Biology subjects

Zhao, Z.

Publications and source records attributed to Zhao, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Engineered Proteins Mimic ssRNA Phage to Disrupt Type IV Pili

Antimicrobial resistance is a growing global health crisis, with ESKAPE pathogens, such as Acinetobacter species, contributing significantly to hospital-acquired infections. These bacteria employ various virulence factors, including extracellular type IV pili (T4P), which serve as essential appendages for DNA uptake, biofilm formation, and resistance to antibiotics. Single-stranded RNA (ssRNA) bacteriophages (phages) exploit these retractile pili as entry receptors, but the exact mechanism of viral RNA delivery following pilus binding and retraction remains poorly understood. In this study, we investigated the entry mechanism of the ssRNA phage AP205 by identifying the specific phage components necessary for T4P detachment, a key step in viral genome entry. Our data reveals the phages maturation protein (Mat) is sufficient to induce pilus detachment on its own, and the overall virion structure further enhances the efficiency of this process. These findings provide mechanistic insights into how ssRNA phages exploit bacterial T4P as part of their infection pathway and suggest a conserved strategy for host entry. ImportanceAcinetobacter species are widespread environmental bacteria and members of the ESKAPE group of pathogens, often associated with hospital-acquired infections amongst immunocompromised patients. A major reason for the increase in antibiotic resistance in Acinetobacter species is its use of T4P to evade antibiotic treatment. With antibiotic resistance becoming a global health crisis, targeting these virulence factors represents a promising approach to combat infections. Since T4P are critical for Acinetobacter virulence, understanding mechanisms that can disrupt them is highly important. ssRNA phages provide a natural model for this, as they can target T4P to initiate infection. Recent research has shown that ssRNA phages can detach pili during their infection process. However, the precise mechanism behind this phenomenon remains unknown. Our research addresses part of this knowledge gap by identifying the key components required for this pilus detachment. This work will enhance the current understanding of the virulent T4P in Acinetobacter species, which could ultimately lead to broader medical advancements.

microbiology↗

bioRxiv2025

VIP-OT: Dissecting Single-Cell Biochemical State Dynamics under Perturbation via Vibrational Painting and Optimal Transport

Dissecting the heterogeneous response of individual cells towards genetic and chemical perturbations is central to understanding the dynamic functions of cells and multicellular systems. However, characterizing and modeling how individual cells transition between different states remains a major challenge. Vibrational imaging provides high-content, biochemically informative, label-free molecular fingerprints of single cells but it remains at its infancy for dynamic or predictive analysis of cell state transition. Here, we introduce Vibrational Painting-Optimal Transport (VIP-OT), an integrated experimental-computational framework that overcomes this fundamental limitation. VIP-OT couples multiplexed infrared (IR) and Raman imaging with optimal transport to computationally reconstruct single-cell perturbation trajectories from unpaired population snapshots. When applying to over 22,000 single-cell spectra profiles from human breast adenocarcinoma cells under 16 drug treatments, this framework can retrospectively trace drug response heterogeneity back to baseline metabolic states. We leverage the inferred cell pairings to develop a machine learning model that accurately predicts the full post-treatment metabolic state of individual cells from their pre-treatment spectra. Furthermore, by modeling transitions across dose gradients, we introduce the concept of Spectral Velocity to map dynamic response trajectories and resolve drug combination effects into distinct, path-dependent molecular routes. Together, VIP-OT opens a new direction for dissecting heterogeneous perturbation responses at single cell resolution and serves as a foundation for building virtual simulators of cells under perturbations through high-throughput, high-content, and low-cost vibrational imaging, as well as interpretable in silico modeling.

bioengineering↗

bioRxiv2025

Caenorhabditis briggsae ancestral genomic hyper-diversity contrasts with globally distributed genome-wide haplotypes

Comparative genomics provides a powerful framework to uncover the molecular and evolutionary mechanisms that shape genetic diversity within and across species, revealing how shared and lineage-specific processes influence their evolutionary trajectories through time. The nematode Caenorhabditis briggsae is distributed world-wide and is a comparative model to Caenorhabditis elegans in the biology of development, cellular mechanisms, neurobiology, genetic mappings of complex traits, and genome evolution. Following massive collection efforts by the nematode research community, we present the isolation of over 2,000 wild strains and analyses of genome sequences that catalog over six million single-nucleotide and insertion-deletion variants. This genome and strain resource provide a powerful means to interrogate the causal genetic bases of phenotypic variation for diverse traits. Additionally, we describe its global population structure and discover new and genetically distinct groups within this primarily self-fertilizing species, including groups of highly related strains that were sampled across different continents. We leverage expansive genetic variation to decipher the effects of linkage and selection on the distribution of genetic diversity across the genome and across geographic regions. Within the species, we find genomic regions with extremely high levels of genetic variation similar to hyper-divergent regions found in C. elegans and other species. These regions harbor new genes and variation enriched for environmental sensing and pathogen responses. In comparison to the outbreeding sister species Caenorhabditis nigoni, we conclude that long-term balancing selection has maintained substantial functional variation since the divergence from their outbreeding ancestor, likely in response to differences in the ecological niche. Overall, this massive strain resource enables future comparative genetics and genomics studies, including genome-wide association studies between Caenorhabditis species.

genomics↗

bioRxiv2025

Insular cortex predictions regulate glucose homeostasis

Brain-body interactions are essential for physical and emotional homeostasis. The brain uses information from the external world to predict upcoming bodily changes. This process involves interoceptive predictions, which are thought to play a central role in brain-body interactions. Yet there is little direct experimental evidence causally linking interoceptive predictions to regulation of bodily physiology. Here we address this by focusing on insular cortex and glucose homeostasis. We find that just before the onset of a meal, insular cortex exhibits a transient burst of activity, reflecting a prediction of the future metabolic state. This transient predictive burst of activity is essential for anticipatory insulin release, subsequent post-meal insulin release, post-meal glucose and lipid homeostasis, and post-meal metabolism signaling in the liver. Our results highlight that insular cortex predictive computations are essential for anticipatory physiological control and for subsequently maintaining metabolic homeostasis.

neuroscience↗

bioRxiv2025

A large-scale dataset of functional mouse ganglion cell layer responses

We present the AO_SCPLOWLLC_SCPLOW-GCL dataset, a large-scale resource of functional two-photon Ca2+-imaging recordings with rich meta-data information from more than 80,000 cells in the ganglion cell layer (GCL) of the ex vivo mouse retina. Collected over nine years across more than 139 experimental sessions, the dataset provides recordings of light-evoked responses to various stimuli, including a shared set of core stimuli. To enable cell-type-specific analyses, cells are probabilistically assigned to 46 previously characterized functional groups, including retinal ganglion cells and displaced amacrine cells. Further, we assessed the influence of experimental and biological factors on the functional responses and found only small batch effects across experimenters, setups, and recording sessions, highlighting the datasets consistency. The AO_SCPLOWLLC_SCPLOW-GCL dataset offers a comprehensive and standardised reference for studying retinal computation at scale. It supports population-level analyses, computational modelling, and the development of machine learning approaches for biological time-series data. Future releases will expand the dataset with additional mouse lines and light stimuli, creating a growing resource for the vision science community.

neuroscience↗

bioRxiv2025

Rapid robust high-fidelity 3D neuronal extraction from multi-view projections

Recent developments in imaging facilitate large-scale three-dimensional (3D) neuronal recording. While these huge amounts of data shed new light on population-level neural coding, it is much harder to extract neuronal calcium dynamics from 3D volumes than 2D images with the existence of noise and scattering. Here, we presented DeepWonder3D, a general end-to- end pipeline for rapid and robust 3D neuronal extraction with high fidelity. Instead of processing voxel by voxel, DeepWonder3D works on the multi-view projections of 3D imaging data obtained either digitally or optically through specific point spread functions (PSFs) for general applicability to diverse techniques, including point-scanning microscopy, light- field microscopy, and two-photon synthetic aperture microscopy. Integrating denoising, resolution registration, background removal, neuronal extraction, and multi-view fusion into a unified pipeline tailored for large-scale high-resolution datasets contaminated by noise and scattering, DeepWonder3D outperforms state-of-the-art methods in 3D localization accuracy with a 10-fold reduction in computational costs, validated by numerical simulations and a hybrid two-photon/light-field imaging system. With the RUSH3D mesoscope, DeepWonder3D achieves rapid high-fidelity 3D calcium extraction of tens of thousands of neurons across the mouse cortex within hours.

neuroscience↗

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↗

bioRxiv2025

Thermal boundaries and underlying systems biology mechanisms in two waterbloom cyanobacteria

Climate change and recent heatwaves have elevated temperature to the level of nutrients in driving CHABs. In this new dimension of CHABs ecology, it is important to understand the thermal boundaries of each blooming species. One well-known example is the temporal and thermal partitioning between filamentous, nitrogen-fixing taxa such as Dolichospermum spp. and Pseudanabaena spp., which dominate in spring, and colonial/coccoid Microcystis aeruginosa, which predominates in summer and autumn. Here we show that Dolichospermum sp. and M. aeruginosa display converse temperature-growth relations, Dolichospermum sp. grows better at low temperatures (13-15{degrees}C) and M. aeruginosa grows better at high temperatures (29-31{degrees}C), with similar growth rates between 18 and 25{degrees}C. This thermal separation is sustained by systems-level changes, in terms of the macromolecule contents--proteins, ATP, carbohydrates, and lipids--and transcriptome and metabolic fluxes to critical unsaturated fatty acids, which were experimentally verified by supplementing these FAs. The gene regulatory and systems biology mechanisms are explored. Through homologous and evolutionary analyses, a conserved Hik34-Rre1-RpoD cascade underlying differential temperature-responsive gene regulation. Enzyme-constrained metabolic models reproduced genus-specific lipid shifts and uncovered contrasting flux reorganizations under thermal stress. Together, these results establish the metabolic and regulatory foundations that shape the distinct thermal niches of bloom-forming cyanobacteria, providing mechanistic insight into how climate warming may restructure their seasonal dominance.

systems biology↗

bioRxiv2025

Gut metabolite IPA alleviates white matter injury post-ICH by enhancing myelin debris phagocytosis via Stap1 inhibition

BackgroundIntracerebral hemorrhage (ICH) causes neurological dysfunction and white matter injury (WMI) characterized by myelin loss, axonal injury and myelin debris accumulation. Microglia-mediated debris clearance is critical for WMI repair. The microbiota-gut-brain axis plays an essential role in the central nervous system diseases, one of the ways in which gut microbiota affects brain is via producing metabolites. Indole-3-proprionic acid (IPA), a tryptophan-derived metabolite that mainly produced by Clostridium sporogenes, exhibits anti-inflammatory and neuroprotective properties. However, its effect on ICH remains unclear. This study aims to investigate the IPA level after ICH and the therapeutic effects of IPA on neurological deficits and WMI, as well as the potential mechanisms underlying IPA-mediated neuroprotection. MethodsAn ICH model was established using C57BL/6 mice, which then received intragastric IPA (20 mg/kg/day). Fecal abundance of IPA-related genes and IPA levels in feces and plasma were measured by qPCR and UPLC-MS/MS. Behavioral tests, qPCR, and immunofluorescence staining were used to assess neurological function, myelin integrity, and axonal injury. In vitro, BV2 microglia, with or without Stap1 knockdown, were co-cultured with myelin debris to assess IPAs effects on phagocytosis. Additionally, targeted plasma IPA profiling was performed in 30 ICH patients and 30 matched healthy controls. ResultsThe relative abundance of IPA production-related genes and IPA levels in feces and plasma were significantly decreased after ICH and remained low into the chronical phase. After IPA administration, the neurological deficits, myelin loss and axonal injury of mice with ICH were significantly improved. In vitro, IPA increased BV2 microglia myelin debris phagocytosis by inhibiting Stap1 expression. IPA levels were significantly reduced in ICH patients, consistent with ICH mouse model. ConclusionsOur findings demonstrated that the gut microbiota-derived metabolite IPA could facilitate neurological deficits recovery and alleviate WMI, which could be a promising therapeutic strategy to improve ICH prognosis.

neuroscience↗

bioRxiv2025

Single-cell transcriptomics reveals spaceflight-induced accelerated aging and impaired recovery in the murine bone marrow

Spaceflight induces physiological changes that resemble accelerated aging, however, how age influences bone marrow response at the cellular level remains poorly understood. Here, we perform single-cell transcriptomic profiling of murine femur and humerus bone marrow from young (12-week-old) and old (29-week-old) mice that underwent a 32-day spaceflight mission followed by a 24-day Earth recovery, with age-matched ground controls. Our analysis reveals that, compared with young cohorts, old mice exhibit persistent dysregulation after spaceflight, most prominently in erythroid and B cell lineages. In erythroid cells, old flight mice show pronounced aging signatures, characterized by impaired maturation, inhibited mitophagy, and increased oxidative stress. In B cells, old flight mice show dysregulation associated with failure of the AP-1 stress-response pathway and complete collapse of the intercellular CXCL signaling network. Our findings dissect the age-dependent effects of spaceflight on the bone marrow hematopoietic and immune system at single-cell resolution, and demonstrate that spaceflight imposes a disproportionate burden on the aged hematopoietic system and blunts post-flight recovery. These insights provide candidate pathways and biomarkers for health monitoring and countermeasures in long-duration missions.

bioinformatics↗

bioRxiv2025

Lessons learned from a Kaggle challenge for particle picking in cryo-electron tomography

The difficulty of particle picking in cryo-electron tomography remains a barrier to routine in situ structure determination. Machine learning is well-suited to overcome this bottleneck with efficient algorithms that generalize across molecular species. To spur new algorithm development, we held a three-month Kaggle challenge that tasked contestants with annotating five molecular species across hundreds of experimental tomograms. This competition successfully engaged >1000 participants from diverse fields and delivered particle pickers that outperformed existing state-of-the-art. Systematic comparisons of the contestants submissions revealed the tolerance of subtomogram averaging to moderate but not severe over-picking and underscored the need for more robust measures of annotation quality. The winning models also highlighted the importance of data augmentation to overcome limited training data. All competition tomograms along with the ground truth and winning teams annotations have been released on the CryoET Data Portal as a resource to benchmark current and future tools for particle picking.

cell biology↗

bioRxiv2025

MERFISH+, a large-scale, multi-omics spatial technology resolves the molecular holograms of the 3D human developing heart

Hybridization-based spatial transcriptomics technologies have advanced our ability to map cellular and subcellular organization in complex tissues. However, existing methods remain constrained in gene coverage, multimodal compatibility, and scalability. Here, we present MERFISH+, an enhanced version of Multiplexed Error-Robust Fluorescence in Situ Hybridization (MERFISH), which integrates chemical probe anchoring in protective hydrogels with high-throughput microfluidics and microscopy. This optimized design supports robust and repeated hybridization cycles across an entire centimeter-scale tissue sample. MERFISH+ allowed to simultaneously quantify over 1,800 genes and resolve the 3D organization of chromatin loci and their associated epigenomic marks in developing human hearts. Using a generative integration framework for spatial multimodal data (Spateo-VI), we harmonized these MERFISH+ transcriptomic and chromatin data to reconstruct a 3D spatially-resolved multi-omic atlas of the developing human heart at subcellular resolution capturing 3.1 million cells across 34 distinct populations. This 3D atlas provides a holistic view of an entire organ enabling the characterization of 3D cellular neighborhoods and transcriptional gradients of substructures such as the descending arteries. Thus, MERFISH+ offers a robust, large-format platform for spatial multi-omics that enables high resolution mapping of gene expression at subcellular resolution and the characterization of cellular organization within 3D organs. One Sentence SummaryMERFISH+ is an spatial multi-omics platform that integrates hydrogel-based probe anchoring, automated high-throughput microfluidics, and large-format multimodal data production to enable comprehensive, subcellular resolution mapping of gene expression and chromatin organization across millions of cells within complex developing human organs. HighlightsO_LIMERFISH+ expands MERFISH capabilities to measure >1,800 genes and at whole-organ 3D imaging scale C_LIO_LICombines chemical probe anchoring with high-throughput volumetric microscopy and microfluidics C_LIO_LIGenerates a 3D molecular atlas of a developing human heart with > 3.1 million cells at subcellular resolution C_LIO_LIIntroduces Spateo-VI, a novel generative framework integrating 3D multimodal datasets C_LI

genomics↗

bioRxiv2025

FADVI: disentangled representation learning for robust integration of single-cell and spatial omics data

Integrating single-cell and spatial omics data remains challenging due to strong batch effects across experiments and platforms. Existing methods focus on minimizing these effects but cannot disentangle technical variation from true biological signals. Here, we present FADVI, a variational autoencoder framework partitioning the latent space into batch-specific, label-related, and residual subspaces. By combining supervised classification, adversarial training, and cross-covariance penalty, FADVI disentangles batch from biological representations, preserving biological variation while correcting batch effects. Benchmarking across scRNA-seq, scATAC-seq, and high-resolution spatial transcriptomics datasets, FADVI consistently outperforms state-of-the-art integration methods. FADVI also enables feature attribution for revealing genes associated with cell type identity and batch variation. Together, these results demonstrate that FADVI provides robust, interpretable integration for large-scale single-cell and spatial omics data, offering a powerful framework for downstream analysis and discovery.

bioinformatics↗

bioRxiv2025

Macrophage-secreted Pyrimidine Metabolites Confer Chemotherapy Resistance in Acute Myeloid Leukemia (AML)

The tumor microenvironment (TME) programs cancer cells to influence therapeutic responses. Macrophages residing in TME switch from pro-phagocytic to tumor-promoting and immunosuppressive phenotypes as cancer develops. While these pro-tumor functions of macrophages are associated with poor outcomes, the underlying mechanisms by which bone-marrow (BM)-associated macrophages fuel myeloid malignancy and their precise contribution to relapse remain undissected. Here, we show expansion of monocyte/macrophage population in leukemia patients post-chemotherapy relapse, and spatial proximity of macrophages to leukemia blasts in the BM niche. This proximity proved functionally consequential--depletion of macrophages delayed leukemia relapse post cytarabine (AraC), a frontline chemotherapy, in patient-derived xenografts (PDX) and syngeneic leukemia models. Mechanistically, a pyrimidine metabolite, deoxycytidine (dC), secreted by BM macrophages, is taken up by leukemia cells to directly inhibit deoxycytidine kinase (DCK) to hamper AraC activation and subsequent resistance in a cell non-autonomous manner. Diagnosis AML patients exhibited significantly higher circulating dC levels than healthy donors, and dC levels further increased following chemotherapy. SAMHD1, which catalyzes deoxynucleoside triphosphates (dNTPs) into deoxynucleoside, was highly abundant in macrophages and mediated dC accumulation. Blockade of dC production in mouse and human macrophages via genetic and pharmacological inhibition of SAMHD1 or DHODH, a critical enzyme in pyrimidine synthesis, restored AraC sensitivity. Combination with DHODH inhibitors significantly delayed AraC relapse in human PDX and mouse syngeneic AML models. Collectively, we identify a metabolic immune-leukemia crosstalk in which SAMHD1high macrophages mediates chemoresistance by secreting pyrimidine metabolites and propose macrophage metabolic reprogramming as a tractable strategy to overcome TME-driven chemoresistance in myeloid leukemia.

cancer biology↗

bioRxiv2025

FveOCRs - a database for open chromatin prediction in wild strawberry based on a large language model

BackgroundWoodland strawberry (Fragaria vesca) is a widely used model system for cultivated strawberries and Rosaceae for molecular genetic studies. Nevertheless, available databases for its cis-regulatory element identification are limited. With the emergence of large language models in plant research, strawberry research could benefit significantly from applying these models. One such model derived from Plant DNA Large Language Models (PDLLMs) effectively predicts open chromatin regions (OCRs), which are nucleosome-depleted areas typically associated with cis-regulatory elements. However, improvement of the models accessibility and utility will be needed to facilitate the models application in strawberry as well as other plant species. ResultsWe developed the FveOCRs database (http://liulab.online:33838/FveOCRLiuLabTestVer25), which predicts open chromatin regions located within 5,000 bp upstream sequences, the first and second introns and exons, and the longest introns in Fragaria vesca genes. Predictions were generated using a sliding-window approach based on one of the PDLLMs. In the database, users could predict open chromatin regions for input DNA sequences from any plant species and obtain visual graphs with precise predicted regions of open chromatins. ConclusionsThe FveOCRs database is the first database for open chromatin region prediction in Fragaria vesca based on a Plant DNA Large Language Model. It can also predict OCRs in user-provided DNA sequences from any plant species. The resource and its accessible visual graphs will facilitate discovery of cis-regulatory elements and engineering of gene expression in strawberry and other plant species.

bioinformatics↗

bioRxiv2025

Multiplexed cytokine and antigen mRNA administration generates durable anti-tumor immunity against pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) remains a devastating malignancy characterized by limited therapeutic options for advanced disease. Immunotherapy, in particular, has had dismal success rates in the PDAC due to a tumor microenvironment (TME) that contributes to immune exclusion and poor drug delivery. Many cytokines necessary for Natural Killer (NK) and T cell chemotaxis, activation, and cytotoxicity are absent in the PDAC TME. Despite their early success, cytokine therapies have largely failed in the treatment of solid tumors as a result of the lack of efficacy of single cytokine administration and toxicities from systemic delivery. To overcome these limitations, we designed multiplexed mRNA cocktails encoding diverse interleukins, chemokines, and interferons for intratumoral delivery. Administration of a cytokine-encoding mRNA mixture into mice with orthotopically transplanted PDAC tumors achieved robust yet transient cytokine expression locally in the PDAC TME, leading to NK cell and CD8+ T cell immunity and reduced tumor growth and fibrosis in multiple mouse models. Combining cytokine mRNAs with those encoding tumor-associated antigens further activated CD8+ T cell-mediated tumor control and enhanced survival after just a single dose in PDAC-bearing mice. Remarkably, lipid-based nanoparticle (NP) encapsulation of an all-in-one cytokine and antigen mRNA cocktail allowed safe systemic administration and local delivery of these immunogenic signals to autochthonous PDAC tumors in genetically engineered mouse models, culminating in complete tumor responses in 50% of animals. These results suggest that multiplexed mRNA approaches to delivering cytokine signals and antigens generally absent in the TME could pave the way for an effective immunotherapy for PDAC.

cancer biology↗

bioRxiv2025

Enhancing Volatile Fatty Acid Accumulation in Seaweed-Arrested Anaerobic Digestion via a Two-Tier Framework of Engineering Diagnostics and Microbial Surveillance

This study presents a two-tier framework for brown seaweed-arrested anaerobic digestion (SW-AAD) by coupling engineering diagnostics (tier-1) with microbial surveillance (tier-2) to transform conventional digesters into volatile fatty acid (VFAs) biorefineries. In 70-day lab-scale batch tests (volume: 2 L), engineering diagnostics revealed that sequential additions of brown seaweed elevated salinity to 3.3% ash content, stabilized pH at 5.8-6.1, collapsed the CH/CO2 ratio from 2.98 to <0.04, suppressed biogas by 96%, and boosted carbon-conversion efficiency from 10% to 52%. More than half of the influent carbon was redirected from methane to a liquid-phase VFAs pool, dominated by butyrate, hexanoate, and acetate, peaking at 14.5 g L-{superscript 1}. Microbial surveillance using 16S rRNA sequencing presented a 10-fold decline in methanogens, alongside an increase in salt- and acid-tolerant acidogenic microbial families, including Lachnospiraceae, Ruminococcaceae, and Clostridiaceae, as well as seaweed-derived microbial families, including Psychromonadaceae, and Marinomonadaceae. Temporal synchrony and asynchrony-resolved analysis confirmed a strong correlation between two tiers, revealing an operational window featured with two patterns: a rapid engineering parameter response (where changes in engineering parameters were followed by a decline in methanogens within 0-3 days) and a slower microbial restructuring (where the surge in VFA concentration lagged the enrichment of seaweed-derived acidogens by 1-5 days). Based on this operation window, feedback control strategies were simulated for SW-AAD, indicating that cumulative VFAs (cVFAs) yield could be bolstered from 11.38 to 16.13 g COD L-{superscript 1} (+41.8%). A techno-economic assessment (TEA) revealed that this VFA-targeted SW-AAD can reduce capital expenditure by [~]20% compared to conventional AD. This study underscores the promise of asynchrony-resolved analysis of SW-AAD systems for robust and economically viable VFAs production from organic waste. Graphics O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/680780v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1dc596dorg.highwire.dtl.DTLVardef@1731cadorg.highwire.dtl.DTLVardef@5fe025org.highwire.dtl.DTLVardef@74d8d3_HPS_FORMAT_FIGEXP M_FIG C_FIG Environmental synopsisBrown seaweed-arrested anaerobic digestion (SW-AAD) leverages seaweed-driven salinity, and acidification to suppress methanogenesis, diverting >50% of carbon to VFAs (14.5 g COD L-{superscript 1}) while cutting methane by 99%. A two-tier framework couples engineering diagnostics with microbial surveillance and asynchrony-resolved analysis, enabling feedback control and low-emission waste valorization in digesters.

bioengineering↗

bioRxiv2025

NQO1 phase condensation promotes stress granule assembly to facilitate pancreatic carcinogenesis

G3BP1 promotes pancreatic ductal adenocarcinoma (PDAC) tumorigenesis driven by oncogenic KRAS mutations through liquid-liquid phase separation (LLPS)-mediated assembly of stress granules (SGs). However, the regulatory mechanisms remain elusive. We identify the antioxidant enzyme NAD(P)H quinone dehydrogenase 1 (NQO1) as a novel SG regulator that enhances SG assembly in pancreatic cancer cells independently of reactive oxygen species (ROS). Mechanistic studies reveal that NQO1 does not regulate the expression of G3BP1 or other SG-associated genes. Instead, NQO1 undergoes LLPS dependent on its RNA-binding K homology (KH) like domain. Further analysis demonstrates that residues 121-131 of NQO1 directly interact with G3BP1s RNA-binding domain (RBD), enhancing the multivalency of G3BP1 complexes to potentiate LLPS-driven SG assembly. This interaction accelerates cell proliferation, KRAS mutation-induced acinar-to-ductal metaplasia (ADM), and pancreatic carcinogenesis. Notably, the interaction between NQO1 residues 121-131 and G3BP1s RBD is essential for NQO1 phase condensation under stress condition. Integrative analysis of human PDAC transcriptomic datasets reveals a weak association between NQO1 and G3BP1 levels. Importantly, both NQO1 and G3BP1 formed biological condensates and co-localized in the lesions of human PDAC tissue sections. Our study uncovers a novel KRAS mutation-driven mechanism of pancreatic carcinogenesis through the lens of phase separation, transcending conventional gene expression regulation and offering new insights into non-canonical KRAS-NQO1-G3BP1-SG regulatory networks in PDAC initiation.

cancer biology↗