Activation of polyamine catabolism promotes glutamine metabolism and creates a targetable vulnerability in lung cancer.

Polyamines are a class of small polycationic alkylamines that play essential roles in both normal and cancer cell growth. Polyamine metabolism is frequently dysregulated and considered a therapeutic target in cancer. However, targeting polyamine metabolism as monotherapy often exhibits limited efficacy, and the underlying mechanisms are incompletely understood. Here we report that activation of polyamine catabolism promotes glutamine metabolism, leading to a targetable vulnerability in lung cancer. Genetic and pharmacological activation of spermidine/spermine N1-acetyltransferase 1 (SAT1), the rate-limiting enzyme of polyamine catabolism, enhances the conversion of glutamine to glutamate and subsequent glutathione (GSH) synthesis. This metabolic rewiring ameliorates oxidative stress to support lung cancer cell proliferation and survival. Simultaneous glutamine limitation and SAT1 activation result in ROS accumulation, growth inhibition, and cell death. Importantly, pharmacological inhibition of either one of glutamine transport, glutaminase, or GSH biosynthesis in combination with activation of polyamine catabolism synergistically suppresses lung cancer cell growth and xenograft tumor formation. Together, this study unveils a previously unappreciated functional interconnection between polyamine catabolism and glutamine metabolism and establishes cotargeting strategies as potential therapeutics in lung cancer.

Warm temperature-triggered developmental reprogramming requires VIL1-mediated, genome-wide H3K27me3 accumulation in Arabidopsis.

Changes in ambient temperature immensely affect developmental programs in many species. Plants adapt to high ambient growth temperature in part by vegetative and reproductive developmental reprogramming, known as thermo-morphogenesis. Thermo-morphogenesis is accompanied by massive changes in the transcriptome upon temperature change. Here, we show that transcriptome changes induced by warm ambient temperature require VERNALIZATION INSENSITIVE 3-LIKE 1 (VIL1), a facultative component of the Polycomb repressive complex PRC2, in Arabidopsis. Warm growth temperature elicits genome-wide accumulation of H3K27me3 and VIL1 is necessary for the warm temperature-mediated accumulation of H3K27me3. Consistent with its role as a mediator of thermo-morphogenesis, loss of function of VIL1 results in hypo-responsiveness to warm ambient temperature. Our results show that VIL1 is a major chromatin regulator in responses to high ambient temperature.

Twelve-hour rhythms in transcript expression within the human dorsolateral prefrontal cortex are altered in schizophrenia.

Twelve-hour (12 h) ultradian rhythms are a well-known phenomenon in coastal marine organisms. While 12 h cycles are observed in human behavior and physiology, no study has measured 12 h rhythms in the human brain. Here, we identify 12 h rhythms in transcripts that either peak at sleep/wake transitions (approximately 9 AM/PM) or static times (approximately 3 PM/AM) in the dorsolateral prefrontal cortex, a region involved in cognition. Subjects with schizophrenia (SZ) lose 12 h rhythms in genes associated with the unfolded protein response and neuronal structural maintenance. Moreover, genes involved in mitochondrial function and protein translation, which normally peak at sleep/wake transitions, peak instead at static times in SZ, suggesting suboptimal timing of these essential processes.

Transcriptomic congruence analysis for evaluating model organisms.

Model organisms are instrumental substitutes for human studies to expedite basic, translational, and clinical research. Despite their indispensable role in mechanistic investigation and drug development, molecular congruence of animal models to humans has long been questioned and debated. Little effort has been made for an objective quantification and mechanistic exploration of a model organism's resemblance to humans in terms of molecular response under disease or drug treatment. We hereby propose a framework, namely Congruence Analysis for Model Organisms (CAMO), for transcriptomic response analysis by developing threshold-free differential expression analysis, quantitative concordance/discordance scores incorporating data variabilities, pathway-centric downstream investigation, knowledge retrieval by text mining, and topological gene module detection for hypothesis generation. Instead of a genome-wide vague and dichotomous answer of "poorly" or "greatly" mimicking humans, CAMO assists researchers to numerically quantify congruence, to dissect true cross-species differences from unwanted biological or cohort variabilities, and to visually identify molecular mechanisms and pathway subnetworks that are best or least mimicked by model organisms, which altogether provides foundations for hypothesis generation and subsequent translational decisions.

Model-based multifacet clustering with high-dimensional omics applications.

High-dimensional omics data often contain intricate and multifaceted information, resulting in the coexistence of multiple plausible sample partitions based on different subsets of selected features. Conventional clustering methods typically yield only one clustering solution, limiting their capacity to fully capture all facets of cluster structures in high-dimensional data. To address this challenge, we propose a model-based multifacet clustering (MFClust) method based on a mixture of Gaussian mixture models, where the former mixture achieves facet assignment for gene features and the latter mixture determines cluster assignment of samples. We demonstrate superior facet and cluster assignment accuracy of MFClust through simulation studies. The proposed method is applied to three transcriptomic applications from postmortem brain and lung disease studies. The result captures multifacet clustering structures associated with critical clinical variables and provides intriguing biological insights for further hypothesis generation and discovery.

Latent space search based multimodal optimization with personalized edge-network biomarker for multi-purpose early disease prediction.

Considering that cancer is resulting from the comutation of several essential genes of individual patients, researchers have begun to focus on identifying personalized edge-network biomarkers (PEBs) using personalized edge-network analysis for clinical practice. However, most of existing methods ignored the optimization of PEBs when multimodal biomarkers exist in multi-purpose early disease prediction (MPEDP). To solve this problem, this study proposes a novel model (MMPDENB-RBM) that combines personalized dynamic edge-network biomarkers (PDENB) theory, multimodal optimization strategy and latent space search scheme to identify biomarkers with different configurations of PDENB modules (i.e. to effectively identify multimodal PDENBs). The application to the three largest cancer omics datasets from The Cancer Genome Atlas database (i.e. breast invasive carcinoma, lung squamous cell carcinoma and lung adenocarcinoma) showed that the MMPDENB-RBM model could more effectively predict critical cancer state compared with other advanced methods. And, our model had better convergence, diversity and multimodal property as well as effective optimization ability compared with the other state-of-art methods. Particularly, multimodal PDENBs identified were more enriched with different functional biomarkers simultaneously, such as tissue-specific synthetic lethality edge-biomarkers including cancer driver genes and disease marker genes. Importantly, as our aim, these multimodal biomarkers can perform diverse biological and biomedical significances for drug target screen, survival risk assessment and novel biomedical sight as the expected multi-purpose of personalized early disease prediction. In summary, the present study provides multimodal property of PDENBs, especially the therapeutic biomarkers with more biological significances, which can help with MPEDP of individual cancer patients.

Cell-type and sex-specific rhythmic gene expression in the nucleus accumbens.

Circadian rhythms are critical for human health and are highly conserved across species. Disruptions in these rhythms contribute to many diseases, including psychiatric disorders. Previous results suggest that circadian genes modulate behavior through specific cell types in the nucleus accumbens (NAc), particularly dopamine D1-expressing medium spiny neurons (MSNs). However, diurnal rhythms in transcript expression have not been investigated in NAc MSNs. In this study we identified and characterized rhythmic transcripts in D1- and D2-expressing neurons and compared rhythmicity results to homogenate as well as astrocyte samples taken from the NAc of male and female mice. We find that all cell types have transcripts with diurnal rhythms and that top rhythmic transcripts are largely core clock genes, which peak at approximately the same time of day in each cell type and sex. While clock-controlled rhythmic transcripts are enriched for protein regulation pathways across cell type, cell signaling and signal transduction related processes are most commonly enriched in MSNs. In contrast to core clock genes, these clock-controlled rhythmic transcripts tend to reach their peak in expression about 2-h later in females than males, suggesting diurnal rhythms in reward may be delayed in females. We also find sex differences in pathway enrichment for rhythmic transcripts peaking at different times of day. Protein folding and immune responses are enriched in transcripts that peak in the dark phase, while metabolic processes are primarily enriched in transcripts that peak in the light phase. Importantly, we also find that several classic markers used to categorize MSNs are rhythmic in the NAc. This is critical since the use of rhythmic markers could lead to over- or under-enrichment of targeted cell types depending on the time at which they are sampled. This study greatly expands our knowledge of how individual cell types contribute to rhythms in the NAc.

Unlocking the link: how hippocampal glutathione-glutamate coupling predicts cognitive impairment in multiple sclerosis patients.

Cognitive impairment is a common symptom of multiple sclerosis and profoundly impacts quality of life. Glutathione (GSH) and glutamate (Glu) are tightly linked in the brain, participating in cognitive function. However, GSH-Glu couplings in cognitive brain regions and their relationship with cognitive impairment in relapsing-remitting multiple sclerosis (RRMS) remains unclear. Forty-one RRMS patients and 43 healthy controls underwent magnetic resonance spectroscopy to measure GSH and Glu levels in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus. Neuropsychological tests were used to evaluate the cognitive function. The Glu/GSH ratio was used to indicate the coupling between GSH and Glu and was tested as a predictor of cognitive performance. The results show that RRMS patients exhibited reduced hippocampal GSH and Glu levels, which were found to be significant predictors of worse verbal and visuospatial memory, respectively. Moreover, GSH levels were dissociated from Glu levels in the left hippocampus of RRMS patients. Hippocampal Glu/GSH ratio is significantly correlated with processing speed and has a greater predictive effect. Here we show the hippocampal Glu/GSH ratio could serve as a new potential marker for characterizing cognitive impairment in RRMS, providing a new direction for clinical detection of cognitive impairment.

Disentangling transcriptomic heterogeneity within the human subgenual anterior cingulate cortex.

The subgenual anterior cingulate cortex (sgACC) is a critical site for understanding the neural correlates of affect and emotion. While the activity of the sgACC is functionally homogenous, it is comprised of multiple Brodmann Areas (BAs) that possess different cytoarchitectures. In some sgACC BAs, Layer 5 is sublaminated into L5a and L5b which has implications for its projection targets. To understand how the transcriptional profile differs between the BAs, layers, and sublayers of human sgACC, we collected layer strips using laser capture microdissection followed by RNA sequencing. We found no significant differences in transcript expression in these specific cortical layers between BAs within the sgACC. In contrast, we identified striking differences between Layers 3 and 5a or 5b that were concordant across sgACC BAs. We found that sublayers 5a and 5b were transcriptionally similar. Pathway analyses of L3 and L5 revealed overlapping biological processes related to synaptic function. However, L3 was enriched for pathways related to cell-to-cell junction and dendritic spines whereas L5 was enriched for pathways related to brain development and presynaptic function, indicating potential functional differences across layers. Our study provides important insight into normative transcriptional features of the sgACC.

MYB44-ENAP1/2 restricts HDT4 to regulate drought tolerance in Arabidopsis.

Histone acetylation has been shown to involve in stress responses. However, the detailed molecular mechanisms that how histone deacetylases and transcription factors function in drought stress response remain to be understood. In this research, we show that ENAP1 and ENAP2 are positive regulators of drought tolerance in plants, and the enap1enap2 double mutant is more sensitive to drought stress. Both ENAP1 and ENAP2 interact with MYB44, a transcription factor that interacts with histone deacetylase HDT4. Genetics data show that myb44 null mutation enhances the sensitivity of enap1enap2 to drought stress. Whereas, HDT4 negatively regulates plant drought response, the hdt4 mutant represses enap1enap2myb44 drought sensitive phenotype. In the normal condition, ENAP1/2 and MYB44 counteract the HDT4 function for the regulation of H3K27ac. Upon drought stress, the accumulation of MYB44 and reduction of HDT4 leads to the enrichment of H3K27ac and the activation of target gene expression. Overall, this research provides a novel molecular mechanism by which ENAP1, ENAP2 and MYB44 form a complex to restrict the function of HDT4 in the normal condition; under drought condition, accumulated MYB44 and reduced HDT4 lead to the elevation of H3K27ac and the expression of drought responsive genes, as a result, plants are drought tolerant.

Diagnosis and prognosis of breast cancer by high-performance serum metabolic fingerprints.

High-performance metabolic analysis is emerging in the diagnosis and prognosis of breast cancer (BrCa). Still, advanced tools are in demand to deliver the application potentials of metabolic analysis. Here, we used fast nanoparticle-enhanced laser desorption/ionization mass spectrometry (NPELDI-MS) to record serum metabolic fingerprints (SMFs) of BrCa in seconds, achieving high reproducibility and low consumption of direct serum detection without treatment. Subsequently, machine learning of SMFs generated by NPELDI-MS functioned as an efficient readout to distinguish BrCa from non-BrCa with an area under the curve of 0.948. Furthermore, a metabolic prognosis scoring system was constructed using SMFs with effective prediction performance toward BrCa (P < 0.005). Finally, we identified a biomarker panel of seven metabolites that were differentially enriched in BrCa serum and their related pathways. Together, our findings provide an efficient serum metabolic tool to characterize BrCa and highlight certain metabolic signatures as potential diagnostic and prognostic factors of diseases including but not limited to BrCa.

Systematic assessment of serum i-tRF-AsnGTT in gastric cancer: a potential clinical biomarker.

Since gastric cancer shows no apparent signs in its early stages, most patients are diagnosed later with a poor prognosis. We therefore seek more sensitive and specific GC biomarkers. Small RNAs formed from tRNAs represent a novel class of non-coding RNAs that are highly abundant in bodily fluids and essential to biological metabolism. This study explores the potential of i-tRF-AsnGTT in gastric cancer diagnostics. To begin with, we sequenced i-tRF-AsnGTT using high-throughput methods. i-tRF-AsnGTT expression levels in GC were determined using real-time fluorescence PCR. Agarose gel electrophoresis, Sanger sequencing, and repeated freezing and thawing were performed to verify molecular properties. A correlation was found between clinical and pathological parameters and i-tRF-AsnGTT expression levels through the χ² test, and ROC was used to analyze its diagnostic value in GC. In serum, i-tRF-AsnGTT has a low and stable expression level. It can differentiate between patients with gastric cancer and gastritis and healthy donors with better diagnostic efficacy. In combination with clinicopathological parameters, i-tRF-AsnGTT correlates with tumor differentiation, infiltration depth of tumors, TNM stage, lymph node metastases, and neural/vascular invasion. Serum i-tRF-AsnGTT expression is low in GC patients. Serum from postoperative patients shows increased i-tRF-AsnGTT expression levels. Potentially, this could be used as a biomarker to help diagnose gastric cancer and monitor its prognosis.

Highly expressed B3GALT5-AS1 contributes to gastric cancer progression by recruiting WDR5 to mediate B3GALT5 and regulating ß-catenin/ZEB1 axis.

Long non-coding RNAs (lncRNAs) play an important role in the progression of gastric cancer (GC), but its specific regulatory mechanism remains to be further studied. We previously identified that lncRNA B3GALT5-AS1 was upregulated in GC serum. Here, we investigated the functions and molecular mechanisms of B3GALT5-AS1 in GC tumorigenesis. qRT-PCR was used to detect B3GALT5-AS1 expression in GC. EdU, CCK-8, and colony assays were utilized to assess the proliferation ability of B3GAL5-AS1, and transwell, tube formation assay were used to assess the invasion and metastasis ability. Mechanically, FISH and nuclear plasmolysis PCR identified the subcellular localization of B3GALT5-AS1. RIP and CHIP assays were used to analyse the regulation of B3GALT5-AS1 and B3GALT5. We observed that B3GALT5-AS1 was highly expressed in GC, and silencing B3GALT5-AS1 could inhibit the proliferation, invasion, and migratory capacities of GC. Additionally, B3GALT5-AS1 was bound to WDR5 and modulated the expression of B3GALT5 via regulating the ZEB1/ß-catenin pathway. High-expressed B3AGLT5-AS1 promoted GC tumorigenesis and regulated B3GALT5 expression via recruiting WDR5. Our study is expected to provide a new idea for clinical diagnosis and treatment.

Dynamical Janus Interface Design for Reversible and Fast-Charging Zinc-Iodine Battery under Extreme Operating Conditions.

Aqueous zinc (Zn) iodine (I2) batteries have emerged as viable alternatives to conventional metal-ion batteries. However, undesirable Zn deposition and irreversible iodine conversion during cycling have impeded their progress. To overcome these concerns, we report a dynamical interface design by cation chemistry that improves the reversibility of Zn deposition and four-electron iodine conversion. Due to this design, we demonstrate an excellent Zn-plating/-stripping behavior in Zn||Cu asymmetric cells over 1000 cycles with an average Coulombic efficiency (CE) of 99.95%. Moreover, the Zn||I2 full cells achieve a high-rate capability (217.1 mA h g-1 at 40 A g-1; C rate of 189.5C) at room temperature and enable stable cycling with a CE of more than 99% at -50 °C at a current density of 0.05 A g-1. In situ spectroscopic investigations and simulations reveal that introducing tetraethylammonium cations as ion sieves can dynamically modulate the electrode-electrolyte interface environment, forming the unique water-deficient and chloride ion (Cl-)-rich interface. Such Janus interface accounts for the suppression of side reactions, the prevention of ICl decomposition, and the enrichment of reactants, enhancing the reversibility of Zn-stripping/-plating and four-electron iodine chemistry. This fundamental understanding of the intrinsic interplay between the electrode-electrolyte interface and cations offers a rational standpoint for tuning the reversibility of iodine conversion.

Multi-modal optimization to identify personalized biomarkers for disease prediction of individual patients with cancer.

Finding personalized biomarkers for disease prediction of patients with cancer remains a massive challenge in precision medicine. Most methods focus on one subnetwork or module as a network biomarker; however, this ignores the early warning capabilities of other modules with different configurations of biomarkers (i.e. multi-modal personalized biomarkers). Identifying such modules would not only predict disease but also provide effective therapeutic drug target information for individual patients. To solve this problem, we developed a novel model (denoted multi-modal personalized dynamic network biomarkers (MMPDNB)) based on a multi-modal optimization mechanism and personalized dynamic network biomarker (PDNB) theory, which can provide multiple modules of personalized biomarkers and unveil their multi-modal properties. Using the genomics data of patients with breast or lung cancer from The Cancer Genome Atlas database, we validated the effectiveness of the MMPDNB model. The experimental results showed that compared with other advanced methods, MMPDNB can more effectively predict the critical state with the highest early warning signal score during cancer development. Furthermore, MMPDNB more significantly identified PDNBs containing driver and biomarker genes specific to cancer tissues. More importantly, we validated the biological significance of multi-modal PDNBs, which could provide effective drug targets of individual patients as well as markers for predicting early warning signals of the critical disease state. In conclusion, multi-modal optimization is an effective method to identify PDNBs and offers a new perspective for understanding tumor heterogeneity in cancer precision medicine.

DiffCircaPipeline: a framework for multifaceted characterization of differential rhythmicity.

SUMMARY: Circadian oscillations of gene expression regulate daily physiological processes, and their disruption is linked to many diseases. Circadian rhythms can be disrupted in a variety of ways, including differential phase, amplitude and rhythm fitness. Although many differential circadian biomarker detection methods have been proposed, a workflow for systematic detection of multifaceted differential circadian characteristics with accurate false positive control is not currently available. We propose a comprehensive and interactive pipeline to capture the multifaceted characteristics of differentially rhythmic biomarkers. Analysis outputs are accompanied by informative visualization and interactive exploration. The workflow is demonstrated in multiple case studies and is extensible to general omics applications. AVAILABILITY AND IMPLEMENTATION: R package, Shiny app and source code are available in GitHub (https://github.com/DiffCircaPipeline) and Zenodo (https://doi.org/10.5281/zenodo.7507989). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Persistent mTORC1 activation due to loss of liver tuberous sclerosis complex 1 promotes liver injury in alcoholic hepatitis.

BACKGROUND AND AIMS: The aim of the study was to investigate the role and mechanisms of tuberous sclerosis complex 1 (TSC1) and mechanistic target of rapamycin complex 1 (mTORC1) in alcohol-associated liver disease. APPROACH AND RESULTS: Liver-specific Tsc1 knockout (L- Tsc1 KO) mice and their matched wild-type mice were subjected to Gao-binge alcohol. Human alcoholic hepatitis (AH) samples were also used for immunohistochemistry staining, western blot, and quantitative real-time PCR (q-PCR) analysis. Human AH and Gao-binge alcohol-fed mice had decreased hepatic TSC1 and increased mTORC1 activation. Gao-binge alcohol markedly increased liver/body weight ratio and serum alanine aminotransferase levels in L- Tsc1 KO mice compared with Gao-binge alcohol-fed wild-type mice. Results from immunohistochemistry staining, western blot, and q-PCR analysis revealed that human AH and Gao-binge alcohol-fed L- Tsc1 KO mouse livers had significantly increased hepatic progenitor cells, macrophages, and neutrophils but decreased HNF4α-positive cells. Gao-binge alcohol-fed L- Tsc1 KO mice also developed severe inflammation and liver fibrosis. Deleting Tsc1 in cholangiocytes but not in hepatocytes promoted cholangiocyte proliferation and aggravated alcohol-induced ductular reactions, fibrosis, inflammation, and liver injury. Pharmacological inhibition of mTORC1 partially reversed hepatomegaly, ductular reaction, fibrosis, inflammatory cell infiltration, and liver injury in alcohol-fed L- Tsc1 KO mice. CONCLUSIONS: Our findings indicate that persistent activation of mTORC1 due to the loss of cholangiocyte TSC1 promotes liver cell repopulation, ductular reaction, inflammation, fibrosis, and liver injury in Gao-binge alcohol-fed L- Tsc1 KO mice, which phenocopy the pathogenesis of human AH.

Single-atom catalysts for electrocatalytic nitrate reduction into ammonia.

Ammonia (NH3) is a versatile and important compound with a wide range of uses, which is currently produced through the demanding Haber-Bosch process. Electrocatalytic nitrate reduction into ammonia (NRA) has recently emerged as a sustainable approach for NH3synthesis under ambient conditions. However, the NRA catalysis is a complex multistep electrochemical process with competitive hydrogen evolution reaction that usually results in poor selectivity and low yield rate for NH3synthesis. With maximum atom utilization and well-defined catalytic sites, single atom catalysts (SACs) display high activity, selectivity and stability toward various catalytic reactions. Very recently, a number of SACs have been developed as promising NRA electrocatalysts, but systematical discussion about the key factors that affect their NRA performance is not yet to be summarized to date. This review focuses on the latest breakthroughs of SACs toward NRA catalysis, including catalyst preparation, catalyst characterization and theoretical insights. Moreover, the challenges and opportunities for improving the NRA performance of SACs are discussed, with an aim to achieve further advancement in developing high-performance SACs for efficient NH3synthesis.

Ars2 links the nuclear cap-binding complex to RNA interference and cell proliferation.

Here we identify a component of the nuclear RNA cap-binding complex (CBC), Ars2, that is important for miRNA biogenesis and critical for cell proliferation. Unlike other components of the CBC, Ars2 expression is linked to the proliferative state of the cell. Deletion of Ars2 is developmentally lethal, and deletion in adult mice led to bone marrow failure whereas parenchymal organs composed of nonproliferating cells were unaffected. Depletion of Ars2 or CBP80 from proliferating cells impaired miRNA-mediated repression and led to alterations in primary miRNA processing in the nucleus. Ars2 depletion also reduced the levels of several miRNAs, including miR-21, let-7, and miR-155, that are implicated in cellular transformation. These findings provide evidence for a role for Ars2 in RNA interference regulation during cell proliferation.

Mitochondria and Cancer.

Decades ago, Otto Warburg observed that cancers ferment glucose in the presence of oxygen, suggesting that defects in mitochondrial respiration may be the underlying cause of cancer. We now know that the genetic events that drive aberrant cancer cell proliferation also alter biochemical metabolism, including promoting aerobic glycolysis, but do not typically impair mitochondrial function. Mitochondria supply energy; provide building blocks for new cells; and control redox homeostasis, oncogenic signaling, innate immunity, and apoptosis. Indeed, mitochondrial biogenesis and quality control are often upregulated in cancers. While some cancers have mutations in nuclear-encoded mitochondrial tricarboxylic acid (TCA) cycle enzymes that produce oncogenic metabolites, there is negative selection for pathogenic mitochondrial genome mutations. Eliminating mtDNA limits tumorigenesis, and rare human tumors with mutant mitochondrial genomes are relatively benign. Thus, mitochondria play a central and multifunctional role in malignant tumor progression, and targeting mitochondria provides therapeutic opportunities.