Biology subjects

Zhang, G.

Publications and source records attributed to Zhang, G..

At least 181 records · Page 10Linked to original sources

bioRxiv2024

Conservation of gene expression patterns between the amniotic epithelium at birth and a newborn's nasal epithelium

BackgroundAmniotic epithelial cells are foetal-derived stem cells, capable of differentiating into all three germ layers, including mature epithelial cell populations. However, the conservation between amniotic epithelium and other epithelial tissues has not been sufficiently explored. We hypothesised that the amniotic epithelium might serve as a surrogate tissue source for investigating transcriptional profiles in the respiratory epithelium of the newborn. We compared gene expression profiles and weighted gene co-expression network structure in paired amniotic and newborn nasal epithelial samples from 85 participants in the Airway Epithelium Respiratory Illnesses and Allergy (AERIAL) birth cohort. ResultsIn total, 11,867 genes (79.7%) were commonly expressed in both amniotic and nasal epithelium, with uniquely expressed genes (2,563 and 458, respectively) enriched for biological functions related to each tissues specialist functions (e.g. developmental programs and ciliated cells, respectively). We observed a strong overlap in weighted gene co-expression network structure between both tissues, with ten co-expression modules identified in consensus network analysis. Genes commonly expressed in both tissues and/or found in the consensus network modules were enriched for biologically relevant gene signatures and pathway terms related to airway function. We also observed significant overlap in gene expression and network structure between the amniotic epithelium and published datasets of epithelial samples from the lower airway and other epithelial tissues including skin and oesophagus, suggesting a global epithelial signature. ConclusionsOverall, we observed significant overlap in gene expression and network structure between paired amniotic and nasal epithelial samples, supporting the potential of the amnion as a non-invasive and abundant tissue surrogate. Observed differences between tissues were related to each tissues specialist functions, which remains an important consideration when assessing their overlap. Future studies aimed at investigating amnion-based biomarkers for respiratory exposures in utero and disease outcomes in childhood are needed to extend these results towards clinical translation.

molecular biology↗

bioRxiv2024

ER stress-induced TREM2 downregulation exacerbates platelet activation and myocardial infarction in patients with coronary artery disease

Coronary artery disease (CAD) is characterized by the chronic immune-inflammation, excessive endoplasmic reticulum (ER) stress, and platelet hyperactivity; however, whether there is a signaling hub linking these events remains unclear. Here, we identified that triggering receptor expressed on myeloid cells 2 (TREM2), an important pattern recognition receptor of the innate immune system, may serve as one such hub. We found that platelets expressed TREM2 and platelets from CAD patients had decreased TREM2 expression compared to healthy subjects. Decreased TREM2 is associated with platelet hyperactivity in CAD patients. This decrease could be due to excessive ER stress, which downregulated TREM2 through the CHOP-C/EBP axis. Loss of TREM2 not only enhanced platelet activation in response to ADP, collagen, and collagen-related peptide (CRP), but also amplified the platelet inflammatory response. Loss of TREM2 exacerbated mouse mesenteric arterial thrombosis and aggravated experimental myocardial infarction (MI). Moreover, a TREM2-activating antibody inhibited platelet activation, alleviated arterial thrombosis and pulmonary embolism. In addition, TREM2-activating antibody exhibited cardioprotective roles against experimental MI and reduced the inflammatory burden. Mechanistically, TREM2/DAP12/SHIP1 axis negatively regulated platelet activation through reducing PIP3 levels and inhibiting Akt phosphorylation. We also provided evidence supporting sphingosine-1-phospage (S1P) as a physiological agonist of TREM2. In summary, we find that TREM2 connects chronic immune-inflammation, excessive ER stress, and platelet hyperactivity in CAD patients. Downregulating TREM2 by ER stress exacerbates platelet activation and amplifies inflammation response in patients with CAD. TREM2-activating antibodies may have therapeutic potential for CAD patients. Key PointsO_LIPlatelets from CAD patients have decreased TREM2 expression, which is caused by ER stress and associated with platelet hyperactivity. C_LIO_LIS1P-TREM2-SHIP1 pathway inhibits platelet activation, alleviates arterial thrombosis, and exhibits cardioprotective roles against experimental myocardial infarction. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/608887v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1e21f2eorg.highwire.dtl.DTLVardef@6d427forg.highwire.dtl.DTLVardef@128af74org.highwire.dtl.DTLVardef@16f48c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOVisual Abstract.C_FLOATNO Downregulation of platelet TREM2 caused by ER stress in CAD patients leads to platelet hyperactivity and aggravates myocardial ischemia, which is rescued by TREM2-activating antibody. Excessive ER stress in CAD upregulates CHOP, which dimerizes with C/EBP, a transcription factor of TREM2, decreases TREM2 transcription and expression in megakaryocytes and further in platelets. TREM2/DAP12/SHIP1/Akt pathway negatively regulates platelet activation; decreased TREM2 thus aggravates platelet hyperactivity, inflammation, and myocardial infarction, which can be rescued by TREM2 activation including antibody or the small molecule agonist. Physiologically, S1P released from platelet granules is an endogenous agonist of TREM2. C_FIG

pharmacology and toxicology↗

bioRxiv2024

Multi-strategies embedded framework for neoantigen vaccine maturation

Effective cancer immunotherapy hinges on the precise recognition of neoantigens, presented as binary complexes with major histocompatibility complex (MHC) molecules, by T cell receptors (TCR). The development of immunogenic peptide predictors and generators plays a central role in personalizing immunotherapies while reducing experimental costs. However, the current methods often fall short in leveraging structural data efficiently and providing comprehensive guidance for neoantigen selection. To address these limitations, we introduce NEOM, a novel neoantigen maturation framework encompassing five distinct modules: "policy", "structure", "evaluation", "selection" and "filter". This framework is designed to enhance precision, interpretability, customizability and cost-effectiveness in neoantigen screening. We evaluated NEOM using a set of random synthetic peptides, followed by available clinically-derived peptides. NEOM achieved higher performance on generated peptide quality compared to other baseline models. Using established predictors for filtering revealed a substantial number of peptides with immunogenic potential. Subsequently, a more rigorous binding affinity evaluation using free energy perturbation methods identified 6 out of 38 candidates showing superior binding characteristics. MHC tetramer peptide exchange assays and flow cytometry experiments further validate five of them. These results demonstrate that NEOM not only excels in identifying diverse peptides with enhanced binding stability and affinity for MHC molecules but also augments their immunogenic potential, showcasing its utility in advancing personalized immunotherapies.

bioinformatics↗

bioRxiv2024

Genomic and transcriptomic analyses of Heteropoda venatoria reveal the expansion of P450 family for starvation resistance in spider

BackgroundSpiders generally exhibit robust starvation resistance, with hunting spiders, represented by Heteropoda venatoria, being particularly outstanding in this regard. Given the challenges posed by climate change and habitat fragmentation, understanding how spiders adjust their physiology and behavior to adapt to the uncertainty of food resources is crucial for predicting ecosystem responses and adaptability. ResultsWe sequenced the genome of H. venatoria and, through comparative genomic analysis, discovered significant expansions in gene families related to lipid metabolism, such as cytochrome P450 and steroid hormone biosynthesis genes. We also systematically analyzed the gene expression characteristics of H. venatoria at different starvation resistance stages and found that the fat body plays a crucial role during starvation in spiders. This study indicates that during the early stages of starvation, H. venatoria relies on glucose metabolism to meet its energy demands. In the middle stage, gene expression stabilizes, whereas in the late stage of starvation, pathways for fatty acid metabolism and protein degradation are significantly activated, and autophagy is increased, serving as a survival strategy under extreme starvation. Additionally, analysis of expanded P450 gene families revealed that H. venatoria has many duplicated CYP3 clan genes that are highly expressed in the fat body, which may help maintain a low-energy metabolic state, allowing H. venatoria to endure longer periods of starvation. We also observed that the motifs of P450 families in H. venatoria are less conserved than those in insects, which may be related to the greater polymorphism of spider genomes. ConclusionsThis research not only provides important genetic and transcriptomic evidence for understanding the starvation mechanisms of spiders but also offers new insights into the adaptive evolution of arthropods.

bioinformatics↗

bioRxiv2024

Characterization of bronchiolitis and vaccine-induced enhanced respiratory disease in Syrian hamsters caused by respiratory syncytial virus infection

Respiratory syncytial virus (RSV) presents a significant health risk to pediatric and old populations. The quest for developing effective RSV vaccines and immunoprophylactic measures remains highly active, while the catastrophic enhanced respiratory disease (ERD) reaction triggered by RSV vaccines poses lingering concerns. Meanwhile, as the basis of vaccine research, the development of animal models of RSV infection has shown less substantial progress, with considerable disparities in immunological and pathological responses compared to humans. The Syrian hamster, which is reported to be susceptible to RSV infection, seems promising, but the lack of in-depth studies has hampered its application. Consequently, we have refined the RSV-infected hamster model by establishing infection models at different ages, reanalyzing virological and pathological data, and applying vaccination with heat-inactivated RSV virus for ERD reaction. In general, neonatal hamsters exhibited the highest level of viral amplification, while old hamsters displayed the most severe pathological manifestations, with adult hamsters in between. Although Syrian hamsters were moderately susceptible to RSV infection, they showed typical pathological changes of bronchitis in all age groups, with adult and old animals even showing clinical signs of coughing. In addition, hamsters demonstrated the typical ERD response to heat-inactivated virus, characterized by the exacerbation of lung injury with extensive neutrophil and eosinophil infiltration, as well as TH2 polarization. Collectively, these characteristics suggest that the Syrian hamster model has significant potential for investigating the pathogenesis of RSV infection, elucidating the mechanism of ERD, and evaluating vaccine efficacy and safety. ImportanceThe Syrian hamster has been shown in our study to be a potential model for respiratory syncytial virus (RSV) infection, according to the following characteristics: Hamsters of three different age groups all developed typical pulmonary bronchiolitis following RSV infection, whereas adult and old hamsters showed typical cough symptoms, comparable to those observed in clinical patients. Hamsters of different ages showed considerable variability. Neonatal hamsters tolerated more viral replication, while old hamsters suffered the most severe pulmonary pathology. Hamsters exhibited typical ERD responses after inoculation with heat-inactivated RSV virus, including enhanced lung pathology, pulmonary eosinophilic and neutrophil infiltration, and Th2 polarization, which was remarkable and more similar to the typical characteristics of the ERD response in humans.

microbiology↗

bioRxiv2024

Size evolution of gigantic genomes suggests stochastic outcomes of transposable element/host silencing interactions

Size evolution among gigantic genomes involves gain and loss of many gigabases of transposable elements (TEs), sequences that parasitize host genomes. Animals suppress TEs using piRNA and KRAB-ZFP pathways. TEs and hosts coevolve in an arms race, where suppression strength reflects TE fitness costs. In enormous genomes, additional TE costs become miniscule. How, then, do TEs and host suppression invoke further addition of massive DNA amounts? We analyzed TE proliferation histories, deletion rates, and community diversities in six salamander genomes (21.3 - 49.9 Gb), alongside gonadal expression of TEs and suppression pathways. TE activity is higher in testes than ovaries, attributable to lower KRAB-ZFP suppression. Unexpectedly, genome size/expansion is uncorrelated with TE deletion rate, proliferation history, expression, and host suppression. Also, TE community diversity increases with genome size, contrasting theoretical predictions. TE/host antagonism in gigantic genomes likely produces stochastic TE accumulation, determined by noisy intermolecular interactions in huge genomes/cells.

evolutionary biology↗

bioRxiv2024

F-CPI: Prediction of activity changes induced by fluorine substitution using multimodal deep learning

There are a large number of fluorine (F)-containing compounds in approved drugs, and F substitution is a common method in drug discovery and development. However, F is difficult to form traditional hydrogen bonds and typical halogen bonds. As a result, accurate prediction of the activity after F substitution is still impossible using traditional drug design methods, whereas artificial intelligence driven activity prediction might offer a solution. Although more and more machine learning and deep learning models are being applied, there is currently no model specifically designed to study the effect of F on bioactivities. In this study, we developed a specialized deep learning model, F-CPI, to predict the effect of introducing F on drug activity, and tested its performance on a carefully constructed dataset. Comparison with traditional machine learning models and popular CPI task models demonstrated the superiority and necessity of F-CPI, achieving an accuracy of approximately 89% and a precision of approximately 67%. In the end, we utilized F-CPI for the structural optimization of hit compounds against SARS-CoV-2 3CLpro. Impressively, in one case, the introduction of only one F atom resulted in a more than 100-fold increase in activity (IC50: 22.99 nM vs. 28190 nM). Therefore, we believe that F-CPI is a helpful and effective tool in the context of drug discovery and design.

bioinformatics↗

bioRxiv2024

A smartphone-based genetically recombinant whole-cell biosensor for highly sensitive monitoring of polychlorinated biphenyls (PCBs)

Polychlorinated biphenyls (PCBs) are highly carcinogenic and persistent pollutants commonly found in ecosystems. Their complex congeners pose a huge challenge to instrumental analysis and ELISA methods, which prefer single and known targets. To overcome this limitation, here we developed an Escherichia coli whole-cell biosensor (WCB) for simultaneously detecting multiple PCB congeners. In this sensor, PCBs were firstly converted into hydroxylated PCBs (OH-PCBs) by bphAB degradation circuits, which then serve as high-affinity targets of transcriptional factor HbpRCBP6-based sensing pathways for sensitive response through extensive chassis screening. The resulting biosensor BL21(DE3)/HbpRCBP6-bphAB shows the lowest detection limits for 2-CBP (2-chlorobiphenyl) to date and can recognize various PCB homologues, including 3-CBP, 4-CBP, 2,3-diCBP and 2,2-diCBP, with detection limits of 0.06-1 M. Further investigation of the docking structure and binding energy reveal that HbpRCBP6 has a stronger affinity for OH-PCBs than for PCBs, indicating that the conversion of PCB by BphAB enzymes is a key step to improve the sensitivity of WCB. Subsequently, we developed an immobilized hydrogel WCB and a smartphone-based detection procedure to facilitate real-time and user-friendly PCB detection. This study will not only advance the biomonitoring of PCB contaminants but also provide an innovative strategy for developing metabolic pathway-sensing proteins combined biosensor. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/601110v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@10772cdorg.highwire.dtl.DTLVardef@22699org.highwire.dtl.DTLVardef@1343c27org.highwire.dtl.DTLVardef@595859_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

A new yeast-based bioreporter for simple, sensitive, and cost-effective detection of dioxin-like compounds

Dioxin-like compounds (DLCs) are environmental xenobiotics that can activate the aryl hydrocarbon receptors (AhR), thereby imposing a significant threat to human health through biomagnifications processes. In this study, a dioxin-activated nano-luminescent Saccharomyces cerevisiae bioreporter, called DnaSc, was developed for simple and rapid detection of DLCs and AhR agonists. The bioreporter used nano-luciferase NLuc as a signal generator to emit bioluminescent signals in response to DLCs without cell lysis. Through optimizing ARNT expression and engineering the aryl hydrocarbon receptor (AhR), the yeast-based bioassay exhibited a detection limit of 10 fM for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) within 6 h, making it the most sensitive whole-cell biosensor reported to date. Furthermore, the detection capacity of the DnaSc bioassay for DLCs and AhR agonists was characterized. In summary, the yeast-based bioreporter developed in this study provided a simple, sensitive, and cost-effective method for DLCs detection.

bioengineering↗

bioRxiv2024

Synergistic amplifier reprograms biosensor behavior to facilitate detection of dioxin-like compounds

Biosensors are prominent detection tools for evaluating various analytical markers. However, these devices that meet practical application scenarios are still limited, and their potential remains to be developed. In these aspects, we attempted to design and construct a synergistic amplifier consisting of two components, namely, a transcriptional activation component mediated by the Gal3C regulator and a transcription recruitment component exploiting the function of dCas9-(SpyC)n, which work together to enhance yeast biosensor performance. This synergistic amplifier increased the signal output by 5.1-folds and the detection limit by 4.4-folds, respectively, while maintaining adjustable sensitivity and avoiding noise introduction during signal amplification. We demonstrated the use of synergistic amplifier in detecting dioxin analogues, aiming to unlock the potential of predictive modulation, and found that it achieved progress in dynamic output and detection limit. This work show that synergistic amplifier is a new paradigm for expanding signal processing pathways within synthetic genetic networks, enabling cell-based biosensors for environmental monitoring.

molecular biology↗

bioRxiv2024

Improving positively tuned voltage indicators for brightness and kinetics

Existing positively tuned ASAP-family voltage indicators such as ASAP4e exhibit superior photostability compared to the negatively tuned ASAP3 and ASAP5, but signal-to-noise ratios for spike detection remained similar to ASAP3. To improve spike detection by positively tuned ASAP indicators, we performed multiple rounds of structure-guided saturation mutagenesis of an ASAP4e predecessor while screening directly for faster responses. One variant, ASAP6c, demonstrated [~]100% increases in fluorescence in response to single action potentials in both one-photon and two-photon imaging in vivo, achieving a 3-fold improvement in signal-to-noise ratios over ASAP4e.

neuroscience↗

bioRxiv2024

Dynamic changes in structure and function of brain mural cells around chronically implanted microelectrodes

1.0Integration of neural interfaces with minimal tissue disruption in the brain is ideal to develop robust tools that can address essential neuroscience questions and combat neurological disorders. However, implantation of intracortical devices provokes severe tissue inflammation within the brain, which requires a high metabolic demand to support a complex series of cellular events mediating tissue degeneration and wound healing. Pericytes, peri-vascular cells involved in blood-brain barrier maintenance, vascular permeability, waste clearance, and angiogenesis, have recently been implicated as potential perpetuators of neurodegeneration in brain injury and disease. While the intimate relationship between pericytes and the cortical microvasculature have been explored in other disease states, their behavior following microelectrode implantation, which is responsible for direct blood vessel disruption and dysfunction, is currently unknown. Using two-photon microscopy we observed dynamic changes in the structure and function of pericytes during implantation of a microelectrode array over a 4-week implantation period. Pericytes respond to electrode insertion through transient increases in intracellular calcium and underlying constriction of capillary vessels. Within days following the initial insertion, we observed an influx of new, proliferating pericytes which contribute to new blood vessel formation. Additionally, we discovered a potentially novel population of reactive immune cells in close proximity to the electrode-tissue interface actively engaging in encapsulation of the microelectrode array. Finally, we determined that intracellular pericyte calcium can be modulated by intracortical microstimulation in an amplitude- and frequency-dependent manner. This study provides a new perspective on the complex biological sequelae occurring the electrode-tissue interface and will foster new avenues of potential research consideration and lead to development of more advanced therapeutic interventions towards improving the biocompatibility of neural electrode technology.

bioengineering↗

bioRxiv2024

Single-cell dissection of prognostic architecture and immunotherapy response in Helicobacter pylori infection associated gastric cancer

Most of the gastric cancer (GC) worldwide are ascribed to Helicobacter pylori (H. pylori) infections, which have a detrimental effect on the immunotherapys efficacy. Comprehensively dissecting the key cell players and molecular pathways associated with cancer immunotherapies is critical for developing novel therapeutic strategies against H. pylori infection associated GC. We performed a comprehensive single-cell transcriptome analysis of nine GC with current H. pylori infection (HpGC), three GC with previous H. pylori infection (ex-HpGC), six GC without H. pylori infection (non-HpGC), and six healthy controls (HC). We also investigated key cell players and molecular pathways associated with GC immunotherapy outcomes. We revealed the molecular heterogeneity of different cell components in GC including epithelium, immune cells, and cancer-associated fibroblasts (CAFs) at the single-cell level. The malignant epithelium of HpGC exhibited high expression level of inflammatory and epithelial-mesenchymal transition (EMT) signature, HpGC and ex-HpGC were enriched with VEGFA+ angiogenic tumor-associated macrophages (Angio-TAM) and IL11+ inflammatory CAF (iCAF), characterized by high expression levels of NECTIN2 and VEGFA/B. Additionally, we found significant correlations between the abundance of iCAF with Angio-TAM and TIGIT+ suppressive T cells, and iCAF interacted with Angio-TAM through the VEGF and ANGPTL angiogenic pathways. We also developed an immune signature and angiogenic signature and demonstrated that the iCAF abundance and angiogenic signature could predict poor immunotherapy outcomes in GC. We revealed the transcriptome characteristics and heterogeneity of various cellular constituents of HpGC and demonstrated that a synergistic combination of immunotherapy and anti-angiogenic targeted therapy may be an effective therapeutic modality for HpGC.

cancer biology↗

bioRxiv2024

AptaGPT: Advancing aptamer design with a generative pre-trained language model

Aptamers, synthetic oligonucleotide ligands, have shown significant promise for therapeutic and diagnostic applications owing to their high specificity and affinity for target molecules. However, the conventional Systematic Evolution of Ligands by Exponential Enrichment (SELEX) for aptamer selection is time-consuming and often yields limited candidates. To address these limitations, we introduce AptaGPT, a novel computational strategy that leverages a Generative Pre-trained Transformer (GPT) model to design and optimize aptamers. By training on SELEX data from early rounds, AptaGPT generated a diverse array of aptamer sequences, which were then computationally screened for binding using molecular docking. The results of this study demonstrated that AptaGPT is an effective tool for generating potential high-affinity aptamer sequences, significantly accelerating the discovery process and expanding the potential for aptamer research. This study showcases the application of generative language models in bioengineering and provides a new avenue for rapid aptamer development.

bioinformatics↗

bioRxiv2024

Characterizing interactions of ER resident proteins in situ through the YST-PPI method

The mutual interactions of ER resident proteins in the ER maintain its functions, prompting the protein folding, modification, and transportation. Here, a new method, named YST-PPI (YESS-based Split fast TEV protease System for Protein-protein Interaction) was developed, targeting the characterization of protein interactions in ER. YST-PPI method integrated the YESS system, split-TEV technology and endoplasmic reticulum retention signal peptide (ERS) to provide an effective strategy for studying ER in situ PPIs in a fast and quantitative manner. The interactions among 15 ER resident proteins of S. cerevisiae were explored using the YST-PPI system, and their interaction network map was constructed, in which more than 74 interacting resident protein pairs were identified. Our studies also showed that Lhs1p plays a critical role in regulating the interactions of most of the ER resident proteins, expect the Sil1p, indicating its potential role in controlling the ER molecular chaperones. Moreover, the mutual interaction revealed by our studies further confirmed that the ER resident proteins perform their functions in a synergetic way and multimer complex might be formed during the process.

microbiology↗

bioRxiv2024

TRAPT: A multi-stage fused deep learning framework for transcriptional regulators prediction via integrating large-scale epigenomic data

It is a challenging task to identify functional transcriptional regulators, which control expression of gene sets via regulatory elements and epigenomic signals, involving context-specific studies such as development and diseases. Integrating large-scale multi-omics epigenomic data enables the elucidation of the complex epigenomic control patterns of regulatory elements and regulators. Here, we propose TRAPT, a multi-modality deep learning framework that predicts functional transcriptional regulators from a queried gene set by integrating large-scale multi-omics epigenomic data, including histone modifications, ATAC-seq and TR-ChIP-seq. We design two-stage self-knowledge distillation model to learn nonlinear embedded representation of upstream and downstream regulatory element activity, and merge multi-modality epigenomic features from TR and the queried gene sets for inferring regulator activity. Experimental results on 1072 TR-related datasets demonstrate that TRAPT outperforms current state-of-the-art methods in predicting transcriptional regulators, especially in the prediction of transcription co-factors and chromatin regulators. Additionally, we have successfully identified key transcriptional regulators associated with the disease, genetic variation, cell fate decisions, and tissues. Our method provides an innovative perspective for integrating epigenomic data and has the potential to significantly assist researchers in deepening their understanding of gene expression regulation mechanisms.

bioinformatics↗

bioRxiv2024

Protein CoAlation on TXNRD2 regulates mitochondrial thioredoxin system to protect against ferroptosis

The Cystine-xCT transporter-Glutathione (GSH)-GPX4 axis is the canonical pathway to protect against ferroptosis. While not required for ferroptosis-inducing compounds (FINs) targeting GPX4, FINs targeting the xCT transporter require mitochondria and its lipid peroxidation to trigger ferroptosis. However, the mechanism underlying the difference between these FINs is still unknown. Given that cysteine is also required for coenzyme A (CoA) biosynthesis, here we show that CoA supplementation specifically prevents ferroptosis induced by xCT inhibitors but not GPX4 inhibitors. We find that, auranofin, a thioredoxin reductase inhibitor, abolishes the protective effect of CoA. We also find that CoA availability determines the enzymatic activity of thioredoxin reductase, but not thioredoxin. Importantly, the mitochondrial thioredoxin system, but not the cytosolic thioredoxin system, determines CoA-mediated ferroptosis inhibition. Our data show that the CoA regulates the in vitro enzymatic activity of mitochondrial thioredoxin reductase (TXNRD2) by covalently modifying the thiol group of cysteine (CoAlation) on Cys-483. Replacing Cys-483 with alanine on TXNRD2 abolishes its in vitro enzymatic activity and ability to protect cells from ferroptosis. Targeting xCT to limit cysteine import and, therefore, CoA biosynthesis reduced CoAlation on TXNRD2, an effect that was rescued by CoA supplementation. Furthermore, the fibroblasts from patients with disrupted CoA metabolism demonstrate increased mitochondrial lipid peroxidation. In organotypic brain slice cultures, inhibition of CoA biosynthesis leads to an oxidized thioredoxin system, mitochondrial lipid peroxidation, and loss in cell viability, which were all rescued by ferrostatin-1. These findings identify CoA-mediated post-translation modification to regulate the thioredoxin system as an alternative ferroptosis protection pathway with potential clinical relevance for patients with disrupted CoA metabolism.

cell biology↗

bioRxiv2024

Quinolinic acid links kidney injury to brain toxicity

Kidney dysfunction often leads to neurological impairment, yet the complex kidney-brain relationship remains elusive. We employed spatial and bulk metabolomics to investigate a mouse model of rapid kidney failure induced by mouse double minute 2 (Mdm2) conditional deletion in the kidney tubules to interrogate kidney and brain metabolism. Pathway enrichment analysis of focused plasma metabolomics panel pinpointed tryptophan metabolism as the most altered pathway with kidney failure. Spatial metabolomics showed toxic tryptophan metabolites in the kidneys and brains, revealing a novel connection between advanced kidney disease and accelerated kynurenine degradation. In particular, the excitotoxic metabolite quinolinic acid was localized in ependymal cells adjacent to the ventricle in the setting of kidney failure. These findings were associated with brain inflammation and cell death. A separate mouse model of acute kidney injury also had an increase in circulating toxic tryptophan metabolites along with altered brain inflammation. Patients with advanced CKD similarly demonstrated elevated plasma kynurenine metabolites and quinolinic acid was uniquely correlated with fatigue and reduced quality of life in humans. Overall, our study identifies the kynurenine pathway as a bridge between kidney decline, systemic inflammation, and brain toxicity, offering potential avenues for diagnosis and treatment of neurological issues in kidney disease.

molecular biology↗