovers cell type and assay labels with >80% accuracy. We show how the Atacformer architecture produces contextualized embeddings of individual genomic regions, which we use to identify unannotated, cell-type-specific promoter elements directly from chromatin accessibility data.

bioinformatics↗

bioRxiv2025

Aberrant splicing of MBD1 reshapes the epigenome to drive convergent myeloerythroid defects in MDS

Myelodysplastic neoplasms (MDS) feature hematopoietic deficits driven in part by transcript splicing abnormalities. Thus far, such disease-driving transcripts have been identified in association with specific splicing factor mutations. However, it remains unclear whether there also exists a set of disease-wide conserved pathological transcripts, which drive MDS independently of mutational status. Here, we characterize an MDS-associated long isoform of MBD1 (MBD1-L) as the first described member of this class of transcripts. Overexpression of MBD1-L in healthy human HSPCs recapitulates archetypal defects of MDS including deficits in erythroid differentiation and reconstitution capacity. These defects arise from an isoform-specific switching of MBD1s binding behavior, refocusing its heterochromatin-promoting activity from methylated to unmethylated CpGs and enacting broad downregulation of CpG-rich promoters as well as secondary epigenetic effects mediated by its downstream target BCOR. Remarkably, we also find that directly reversing abnormal MBD1 splicing in primary human MDS using nanoparticle-encapsulated ASOs enhances erythroid differentiation. Key pointsO_LIGlobal mis-splicing of MBD1 represents a novel gain-of-function epigenetic axis driving erythropoietic and proliferative defects in MDS. C_LIO_LIASO based depletion of pathogenic MBD1 transcripts restores erythroid differentiation, advancing RNA-based therapies for MDS. C_LI

cancer biology↗

bioRxiv2025

Neural basis of social-categorization function of language

Languages provide social-category markers that tag people as one or another social group. How does the brain sort words into different language categories as a basis of the social-categorization function of language? We addressed this issue by testing neural categorization of visual words of different writing systems in nine studies using electroencephalography, magnetoencephalography, and a repetition suppression paradigm. We showed that a neural network, including the anterior temporal, insular, orbital frontal, and ventral occipito-temporal cortices in both hemispheres, was engaged in computations of correlation distances between two words to represent intra-language similarity and inter-language difference during categorization of visual words of alphabetic and non-alphabetic languages. These processes occurred as early as 150 ms post-stimulus, recruited within-hemisphere functional connections, operated independently of words semantic meanings and pronunciations, and exhibited consistently across individuals with diverse language backgrounds. These findings highlight the neural mechanisms of language-based spontaneous neural categorization of visual words as a basis of the social-categorization function of language.

neuroscience↗

bioRxiv2025

Dual Targeting of IKKβ and NR4A1 for AML Therapy

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy with poor clinical outcomes and limited therapeutic options. Aberrant activation of the IKK{beta}-NF-{kappa}B pathway occurs in approximately 40% of AML cases and contributes to leukemogenesis. However, pharmacological inhibition of IKK{beta} has been limited by serious toxicities, including neutrophilia. Here we identify IKK{beta} and NR4A1 as critical drivers of AML progression in certain models and develop a proteolysis-targeting chimera (PROTAC) capable of degrading the proteins. Although NR4A1 has previously been described as a tumor suppressor in AML, our findings demonstrate that NR4A1 exhibits oncogenic functions in some AMLs of the (pro)monocytic lineage. Notably, elevated expression of IKK{beta} and NR4A1 in AML is associated with poor clinical outcomes, playing non-redundant oncogenic roles in AML. To therapeutically target IKK{beta} and NR4A1, we designed and synthesized a series of celastrol-based PROTACs that exploit celastrols ability to bind both IKK{beta} and NR4A1. Among these compounds, the lead A9 induces potent cytotoxicity in multiple AML cell lines and primary AML samples through cereblon E3 ligase-dependent degradation of IKK{beta} and/or NR4A1. In vivo, A9 suppresses leukemia progression in a KMT2A::MLLT3 AML mouse model without inducing neutrophilia, supporting PROTAC-mediated degradation of IKK{beta} and NR4A1 as a promising therapeutic strategy. Plain language summaryAcute myeloid leukemia (AML) is a predominant form of blood cancer with devastating consequences in both young and adult populations. Despite some advances in AML treatment over the last decade, there is still an unmet medical need to develop new drugs for difficult-to- treat AMLs. We discover that two proteins, namely IKK{beta} and NR4A1, play important roles in promoting the AML disease and could be associated with more severe AML subtypes. To target and destroy those proteins within AML cells, we employ a novel targeted protein degradation approach, which involved design, synthesis, and screening of PROTAC drugs, to discover a drug possessing pronounced AML cell killing activity by virtue of IKK{beta} and NR4A1 degradations. The drug also significantly reduces AML progression in mice without any noticeable adverse effects. Our current efforts involve more comprehensively testing the benefit of the drug (and its analogs) in a wide range of clinically relevant AML models. Key PointsO_LIIKK{beta} and NR4A1 are clinically relevant drivers of AML pathogenesis. C_LIO_LIA novel celastrol-based PROTAC can effectively degrade IKK{beta} and/or NR4A1 to potentially treat AML. C_LI

cancer biology↗

bioRxiv2025

Quiescent OXPHOS-high triple-negative breast cancer cells that persist after chemotherapy depend on BCL-XL for survival

The persistent residual tumor cells that survive after chemotherapy are a major cause of treatment failure, but their survival mechanisms remain largely elusive. These cancer cells are typically characterized by a quiescent state with suppressed activity of MYC and MTOR. We observed that the MYC-suppressed persistent triple-negative breast cancer (TNBC) cells are metabolically flexible and can upregulate mitochondrial oxidative phosphorylation (OXPHOS) genes and respiratory function ("OXPHOS-high" cell state) in response to DNA-damaging anthracyclines such as doxorubicin, but not to taxanes. The elevated biomass and respiratory function of mitochondria in OXPHOS-high persistent cancer cells were associated with mitochondrial elongation and remodeling suggestive of increased mitochondrial fusion. A genome-wide CRISPR editing screen in doxorubicin-persistent OXPHOS-high TNBC cells revealed BCL-XL gene as the top survival dependency in these quiescent tumor cells, but not in their untreated proliferating counterparts. Quiescent OXPHOS-high TNBC cells were highly sensitive to BCL-XL inhibitors, but not to inhibitors of BCL2 and MCL1. Interestingly, inhibition of BCL-XL in doxorubicin-persistent OXPHOS-high TNBC cells rapidly abrogated mitochondrial elongation and respiratory function, followed by caspase 3/7 activation and cell death. The platelet-sparing proteolysis targeted chimera (PROTAC) BCL-XL degrader DT2216 enhanced the efficacy of doxorubicin against TNBC xenografts in vivo without induction of thrombocytopenia that is often observed with the first-generation BCL-XL inhibitors, supporting the development of this combinatorial treatment strategy for eliminating dormant tumor cells that persist after treatment with anthracycline-based chemotherapy.

cancer biology↗

bioRxiv2025

Ecological Toxicity Effects of Marine Pollutants Based on Microalgal Locomotory Behavior

Understanding the ecological toxicity of marine pollutants is essential for assessing marine environmental quality and developing effective protection strategies. This study presents a novel approach using the motility of the marine microalgae as a sensitive physiological indicator for rapid toxicity assessment. Results demonstrated that both copper (0{micro}mol l-1-4.4{micro}mol l-1) and phenol (0mmol l-1-9.1mmol l-1) significantly inhibited algal locomotory behavior parameters (movement patterns, mobility, and swimming speed) within 2 hours, exhibiting clear dose-response relationships. The 2 h-EC50 values determined by logistic regression were 2.2{micro}mol l-1-2.7{micro}mol l-1 for copper and 4.5{micro}mol l-1-5.7 mmol l-1 for phenol. Notably, combined exposure showed antagonistic effects (2 h-EC50 >1 TU). The motility-based assay showed strong correlation with traditional toxicity tests (72h growth inhibition, 24-48 h Daphnia immobilization, and 96h fish mortality), while providing significant advantages in speed and sensitivity. These findings establish microalgal motility as an efficient, ecologically relevant biomarker for comprehensive marine pollutant assessment, offering great potential for environmental monitoring and risk evaluation.

ecology↗

bioRxiv2025

Microfluidic Droplet-Assisted Single-Cell Raman Sorting for High-Throughput Screening of Functional Lignin-Degrading Microbes

Lignin, a major component of plant biomass, poses significant challenges for sustainable valorization due to its structural recalcitrance. Traditional microbial screening methods are hindered by culturability limitations and time-consuming workflows. This study introduces a novel Microfluidic Droplet-assisted Single-Cell Raman sorting system (MD-SCR sorting) to address these bottlenecks. By integrating droplet microfluidics with single-cell Raman spectroscopy (SCRS), the platform enables non-destructive, high-throughput screening of lignin-degrading microbes directly from environmental samples. A deuterium tracing strategy was developed, where microbial strains were cultured in lignin media containing 30% D2O. Raman detection of C-D bond vibrations (2040-2300 cm-1) allowed in situ identification of active degraders within 12 hours. The MD-SCR system achieved precise single-cell encapsulation, cultivation, and sorting using a custom-designed three-layered microfluidic chip. Validation experiments demonstrated strong correlation (R2=0.92) between %C-D values (quantifying deuterium assimilation) and traditional shake-flask degradation efficiency. Two lignin-degrading fungi (Pleurotus ostreatus G5 and P. eryngii PB) exhibited distinct C-D peaks, while non-degrading controls showed no deuterium incorporation. Laser intensity optimization (5% power) ensured spectral fidelity with >95% cell viability. The platforms label-free, culture-independent workflow facilitates rapid functional screening of unculturable microbes, overcoming limitations of fluorescence-based methods. This technology not only advances lignin bioconversion by enabling targeted isolation of high-efficiency degraders but also establishes a scalable framework for exploring complex microbiomes. By bridging metabolic phenotyping with single-cell resolution sorting, the MD-SCR system offers transformative potential for sustainable resource utilization and environmental biotechnology.

microbiology↗

bioRxiv2025

Deciphering of single-cell chromatin accessibility and transcriptome reveals the discrepancy for ex vivo human erythropoiesis

BackgroundErythroid cells can be generated from hematopoietic stem and progenitor cells (HSPC) derived from various sources; however, few studies decode ex vivo human erythropoiesis for the discrepancies at single-cell multi-omics resolution and uncover the underlying restraints for erythrocyte regeneration. ResultsWe deciphered ex vivo human erythropoiesis at two differentiation states from three sources at single-cell chromatin accessibility and transcriptomes level. We identified detrimental myeloid differentiation tendencies during early differentiation. These tendencies were linked to low glutamine activity in cord blood- and iPSC-derived erythropoiesis. The erythroid progenitor differentiation is restricted by cell cycle and hypoxia signaling deficiencies, which are pronounced in the iPSC-derived erythropoiesis. We delineated the erythroid differentiation trajectory of various ex vivo erythropoiesis systems, and revealed a distinct roadmap from HSC to orthochromatic erythroblast with unprecedented resolution. The integrative analysis of single-cell chromatin accessibility and transcriptome across developmental stages uncovered a dynamic coordination, and highlighted the pivotal role of chromatin accessibility and associated enhancers in regulating ex vivo erythropoiesis. Cell-cell communications in the ex vivo erythropoiesis system were not as well established as those in the BM, suggesting that modulating cell-cell communication signals in distinct ex vivo erythropoiesis system may facilitate erythrocyte regeneration. ConclusionsThis study comprehensively characterized the discrepancies and constraints in ex vivo human erythropoiesis at single-cell multi-omics resolution, offering novel strategies to overcome these constraints. These insights are critical for advancing functional erythrocyte generation and have significant implications for clinical applications.

developmental biology↗