Biology subjects

Deng, Y.

Publications and source records attributed to Deng, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Integrating Multimodal Data for a Comprehensive Knowledge Graph to Advance Infectious Disease Research

Infectious diseases remain a formidable threat to global public health, with their escalating morbidity and mortality rates compounded by recurrent epidemics and the alarming rise of antimicrobial resistance (AMR). These challenges have intensified the urgent demand for innovative therapeutic strategies that can accelerate drug development cycles and overcome traditional research bottlenecks. To address these critical needs, we present IDKG (Infectious Disease Knowledge Graph), a specialized large-scale biomedical knowledge network designed to bridge data fragmentation through multimodal data integration. The IDKG constructs comprehensive associations from 345 infectious diseases and 708 pathogens across heterogeneous biomedical sources systematically. The graph architecture comprises nearly 50,000 nodes (8 types, including Pathogen, Protein, etc.) and over 1.2 million edges (11 types, including treats, contains, etc.), establishing an interconnected framework that enables systematic interrogation of cross-disciplinary knowledge. The integrative approach effectively dismantles conventional data silos while preserving biological contextuality. We validated the IDKGs potential by applying graph neural network-based approaches for drug repurposing prediction in human metapneumovirus (hMPV) infection, a common acute respiratory infection for which effective specific antiviral drugs are currently absent. The successfully identification of established antiviral agents, such as ribavirin and emetine, by our M1 model demonstrated its predictive accuracy and biological relevance. IDKG unifies multimodal biomedical data into a network to accelerate drug discovery and bolster outbreak response. This establishes a data-driven, knowledge-based paradigm for infectious disease research. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/657361v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@f5dc24org.highwire.dtl.DTLVardef@147d584org.highwire.dtl.DTLVardef@113083corg.highwire.dtl.DTLVardef@81d523_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Peptides alleviate cognitive impairment by inhibiting and disassembling amyloid-beta aggregates in Alzheimer disease

Alzheimers disease (AD) is a devasting neurodegenerative disorder characterized by {beta}-amyloid formation, further exacerbated by RIPK1/RIPK3 necrosome-induced programmed necrosis (necroptosis). We previously showed that the RIPK1/RIPK3 necrosome forms a functional amyloid complex using its RIP homotypic interaction motifs (RHIMs). Here, we discovered that the core RIPK1/RIPK3 necrosome shares strikingly structural similarity to the C-terminal region of {beta}-amyloid (A{beta}42), and the RHIM-derived tetrapeptides (IQIG or VQVG) directly inhibit A{beta} aggregation, disassemble preformed A{beta} fibrils (PFFs), and reduce RIPK1 polymerization. Also, the peptides exhibit effective membrane permeability and could reduce A{beta}40 or A{beta}42-induced neural death and TNF-induced necroptosis in SH-SY5Y cells. IQIG and VQVG injected by ICV increase learning and memory abilities by reducing A{beta} plaques and hyperphosphorylated tau in the cortex and hippocampus of APP/PS1 double-transgenic mice. Mechanistically, the peptides directly interact with A{beta} to block A{beta} aggregation and alleviate microglia-mediated neuroinflammation. Strikingly, single-cell RNA sequencing revealed that the peptides-treated AD transgenic mice restored neuronal homeostasis with increased GABAergic neurons and decreased glutamatergic neurons. Furthermore, total cell-cell interaction strength increased while the AD risk gene Apoe expression decreased in the specific oligodendrocyte subtype of peptides-treated AD mice. Thus, our findings revealed that the peptides could improve cognition and memory capabilities and serve as promising structural templates for potential drugs against AD.

neuroscience↗

bioRxiv2025

Analysis of isobaric quantitative proteomic data using TMT-Integrator and FragPipe computational platform

Isobaric mass tags, such as iTRAQ and TMT, are widely utilized for peptide and protein quantification in multiplex quantitative proteomics. We present TMT-Integrator, a bioinformatics tool for processing quantitation results from TMT and iTRAQ experiments, offering integrative reports at the gene, protein, peptide, and post-translational modification site levels. We demonstrate the versatility of TMT-Integrator using five publicly available TMT datasets: an E. coli dataset with 13 spike-in proteins, the clear cell renal cell carcinoma (ccRCC) whole proteome and phosphopeptide-enriched datasets from the Clinical Proteomic Tumor Analysis Consortium, and two human cell lysate datasets showcasing the latest advances with the Astral instrument and TMT 35-plex reagents. Integrated into the widely used FragPipe computational platform (https://fragpipe.nesvilab.org/), TMT-Integrator is a core component of TMT and iTRAQ data analysis workflows. We evaluate the FragPipe/TMT-Integrator analysis pipelines performance against MaxQuant and Proteome Discoverer with multiple benchmarks, facilitated by the bioinformatics tool OmicsEV. Our results show that FragPipe/TMT-Integrator quantifies more proteins in the E. coli and ccRCC whole proteome datasets, identifies more phosphorylated sites in the ccRCC phosphoproteome dataset, and delivers overall more robust quantification performance compared to other tools.

bioinformatics↗

bioRxiv2025

The potential of 4-Methylumbelliferone to be repurposed for treating liver fibrosis

4-Methylumbelliferone (4-MU) is the active component of hymecromone, a choleretic and antispasmodic drug with an excellent safety profile. In rodent studies, high doses of 4-MU are also used to inhibit the production of hyaluronan (HA), a biomarker of liver fibrosis. Further, 4-MU shows excellent efficacy in inhibiting liver fibrosis of different etiologies in animal studies, eliciting interest in its repurposing for this condition. However, 4-MUs mechanism of action, and whether it inhibits liver fibrosis by impeding HA synthesis, remains unclear. Using several transgenic mouse models with HA overproduction or degradation in different types of liver cells, we found that both directions of perturbation reduced liver fibrosis levels. In addition, degrading HA via hyaluronidase PH20 overexpression impaired liver function manifested by increased serum aminotransferase (ALT) activity levels. These findings challenge both the role of HA modulation in 4-MUs action and the strategy of targeting HA to treat liver fibrosis. Additional mouse models also excluded the possibility that 4-MU modulates intestinal farnesoid X receptor (FXR) to inhibit liver fibrosis. Ablation of gut microbiota partially abolishes 4-MUs anti-liver fibrosis effect. However, the anti-liver fibrosis effect of 4-MU was lost in the lower-dose group, and the high doses effect in reducing ALT disappeared over time despite its liver fibrosis-reducing effect. Based on these findings, we argue that the lack of efficacy of 4-MU at a translatable dose and lack of a clear mechanism that allows further improvement of 4-MUs efficacy make 4-MU impractical for development as an anti-liver fibrosis treatment. HighlightsO_LI4-MU inhibits MASH fibrosis. C_LIO_LIBoth HA overproduction and digestion in the liver reduce liver fibrosis. C_LIO_LIIntestinal epithelial cell FXR is not required for 4-MU to reduce liver fibrosis. C_LIO_LIThe gut microbiota is partially responsible for 4-MUs antifibrotic effect in the liver. C_LIO_LI4-MU lacks the potential to be further developed into anti-liver fibrosis treatment. C_LI

molecular biology↗

bioRxiv2025

Trophic and temporal dynamics of macrophage biology in human inner ear organogenesis

Recent single-cell transcriptomic approaches are uncovering the breadth and depth of cell diversity within the mammalian inner ear. Macrophages, detected from gestational week 7 in the human inner ear, persist into adulthood, and yet remain poorly understood in terms of their origin and function. Using self-generated and public scRNA-seq data, we identify seven distinct macrophage subtypes spanning fetal weeks 7.5 to 16.4 and adulthood. Each macrophage subtype is linked to specific developmental stages and displays a unique gene expression profile. These findings corroborate earlier histological evidence of resident and non-resident macrophages in both the developing and adult human cochlea. We also show that the human inner ear is seeded by macrophages from both embryonic and more definitive sources, corroborating studies in mouse. By analyzing ligand-receptor interactions, we highlight potential macrophage contributions to inner ear organogenesis. This research provides new insights into the diverse roles of human inner ear macrophages.

bioinformatics↗

bioRxiv2025

mtgRNA-db: An annotated database of multi-target CRISPR-Cas9 guide-RNAs in the human genome

CRISPR-Cas9 guide-RNA design tools can be used to identify guide-RNAs that target single human genomic loci. However, these approaches limit their effect to a single locus. Here, we generate a database of potential individual guide-RNAs that target multiple sites in the genome at once. All guide-RNAs in this database are curated with on- and off-target quantification and enrichment scores for genomic elements such as gene elements, regulatory elements, repetitive elements, and transcription factor motifs. This tool enables rationale mass targeting of genomic loci with a single guide for functional studies. We created a web-app for user-friendly guide-RNA selection (https://modreklab.shinyapps.io/guiderna/).

bioinformatics↗

bioRxiv2025

Spatial distribution of cytoskeleton-mediated feedback controls cell polarization: a computational study

In the social amoeba Dictyostelium, cell motility is regulated through a signal transduction excitable network that interfaces with the cytoskeleton to control actin polymerization patterns. In turn, the cytoskeleton influences the signaling machinery via several feedback loops, but the nature and function of this feedback remain poorly understood. In this study, we use computational models to discern the essential role of complementary positive and negative feedback loops in polarizing cells. We contrast two potential mechanisms for the negative feedback: local inhibition and global inhibition. Our results indicate that both mechanisms can stabilize the leading edge and inhibit actin polymerization in other sites, preventing multipolarity. While some experimental perturbations align more closely with the local inhibition model, statistical analyses reveal its limited polarization potential within a wide excitability range. Conversely, global inhibition more effectively suppresses secondary and tertiary leading-edge formation, making it a more robust polarization mechanism. This raises an intriguing question: if local inhibition better replicates experimental observations but is less effective for polarization than local excitation and global inhibition, could there be a supplementary mechanism enhancing its polarization potential? To address this, we propose a novel mechanism involving the dynamic partitioning of back molecules which enhances communication between the front and back of the cell and can be leveraged by local feedback interactions between the cytoskeleton and signal transduction to improve polarization efficiency.

cell biology↗

bioRxiv2025

Exploring Population Differences in the Human Gut Microbiome: from Microbial Abundance to Single Nucleotide Polymorphisms

The human gut microbiota exhibits significant diversity across populations, influenced by factors such as geography, diet, and lifestyle, particularly between the Han Chinese and non-Chinese populations. While previous studies have predominantly focused on the taxonomic abundance of the gut microbiome, the impact of single nucleotide polymorphisms (SNPs) in driving population-specific differences remains largely underexplored. In this study, we systematically investigated gut microbial differences between the Han Chinese and non-Chinese populations using the Human Gut Microbiome Reference Genome Catalog (HGMRGC). HGMRGC includes 271,480 non-redundant genomes from 5,785 prokaryotic species, which was generated by metagenomic sequencing data from 9,320 publicly available samples across 22 countries and 3,584 newly sequenced samples from Han Chinese individuals across 29 provinces and regions in China. We observed geography was the primary driver of microbial variation of abundance and SNPs. We identified 625 novel population-specific genome clusters from HGMRGC with functional differences in carbohydrate utilization and 126 species exhibiting distinct prevalence related to vitamin biosynthesis, antibiotic resistance, and carbohydrate metabolism. Beta diversity analysis highlighted significant inter-population differences in both microbial abundance and SNPs, while alpha diversity analysis revealed that non-Chinese populations exhibited higher diversity in microbial abundance, and Han Chinese populations displayed greater diversity in SNPs. These results provide valuable insights into population-specific microbial diversity, laying the groundwork for future research on its functional and health implications.

microbiology↗

bioRxiv2025

Gap-free genomes and transcriptomes uncover race-specific effectors in watermelon wilt pathogen Fusarium oxysporum f. sp. niveum

Watermelon (Citrullus lanatus L.) is one of the worlds most economically important fruit crops, yet it is susceptible to devastating diseases such as vascular wilt caused by Fusarium oxysporum f. sp. niveum (Fon), with limited effective control measures. Fon evolves rapidly in the field to overcome host resistance and global watermelon production is constantly threatened by new pathogenic races. High-quality genomic resources are key to understanding the molecular mechanisms underlying Fon virulence evolution for disease management. Here, we de novo assembled and annotated gapless genomes of three physiological races of Fon (race 1, 2, and 3), and dissected the mechanisms behind their distinctive virulence through comparative genomics and transcriptomics. Whole-genome alignments identified core and accessory chromosomes in Fon where each race carried a unique set of accessory chromosomes or regions. Comparative transcriptomics of Fon infection revealed distinctive temporal patterns of gene expression even among core gene families, particularly those related to cell wall degradation enzymes. Effectoromic prediction and comparative analysis in three gap-free genomes identified 13 race-specific effectors (RSEs) in FonR3, one (FonRSE1) of which was a critical virulence factor of FonR3 on watermelon as demonstrated via functional experiments. The gap-free genome assemblies and annotations, and the RSEs are valuable resources for studying Fon pathobiology and genome evolution, adding in the design of improved disease control strategies.

genomics↗

bioRxiv2025

Device encapsulated MSCs for adaptive secretome therapy to effectively target ischaemic heart injury

Effective long-term strategies to protect the ischaemic heart remain a significant challenge. Mesenchymal stem cells (MSCs) offer therapeutic potential primarily through their secretome, a bioactive factor-rich milieu with broad beneficial effects. However, existing delivery methods have not been shown to provide sustained benefits. Herein, we introduce an innovative approach for sustained MSC-secretome delivery for long-term cardioprotection. In a rat model of chronic myocardial infarction, Cymerus MSCs, derived from human induced pluripotent stem cells (iPSCs), were encapsulated in a Procyon immunoisolation device and implanted subcutaneously. A human-iPSC-derived engineered cardiac microtissue model was used to simulate ischaemia-reperfusion injury and assess cardioprotective effects in a human context. The MSC-loaded Procyon device significantly improved cardiac function and reduced adverse left ventricular remodelling over a 12-week period. These positive effects were consistent across both young and middle-aged, male and female rats, indicating broad applicability. The encapsulated MSCs remained viable and continuously released therapeutic secretome for 12 weeks. In vitro, the MSC secretome protected human engineered cardiac microtissues from simulated ischaemia-reperfusion injury, restoring contractile function, improving cell viability, and reducing oxidative stress. Proteomic analysis of MSCs revealed 179 unique cellular proteins post-implantation, linked to adaptive immune and inflammatory responses as well as wound healing. MSC secretome profiling revealed increased protein diversity associated with tissue repair and immune regulation, suggesting MSCs undergo an adaptive response to ischaemic conditions, enhancing their therapeutic potential. This translational study highlights a clinically viable, minimally invasive method for sustained cardioprotection, harnessing the MSC secretome to address a pivotal gap in current treatments for ischaemic heart disease.

pathology↗

bioRxiv2025

Comparison of Urinary Proteome Modifications Between Methamphetamine-Abstinent Rehabilitation Patients for Over Three Months and Healthy Individuals

Methamphetamine addiction is characterized by complex mechanisms and a high relapse rate, posing a serious public health threat. In this study, urinary proteome modifications of rehabilitation patients who had abstained from methamphetamine for over three months and those of healthy individuals were analyzed and compared. A total of 984 differentially modified peptides were identified, 362 of which showed changes from presence to absence or vice versa. Results from the randomized grouping test indicated that at least 74.85% of these differentially modified peptides were not randomly generated. Several proteins containing these peptides have been reported to be associated with methamphetamine, including prostaglandin-H2 D-isomerase, complement factor H, filamin-A, and plasminogen. Additionally, some significantly changed modified peptides and the proteins they are located in, which have not been previously reported to be associated with methamphetamine, may provide new insights into addiction rehabilitation. This study establishes a method for investigating drug addiction through urinary proteome modifications and observes differences between methamphetamine-abstinent rehabilitation patients and healthy individuals, which may help explain the drugs high relapse rate. It offers a new perspective on drug withdrawal research and holds potential for tracking and assessing the rehabilitation process of methamphetamine addiction.

biochemistry↗

bioRxiv2025

NeighbourNet: Scalable cell-specific co-expression networks for granular regulatory pattern discovery

Gene regulatory networks (GRNs) provide a fundamental framework for understanding the molecular mechanisms that govern gene expression. Advances in single-cell RNA sequencing (scRNA-seq) have enabled GRN inference at cellular resolution; however, most existing approaches rely on predefined clusters or cell states, implicitly assuming static regulatory programs and potentially missing subtle, dynamic variation in regulation across individual cells. To address these limitations, we introduce NeighbourNet (NNet), a method that constructs cell-specific co-expression networks. NNet first applies principal component analysis to embed gene expression into a low-dimensional space, followed by local regression within each cells k-nearest neighbourhood (KNN) to quantify co-expression. This approach improves computational efficiency and stabilises co-expression estimates, mitigating challenges posed by small sample sizes in KNN regression and the inherent noise and sparsity of scRNA-seq data. Beyond co-expression, NNet supports scalable downstream analyses, including (i) clustering and aggregating cell-specific networks into meta-networks that capture primary co-expression patterns, and (ii) integrating prior knowledge to annotate co-expression and infer active signalling interactions at the individual cell level. All functional modules of NNet are implemented with an efficient algorithm that enables application to large-scale single-cell datasets. We demonstrate NNets effectiveness through three case studies on transcription factor activity prediction, early haematopoiesis, and tumour microenvironments. Provided as an R package, NNet offers a novel framework for exploring cellular variation in co-expression and integrates seamlessly with existing single-cell analysis workflows.

bioinformatics↗

bioRxiv2025

RNA Architecture Underlies Discontinuous Transcription and Evolution of Coronavirus

Coronaviruses employ discontinuous transcription to produce canonical subgenomic RNAs (sgRNAs) essential for gene expression, as well as non-canonical sgRNAs with unclear function. Nevertheless, the mechanisms regulating the balance between canonical and non-canonical sgRNAs throughout the viral replication cycle remain unknown. We conducted an integrated analysis on 234 transcriptome and 12 RNA-RNA interactome samples across various coronavirus genera. RNA-RNA interactions were identified between TRS-B and TRS-L flanking regions in the same genomic direction, correlating with the formation of canonical junctions. Non-canonical junctions frequently span short or long genomic distance, with short-range junctions generally mediated by reverse complementary stem-loops and coinciding with genomic deletion regions. Conserved long-range non-canonical sgRNAs were identified across different coronaviruses, and these sgRNAs harbor ORF10 or an evolving gene to suppress antiviral innate immune responses. This work establishes a structural framework that enables an understanding of the regulatory mechanism behind discontinuous transcription and the evolutionary pathway of coronaviruses. TeaserDeciphering coronavirus transcription and evolution: an integration analysis of transcriptome and RNA-RNA interactome. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=165 HEIGHT=200 SRC="FIGDIR/small/642953v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1c58502org.highwire.dtl.DTLVardef@9f87d7org.highwire.dtl.DTLVardef@18f3492org.highwire.dtl.DTLVardef@c49362_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Dynamic and Biphasic Regulation of Cell Migration by Ras

Ras has traditionally been regarded as a positive regulator and therapeutic target due to its role in cell proliferation, but recent findings indicate a more nuanced role in cell migration, where suppressed Ras activity can unexpectedly promote migration. To clarify this complexity, we systematically modulate Ras activity using various RasGEF and RasGAP proteins and assess their effects on migration dynamics. Leveraging optogenetics, we assess the immediate, non-transcriptional effects of Ras signaling on migration. Local RasGEF recruitment to the plasma membrane induces protrusions and new fronts to effectively guide migration, even in the absence of GPCR/G-protein signaling whereas global recruitment causes immediate cell spreading halting cell migration. Local RasGAP recruitment suppresses protrusions, generates new backs, and repels cells whereas global relocation either eliminates all protrusions to inhibit migration or preserves a single protrusion to maintain polarity. Consistent local and global increases or decreases in signal transduction and cytoskeletal activities accompany these morphological changes. Additionally, we performed cortical tension measurements and found that RasGEFs generally increase cortical tension while RasGAPs decrease it. Our results reveal a biphasic relationship between Ras activity and cellular dynamics, reinforcing our previous findings that optimal Ras activity and cortical tension are critical for efficient migration. SignificanceThis study challenges the traditional view of Ras as solely a positive regulator of cell functions by controlling of gene expression. Using optogenetics to rapidly modulate Ras activity in Dictyostelium, we demonstrate a biphasic relationship between Ras activity and migration: both excessive and insufficient Ras activity impair cell movement. Importantly, these effects occur rapidly, independent of transcriptional changes, revealing the mechanism by which Ras controls cell migration. The findings suggest that optimal Ras activity and cortical tension are crucial for efficient migration, and that targeting Ras in cancer therapy should consider the cells initial state, aiming to push Ras activity outside the optimal range for migration. This nuanced understanding of the role of Ras in migration has significant implications for developing more effective cancer treatments, as simply inhibiting Ras might inadvertently promote metastasis in certain contexts.

cell biology↗

bioRxiv2025

A General Framework for Branch Length Estimation in Ancestral Recombination Graphs

Inference of Ancestral Recombination Graphs (ARGs) is of central interest in the analysis of genomic variation. ARGs can be specified in terms of topologies and coalescence times. The coalescence times are usually estimated using an informative prior derived from coalescent theory, but this may generate biased estimates and can also complicate downstream inferences based on ARGs. Here we introduce, POLEGON, a novel approach for estimating branch lengths for ARGs which uses an uninformative prior. Using extensive simulations, we show that this method provides improved estimates of coalescence times and lead to more accurate inferences of effective population sizes under a wide range of demographic assumptions (population expansion, bottleneck, split, etc). It also improves other downstream inferences including estimates of mutation rates. We apply the method to data from the 1000 Genomes Project to investigate population size histories and differential mutation signatures across populations. We also estimate coalescence times in the HLA region, and show that they exceed 30 million years in multiple segments. Significance StatementModel misspecification is a common challenge in population genetic inference, as oversimplified mathematical models often fail to capture complex evolutionary processes. Here we introduce a novel framework for branch length estimation in whole-genome genealogies, which enables accurate inference using non-informative priors and subsequent posterior calibration, rather than relying on heavily parametrized models. This flexible approach has been validated in various simulation settings. When applied to real genomic data, it enables robust inference of demography, mutation rates, and transspecies polymorphisms.

evolutionary biology↗

bioRxiv2025

Tracking mobilization uncovers an evolutionarily conserved mechanism in suppressing transpositions during somatic development

Transposon mobilizations could cause gene mutations and even genomic instability, whose aberrant activation is tightly linked with cancer, neurodegenerative disorder and other pathologies. However, the precise suppression mechanisms of transposon mobilizations during somatic development throughout evolution remain largely obscure. Here, by spatiotemporally monitoring transpositions with single-cell resolution, we determined a highly conserved mechanism in suppressing transposon mobilizations. We identified that Cramp1 safeguards the genomic integrity in both Drosophila hindgut regeneration and mouse embryonic erythropoiesis through silencing transposon mobility. Cramp1 is characterized as a major hallmark that specifically binds to the DNA sequences of histone gene cluster to initiate transcription of linker histone H1, which subsequently promotes H3K36me2-established heterochromatin for transposon silencing. Our finding highlights that with the endless arms race between hosts and transposons during evolution, the core mechanisms will also evolve to suppress transposon mobilizations during somatic development. One-sentence abstractCramp1 plays an evolutionarily conserved role in specifically initiating linker histone H1 transcription and triggering H1-H3K36me2-established heterochromatin to suppress transposon mobilizations and maintain genome integrity during somatic development.

genetics↗

bioRxiv2025

TRAF6 integrates innate immune signals to regulate glucose homeostasis via Parkin-dependent and -independent mitophagy

Activation of innate immune signaling occurs during the progression of immunometabolic diseases, including type 2 diabetes (T2D), yet the impact of innate immune signaling on glucose homeostasis is controversial. Here, we report that the E3 ubiquitin ligase TRAF6 integrates innate immune signals following diet-induced obesity to promote glucose homeostasis through the induction of mitophagy. Whereas TRAF6 was dispensable for glucose homeostasis and pancreatic {beta}-cell function under basal conditions, TRAF6 was pivotal for insulin secretion, mitochondrial respiration, and increases in mitophagy following metabolic stress in both mouse and human islets. Indeed, TRAF6 was critical for the recruitment and function of machinery within both the ubiquitin-mediated (Parkin-dependent) and receptor-mediated (Parkin-independent) mitophagy pathways upon metabolic stress. Intriguingly, the effect of TRAF6 deficiency on glucose homeostasis and mitophagy was fully reversed by concomitant Parkin deficiency. Thus, our results implicate a role for TRAF6 in the cross-regulation of both ubiquitin-and receptor-mediated mitophagy through the restriction of Parkin. Together, we illustrate that {beta}-cells engage innate immune signaling to adaptively respond to a diabetogenic environment.

molecular biology↗

bioRxiv2025

Integrating transcriptomic data with metabolic model unravels the electron transfer mechanisms of Methanosarcina barkeri

Methanogenic archaea, particularly Methanosarcina, are pivotal to the global carbon cycle and renewable energy production due to their versatile metabolic capabilities. Although transcriptomic analysis is widely employed to identify key genes and pathways in Methanosarcina under various methanogenic conditions--including the emerging direct interspecies electron transfer (DIET)-based methanogenesis--the weak correlation between gene expression levels and protein abundances poses challenges for interpreting transcriptomic data. To address this, we integrated transcriptomic data into a metabolic model of Methanosarcina barkeri for the first time, enabling more refined predictions and enhancing the interpretability of transcriptomic insights. This novel integrated model was subsequently utilized to simulate aceticlastic, hydrogenotrophic, and DIET-based methanogenesis. The results revealed that previous assumptions failed to account for the role of the CO2 reduction pathway in aceticlastic methanogenesis. The model also successfully captured key transcriptomic features of DIET-based methanogenesis, clarifying the functional roles of crucial enzymes like the F420H2 dehydrogenase Fpo and the transmembrane hydrogenase Vht in electron transfer. This integrative approach provided a deeper understanding of electron transfer mechanisms in M. barkeri and offered valuable insights for advancing methanogen-based biotechnologies. Moreover, the study critically evaluated the relationship between gene expression and metabolic flux, establishing a practical framework for deriving meaningful insights from the growing volume of transcriptomic data.

bioengineering↗