TNFα increases the degradation of pyruvate dehydrogenase kinase 4 by the Lon protease to support proinflammatory genes.

The endothelium is a major target of the proinflammatory cytokine, tumor necrosis factor alpha (TNFα). Exposure of endothelial cells (EC) to proinflammatory stimuli leads to an increase in mitochondrial metabolism; however, the function and regulation of elevated mitochondrial metabolism in EC in response to proinflammatory cytokines remain unclear. Studies using high-resolution metabolomics and 13C-glucose and 13C-glutamine labeling flux techniques showed that pyruvate dehydrogenase activity (PDH) and oxidative tricarboxylic acid cycle (TCA) flux are elevated in human umbilical vein ECs in response to overnight (16 h) treatment with TNFα (10 ng/mL). Mechanistic studies indicated that TNFα mediated these metabolic changes via mitochondrial-specific protein degradation of pyruvate dehydrogenase kinase 4 (PDK4, inhibitor of PDH) by the Lon protease via an NF-κB-dependent mechanism. Using RNA sequencing following siRNA-mediated knockdown of the catalytically active subunit of PDH, PDHE1α (PDHA1 gene), we show that PDH flux controls the transcription of approximately one-third of the genes that are up-regulated by TNFα stimulation. Notably, TNFα-induced PDH flux regulates a unique signature of proinflammatory mediators (cytokines and chemokines) but not inducible adhesion molecules. Metabolomics and ChIP sequencing for acetylated modification on lysine 27 of histone 3 (H3K27ac) showed that TNFα-induced PDH flux promotes histone acetylation of specific gene loci via citrate accumulation and ATP-citrate lyase-mediated generation of acetyl CoA. Together, these results uncover a mechanism by which TNFα signaling increases oxidative TCA flux of glucose to support TNFα-induced gene transcription through extramitochondrial acetyl CoA generation and histone acetylation.

Ultrahigh resolution MS1/MS2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action.

Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite.

An Accurate and Individualized Preoperative Estimation Method for the Linear Insertion Depth of Cochlear Implant Electrode Arrays Based on Computed Tomography.

OBJECTIVES: Cochlear implantation or auditory brainstem implantation is currently the only accepted method for improving severe or profound sensorineural hearing loss. The length of the electrodes implanted during cochlear implantation is closely related to the degree of hearing improvement of hearing after the surgery. We aimed to explore new methods to accurately estimate the electrode array (EA) linear insertion depth based on computed tomography (CT) images prior surgery, which could help surgeons select the appropriate EA length for each patient. DESIGN: Previous studies estimated the linear insertion depth by measuring the length of the lateral wall of the cochlea rather than the electrode's path in the cochlea duct. Here, we determined the actual position of the EA on the CT image after cochlear surgery in order to predict the path of the EA, and the length of the predicted EA path was measured by the contouring technique (CoT) to estimate the linear insertion depth of the EA. Because CoT can only measure the length of the estimated EA path on a two-dimensional plane, we further modified the measurement by weighting the height of the cochlea and the length of the EA tail (the length of the last stimulating electrode to the end, which cannot be displayed on the CT image), which we termed the modified CoT + height + tail (MCHT) measurement. RESULTS: Based on our established method, MCHT could reduce the error to the submillimeter range (0.67 ± 0.37 mm) when estimating the linear insertion depth of various kinds of EAs compared with the actual implant length. The correlation coefficient between the linear insertion depth as predicted by MCHT and the actual was 0.958. The linear insertion depth estimated by this method was more accurate than that estimated using the classical CoT technique ( R = 0.442) and using the modified Escudé's method ( R = 0.585). CONCLUSIONS: MCHT is a method based on CT images that can accurately predict the linear insertion depth of cochlear implants preoperatively. This is the first report that we are aware of a method for predicting linear insertion depth before cochlear implantation with only submillimeter errors and that is tailored to different types of EAs.

Memory-like response in platelet attenuates platelet hyperactivation in arterial thrombosis.

Recent studies showed that in responding of pathogens stimulation, immune cells and other cells display memory-like effects. Platelets are primary effectors of hemostasis and thrombosis which also participate in immune responses. However, there is no relevant research on whether memory-like effect exists in platelets. In our study after recovery from repetitive LPS stimulus, platelets aggregation, diffusion and clot retraction exhibit a significant reduction. It proves that memory-like response could be aroused in platelets. Furthermore, in the mouse arterial thrombosis model, LPS pretreated platelets showed lower integrin activation, shorter thrombus length and longer occlusion time, indicating that the memory-like response of platelet could alleviate arterial thrombosis. Moreover, memory-like response of platelets was also found to be related to PI3K/AKT signaling pathway. The decreased mitochondrial DNA methylation reveal that platelet memory-like responses may be produced from epigenetic reprogramming. Our research proves for the first time that memory-like response in platelets protects mice from arterial thrombosis, extends the understanding of trained memory.

Anisomycin inhibits angiogenesis, growth, and survival of triple-negative breast cancer through mitochondrial dysfunction, AMPK activation, and mTOR inhibition.

Aberrant upregulation of mitochondrial biogenesis is observed in breast cancer and holds potential therapeutic option. In our work, we showed that inhibition of mitochondrial function by anisomycin is effective against triple-negative breast cancer (TNBC). Anisomycin inhibits growth and induces caspase-dependent apoptosis in a panel of TNBC cell lines. Of note, anisomycin at a tolerable dose remarkably suppresses growth of TNBC in mice. In addition, anisomycin effectively targets breast cancer angiogenesis through inhibiting capillary network formation, migration, proliferation, and survival. Mechanistic studies show that although anisomycin activates p38 and JNK, their activations are not required for anisomycin's action. In contrast, anisomycin inhibits mitochondrial respiration, and decreases mitochondrial membrane potential and adenosine triphosphate (ATP) level. The inhibitory effect of anisomycin is significantly reversed in mitochondria respiration-deficient ρ0 cells. As a consequence, anisomycin activates AMPK and inhibits mammalian target-of-rapamycin signaling pathways. Our work demonstrated that anisomycin is a useful addition to the treatment armamentarium for TNBC.

An Ion Chromatography-Ultrahigh-Resolution-MS1/Data-Independent High-Resolution MS2 Method for Stable Isotope-Resolved Metabolomics Reconstruction of Central Metabolic Networks.

The metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, the reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh -resolution (UHR)-mass spectrometry (MS). UHR-MS1 readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS1 with its long acquisition time, while acquiring MS2 data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS1/data-independent(DI)-HR-MS2 method to trace the fate of 13C atoms from [13C6]-glucose ([13C6]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously 13C/15N atoms from [13C5,15N2]-glutamine ([13C5,15N2]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS1 while simultaneously acquiring substructure label information via DI-MS2. These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme-catalyzed reactions that are impacted by selenite or arsenite treatments.

Trans-splicing enhances translational efficiency in C. elegans.

Translational efficiency is subject to extensive regulation. However, the factors influencing such regulation are poorly understood. In Caenorhabditis elegans, 62% of genes are trans-spliced to a specific spliced leader (SL1), which replaces part of the native 5' untranslated region (5' UTR). Given the pivotal role the 5' UTR plays in the regulation of translational efficiency, we hypothesized that SL1 trans-splicing functions to regulate translational efficiency. With genome-wide analysis on Ribo-seq data, polysome profiling experiments, and CRISPR-Cas9-based genetic manipulation of trans-splicing sites, we found four lines of evidence in support of this hypothesis. First, SL1 trans-spliced genes have higher translational efficiencies than non-trans-spliced genes. Second, SL1 trans-spliced genes have higher translational efficiencies than non-trans-spliced orthologous genes in other nematode species. Third, an SL1 trans-spliced isoform has higher translational efficiency than the non-trans-spliced isoform of the same gene. Fourth, deletion of trans-splicing sites of endogenous genes leads to reduced translational efficiency. Importantly, we demonstrated that SL1 trans-splicing plays a key role in enhancing translational efficiencies of essential genes. We further discovered that SL1 trans-splicing likely enhances translational efficiency by shortening the native 5' UTRs, hence reducing the presence of upstream start codons (uAUG) and weakening mRNA secondary structures. Taken together, our study elucidates the global function of trans-splicing in enhancing translational efficiency in nematodes, paving the way for further understanding the genomic mechanisms of translational regulation.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks.

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

3D Printed Tubulanes as Lightweight Hypervelocity Impact Resistant Structures.

Lightweight materials with high ballistic impact resistance and load-bearing capabilities are regarded as a holy grail in materials design. Nature builds these complementary properties into materials using soft organic materials with optimized, complex geometries. Here, the compressive deformation and ballistic impact properties of three different 3D printed polymer structures, named tubulanes, are reported, which are the architectural analogues of cross-linked carbon nanotubes. The results show that macroscopic tubulanes are remarkable high load-bearing, hypervelocity impact-resistant lightweight structures. They exhibit a lamellar deformation mechanism, arising from the tubulane ordered pore structure, manifested across multiple length scales from nano to macro dimensions. This approach of using complex geometries inspired by atomic and nanoscale models to generate macroscale printed structures allows innovative morphological engineering of materials with tunable mechanical responses.

Anthelmintic drug ivermectin inhibits angiogenesis, growth and survival of glioblastoma through inducing mitochondrial dysfunction and oxidative stress.

Glioblastoma is one of the most vascular brain tumour and highly resistant to current therapy. Targeting both glioblastoma cells and angiogenesis may present an effective therapeutic strategy for glioblastoma. In our work, we show that an anthelmintic drug, ivermectin, is active against glioblastoma cells in vitro and in vivo, and also targets angiogenesis. Ivermectin significantly inhibits growth and anchorage-independent colony formation in U87 and T98G glioblastoma cells. It induces apoptosis in these cells through a caspase-dependent manner. Ivermectin significantly suppresses the growth of two independent glioblastoma xenograft mouse models. In addition, ivermectin effectively targets angiogenesis through inhibiting capillary network formation, proliferation and survival in human brain microvascular endothelial cell (HBMEC). Mechanistically, ivermectin decreases mitochondrial respiration, membrane potential, ATP levels and increases mitochondrial superoxide in U87, T98G and HBMEC cells exposed to ivermectin. The inhibitory effects of ivermectin are significantly reversed in mitochondria-deficient cells or cells treated with antioxidants, further confirming that ivermectin acts through mitochondrial respiration inhibition and induction of oxidative stress. Importantly, we show that ivermectin suppresses phosphorylation of Akt, mTOR and ribosomal S6 in glioblastoma and HBMEC cells, suggesting its inhibitory role in deactivating Akt/mTOR pathway. Altogether, our work demonstrates that ivermectin is a useful addition to the treatment armamentarium for glioblastoma. Our work also highlights the therapeutic value of targeting mitochondrial metabolism in glioblastoma.

Optimization of an accelerated solvent extraction dispersive liquid-liquid microextraction method for the separation and determination of essential oil from Ligusticum chuanxiong Hort by gas chromatography with mass spectrometry.

In this study, an accelerated solvent extraction dispersive liquid-liquid microextraction coupled with gas chromatography and mass spectrometry was established and employed for the extraction, concentration and analysis of essential oil constituents from Ligusticum chuanxiong Hort. Response surface methodology was performed to optimize the key parameters in accelerated solvent extraction on the extraction efficiency, and key parameters in dispersive liquid-liquid microextraction were discussed as well. Two representative constituents in Ligusticum chuanxiong Hort, (Z)-ligustilide and n-butylphthalide, were quantitatively analyzed. It was shown that the qualitative result of the accelerated solvent extraction dispersive liquid-liquid microextraction approach was in good agreement with that of hydro-distillation, whereas the proposed approach took far less extraction time (30 min), consumed less plant material (usually <1 g, 0.01 g for this study) and solvent (<20 mL) than the conventional system. To sum up, the proposed method could be recommended as a new approach in the extraction and analysis of essential oil.

LC-ESI-MS/MS analysis and pharmacokinetics of GP205, an innovative potent macrocyclic inhibitor of hepatitis C virus NS3/4A protease in rats.

A high-throughput, sensitive and specific LC-ESI-MS/MS method was established for the quantitative determination of GP205, a potent inhibitor of hepatitis C virus NS3/4A protease, in rat. The analyte was isolated from 25 µL plasma sample by 96-well LLE. Good linearity was achieved within the concentration range of 2-5000 ng/mL (r2 > 0.996). The intra- and inter-day precision was less than 10%. The accuracy ranged from 0.8% to 5.5% for GP205 in quality control samples at three levels. GP205 was stable during the analysis and the storage period. The method was successfully applied to pharmacokinetic studies of GP205 in Sprague-Dawley rats. The pharmacokinetic profiles of GP205 at three dose levels with oral administration and one dose level with intravenous administration were successfully studied for the first time in SD rats, respectively. After single oral administration of GP205 at the doses of 2.5, 5, 10 mg/kg, respectively, Cmax and AUC0-τ were proportional to the doses given. The absolute bioavailability was estimated as 34% based on the AUCs of oral administration at the dose of 5 mg/kg and intravenous administration at the dose of 1 mg/kg. The data presented in this study provides useful information for further study for GP205.

Isolation and identification of two unknown impurities from the raw material of clindamycin hydrochloride.

Clindamycin hydrochloride belongs to the antibiotic family of lincomycin. It has the same antibacterial spectrum as lincomycin, but the antibacterial activity is four to eight times stronger than that of lincomycin. There have been some adverse reactions in clinical use of clindamycin hydrochloride and its finished drug products. The impurities in drugs are directly related to their safety. In this study, two unknown impurities were isolated from the raw material of clindamycin hydrochloride through various chromatographic methods. Their structures were identified as clindamycin isomer (impurity 1) and dehydroclindamycin (impurity 2) by mass spectrometry and NMR spectroscopy. Both of them were found for the first time. The two impurities exhibit a similar but lower antibacterial activity compared with clindamycin hydrochloride.

Development and validation of a cost-effective virtual reality educational tool to reduce anxiety and improve set-up accuracy in radiotherapy patients.

PURPOSE: This study proposes a cost-effective method for educating radiotherapy patients through an immersive virtual reality (VR) system. METHODS: The VR educational tool comprises VR glasses, a handheld controller, the scientific knowledge of radiotherapy, radiotherapy demonstration, and an audio introduction. To verify its efficacy, 120 radiotherapy patients with tumors were prospectively enrolled and divided into the control group or VR intervention group. After the first treatment, set-up errors, including three translation errors and three rotation errors, were recorded in six directions. In addition, participants were required to complete a questionnaire before radiotherapy to assess anxiety and understanding degrees. The questionnaire was scored using a five-point Likert Scale. Finally, Spearman's rank correlation test was used to evaluate set-up errors and questionnaire scores. RESULTS: The set-up errors are significantly reduced in AP, SI, total translation, Roll and total rotation in the intervention group compared with the control group (p < 0.05). The scores are higher in the intervention group than in the control group in question 1 (2.1 ± 0.58 vs. 3.3 ± 0.55), question 2 (1.3 ± 0.44 vs. 2.5 ± 0.65), question 4 (2.2 ± 0.65 vs. 3.2 ± 0.82), question 5 (1.8 ± 0.59 vs. 3.1 ± 0.79), and all subscales (5.5 ± 1.2 vs. 8.9 ± 1.3 and 6.4 ± 1.3 vs. 9.2 ± 1.5). The scores of high, moderate, and low correlation are 47 (74%), 15 (23%), and 2 (3%) for the control group and 44 (69%), 17 (26%), and 3 (5%) for the intervention group, respectively. CONCLUSION: The VR educational tool can significantly improve comprehension and reduce anxiety. There is a strong correlation between set-up errors and questionnaire scores. The VR educational tool may help reduce set-up errors for radiotherapy patients.

A live-cell image-based machine learning strategy for reducing variability in PSC differentiation systems.

The differentiation of pluripotent stem cells (PSCs) into diverse functional cell types provides a promising solution to support drug discovery, disease modeling, and regenerative medicine. However, functional cell differentiation is currently limited by the substantial line-to-line and batch-to-batch variabilities, which severely impede the progress of scientific research and the manufacturing of cell products. For instance, PSC-to-cardiomyocyte (CM) differentiation is vulnerable to inappropriate doses of CHIR99021 (CHIR) that are applied in the initial stage of mesoderm differentiation. Here, by harnessing live-cell bright-field imaging and machine learning (ML), we realize real-time cell recognition in the entire differentiation process, e.g., CMs, cardiac progenitor cells (CPCs), PSC clones, and even misdifferentiated cells. This enables non-invasive prediction of differentiation efficiency, purification of ML-recognized CMs and CPCs for reducing cell contamination, early assessment of the CHIR dose for correcting the misdifferentiation trajectory, and evaluation of initial PSC colonies for controlling the start point of differentiation, all of which provide a more invulnerable differentiation method with resistance to variability. Moreover, with the established ML models as a readout for the chemical screen, we identify a CDK8 inhibitor that can further improve the cell resistance to the overdose of CHIR. Together, this study indicates that artificial intelligence is able to guide and iteratively optimize PSC differentiation to achieve consistently high efficiency across cell lines and batches, providing a better understanding and rational modulation of the differentiation process for functional cell manufacturing in biomedical applications.

CIEGAN: A Deep Learning Tool for Cell Image Enhancement.

Long-term live-cell imaging technology has emerged in the study of cell culture and development, and it is expected to elucidate the differentiation or reprogramming morphology of cells and the dynamic process of interaction between cells. There are some advantages to this technique: it is noninvasive, high-throughput, low-cost, and it can help researchers explore phenomena that are otherwise difficult to observe. Many challenges arise in the real-time process, for example, low-quality micrographs are often obtained due to unavoidable human factors or technical factors in the long-term experimental period. Moreover, some core dynamics in the developmental process are rare and fleeting in imaging observation and difficult to recapture again. Therefore, this study proposes a deep learning method for microscope cell image enhancement to reconstruct sharp images. We combine generative adversarial nets and various loss functions to make blurry images sharp again, which is much more convenient for researchers to carry out further analysis. This technology can not only make up the blurry images of critical moments of the development process through image enhancement but also allows long-term live-cell imaging to find a balance between imaging speed and image quality. Furthermore, the scalability of this technology makes the methods perform well in fluorescence image enhancement. Finally, the method is tested in long-term live-cell imaging of human-induced pluripotent stem cell-derived cardiomyocyte differentiation experiments, and it can greatly improve the image space resolution ratio.

Reduced DMPC and PMPC in lung surfactant promote SARS-CoV-2 infection in obesity.

OBJECTIVE: Obesity is an established risk factor for higher SARS-CoV-2 viral loads, severe COVID-19 pneumonia requiring hospitalization, and worse outcomes. However, the underlying mechanisms for the increased risk are not well understood. SARS-CoV-2 is a respiratory virus with the primary route of entry through the lungs, where the Spike protein of SARS-CoV-2 binds to the ACE2 receptor on pneumocytes. Lung surfactant produced by type II pneumocytes plays a major role in respiratory defense against infections. Surfactant predominantly contains lipids, especially phosphatidylcholines (PC), and obesity is characterized by aberrant lipid metabolism. We hypothesized that altered lipid composition in lung surfactant in obesity may promote SARS-CoV-2 infection, leading to severe COVID-19 disease. METHODS: Lipidomic analysis of lung tissue and bronchoalveolar lavage fluid (BALF) was performed using LC-MS/MS. The effects of PCs on SARS-CoV-2 pseudovirus infection were studied in HEK293T cells with ACE2 overexpression and in Vero-E6 cells with endogenous ACE2 expression. For the cell-cell fusion assay, HEK293T-ACE2 and HEK293T expressing SARS-CoV-2 Spike/eGFP were used as the target and effector cells, respectively. RESULTS: Lipidomic analysis revealed that myristic acid-containing dimyristoyl-PC (DMPC) and palmitoylmyristoyl-PC (PMPC) were reduced in lung tissue and BALF from high fat diet-induced obese mice. DMPC and PMPC markedly inhibited wild type and D614G mutant SARS-CoV-2 infection in HEK293T-ACE2 and Vero-E6 cells. Feeding obese mice with trimyristin, the triglycerides of myristic acid, increased DMPC and PMPC levels in lung surfactant. Lipid extract from BALF of trimyristin-treated obese mice mitigated the elevated wild type and D614G mutant SARS-CoV-2 infection. The inhibitory effects of DMPC and PMPC on SARS-CoV-2 infection were reversed by cholesterol. CONCLUSIONS: The reduced DMPC and PMPC in lung surfactant may promote SARS-CoV-2 infection. Increasing DMPC and PMPC in lung surfactant could be an innovative strategy for preventing and treating severe COVID-19 disease in obesity.

UCP2-dependent redox sensing in POMC neurons regulates feeding.

Paradoxically, glucose, the primary driver of satiety, activates a small population of anorexigenic pro-opiomelanocortin (POMC) neurons. Here, we show that lactate levels in the circulation and in the cerebrospinal fluid are elevated in the fed state and the addition of lactate to glucose activates the majority of POMC neurons while increasing cytosolic NADH generation, mitochondrial respiration, and extracellular pyruvate levels. Inhibition of lactate dehydrogenases diminishes mitochondrial respiration, NADH production, and POMC neuronal activity. However, inhibition of the mitochondrial pyruvate carrier has no effect. POMC-specific downregulation of Ucp2 (Ucp2PomcKO), a molecule regulated by fatty acid metabolism and shown to play a role as transporter in the malate-aspartate shuttle, abolishes lactate- and glucose-sensing of POMC neurons. Ucp2PomcKO mice have impaired glucose metabolism and are prone to obesity on a high-fat diet. Altogether, our data show that lactate through redox signaling and blocking mitochondrial glucose utilization activates POMC neurons to regulate feeding and glucose metabolism.

Sall4 and Myocd Empower Direct Cardiac Reprogramming From Adult Cardiac Fibroblasts After Injury.

Direct conversion of fibroblasts into induced cardiomyocytes (iCMs) holds promising potential to generate functional cardiomyocytes for drug development and clinical applications, especially for direct in situ heart regeneration by delivery of reprogramming genes into adult cardiac fibroblasts in injured hearts. For a decade, many cocktails of transcription factors have been developed to generate iCMs from fibroblasts of different tissues in vitro and some were applied in vivo. Here, we aimed to develop genetic cocktails that induce cardiac reprogramming directly in cultured cardiac fibroblasts isolated from adult mice with myocardial infarction (MICFs), which could be more relevant to heart diseases. We found that the widely used genetic cocktail, Gata4, Mef2c, and Tbx5 (GMT) were inefficient in reprogramming cardiomyocytes from MICFs. In a whole well of a 12-well plate, less than 10 mCherry+ cells (<0.1%) were observed after 2 weeks of GMT infection with Myh6-reporter transgenic MICFs. By screening 22 candidate transcription factors predicted through analyzing the gene regulatory network of cardiac development, we found that five factors, GMTMS (GMT plus Myocd and Sall4), induced more iCMs expressing the cardiac structural proteins cTnT and cTnI at a frequency of about 22.5 ± 2.7% of the transduced MICFs at day 21 post infection. What is more, GMTMS induced abundant beating cardiomyocytes at day 28 post infection. Specifically, Myocd contributed mainly to inducing the expression of cardiac proteins, while Sall4 accounted for the induction of functional properties, such as contractility. RNA-seq analysis of the iCMs at day 28 post infection revealed that they were reprogrammed to adopt a cardiomyocyte-like gene expression profile. Overall, we show here that Sall4 and Myocd play important roles in cardiac reprogramming from MICFs, providing a cocktail of genetic factors that have potential for further applications in in vivo cardiac reprogramming.