Biology subjects

Gu, L.

Publications and source records attributed to Gu, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Benchmarking the Performance of a Commercial Electrostatic Linear Ion Trap (ELIT) Charge Detection Mass Spectrometer For Higher-Order Antibody Aggregate Analysis

Higher-order antibody aggregates remain challenging to characterize using conventional mass spectrometry because of their low abundance, broad mass distributions, and extensive heterogeneity. Here, the practical performance of a commercial electrostatic linear ion trap charge detection mass spectrometer (XevoTM CDMS) was evaluated for therapeutic antibody analysis. The platform provided reproducible mass and charge measurements, with repeatability and intermediate-precision RSDs below 1%, and maintained consistent mass determination across the concentration and solution conditions examined. Controlled mixtures of antibody-derived species showed a linear molar-ratio-dependent ion response, supporting semi-quantitative estimation of relative species abundance under defined conditions. For heat-stressed trastuzumab, CDMS measurements were qualitatively consistent with SEC-MALS, mass photometry, and conventional native MS, while enabling direct mass determination of individual ions within highly heterogeneous high-molecular-weight (HMW) populations that exhibited extensive charge-state overlap and could not be reliably deconvoluted by conventional native MS. High-duty-cycle acquisition increased sampling of low-abundance, high-m/z ions and improved access to higher-order aggregate signals. Joint single ion mass-charge analysis further differentiated statistical ion families within the broad HMW fraction and related major mass differences to independently obtained compositional information. These results support commercial XevoTM CDMS as a practical multidimensional platform for antibody aggregate characterization.

biochemistry↗

bioRxiv2026

A decision-based criterion and a resolution threshold for ranking genomic prediction models within trials

Breeding programmes choose genomic prediction models by accuracy rankings, and the metric behind a ranking decides which model wins. Selecting the best genotypes within a trial depends only on the order of the predictions, so a metric that guides the choice must be unchanged by any order-preserving change of the predictions and respond when their order is reversed. Of the 22 official metrics of the Genomes to Fields maize competition, one meets both conditions, the within-environment rank correlation; the within-environment Pearson correlation is protected against rescaling only; and twenty fail, including the root mean squared error that decided the 2022 ranking. Switching between the competitions two official metrics reverses 27 % of team pairs, and an exact decomposition shows why pooled metrics mislead: in three constructed panels, 94-95 % of the attainable square of pooled correlation is carried by the environment means. The accuracy difference a trial can resolve falls as about 3/{surd}N with its N genotype-environment cells: at least 0.03 at the competitions design and 0.04-0.12 once calibrated on real panels, against 0.003 between the first two teams; tests that two correlations differ declare far smaller differences, which do not reliably change selection. In soybean, where the two most accurate methods stand clear of most others by more than the trial resolves, ranking by either within-environment correlation selects better material, 98-99 % of the attainable selection gain in held-out environments against 13-34 % for error-magnitude rankings; in common bean and a Chinese maize population, where the leading methods lie within the resolvable gap, all rules pick material of similar value. GPverdict runs these checks on any programmes cross-validated predictions.

plant biology↗

bioRxiv2026

The multiscale architecture of trait aggression: from meta-analytic convergence to multimodal characterization

Background. Trait aggression shows substantial interindividual variability, yet its neurobiological architecture across structural, functional, molecular, and macroscale organizational levels remains poorly understood. Methods. We developed a convergent multiscale framework to characterize the neurobiological architecture associated with trait aggression. We first integrated a large-sample voxel-based morphometry analysis (n = 922) with published neuroimaging studies using two complementary coordinate-based meta-analytic approaches, activation likelihood estimation and seed-based d mapping (total N = 3,671). Convergent meta-analytic findings were subsequently mapped onto functional connectivity networks, and their molecular signatures were characterized using imaging transcriptomics and neurotransmitter mapping. Finally, we examined whether the spatial organization of aggression-related networks was embedded within intrinsic multimodal brain hierarchies spanning morphometric, functional, transcriptomic, and neurochemical dimensions. Results. Across complementary analyses, trait aggression converged on a reproducible structural-functional network centered on the dorsomedial prefrontal cortex and dorsal anterior cingulate cortex. This architecture exhibited distinct molecular signatures, including gene-expression patterns enriched for synaptic functions and robust spatial associations with serotonergic, dopaminergic, and noradrenergic transporter systems. Moreover, the spatial organization of the aggression-related functional network was systematically predicted by the brain's intrinsic multimodal gradients, indicating that it is embedded within broader principles of cortical hierarchical organization. Conclusions. these findings move beyond the localization of aggression to discrete brain regions and identify a reproducible multiscale architecture linking aggression-related structural variation to functional network organization, molecular signatures, and the brain's intrinsic multimodal hierarchy. This integrative framework provides a systems-level account of the neurobiological basis of individual differences in trait aggression.

neuroscience↗

bioRxiv2026

Matrix Viscoelasticity Regulates the Stemness and Multilineage differentiation of Primary Neural Progenitor-Stem Cells in 3D

Neural progenitor-stem cells (NPSCs) reside in mechanically dynamic brain microenvironments and give rise to neurons, astrocytes, and oligodendrocytes. Although recent studies have shown that matrix viscoelasticity can influence neural maturation and neurogenic differentiation, its role in primary NPSCs beyond neurogenesis remains less defined. How matrix viscoelasticity or stress relaxation regulates primary NPSC stemness, neuronal and glial differentiation, and the associated matrix-cell mechanotransduction pathways are not well understood. Here, we use alginate hydrogels with independently tunable stiffness and stress relaxation properties to investigate how matrix stress relaxation regulates the fate of primary subventricular zone (SVZ)-derived NPSCs in 3D. The results suggested that matrices with faster stress relaxation enhances stemness maintenance, radial glial-like marker expression, and differentiation of NPSCs toward neuronal, astrocytic, and oligodendrocytic lineages in the corresponding biochemical environments. In mixed neuronal/astrocytic differentiation conditions, fast-relaxing matrices preferentially promote neuronal differentiation. Mechanistically, NPSC responses to matrix stress relaxation involve integrin-mediated adhesion, actomyosin contractility, actin polymerization, and Piezo1 activity, with distinct contributions across differentiation lineages. Together, these findings reveal how matrix stress relaxation regulates primary NPSC stemness and multilineage differentiation through multiple mechanotransduction pathways in 3D.

neuroscience↗

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

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

synthetic biology↗

bioRxiv2026

M6AFormer Prioritizes Unannotated Functional m6A Candidate Sites in the Human m6A Epitranscriptome

N6-methyladenosine (m6A) is a pervasive RNA modification with critical roles in post-transcriptional regulation, yet accurate transcriptome-wide identification of functional m6A sites remains challenging. Here, we present M6AFormer, a hybrid deep-learning framework that combines convolutional feature extraction with a lightweight Transformer to capture both local sequence motifs and broader contextual dependencies. M6AFormer consistently outperformed representative m6A predictors, including MST-M6A, CLSM6A and deepSRAMP. Transcriptome-wide scanning revealed a large repertoire of previously unannotated candidate m6A sites that retained hallmark m6A features, including canonical motif enrichment, characteristic spatial distribution and preferential overlap with m6A writer and reader binding regions. Importantly, M6AFormer-predicted sites were broadly associated with genetic and disease-relevant features, including SNPs, sequence variants and GWAS-linked loci, suggesting their potential contribution to human disease mechanisms. Finally, experimental validation confirmed a previously unreported m6A site in NEU4 mRNA and demonstrated its functional impact on cancer cell migration. Together, M6AFormer provides an accurate, interpretable and biologically informative framework for m6A site discovery.

bioinformatics↗

bioRxiv2026

Linker-Length Landscape Mapping Enables Coupling of Diverse Synthetic Chemically Induced Dimerization Systems to Molecular Readouts

Programmable molecular biology increasingly requires strategies for converting engineered recognition or proximity modules into measurable outputs, particularly within transcriptional regulation, RNA imaging, and CRISPR-associated systems. Synthetic chemically induced dimerization (CID) systems provide a class of programmable recognition modules for such applications, yet generalized strategies for coupling structurally diverse CIDs to functional readouts remain limited. Here, we introduce a CID-to-output conversion strategy based on engineering of the linker-mediated coupling interface. Using single-fluorescent-protein sensors as an experimentally tractable optical model readout, we systematically varied paired N- and C-terminal linkers flanking circularly permuted green fluorescent protein (cpGFP) to map coupling landscapes across synthetic CID systems derived from combinatorial selection and computational protein design. The results revealed strong non-additive interactions across paired linkers and suggest that linker length is a first-order determinant of CID-to-output coupling. Across nanobody-, monobody-, and de novo-designed CID architectures, this framework yielded functional sensors with dynamic ranges up to 1270% and robust responses in mammalian cells. Together, this work demonstrates that effective CID-to-output conversion can be achieved by empirically mapping the linker-mediated coupling interface, providing a practical route for adapting synthetic CID to diverse programmable molecular readouts and nucleic-acid-associated synthetic biology systems O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/735888v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1ecc594org.highwire.dtl.DTLVardef@19fb822org.highwire.dtl.DTLVardef@f1e2ddorg.highwire.dtl.DTLVardef@653131_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

Nitrogen-Responsive Extracellular Proteomics Reveals Evidence for a Novel Heterocyst-Specific Protein Secretion Pathway in Anabaena

Nitrogen availability is a major factor governing the physiology, ecology, and metabolism of cyanobacteria. Here, we performed a comparative extracellular proteomic analysis of Anabaena sp. PCC 7120 grown under nitrate-replete and diazotrophic conditions. Using LC-MS/MS, we identified 115 extracellular proteins in nitrate-grown cultures and 113 proteins under N2-fixing conditions. Remarkably, SignalP 6.0 predicted canonical signal peptides in only [~]22% of the identified proteins, suggesting that extracellular protein export in Anabaena predominantly occurs through non-classical secretion mechanisms, potentially involving extracellular vesicles or other unrecognized pathways. Six highly abundant extracellular proteins (Alr2938, Alr4550, Alr2328, All4121, Alr0528, and Alr0529) were detected under both nitrogen regimes. In contrast, All4337, Alr0608, and All3093 were preferentially enriched under nitrate-replete conditions, whereas Alr0267 and Alr1050 emerged among the most abundant extracellular proteins during diazotrophic growth. Notably, an Alr0267-GFP fusion protein was detected exclusively in heterocysts, the specialized N2-fixing cells of Anabaena, with GFP fluorescence concentrated at the cell periphery. The extracellular localization of Alr0267 is particularly intriguing because heterocysts are surrounded by specialized polysaccharide and glycolipid envelope layers that establish the microoxic environment required for nitrogenase activity. The apparent export of Alr0267 across these barriers provides evidence for a previously unrecognized heterocyst-associated protein secretion pathway. Together, these findings reveal a nitrogen-responsive extracellular proteome and provide the first evidence for heterocyst-specific extracellular protein secretion. This work advances our understanding of heterocyst biology and protein trafficking while laying a foundation for engineering Anabaena as a sustainable photosynthetic platform for secreting high-value proteins using sunlight, CO2, N2, and mineralized water.

molecular biology↗

bioRxiv2026

Fasting disrupts the InsP6 HDAC3 axis to drive ER stress-mediated clearance of DNA-damaged cells and enforce tissue quality control.

Fasting drives metabolic adaptation but also elicits acute cellular stress. How this stress shapes tissue integrity is unknown. Here, we show that in the intestine, fasting depletes growth factor signaling, which triggers cellular stress. This response functions as a tissue quality-control checkpoint that selectively eliminates pre-existing DNA-damaged cells while sparing healthy counterparts. A short-term fast diminishes TGF-{beta} signaling and elicits endoplasmic reticulum (ER) stress, driving DNA-damaged intestinal cells beyond an apoptotic threshold, thereby reducing the inflammatory burden. Mechanistically, loss of TGF-{beta} signaling triggers FBXO22-Cullin1-mediated degradation of the inositol kinase IPMK, leading to depletion of inositol hexaphosphate (InsP). InsP loss attenuates HDAC3 activity and initiates coordinated epigenetic and post-translational reprogramming, thereby increasing CDK5RAP3 abundance. Elevated CDK5RAP3 inhibits ribosomal RPL26 UFMylation, thereby amplifying ER stress and selectively licensing apoptosis in DNA-damaged cells. Collectively, fasting disrupts a TGF-{beta}-InsP6-HDAC3 axis to drive ER stress-dependent clearance of DNA-damaged cells, enforcing tissue quality control.

cell biology↗

bioRxiv2026

Nitrosomes: protein language modeling and live-cell imaging reveal condensate-like nitrogenase organization in heterocysts

Biological nitrogen fixation in some filamentous cyanobacteria occurs in heterocysts, yet the subcellular organization of nitrogenase in these cells remains poorly defined. Using fluorescence microscopy of living Anabaena sp. PCC 7120, we found that a NifH-GFP fusion forms discrete puncta restricted to mature heterocysts, whereas constitutively expressed GFP in vegetative cells and a nifB-linked GFP reporter remained diffuse. To contextualize this phenotype, we built a homology-aware cyanobacterial condensate-prioritization framework across 31,028 proteins from seven proteomes, integrating ESM-2 embeddings, 27 biophysical features, and 44 curated condensate-associated positives. Because direct positives remain limited, we present the model as a ranking resource rather than a calibrated classifier. Under a deliberately conservative nitrogenase-withheld analysis that removed nitrogenase-family labels and homologous clusters from the training data, NifH retained a median rank in the highest-scoring 4.8% of cyanobacterial proteins. catGRANULE 2.0 also assigned high scores to nitrogenase iron proteins, while having only modest rank concordance to the whole atlas. Together, these data identify heterocyst-restricted NifH-GFP puncta as evidence of sub-cellular spatial organization and provide a curated resource for prioritizing cyanobacterial condensate candidates, some of which are also important for nitrogen fixation.

molecular biology↗

bioRxiv2026

Development of KASP Molecular Markers and Construction of Fingerprinting for Cowpea (Vigna unguiculata (L.) Walp) unguiculata Based on ddRAD-Seq

Cowpea (Vigna unguiculata (L.) Walp.) is a globally important legume crop. However, the scarcity of efficient molecular markers has hindered molecular breeding efforts and the protection of plant breeders rights. In this study, we employed double-digest restriction-site associated DNA sequencing (ddRAD-seq) to characterize the genetic diversity of 19 core cowpea germplasm accessions. We generated 791,621 SNPs, from which 13,469 high-quality SNPs were filtered. Population structure and phylogenetic analyses revealed that these accessions cluster into three distinct groups. To facilitate cost-effective and rapid genotyping, we developed a panel of KASP (Kompetitive Allele Specific PCR) markers. Through rigorous screening for polymorphism and stability, we identified six core KASP markers located in exonic regions. These six markers alone were sufficient to discriminate all 19 accessions. Based on these core markers, we constructed a unique DNA fingerprinting profile and assigned specific QR codes for each accession. This study demonstrates that extracting core KASP markers from ddRAD-seq data is a powerful strategy for germplasm identification. The developed fingerprinting system provides a robust, low-cost tool for seed purity testing, variety authentication, and marker-assisted selection in cowpea breeding programs.

plant biology↗

bioRxiv2026

TERT drives liver tumorigenesis beyond telomere elongation

We generated two mouse models, p21/Tert and p21/TertCi, expressing either telomerase reverse transcriptase (TERT) or a catalytically inactive variant under the control of the p21 promoter. By 18-20 months of age, approximately 25% of mice from both genotypes developed liver tumors with histopathological features resembling human hepatocellular carcinoma (HCC). Whole-exome sequencing identified activating Ctnnb1 mutations and recurrent PP1 subunit alterations in p21/Tert tumors, whereas p21/TertCi tumors harbored activating HrasGln61Lys mutations associated with elevated C>A transversions. Both models exhibited chromosomal aberrations commonly observed in human HCC. Transcriptomic analyses revealed that {beta}-catenin-activated tumors recapitulated gene expression signatures of human HCC, while MAPK-mutated tumors showed profiles consistent with MAPK/ERK pathway activation. Metabolically, both genotypes demonstrated increased glycolysis and suppression of gluconeogenesis, including downregulation of FBP1, but expressed distinct NRF2 target genes. Spatial profiling further revealed reduced HNF4-positive hepatocytes across tumors, independent of Hnf4 transcription, and markedly diminished immune cell infiltration particularly in {beta}-catenin-activated tumors. Collectively, these findings uncover telomere-independent functions of TERT and identify molecular and metabolic features with potential relevance for predicting immunotherapy response.

cancer biology↗

bioRxiv2026

A selective Cullin 3 RING E3 ligase inhibitor attenuates hyperglycemia via dual insulin sensitizing and insulinotropic action

Hyperglycemia is a hallmark of type-2 diabetes and a key pathogenic driver of diabetic complications. Cullin RING E3 ligases (CRLs) are multi-subunit E3 ubiquitin ligases that mediate cellular protein turnover. The activity of CRLs requires cullin neddylation, a post-translational modification that can be pharmacologically targeted with therapeutic potentials. By using hyperinsulinemic-euglycemic clamp analysis, we discover that pan neddylation inhibitor exerts both insulin sensitization effect in liver and muscle and insulinotropic effect in pancreatic {beta} cells. This dual action is mediated by Cullin 3 (Cul3), a member of the 7 canonical cullin family proteins. DI-1859, a selective Cul3 neddylation inhibitor, effectively protects against hyperglycemia in obese mice. DI-1859 enhances insulin signaling by preventing Cul3-mediated insulin receptor substrate degradation in liver and muscle cells. DI-1859 increases insulin secretion in a glucagon-like peptide-1-independent manner in mice and directly potentiates glucose-stimulated insulin secretion in INS-1 832/13 {beta} cells and human islets. Mechanistic studies reveal that DI-1859 does not promote glycolytic flux or bioenergetics function but potentiates glucose-stimulated insulin secretion via mechanisms involving RhoA activation and cytoskeleton remodeling in {beta} cells. This study shows that a single agent targeting Cul3 neddylation simultaneously promotes insulin sensitization and insulin secretion to attenuate hyperglycemia in mice. Article Highlightsa. Pan cullin neddylation inhibitors exhibit potent hypoglycemic effect. b. The target organs and mechanisms underlying the hypoglycemia effect of cullin pan neddylation inhibitors are incompletely understood. c. We found that inhibition of Cul3 leads to a dual insulin sensitization and insulinotropic effect. d. Selective inhibition of Cul3 neddylation is a feasible approach to lower hyperglycemia.

physiology↗

bioRxiv2026

MR-μScope: a multi-scale and simultaneous MRI-miniaturized microscopy system for elucidating neurovascular coupling

Blood Oxygen Level Dependent functional MRI (BOLD-fMRI) revolutionized non-invasive brain mapping, yet the physiological origins of its signal, linking microscopic neurovascular activity to macroscopic hemodynamics, remain elusive. To bridge this gap, we developed MR-Scope: a simultaneous and multimodal platform that integrates preclinic high-field MRI (9.4T) and miniaturized fluorescence microscopy (Miniscope). Our system contains an MR-compatible Miniscope with electromagnetic shielding, a customized radiofrequency coil with a central optical window, and an adjustable animal cradle, enabling artifact-free acquisition of whole-brain fMRI alongside microscopic vascular dynamics. Phantom validation confirmed negligible cross-modal interference (fMRI SNR [≥] 15 dB; optical SNR [≥] 26 dB). MR-Scope captured stimulus-evoked microvascular dilation and blood flow velocity changes in the somatosensory cortex concurrent with BOLD signals, revealing vessel-size-dependent neurovascular coupling. MR-Scope provides an effective solution for deciphering multi-scale neurovascular interactions and offers unique potential for advancing research into brain function and disease mechanisms involving vascular pathology.

bioengineering↗

bioRxiv2025

PCNA Inhibition Enhances the Antitumor Activity of KRAS-Targeted Therapies in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with a dismal prognosis. More than 90% of PDAC tumors harbor KRAS mutations, and several KRAS inhibitors, such as off-state, on-state, mutation-specific, and pan-RAS inhibitors, are being tested in preclinical and clinical settings. However, the response to these inhibitors as single agents is less than optimal, indicating the need to identify novel combination therapies to improve treatment outcomes. Proliferating cell nuclear antigen (PCNA) is a ring-shaped clamp protein that regulates DNA replication, repair, and resolution of transcription-replication conflict, which are critical processes for pancreatic cancer survival. AOH1996 is a first-in-class, selective PCNA inhibitor in Phase I trials. Here, we found that AOH1996 treatment is efficacious in various PDAC models in vitro. PCNA and KRAS are predicted to be synthetic lethal partners, and RNA sequencing of AOH1996-treated PDAC cells reveals enrichment of MAPK and PI3K signaling pathways. Combination of AOH1996 with KRAS inhibitors demonstrates strong synergy across KRAS G12C and G12D mutant models. Treatment with a combination of AOH1996 and KRAS inhibitors induces cell cycle arrest and apoptosis in PDAC cells. Robust antitumor activity of AOH1996 in combination with RMC-6236 was observed in PDAC tumoroids. In vivo, the combination of AOH1996 with sotorasib or MRTX1133 reduced tumor growth rates compared to single-agent therapy, with no impact on mouse body weight. Residual tumor analysis showed sustained pERK and Myc inhibition in the combination arm. In conclusion, combination of AOH1996 with KRAS inhibitors is a promising therapeutic strategy for KRAS-driven PDAC, warranting further clinical investigation.

cancer biology↗

bioRxiv2025

Hepatocyte and adipocyte CDO1-mediated intracellular cysteine catabolism differentially modulates diet-induced obesity and fatty liver in mice

Background and AimsPlasma cysteine has been positively linked to BMI in humans. Consistently, dietary cysteine restriction significantly decreases obesity in mice via mechanisms that are incompletely defined. Cysteine dioxygenase type 1 (CDO1) mediates the major cysteine catabolism pathway and is highly expressed in hepatocytes and adipocytes. The goal of this study is to determine the impact of this endogenous cysteine catabolism pathway on obesity and fatty liver disease. MethodsDiet-induced obesity and fatty liver disease were studied in hepatocyte-specific CDO1 knockout mice (L-CDO1-KO), hepatocyte-specific CDO1 transgenic mice (L-CDO1-Tg), adipocyte-specific CDO1 knockout mice (Ad-CDO1-KO), and adipocyte-specific CDO1 transgenic mice (Ad-CDO1-Tg). ResultsDeletion of hepatocyte CDO1 decreased cysteine conversion to cysteine sulfinic acid, and had modest impact on liver cysteine, GSH, or taurine abundance. When fed a Western diet (WD), L-CDO1-KO mice showed elevated liver injury markers and inflammatory infiltration independent of obesity or steatosis. When fed a fibrogenic high fat/cholesterol/fructose diet (HFCFr), L-CDO1-KO mice developed worsened liver fibrosis. In contrast, L-CDO1-Tg mice fed WD showed lower blood glucose, but similar degree of obesity and steatosis compared to WT mice. Deletion of CDO1 in white and brown adipocytes of Ad-CDO1-KO mice had no effect on WD-induced obesity. In contrast, overexpression of CDO1 in white and brown adipocytes attenuated WD-induced obesity, which resulted in reduced hepatic steatosis. ConclusionGenetic manipulation of intracellular cysteine catabolism in hepatocytes and adipocytes differentially modulates diet-induced obesity and fatty liver, which warrants future mechanistic investigation to better understand cellular cysteine sensing mechanisms and cysteine control of cell metabolism.

physiology↗

bioRxiv2025

Ethylene signal-driven plant-multitrophic synergy boosts crop performance

Efficient nutrient use in agriculture depends on the dynamic interplay between plant roots, soil, and microbial communities. The root-rhizosphere interface is central to nutrient uptake and serves as a key hub for interactions with beneficial microbes. Arbuscular mycorrhizal (AM) fungi, positioned at the nexus between plant roots and soil microbiota, play a critical role in enhancing crop performance under nutrient-limited conditions. In this study, we dissected the genetic and molecular basis of AM fungi-induced lateral root development in maize (Zea mays), focusing on the role of ethylene-responsive transcription factors (ERFs). We identified ERF genes as essential regulators of pericycle cell division, acting downstream of ethylene biosynthesis genes (ACS6 and ACS7) and AM fungal signaling. Our findings reveal that AM fungi promote lateral root initiation by activating ERF expression and reprogramming flavonoid metabolism, particularly reducing the accumulation of flavonols such as kaempferol and quercetin, which otherwise inhibit root development when over-accumulated. Furthermore, we demonstrated that Massilia, a beneficial rhizobacterium, synergizes with AM fungi to enhance lateral root formation by colonizing fungal hyphae, degrading flavonoids, and contributing to auxin production. Together, our results uncover a tripartite signaling network linking ethylene signaling, flavonoid-mediated microbial recruitment, and AM symbiosis. This study highlights ERFs as central integrators of plant-microbe interactions and provides a molecular framework for engineering root architecture and microbiome assembly to improve nutrient acquisition and support sustainable crop productivity.

plant biology↗