Biology subjects

Ouyang, Y.

Publications and source records attributed to Ouyang, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Senolytic therapy preserves blood-brain barrier integrity and promotes microglia homeostasis in a tauopathy model

Cellular senescence, characterized by expressing the cell cycle inhibitory proteins, is evident in driving age-related diseases. Senescent cells play a crucial role in the initiation and progression of tau-mediated pathology, suggesting that targeting cell senescence offers a therapeutic potential for treating tauopathy associated diseases. This study focuses on identifying non-invasive biomarkers and validating their responses to a well-characterized senolytic therapy combining dasatinib and quercetin (D+Q), in a widely used tauopathy mouse model, PS19. We employed human-translatable MRI measures, including water extraction with phase-contrast arterial spin tagging (WEPCAST) MRI, T2 relaxation under spin tagging (TRUST), longitudinally assessed brain physiology and high-resolution structural MRI evaluated the brain regional volumes in PS19 mice. Our data reveal increased BBB permeability, decreased oxygen extraction fraction, and brain atrophy in 9-month-old PS19 mice compared to their littermate controls. (D+Q) treatment effectively preserves BBB integrity, rescues cerebral oxygen hypometabolism, attenuates brain atrophy, and alleviates tau hyperphosphorylation in PS19 mice. Mechanistically, D+Q treatment induces a shift of microglia from a disease-associated to a homeostatic state, reducing a senescence-like microglial phenotype marked by increased p16/INK4a. D+Q-treated PS19 mice exhibit enhanced cue-associated cognitive performance in the tracing fear conditioning test compared to the vehicle-treated littermates, implying improved cognitive function by D+Q treatment. Our results pave the way for application of senolytic treatment as well as these noninvasive MRI biomarkers in clinical trials in tauopathy associated neurological disorders.

neuroscience↗

bioRxiv2023

Benchmarking Machine Learning Methods for Synthetic Lethality Prediction in Cancer

Synthetic lethality (SL) is a type of genetic interaction that occurs when defects in two genes cause cell death, while a defect in a single gene does not. Targeting an SL partner of a gene mutated in cancer can selectively kill tumor cells. Traditional wet-lab experiments for SL screening are resource-intensive. Hence, many computational methods have been developed for virtual screening of SL gene pairs. This study benchmarks recent machine learning methods for SL prediction, including three matrix factorization and eight deep learning models. We scrutinize model performance using various data splitting scenarios, negative sample ratios, and negative sampling methods on both classification and ranking tasks to assess the models generalizability and robustness. Our benchmark analyzed performance differences among the models and emphasized the importance of data and real-world scenarios. Finally, we suggest future directions to improve machine learning methods for SL discovery in terms of predictive power and interpretability.

bioinformatics↗

bioRxiv2023

Combining Bulk and Single-Cell RNA Sequencing Data to Identify RNA methylation and Autophagy-Related Signatures in Patients with Chronic Obstructive Pulmonary Disease

BackgroundChronic Obstructive Pulmonary Disease (COPD) is a heterogeneous lung condition associated with RNA methylation and autophagy. However, the specific autophagy-related genes and RNA methylation regulators involved in COPD development remain unknown. MethodsWe analyzed COPD and non-COPD patients datasets obtained from the Gene Expression Omnibus database, including Tissue Sequencing Transcriptome (bulk-seq) and single-cell sequencing (scRNA-seq) data. Differentially expressed genes (DEGs) were identified through differential genetic analysis using non-COPD bulk-seq data as the control group and COPD samples were used as the experimental group. Animal experiments were conducted to validate the expression of key genes. COPD model mice were exposed to smoke for four months, and lung function and histopathological changes were assessed. The mRNA and protein expression levels of FTO, IGF2BP2, DDIT3, DNAJB1, and YTHDF3 were measured using RT-qPCR and Western blotting, respectively. ResultsWe identified FTO, IGF2BP2, and YTHDF3 as key methylation genes, along with autophagy hub genes DDIT3 and DNAJB1. Animal experiments showed significantly increased mRNA and protein levels of FTO, YTHDF3 and DNAJB1 and significantly decreased levels of IGF2BP2 in lung tissue of COPD mice compared to the control group. ConclusionOur findings suggest that DDIT3 and DNAJB1 as autophagy hub genes, along with FTO, IGF2BP2 and YTHDF3 as RNA methylation genes, may play crucial roles in the development of COPD. These findings, supported by bulk-seq and scRNA-seq data, contribute novel genetic evidence for understanding the epigenetics of COPD.

cell biology↗

bioRxiv2023

Living cell mTORC1 inhibition reporter mTIR reveals nutrient-sensing targets of histone deacetylase inhibitor

Mammalian or mechanistic target of rapamycin complex 1 (mTORC1) is a clinically effective therapeutic target for diseases such as cancer, diabetes, aging, and neurodegeneration, yet an efficient tool to monitor mTORC1 inhibition in living cells or tissues is still lacking. Here we devised a genetically encoded mTORC1 inhibition reporter termed mTIR that exhibits a highly contrasted fluorescence puncta pattern in response to mTORC1 inhibition. mTIR specifically senses physiological, pharmacological and genetic inhibition of mTORC1 signaling in living cells and tissues. Importantly, mTIR can be applied as an powerful tool for imaging-based visual screening of mTORC1 inhibitors. By this method, we identified histone deacetylase inhibitors (HDACi) that selectively inhibit mTORC1 by inducing nutrient-sensing gene expression. Thus, mTIR is a unique living cell reporter efficiently detecting the inhibition of mTORC1 activity, and the HDACi Panobinostat transcriptionally target mTORC1 signaling via amino acids sensing.

cell biology↗

bioRxiv2023

Rice Gene Index (RGI): a comprehensive pan-genome database for comparative and functional genomics of Asian rice

To integrate the genomic information of the rice pan-genome, we performed comparative analyses and established a user-friendly Rice Gene Index (RGI, https://riceome.hzau.edu.cn) platform with 16 platinum standard reference genomes and supplementary transcriptome data. To logically organize and scientifically the index of 744,233 genes among rice accessions, we detected 112,658 Ortholog Gene Indices, and provide GeneCard pages to query genomic, transcriptomic, and homology information for each gene. The RGI allows users to search for relationships and comprehensive information of genes in keyword-based, sequence-based, and relationship-based ways. Furthermore, users can visualize these relationships at local and global scales corresponding to Microcollinearity and Macrocollinearity modules.

genomics↗

bioRxiv2022

Phosphate Starvation Signaling Increases Mitochondrial Membrane Potential through Respiration-independent Mechanisms

Mitochondrial membrane potential directly powers many critical functions of mitochondria, including ATP production, mitochondrial protein import, and metabolite transport. Its loss is a cardinal feature of aging and mitochondrial diseases, and cells closely monitor membrane potential as an indicator of mitochondrial health. Given its central importance, it is logical that cells would modulate mitochondrial membrane potential in response to demand and environmental cues, but there has been little exploration of this question. We report that loss of the Sit4 protein phosphatase in yeast increases mitochondrial membrane potential, both through inducing the electron transport chain and the phosphate starvation response. Indeed, a similarly elevated mitochondrial membrane potential is also elicited simply by phosphate starvation or by abrogation of the Pho85-dependent phosphate sensing pathway. This enhanced membrane potential is primarily driven by an unexpected activity of the ADP/ATP carrier. We also demonstrate that this connection between phosphate limitation and enhancement of the mitochondrial membrane potential is also observed in primary and immortalized mammalian cells as well as in Drosophila. These data suggest that mitochondrial membrane potential is subject to environmental stimuli and intracellular signaling regulation and raise the possibility for therapeutic enhancement of mitochondrial functions even with defective mitochondria.

cell biology↗

bioRxiv2022

An uncertainty-based interpretable deep learning framework for breast cancer outcomes prediction

Accurate prediction of breast cancer outcomes is important for selecting appropriate treatment, which can prolong the survival period of the patients and improve the life quality. Recently, different deep learning-based methods are carefully designed for cancer outcomes prediction. However, the applications of these methods are still challenging due to the model interpretability. In this study, we proposed a novel multi-task deep neural network UISNet to interpret the feature importance of the prediction model by an uncertainty-based integrated gradients algorithm. Additionally, UISNet improves the prediction accuracy by introducing the prior biological pathway knowledge and utilizing the patients heterogeneity information. By applications to seven breast cancer public datasets, the method was shown to outperform state-of-the-art methods by achieving a 5.79% higher C-index value on average. For the identified genes based on the interpretable model, 11 out of the top 20 genes have been proved to be associated with breast cancer by literature review. The comprehensive tests indicated that our proposed method is accurate and robust to predict breast cancer outcomes, and is an effective way to identify the prognosis-related genes. The method codes are available at: https://github.com/chh171/UISNet.

bioinformatics↗

bioRxiv2022

Gli1+ mesenchymal progenitors contribute to multilineage differentiation in a mouse model of post-traumatic joint injury

Complex injury and open reconstructive surgeries of the knee often lead to joint dysfunction that may alter the normal biomechanics of the joint. Two major complications that often arise are excessive deposition of fibrotic tissue and acquired heterotopic endochondral ossification. Knee arthrofibrosis is a fibrotic joint disorder where aberrant buildup of scar tissue and adhesions develop around the joint. Heterotopic ossification is ectopic bone formation around the periarticular tissues. Even though arthrofibrosis and heterotopic ossification pose an immense clinical problem, limited studies focus on their cellular and molecular mechanisms. Effective cell-targeted therapeutics are needed, but the cellular origin of both knee disorders remains elusive. Moreover, all the current animal models of knee arthrofibrosis and stiffness are developed in rats and rabbits, limiting genetic experiments that would allow us to explore the contribution of specific cellular targets to these knee pathologies. Here, we present a novel mouse model of post-traumatic joint injury where surgically induced injury and hyperextension of the knee lead to excessive deposition of disorganized collagen in the meniscus, synovium, and joint capsule in addition to formation of extra-skeletal bone in muscle and soft tissues within the joint capsule. As a functional outcome, arthrofibrosis and heterotopic endochondral ossification coupled with a significant increase in total joint stiffness were observed. By employing this model and genetic lineage tracing, we also demonstrate that Gli1+ mesenchymal progenitors proliferate after joint injury and contribute to fibrotic cells in the synovium and ectopic osteoblasts within the joint capsule. These findings demonstrate that Gli1+ cells are a major cellular contributor to knee arthrofibrosis and heterotopic ossification that manifests after knee injury. Our data collectively shows that genetic manipulation of Gli1+ cells in mice may offer a platform for identification of novel therapeutic targets to prevent chronic knee joint dysfunction after chronic injury.

pathology↗

bioRxiv2022

G6PD Inhibition Sensitizes Ovarian Cancer Cells to Oxidative Stress in the Metastatic Omental Microenvironment

Ovarian cancer (OC) is the most lethal gynecological malignancy, with aggressive metastatic disease responsible for the majority of ovarian cancer related deaths. In particular, OC tumors preferentially metastasize to and proliferate rapidly in the omentum. Here, we show metastatic OC cells experience increased oxidative stress in the omental microenvironment. Metabolic reprogramming, including upregulation of the pentose phosphate pathway (PPP), a key cellular redox homeostasis mechanism, allows OC cells to compensate for this challenge. Inhibition of G6PD, the rate-limiting enzyme of the PPP, reduces tumor burden in pre-clinical models of OC, suggesting this adaptive metabolic dependency is important for OC omental metastasis. HighlightsO_LIThe omental microenvironment poses a high oxidative stress metastatic niche for ovarian cancer cells. C_LIO_LIG6PD, a key enzyme involved in redox homeostasis and the rate-limiting enzyme of the pentose phosphate pathway (PPP) is upregulated in omental metastasis. C_LIO_LIInhibition of G6PD increases oxidative stress and cytotoxicity in the omental microenvironment. C_LIO_LIPharmacological G6PD inhibition reduces omental metastases in vivo. C_LI

cancer biology↗

bioRxiv2021

A non-canonical convergence of carbohydrate and glutamine metabolism is required after metabolic rewiring in 3D environment

The fate of pyruvate, which is modulated by the activity of the mitochondrial pyruvate carrier (MPC), is a defining metabolic feature in many cancers. Diffuse large B-cell lymphomas (DLBCLs) are a genetically and metabolically heterogeneous cancer. Although MPC expression and activity differed between DLBCL subgroups, mitochondrial pyruvate was uniformly consumed by glutamate pyruvate transaminase 2 (GPT2) to support -ketoglutarate production as part of glutaminolysis. This led us to discover that glutamine exceeds pyruvate as a carbon source for the tricarboxylic acid (TCA) cycle in DLBCLs. Furthermore, we found that MPC inhibition unexpectedly leads to decreased glutaminolysis, which is contrary to previous observations in other cell types. We also discovered that MPC inhibition and depletion only decreased DLBCL proliferation in an extracellular matrix (ECM) environment and in vivo xenografts, but not in the typical DLBCL suspension environment. We also have found that the metabolic profile of DLBCL cells in ECM is markedly different from cells in suspension environment. Thus, we report that besides the canonical glutamate dehydrogenase (GDH)-mediated glutaminolysis, the non-canonical GPT2 mediated consumption and assimilation of glutamine and pyruvate in DLBCLs enables their proliferation in an extracellular environment-dependent manner. HIGHLIGHTSO_LIGlutamine, but not glucose, is a major carbon source for the tricarboxylic acid cycle in diffuse large B-cell lymphomas. C_LIO_LIMitochondrial pyruvate supports glutaminolysis in diffuse large B-cell lymphomas by supplying pyruvate for glutamate pyruvate transaminase 2-mediated -ketoglutarate production. C_LIO_LIMitochondrial pyruvate carrier inhibition leads to decreased glutaminolysis in diffuse large B-cell lymphomas. C_LIO_LI -ketoglutarate production is important for diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment. C_LIO_LIMitochondrial pyruvate carrier activity supports diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment and in mouse xenografts. C_LI

cancer biology↗

bioRxiv2021

Based on the identification of tumor antigens and immune subtypes in renal clear cell carcinoma for mRNA vaccine development

BackgroundCancer vaccine based on mRNA is considered as a promising strategy and has become a new hot spot in cancer immunotherapy. However, its application to KIRC is not clear. A growing body of research has shown that immunotyping can reflect the comprehensive immune status and immune microenvironment of tumor, which is closely related to treatment response and vaccination potential. The aim of this study was to identify the potential antigens of KIRC for the development of anti-KIRC mRNA vaccines, and to further differentiate the immune subtypes of KIRC to construct an immune landscape for the selection of appropriate patients for vaccination. MethodsGene expression profiles and corresponding clinical information of 265 KIRC patients and RNA-seq data of 539 KIRC patients were retrieved from were collected from GEO and TCGA. cBioPortal was used to visualize and compare genetic alterations, while GEPIA2 was used to calculate the prognostic index of selected antigens. The relationship between the infiltration of antigen presenting cells and the expression of the identified antigen was visualized with TIMER, and consensus clustering analysis was used to determine the immune subtypes. Finally, the immune landscape of KIRC is visualized through the dimensionality reduction analysis based on graph learning. ResultsTwo tumor antigens associated with prognostic and antigen-presenting infiltrating cells were identified in KIRC, including LRP2, and DOCK8. KIRC patients were classified into six immune subtypes based on different molecular, cellular, and clinical characteristics. Patients with IS5 and IS6 tumors had an immune "hot" and immunosuppressive phenotype, which was associated with better survival compared to other subtypes, whereas patients with IS1-4 tumors had an immune "cold" phenotype, which was associated with a higher tumor mutation burden. In addition, the expression of immune checkpoints and immunogenic cell death modulators differed significantly in different immunosubtypes of tumors. Finally, the immune landscape of KIRC shows a high degree of heterogeneity across patients. ConclusionsLRP2 and FEM2 are potential KIRC antigens for mRNA vaccine development, and patients with immune subtypes IS1-4 are suitable for vaccination.

bioinformatics↗

bioRxiv2021

Protein phosphatase 1 regulatory inhibitor subunit 14C promotes triple-negative breast cancer progression via sustaining inactive glycogen synthase kinase 3 beta

The majority of clinical deaths among patients with triple-negative breast cancer (TNBC) are caused by uncontrolled cell proliferation and aggressive metastases, which is regulated by hyperactive glycogen synthase kinase 3 beta (GSK3{beta}); however, the underlying mechanisms remain largely unknown. In the present study, we found that protein phosphatase 1 regulatory inhibitor subunit 14C (PPP1R14C) was specifically upregulated in TNBC, compared with that in normal tissues and non-TNBC. High PPP1R14C expression correlated significantly with shorter 5-year relapse-free survival and overall survival in patients with TNBC. Overexpressing PPP1R14C promoted, while suppression of PPP1R14C decreased the cell proliferation and the aggressive phenotype of TNBC cells, in vitro and in vivo. Importantly, we revealed that PPP1R14C interacted with and inactivated type 1 Ser/Thr protein phosphatase (PP1) to sustain GSK3{beta} phosphorylation at S9, and induced the ubiquitylation and degradation of non-phosphorylated GSK3{beta} (S9A) via recruiting E3 ligase, TRIM25. Furthermore, treating with C2 ceramide (C2), which recovered kinase activity of GSK3{beta}, resulted in tumor growth inhibition in PPP1R14C-overexpressing TNBC cells. Our findings reveal a novel mechanism whereby PPP1R14C sustains inactive GSK3{beta}, which might lead to targeted therapy for TNBC.

cancer biology↗

bioRxiv2021

Untargeted 1H NMR Metabolomics and Pathway Analysis Reveals Dysregulated Proteostasis in Cyclophilin D (CypD)-deficient Mice Tissues

Cyclophilin D (CypD) is a nuclear-encoded mitochondrial protein. Although best known as a regulator of the mitochondrial permeability transition pore (MPTP), it is also implicated in the regulation of cellular bioenergetics and extramitochondrial activities. In addition, being a peptidyl prolyl cis-trans isomerase (PPIase), deletion of CypD is likely to affect protein stability in the mitochondria; however, there is little direct evidence of this. In this study, untargeted 1H NMR metabolomics, coupled with multivariate analysis, was used to describe simultaneous changes in the metabolic system of CypD-deficient mice liver, heart, and pancreas, with data from the serum to identify systematic changes. Metabolomics Pathway Analyses (MetPA) revealed commonly perturbed metabolites in the different mouse tissues lacking CypD, with significantly enriched pathways that are related to amino acid, glucose and purine metabolisms, and bioenergetics. Serum from CypD-deficient mice confirmed changes in tissue urea cycle, lipid metabolism and ketogenesis. Overall this study reveals the role of CypD in maintaining protein homeostasis, concurring with its biochemical property as a peptidyl-prolyl isomerase and also demonstrates the wider metabolic adaptations induced by the deletion of the ppif gene, resulting in a CypD-deficient mice metabolome that is different from the wild-type system.

biochemistry↗

bioRxiv2021

Species-specific gene duplication in Arabidopsis thaliana evolved novel phenotypic effects on morphological traits under strong positive selection

Gene duplication is increasingly recognized as an important mechanism for the origination of new genes, as revealed by comparative genomic analysis. However, the ways in which new duplicate genes contribute to phenotypic evolution remain largely unknown, especially in plants, owing to a lack of experimental and phenotypic data. In this study, we identified the new gene Exov, derived from a partial gene region duplication of its parental gene Exov-L, which is a member of an exonuclease family, into a different chromosome in Arabidopsis thaliana. We experimentally investigated the phenotypic effects of Exov and Exov-L in an attempt to understand how the new gene diverged from the parental copy and contributes to phenotypic evolution. Evolutionary analysis demonstrated that Exov is a species-specific gene that originated within the last 3.5 million years and shows strong signals of positive selection. Unexpectedly, RNAseq analyses reveal that the new gene, despite its young age, has acquired a large number of novel direct and indirect interactions in which the parental gene does not engage. This is consistent with a high, selection-driven substitution rate in the protein sequence encoded by Exov in contrast to the slowly evolving Exov-L, suggesting an important role for Exov in phenotypic evolution. We analyzed phenotypic effects of exov and exov-l single T-DNA-insertion mutants;double exov, exov-l T-DNA insertion mutants; and CRISPR/Cas9-mediated exovcrp and exov-lcrp knockouts on seven morphological traits in both the new and parental genes. We detected significant segregation of morphological changes for all seven traits when assessed in terms of single mutants, as well as morphological changes for seven traits associated with segregation of double exov, exov-l mutants. Substantial divergence of phenotypic effects between new and parental genes was revealed by principal component analyses, suggesting neofunctionalization in the new gene. These results reveal a young gene that plays critical roles in biological processes that underlie morphological and developmental evolution in Arabidopsis thaliana.

evolutionary biology↗

bioRxiv2020

MetaFunPrimer: primer design for targeting genes observed in metagenomes

High throughput primer design is needed to simultaneously design primers for multiple genes of interest, such as a group of functional genes. We have developed MetaFunPrimer, a bioinformatic pipeline to design primer targets for genes of interests, with a prioritization based on ranking the presence of gene targets in references, such as metagenomes. MetaFunPrimer takes inputs of protein and nucleotide sequences for gene targets of interest accompanied by a set of reference metagenomes or genomes for determining genes of interest. Its output is a set of primers that may be used to amplify genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 HT-qPCR primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 soil metagenomes. We demonstrate that these primers can significantly improve targeting of amoA-AOB genes in soil metagenomes compared to previously published primers. IMPORTANCEAmplification-based gene characterization allows for sensitive and specific quantification of functional genes. Often, there is a large diversity of genes represented for a function of interest, and multiple primers may be necessary to target associated genes. Current primer design tools are limited to designing primers for only a few genes of interest. MetaFunPrimer allows for high throughput primer design for functional genes of interest and also allows for ranking gene targets by their presence and abundance in environmental datasets. This tool enables high throughput qPCR approaches for characterizing functional genes.

bioinformatics↗

bioRxiv2020

Gazing into the Metaboverse: Automated exploration and contextualization of metabolic data

Metabolism forms a complex, interdependent network, and perturbations can have indirect effects that are pervasive. Identifying these patterns and their consequences is difficult, particularly when the effects occur across canonical pathways, and these difficulties have long acted as a bottleneck in metabolic data analysis. This challenge is compounded by technical limitations in metabolomics approaches that garner incomplete datasets. Current network-based tools generally utilize pathway-level analysis lacking the granular resolution required to provide context into the effects of all perturbations, regardless of magnitude, across the metabolic network. To address these shortcomings, we introduce algorithms that allow for the real-time extraction of regulatory patterns and trends from user data. To minimize the impact of missing measurements within the metabolic network, we introduce methods that enable complex pattern recognition across multiple reactions. These tools are available interactively within the user-friendly Metaboverse app (https://github.com/Metaboverse) to facilitate exploration and hypothesis generation. We demonstrate that expected signatures are accurately captured by Metaboverse. Using public lung adenocarcinoma data, we identify a previously undescribed multi-dimensional signature that correlated with survival outcomes in lung adenocarcinoma patients. Using a model of respiratory deficiency, we identify relevant and previously unreported regulatory patterns that suggest an important compensatory role for citrate during mitochondrial dysfunction. This body of work thus demonstrates that Metaboverse can identify and decipher complex signals from data that have been otherwise difficult to identify with previous approaches.

biochemistry↗

bioRxiv2020

SLE non-coding Genetic Risk Variant Determines the Epigenetic Dysfunction of an Immune Cell Specific Enhancer that Controls Disease-critical microRNA Expression

The human genome contains millions of putative regulatory elements, which regulate gene expression. We are just beginning to understand the functional consequences of genetic variation within these regulatory elements. Since the bulk of common genetic variation impacting polygenic disease phenotypes localizes to these non-coding regions of the genome, understanding the consequences will improve our understanding of the mechanisms mediating genetic risk in human disease. Here, we define the systemic lupus erythematosus (SLE) risk variant rs2431369 as likely causal for SLE and show that it is located in a functional regulatory element that modulates miR-146a expression. We use epigenomic analysis and genome-editing to show that the rs2431697-containing region is a distal enhancer that specifically regulates miR-146a expression in a cell-type dependent manner. 3D chromatin structure analysis demonstrates physical interaction between the rs2431697-containing region and the miR-146a promoter. Further, our data show that NF-kB binds the disease protective allele in a sequence-specific manner, leading to increased expression of this immunoregulatory microRNA. Our work provides a strategy for using disease-associated variants to define the functional regulatory elements of non-coding RNA molecules such as miR-146a and provides mechanistic links between autoimmune disease risk genetic variation and disease etiology.

genetics↗

bioRxiv2020

Mitochondrial fatty acid synthesis coordinates mitochondrial oxidative metabolism

Cells harbor two systems for fatty acid synthesis, one in the cytoplasm (catalyzed by fatty acid synthase, FASN) and one in the mitochondria (mtFAS). In contrast to FASN, mtFAS is poorly characterized, especially in higher eukaryotes, with the major product(s), metabolic roles, and cellular function(s) being essentially unknown. Here we show that hypomorphic mtFAS mutants display a severe loss of electron transport chain (ETC) complexes and exhibit compensatory metabolic activities including reductive carboxylation. This effect on ETC complexes appears to be independent of protein lipoylation, the best characterized function of mtFAS, as mutants lacking lipoylation have an intact ETC. Finally, mtFAS impairment blocks the differentiation of skeletal myoblasts in vitro. Together, these data suggest that ETC activity in mammals is profoundly controlled by mtFAS function, thereby connecting anabolic fatty acid synthesis with the oxidation of carbon fuels.

biochemistry↗