Biology subjects

Zuo, Z.

Publications and source records attributed to Zuo, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

An AI System for Autonomous Algorithm Evolution in Drug Development

Artificial intelligence (AI) is increasingly permeating the drug development pipeline. Numerous algorithms for accelerating this multi-stage and multi-task process have been constructed, which depends heavily on expert design and labor-intensive task-specific optimization. Given that AI-driven acceleration of drug development is recognized as a cumulative, often synergistic, effect across multiple stages, the autonomous evolution of existing algorithms across the entire pipeline is demanded to achieve a holistic advancement. Here, we present DrugEvolve, a multi-role large language model system for systematic and autonomous algorithm evolution in drug development. DrugEvolve realizes a closed-loop evolution process by incorporating Researcher, Engineer, and Analyst domains, and enables an iterative design, implementation, evaluation, and refinement of algorithm by leveraging scientific knowledge and accumulated evolutionary experience. Across eleven representative tasks spanning target identification, drug discovery, preclinical study, and clinical trial, DrugEvolve autonomously evolved the corresponding task-specific algorithms and achieved substantial performance enhancement on 120 benchmark test sets. Moreover, it showed robust generalizabilities across heterogeneous data modalities (ranging from biological sequence and graph to molecular topology and textual language), and realized gains in both predictive and generative tasks. Collectively, this AI system can serve not only as an algorithmic infrastructure for drug development, but also as a transferable paradigm for broader scientific domains.

pharmacology and toxicology↗

bioRxiv2026

Synora: vector-based boundary detection for spatial omics

Tumor-stroma boundaries are critical microenvironmental niches where malignant and non-malignant cells exchange signals that shape invasion, immune modulation and therapeutic response. Spatial omics platforms now resolve these interfaces at single-cell scale, but computational boundary detection remains challenging because heterogeneous neighborhoods can arise either from true compartment interfaces or from unstructured immune infiltration. Here we present Synora, a modality-agnostic computational framework that identifies tumor boundaries using only cell coordinates and binary tumor/non-tumor annotations, making it readily applicable across a broad range of spatial omics modalities. Synora introduces orientedness, a novel metric that quantifies directional neighborhood asymmetry and distinguishes true boundary cells, where neighbors are spatially segregated by type, from infiltrated regions where cell types intermingle randomly. By integrating orientedness with traditional diversity measures into a unified BoundaryScore, Synora achieves robust boundary identification across synthetic datasets with ground-truth boundaries, maintaining performance under realistic perturbations including 50% missing cells and 25% infiltration. Application to 15 Visium HD spatial transcriptomic datasets across multiple cancer types reveals consistent boundary-enriched gene signatures and cell-type spatial gradients. Validation on a CODEX multiplexed protein dataset demonstrates that Synoras precise boundary identification enables discovery of clinically relevant cellular neighborhoods and disease-associated spatial patterns missed by frequency-based approaches. Synora enables boundary-aware spatial analyses by making tissue interfaces quantifiable from minimal inputs, helping to standardize interface detection and comparison across spatial omics platforms and biological contexts.

bioinformatics↗

bioRxiv2026

Mapping the North American Terrestrial Carbon Cycle: A Process-based Reanalysis Using State Data Assimilation (SDA)

AbstractThe ability to accurately assess ecosystem C budgets across scales from individual sites to continents is essential for C accounting, management, and ultimately mitigating climate change. State data assimilation (SDA) provides a framework for harmonizing observations with models, while robustly accounting for and reducing multiple sources of uncertainty. In this study, we employed a hybrid SDA framework that combines process-based terrestrial biosphere modeling, hierarchical Bayesian inference, and machine learning to harmonize bottom-up and remotely-sensed data streams for 8,000 pre-selected 1km2 locations across North America within a hybrid structure. Combining bottom-up soils data (SoilGrids) with spectral (MODIS and Landsat) and microwave (SMAP) remote sensing helps constrain the major C and water stocks through space and time. Machine learning is used both to identify and correct systematic errors in the process model (SIPNET) and to interpolate the pre-selected locations onto a 1km grid, making it computationally feasible to generate annual ensemble maps of the North American carbon budget. Furthermore, the uncertainties for each variable were reduced compared to those from observations or models alone. Spatiotemporal analysis showed a slight decrease in aboveground biomass (AGB) across the western US, a loss of leaf area across the boreal, and a slight greening of the Alaskan tundra. The uncertainty trends suggest a significant reduction in the uncertainty about soil organic carbon (SOC), the largest C reservoir. Validation results show that we accurately estimate C pools, compared to the assimilated data streams and held-out observations of AGB from GEDI, ICESat-2, and the US FIA, and SOC from the ISCN network. Our ML-debiasing algorithm further improved the accuracy of major C pools (AGB, SOC). In general, our continental SDA framework will facilitate global C MRV (monitoring, reporting, and verification) by providing accurate and precise C-cycle estimates, along with their corresponding spatiotemporal uncertainties.

ecology↗

bioRxiv2026

MATR3 is essential for oocyte growth and maturation quality through a dual molecular mechanism

The molecular mechanisms governing mRNA accumulation during oocyte growth, essential for developmental competence, remain poorly understood. This study investigates the role of Matrin-3 (MATR3), a highly expressed RNA-binding protein in growing oocytes (GOs), using oocyte-specific knockout mouse models and human oocyte maturation arrest (OMA) samples. The results showed that MATR3 was more abundant in GOs than fully-grown oocytes (FGOs), highly expressed in the nucleus of non-surrounded nucleolus (NSN) oocytes, and exited the nucleus during the NSN-to-surrounded nucleolus (SN) transition. In OMA patients, MATR3 nuclear localization was missed, with smaller oocytes than FGOs. Further, Matr3 deletion in mouse GOs caused restricted oocyte growth, global transcription disorders, follicle development failure, blocked GO-granulosa cell communication (via reduced Gdf9 and Radixin expression), and infertility. Mechanistically, MATR3 regulated transcription by recruiting H3K9me2-demethylating lysine-specific demethylase 3B or binding target gene promoters, like Radixin. These findings reveal a critical role of MATR3 in orchestrating transcription and paracrine signaling during oogenesis and suggest its potential as a diagnostic and therapeutic target for OMA.

physiology↗

bioRxiv2026

PlotGDP: an AI Agent for Bioinformatics Plotting

High-quality bioinformatics plotting is important for biology research, especially when preparing for publications. However, the long learning curve and complex coding environment configuration often appear as inevitable costs towards the creation of publication-ready plots. Here, we present PlotGDP (https://plotgdp.biogdp.com/), an AI agent-based web server for bioinformatics plotting. Built on large language models (LLMs), the intelligent plotting agent is designed to accommodate various types of bioinformatics plots, while offering easy usage with simple natural language commands from users. No coding experience or environment deployment is required, since all the user-uploaded data is processed by LLM-generated codes on our remote high-performance server. Additionally, all plotting sessions are based on curated template scripts to minimize the risk of hallucinations from the LLM. Aided by PlotGDP, we hope to contribute to the global biology research community by constructing an online platform for fast and high-quality bioinformatics visualization. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/702995v3_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@73c77dorg.highwire.dtl.DTLVardef@12ddfc6org.highwire.dtl.DTLVardef@be5963org.highwire.dtl.DTLVardef@de90b6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract.C_FLOATNO PlotGDP: an AI Agent for Bioinformatics Plotting C_FIG

bioinformatics↗

bioRxiv2025

An approach to differentiating biological from chemical sulfide oxidation on corroded concrete sewer surfaces

Hydrogen sulfide (H2S)-induced sewer corrosion largely impacts the longevity of infrastructure worldwide. The corrosion incorporates two pathways, i.e., chemical and biological oxidation of H2S to sulfuric acid; however, their rates are difficult to differentiate on corroded sewer pipelines, limiting understanding and application of effective strategies for corrosion control. Here, this study develops and reports a kinetic approach to determining rates of chemical and biological sulfide oxidation. By measuring the total sulfide uptake rate of sewer corrosion concretes, extensive experimental data was obtained for calibration and validation of the proposed kinetic model. The modelling results fit with measured data indicating that both chemical and biological sulfide oxidation can be well-described by the developed model. Model predictions revealed that along with sewer corrosion (i.e., pH decrease), chemical sulfide oxidation rate was significantly accelerated, along with an increase in biological rate. This result suggests that the chemical sulfide oxidation process should not be overlooked for seriously corroded concretes, and synergistic strategies to suppress both biological and chemical rates are required. Specifically, the chemical process can predominate sulfide oxidation with a gas-H2S concentration higher than 300 ppm. The work provides a useful tool for future corrosion studies and also valuable insights for sewer corrosion management practices. SynopsisThis study reports a kinetic approach to determining chemical and biological H2S oxidation rates of sewer concretes. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/653906v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1cfd16aorg.highwire.dtl.DTLVardef@bd9677org.highwire.dtl.DTLVardef@e1610forg.highwire.dtl.DTLVardef@ab3dfc_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Electromotility can be disassociated from gating charge movement in outer hair cells of conditional alpha2 spectrin knockout mice.

Electromotility in mammalian outer hair cells (OHC) is the mechanism underlying cochlear amplification. It is brought about by the piezoelectric-like property of the membrane protein prestin (Slc26a5) that lies in the OHCs lateral plasma membrane. Prestin connects to an underlying cytoskeletal network of circumferential actin filaments that bridge longitudinal spectrin filaments. This network, in turn, lies between the plasma membrane and a closely apposed ER-like tubular array of subsurface cisternae (SSC). Two previous papers examining spectrin knockouts in embryonic hair cells were confined to analyzing the effects on the apical cuticular plate and overlying stereocilia. In this paper, we examine the effects of conditional knockouts of alpha2 spectrin in postnatal OHCs. We find a significant auditory phenotype likely due to the novel disassociation of prestins gating charge movement from OHC electromotility. In addition, OHCs show enlargement in their SSC and plasma membrane-SSC space with preserved cuticular plates and overlying stereocilia, which contrasts with the findings in embryonic knockouts.

physiology↗

bioRxiv2024

Tetanizing wakeful consolidation: ten-hertz repetitive visual stimulation enhances the offline gain of visual learning

Consolidation of encoded information is vital for learning and memory, often explored during sleep. However, the consolidation during post-encoding offline wakefulness remains largely uncharted, especially regarding its modulation and brain mechanisms. Here, we unraveled frequency-dependent modulatory effects of repetitive visual stimulation (RVS) on wakeful consolidation of visual learning and investigated the underlying neural substrates. After training on an orientation discrimination task, exposure to 10-Hz grating-form RVS enhanced, while 1-Hz RVS deteriorated, the discrimination performance in a subsequent retest. However, 10-Hz uniform-disk RVS failed to facilitate wakeful consolidation, suggesting that alpha entrainment alone was not the facilitative mechanism. Using neuroimaging of multiple modalities, we observed augmented event-related potential and heightened neural excitation in the early visual cortex after 10-Hz grating-form RVS, implying an involvement of long-term potentiation-like (LTP-like) plasticity. Collectively, we provide a new photic method for modulating the offline processing of encoded sensory information and suggest a role of sensory tetanization in the modulation.

neuroscience↗

bioRxiv2024

Centimeter-scale, physiologically relevant intestinal organoids generated entirely from pluripotent stem cells

Over the past decade, intestinal organoids have shown great promise as a platform to study the development of intestine, elucidate the pathogenesis of diseases such as inflammatory bowel disease (IBD), and model physiological features of intestinal tissue for high-throughput drug screening. However, intestinal organoids derived from adult epithelial stem cells lack cellular diversity, especially those resides in the lamina propria. Intestinal organoids derived from embryonic stem (ES) cells or induced-pluripotent stem cells (iPSCs) has greater cellular diversity, but are still limited in size and physiological features such as peristalsis. In this study, we generated centimeter-scale, full-thickness, and physiologically relevant intestinal organoids in suspension culture without usage of Matrigel. Using a series of optimized culture media, multiple lineages of cells were differentiated from iPSCs and spontaneously assembled to achieve the intestinal architecture. These bubble-like organoids have a thickness of 500 microns, exhibit a mature vasculature network, and have smooth muscle-like cells to conduct regular peristalsis. In addition, adipocyte-like cells and granulocyte-like cells are also observed in these organoids, which are important in immune homeostasis. Lastly, these organoids show mature crypt structures, response to lipopolysaccharides (LPS), and increases luminal influx upon forskolin treatment, suggesting the organoids have intact epithelial integrity. Thus, this study provides a highly reproducible approach to produce large and physiologically relevant intestinal organoids that are suitable for different biomedical applications.

cell biology↗

bioRxiv2024

Thermophilic Fungus Uses Anthraquinones to Modulate Ferrous Excretion, Sterol-Mediated Endocytosis and Iron Storage in Response to Cold Stress

To date, there is no real physiological mechanisms for iron excretion in eukaryote, and no physiological "actuator" that can control all the three fundamental biologic processes of absorption, storage and excretion. Here we observed that the accumulation of anthraquinones by Thermomyces dupontii under cold stress can achieve this process. Through mutation analysis, we found that mutant {Delta}An deficiency in anthraquinones accumulated ferrous and total free iron due to adopting a rare lifestyle with no endocytosis but accumulation of membrane-derived vesicles. Anthraquinone complement indicated that the vesicles in {Delta}An could coat the extrinsic anthraquinone-induced granules to prevent contact with the fungal interiors. Detailed chemical investigation on {Delta}An led to characterization of a rare oxygen-free ergosterene with unstable nature in air as the major membrane steroid in {Delta}An, suggesting hypoxia inner in {Delta}An cells, consistent with dramatically low oxygen-consuming rates in {Delta}An. A series of physiological and metabolic analysis indicated anthraquinones were involved in exporting ferrous and promoting formation of oxygen-containing metabolites, including ergosterols for endocytosis and iron chelators for iron storage. Moreover, we found that both the anticancer agent mitoxantrone with well know-cardiotoxicity side effect and the major terpenoid-derived polycyclic aromatics from Danshen for treating cardiovascular disease showed potent ferrous transporting capabilities in human cancer cells. Our findings provide a novel insight into the underlying mechanisms of polycyclic aromatics in nature and pharmacology, and offer new strategy for developing potential therapeutics and agents for membrane transport, iron homestasis and anticold. Graphical AbstractUp to now, regulation of iron homeostasis by metabolites have rarely been characterized. Moreover, no excretory mechanisms for iron in fungi have been reported. In this study, we found that Thermomyces dupontii can accumulate a large amount of anthraquinones under cold stress. The anthraquinones can release free ferric ion, reduce ferric to ferrous ions, and export ferrous ions, greatly enhancing thermophilic fungus to survive in the bio-system environment. Furthermore, lack of the anthraquinones can inhibit oxygen-dependent ergosterol mediated endocytosis, leading to an self-imposed isolation via oxygen-free ergosterene-mediated cell membranes. Importantly, the well known anthraquinone compound Mitoxantraquinone for anticancer and the main terpenoid polycyclic aromatic metabolites in traditional Chinese medicine Danshen for the treatment of cardiovascular diseases both exhibit strong ferrous ions transport capabilities. Our findings provided new insights for developing potential therapies and drugs for iron homeostasis and drug delivery. O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/605589v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@114551eorg.highwire.dtl.DTLVardef@1e03589org.highwire.dtl.DTLVardef@dad51borg.highwire.dtl.DTLVardef@dd0601_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

The asymmetric transfers of visual perceptual learning determined by the stability of geometrical invariants

We quickly and accurately recognize the dynamic world by extracting invariances from highly variable scenes, a process can be continuously optimized through visual perceptual learning (VPL). While it is widely accepted that the visual system prioritizes the perception of more stable invariants, the influence of the structural stability of invariants on VPL remains largely unknown. In this study, we designed three geometrical invariants with varying levels of stability for VPL: projective (e.g., collinearity), affine (e.g., parallelism), and Euclidean (e.g., orientation) invariants, following the Kleins Erlangen program. We found that learning to discriminate low-stability invariant transferred asymmetrically to those with higher stability, and that training on high-stability invariants enabled location transfer. To explore learning-associated plasticity in the visual hierarchy, we trained deep neural networks (DNNs) to model this learning procedure. We reproduced the asymmetric transfer between different invariants in DNN simulations and found that the distribution and time course of plasticity in DNNs suggested a neural mechanism similar to the reverse hierarchical theory (RHT), yet distinct in that invariant stability--not task difficulty or precision--emerged as the key determinant of learning and generalization. We propose that VPL for different invariants follows the Klein hierarchy of geometries, beginning with the extraction of high-stability invariants in higher-level visual areas, then recruiting lower-level areas for the further optimization needed to discriminate less stable invariants.

neuroscience↗

bioRxiv2023

Towards ultra-low-cost smartphone microscopy

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to [~]9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of [~] 5 {micro}m, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we use an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We use the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance. Research highlightsWe propose a solution for ultra-low-cost smartphone microscopy. Utilizing the flexibility of 3D-printed material, we can achieve focusing accuracy of [~] 5 {micro}m. Such a low-cost device will benefit point-of-care diagnosis and home health surveillance.

bioengineering↗

bioRxiv2023

Integrated multi-omics single cell atlas of the human retina

Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here, we present an integrated multimodal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 2.4 million cells from 55 donors, including 1.4 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) of transcriptome and chromatin accessibility, unveiling over 110 types. Engaging the retina community, we annotated each cluster, refined the Cell Ontology for the retina, identified distinct marker genes, and characterized cis-regulatory elements and gene regulatory networks (GRNs) for these cell types. Our analysis uncovered intriguing differences in transcriptome, chromatin, and GRNs across cell types. In addition, we modeled changes in gene expression and chromatin openness across gender and age. This integrated atlas also enabled the fine-mapping of GWAS and eQTL variants. Accessible through interactive browsers, this multimodal cross-donor and cross-lab HRCA, can facilitate a better understanding of retinal function and pathology.

molecular biology↗

bioRxiv2023

Metabolic Nutrient Preferences of Vibrio mimicus: Leveraging Nucleotides and Oligopeptides from Yellow Catfish for Enhanced Infectivity

In the context of host-microbe interactions, the microenvironment plays a critical role in facilitating microbial survival, and variations in these microenvironments may influence the pathogenicity of microorganisms. Vibrio mimicus, a major pathogen responsible for infections in aquatic animals, poses a substantial threat to yellow catfish (Pelteobagrus fulvidraco) and grass carp (Ctenopharyngodon idella), two naturally occurring hosts displaying markedly different susceptibility levels. This study aims to unravel the underlying mechanisms behind this susceptibility discrepancy in the two teleost species. Employing metabolomic analysis, we identified a distinctive microenvironment in yellow catfish, characterized by abundant purine nucleotides and oligopeptides. Furthermore, a total of 67 specific metabolites were identified from both yellow catfish and grass carp, with 33 displaying heightened expression on the body surface of yellow catfish, including nucleotides, amino acids, and gangliosides, while 34 were predominantly expressed on the body surface of grass carp, primarily comprising lipids. Subsequent investigations revealed that certain compounds related to nucleotides and oligopeptides exhibited significant growth-promoting effects and were utilized by V. mimicus as nutrients, with deoxyguanosine proving to be notably more than twice as effective as glucose. Moreover, during V. mimicus infection, numerous metabolites such as oligopeptides, purine nucleotides, and specific metabolites experienced considerable depletion in the skin of yellow catfish. Concurrently, several genes associated with nucleosidase and peptidase were upregulated in the skin and muscles of infected fish. These findings suggest that the microenvironment provided by different hosts plays a pivotal role in determining the infectivity of the pathogen. Additionally, our results indicate that the microenvironment on the surface of yellow catfish, characterized by an abundance of purine nucleotides and oligopeptides, indirectly enhances V. mimicus growth, ultimately augmenting its infectivity.

microbiology↗

bioRxiv2023

FM3VCF: A Software Library for Accelerating the Loading of Large VCF Files in Genotype Data Analyses

BackgroundThe increasing size of genotype data has led to the loading of VCF files becoming a computational bottleneck in various analyses, including imputation and genome-wide association studies (GWAS). To address this issue, we developed a software library, FM3VCF (fast M3VCF), that utilizes multiple CPU threads to accelerate this process. FindingsFM3VCF can convert VCF files into the exclusive data format of MINIMAC4[1], M3VCF[1], and efficiently read and parse data from VCF files. In comparison to m3vcftools[1], FM3VCF is approximately 20 times faster for compressing VCF files to M3VCF format. Furthermore, FM3VCF is approximately 3 times faster than HTSlib[2], including decompressing and parsing, for reading compressed VCF files. FM3VCF is written in C and is open-source, available for download from https://github.com/Oliver-111/m3vcf under the MIT/BSD license. ConclusionFM3VCF is a powerful tool for accelerating the loading of large VCF files in genotype data analyses. By fully utilizing multiple CPU threads, FM3VCF can significantly reduce the computational burden in various genomic analyses.

bioinformatics↗

bioRxiv2023

Diversification of Nucleoside Analogues as Potent Antiviral Drug Leads

Nucleoside analogues are potent antiviral agents, but the continuous emergence of pathogenic viruses demands novel and diverse structures. Herein, we have created a diversified library of highly bioactive and non-cytotoxic nucleoside analogues featuring an unprecedented carbobicyclic core that mimics natural ribonucleoside conformation. These regio- and stereo-divergent analogues exhibit up to 16-fold greater antiviral efficacy than the FDA-approved antiviral, ribavirin. Importantly, the carbobicyclic core structure is critical for the potent antiviral efficacy, thus opening up ample opportunities for further lead optimization and mechanistic investigations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/545395v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@fbd078org.highwire.dtl.DTLVardef@3399a9org.highwire.dtl.DTLVardef@1ad5fcborg.highwire.dtl.DTLVardef@16c2f3d_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Leading Basic Modes of Spontaneous Activity Drive Individual Functional Connectivity Organization in the Resting Human Brain

Spontaneous activity of the human brain provides a window to explore intrinsic principles of functional organization. However, most studies have focused on interregional functional connectivity. The principles underlying rich repertoires of instantaneous activity remain largely unknown. We apply a novel eigen-microstate analysis to three resting-state functional MRI datasets to identify basic modes that represent fundamental activity patterns that coexist over time. We identify a few (i.e., five) leading basic modes that dominate activity fluctuations. Each of these modes exhibits a distinct functional system-dependent coactivation pattern and corresponds to specific cognitive profiles. In particular, the spatial pattern of the first leading basis mode shows the separation of activity between the default-mode and primary and attention regions. We further reconstruct individual functional connectivity as the weighted contribution of these leading basic modes based on theoretical modelling. Moreover, these leading basic modes capture sleep deprivation-induced changes in brain activity and interregional connectivity, primarily involving the default-mode and task-positive regions. Our findings reveal a dominant set of basic modes of spontaneous activity that reflect multiplexed interregional coordination and drive conventional functional connectivity, furthering the understanding of the functional significance of spontaneous brain activity.

neuroscience↗

bioRxiv2023

Loss of Mitochondrial Enoyl CoA Reductase causes elevated ceramide levels and impairs iron metabolism

In most eukaryotic cells fatty acid synthesis occurs in the cytoplasm as well as in mitochondria. However, the relative contribution of mitochondrial fatty acid synthesis (mtFAS) to the cellular lipidome of metazoans is ill-defined. Hence, we studied the function of the fly Mitochondria enoyl CoA reductase (Mecr), the enzyme required for the last step of mtFAS. Loss of mecr causes lethality while neuronal loss leads to progressive neurological defects. We observe an elevated level of ceramides, a defect in Fe-S cluster biogenesis and increased iron levels in mecr mutants. Reducing the levels of either iron or ceramide suppresses the neurodegenerative phenotypes indicating that increased ceramides and iron metabolism are interrelated and play an important role in the pathogenesis. Mutations in human MECR cause pediatric-onset neurodegeneration and patient-derived fibroblasts display similar elevated ceramide levels and impaired iron homeostasis. In summary, this study shows an as-yet-unidentified role of mecr/MECR in ceramide and iron metabolism providing a mechanistic link between mtFAS and neurodegeneration.

neuroscience↗