CNS-Native Myeloid Cells Drive Immune Suppression in the Brain Metastatic Niche through Cxcl10.

Brain metastasis (br-met) develops in an immunologically unique br-met niche. Central nervous system-native myeloid cells (CNS-myeloids) and bone-marrow-derived myeloid cells (BMDMs) cooperatively regulate brain immunity. The phenotypic heterogeneity and specific roles of these myeloid subsets in shaping the br-met niche to regulate br-met outgrowth have not been fully revealed. Applying multimodal single-cell analyses, we elucidated a heterogeneous but spatially defined CNS-myeloid response during br-met outgrowth. We found Ccr2+ BMDMs minimally influenced br-met while CNS-myeloid promoted br-met outgrowth. Additionally, br-met-associated CNS-myeloid exhibited downregulation of Cx3cr1. Cx3cr1 knockout in CNS-myeloid increased br-met incidence, leading to an enriched interferon response signature and Cxcl10 upregulation. Significantly, neutralization of Cxcl10 reduced br-met, while rCxcl10 increased br-met and recruited VISTAHi PD-L1+ CNS-myeloid to br-met lesions. Inhibiting VISTA- and PD-L1-signaling relieved immune suppression and reduced br-met burden. Our results demonstrate that loss of Cx3cr1 in CNS-myeloid triggers a Cxcl10-mediated vicious cycle, cultivating a br-met-promoting, immune-suppressive niche.

Genetic variants of phospholipase C-γ2 alter the phenotype and function of microglia and confer differential risk for Alzheimer's disease.

Genetic association studies have demonstrated the critical involvement of the microglial immune response in Alzheimer's disease (AD) pathogenesis. Phospholipase C-gamma-2 (PLCG2) is selectively expressed by microglia and functions in many immune receptor signaling pathways. In AD, PLCG2 is induced uniquely in plaque-associated microglia. A genetic variant of PLCG2, PLCG2P522R, is a mild hypermorph that attenuates AD risk. Here, we identified a loss-of-function PLCG2 variant, PLCG2M28L, that confers an increased AD risk. PLCG2P522R attenuated disease in an amyloidogenic murine AD model, whereas PLCG2M28L exacerbated the plaque burden associated with altered phagocytosis and Aß clearance. The variants bidirectionally modulated disease pathology by inducing distinct transcriptional programs that identified microglial subpopulations associated with protective or detrimental phenotypes. These findings identify PLCG2M28L as a potential AD risk variant and demonstrate that PLCG2 variants can differentially orchestrate microglial responses in AD pathogenesis that can be therapeutically targeted.

High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes.

Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.

Hair-bearing human skin generated entirely from pluripotent stem cells.

The skin is a multilayered organ, equipped with appendages (that is, follicles and glands), that is critical for regulating body temperature and the retention of bodily fluids, guarding against external stresses and mediating the sensation of touch and pain1,2. Reconstructing appendage-bearing skin in cultures and in bioengineered grafts is a biomedical challenge that has yet to be met3-9. Here we report an organoid culture system that generates complex skin from human pluripotent stem cells. We use stepwise modulation of the transforming growth factor ß (TGFß) and fibroblast growth factor (FGF) signalling pathways to co-induce cranial epithelial cells and neural crest cells within a spherical cell aggregate. During an incubation period of 4-5 months, we observe the emergence of a cyst-like skin organoid composed of stratified epidermis, fat-rich dermis and pigmented hair follicles that are equipped with sebaceous glands. A network of sensory neurons and Schwann cells form nerve-like bundles that target Merkel cells in organoid hair follicles, mimicking the neural circuitry associated with human touch. Single-cell RNA sequencing and direct comparison to fetal specimens suggest that the skin organoids are equivalent to the facial skin of human fetuses in the second trimester of development. Moreover, we show that skin organoids form planar hair-bearing skin when grafted onto nude mice. Together, our results demonstrate that nearly complete skin can self-assemble in vitro and be used to reconstitute skin in vivo. We anticipate that our skin organoids will provide a foundation for future studies of human skin development, disease modelling and reconstructive surgery.

Structures of human TR4LBD-JAZF1 and TR4DBD-DNA complexes reveal the molecular basis of transcriptional regulation.

Testicular nuclear receptor 4 (TR4) modulates the transcriptional activation of genes and plays important roles in many diseases. The regulation of TR4 on target genes involves direct interactions with DNA molecules via the DNA-binding domain (DBD) and recruitment of coregulators by the ligand-binding domain (LBD). However, their regulatory mechanisms are unclear. Here, we report high-resolution crystal structures of TR4DBD, TR4DBD-DNA complexes and the TR4LBD-JAZF1 complex. For DNA recognition, multiple factors come into play, and a specific mutual selectivity between TR4 and target genes is found. The coactivators SRC-1 and CREBBP can bind at the interface of TR4 originally occupied by the TR4 activation function region 2 (AF-2); however, JAZF1 suppresses the binding through a novel mechanism. JAZF1 binds to an unidentified surface of TR4 and stabilizes an α13 helix never reported in the nuclear receptor family. Moreover, the cancer-associated mutations affect the interactions and the transcriptional activation of TR4 in vitro and in vivo, respectively. Overall, our results highlight the crucial role of DNA recognition and a novel mechanism of how JAZF1 reinforces the autorepressed conformation and influences the transcriptional activation of TR4, laying out important structural bases for drug design for a variety of diseases, including diabetes and cancers.

The impact of SBF2 on taxane-induced peripheral neuropathy.

Taxane-induced peripheral neuropathy (TIPN) is a devastating survivorship issue for many cancer patients. In addition to its impact on quality of life, this toxicity may lead to dose reductions or treatment discontinuation, adversely impacting survival outcomes and leading to health disparities in African Americans (AA). Our lab has previously identified deleterious mutations in SET-Binding Factor 2 (SBF2) that significantly associated with severe TIPN in AA patients. Here, we demonstrate the impact of SBF2 on taxane-induced neuronal damage using an ex vivo model of SBF2 knockdown of induced pluripotent stem cell-derived sensory neurons. Knockdown of SBF2 exacerbated paclitaxel changes to cell viability and neurite outgrowth while attenuating paclitaxel-induced sodium current inhibition. Our studies identified paclitaxel-induced expression changes specific to mature sensory neurons and revealed candidate genes involved in the exacerbation of paclitaxel-induced phenotypes accompanying SBF2 knockdown. Overall, these findings provide ex vivo support for the impact of SBF2 on the development of TIPN and shed light on the potential pathways involved.

Human neutrophil peptides 1-3 protect the murine urinary tract from uropathogenic Escherichia coli challenge.

Antimicrobial peptides (AMPs) are critical to the protection of the urinary tract of humans and other animals from pathogenic microbial invasion. AMPs rapidly destroy pathogens by disrupting microbial membranes and/or augmenting or inhibiting the host immune system through a variety of signaling pathways. We have previously demonstrated that alpha-defensins 1-3 (DEFA1A3) are AMPs expressed in the epithelial cells of the human kidney collecting duct in response to uropathogens. We also demonstrated that DNA copy number variations in the DEFA1A3 locus are associated with UTI and pyelonephritis risk. Because DEFA1A3 is not expressed in mice, we utilized human DEFA1A3 gene transgenic mice (DEFA4/4) to further elucidate the biological relevance of this locus in the murine urinary tract. We demonstrate that the kidney transcriptional and translational expression pattern is similar in humans and the human gene transgenic mouse upon uropathogenic Escherichia coli (UPEC) stimulus in vitro and in vivo. We also demonstrate transgenic human DEFA4/4 gene mice are protected from UTI and pyelonephritis under various UPEC challenges. This study serves as the foundation to start the exploration of manipulating the DEFA1A3 locus and alpha-defensins 1-3 expression as a potential therapeutic target for UTIs and other infectious diseases.

Enhanced performance of thermally activated delayed fluorescent light emitting diodes by optimized host polarity.

The interaction between the intrinsic polarity of the host material and the TADF guest material affects charge injection and transport, exciton formation, charge recombination, and emission mechanisms. Therefore, understanding and controlling the interaction between the intrinsic polarity of the host material and the TADF guest material is very important to realize efficient TADF-OLED devices. This study investigated the molecular interaction between different polar host materials and a thermally activated delayed fluorescence material (DMAc-PPM). It has been found that interaction between the host and guest (π-π stacking interaction, multiple CH/π contacts) greatly influence the molecular transition dipole moment orientation of the guest. And the OLED devices based on the strong polar host (DPEPO) exhibited the highest EQEmax and lowest luminescence intensity, while devices using the weaker polar hosts mCP and CBP achieved higher luminance and lower EQEmax. Then, the strong polar host DPEPO was mixed with the weaker polar hosts CBP and mCP, respectively. The devices prepared based on the mixed-host DPEPO: mCP showed a 2.2 times improvement in EQEmax from 6.3% to 20.1% compared to the single-host mCP. The devices prepared based on the mixed-host DPEPO: CBP showed a 3.1 times improvement in luminance intensity from 1023 cd/m2 to 4236 cd/m2 compared to the single host of DPEPO. This suggests that optimizing the polarity of host materials has the potential to enhance the performance of solution prepared OLED devices.

The Pharus latifolius genome bridges the gap of early grass evolution.

The grass family (Poaceae) includes all commercial cereal crops and is a major contributor to biomass in various terrestrial ecosystems. The ancestry of all grass genomes includes a shared whole-genome duplication (WGD), named rho (ρ) WGD, but the evolutionary significance of ρ-WGD remains elusive. We sequenced the genome of Pharus latifolius, a grass species (producing a true spikelet) in the subfamily Pharoideae, a sister lineage to the core Poaceae including the (Panicoideae, Arundinoideae, Chloridoideae, Micrairoideae, Aristidoideae, and Danthonioideae (PACMAD) and Bambusoideae, Oryzoideae, and Pooideae (BOP) clades. Our results indicate that the P. latifolius genome has evolved slowly relative to cereal grass genomes, as reflected by moderate rates of molecular evolution, limited chromosome rearrangements and a low rate of gene loss for duplicated genes. We show that the ρ-WGD event occurred approximately 98.2 million years ago (Ma) in a common ancestor of the Pharoideae and the PACMAD and BOP grasses. This was followed by contrasting patterns of diploidization in the Pharus and core Poaceae lineages. The presence of two FRIZZY PANICLE-like genes in P. latifolius, and duplicated MADS-box genes, support the hypothesis that the ρ-WGD may have played a role in the origin and functional diversification of the spikelet, an adaptation in grasses related directly to cereal yields. The P. latifolius genome sheds light on the origin and early evolution of grasses underpinning the biology and breeding of cereals.

RNA alternative splicing impacts the risk for alcohol use disorder.

Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.

In-Silico and in vitro Studies Revealed that Rosmarinic Acid Inhibited Methanogenesis via Regulating Composition and Function of Rumen Microbiota.

Inhibition of methyl-coenzyme M reductase can suppress the activity of ruminal methanogens, thereby reducing enteric methane emissions of ruminants. However, developing specific and environmentally friendly inhibitors is a challenging endeavor. To identify a natural and effective methane inhibitor that specifically targets methyl-coenzyme M reductase, molecular docking technology was employed to screen a library of phytogenic compounds. A total of 52 candidate compounds were obtained through molecular docking technique. Rosmarinic acid (RA) was one of the compounds that could traverse a narrow channel and bind to the active sites of methyl-coenzyme M reductase, with a calculated binding free energy of -9.355 kcal/mol. Furthermore, the effects of rosmarinic acid supplementation on methane production, rumen fermentation, and the microorganism's community in dairy cows were investigated through in vitro rumen fermentation simulations according to a random design. Supplementation of RA resulted in a 15% decrease in methane production compared with the control. In addition, RA increased the molar proportion of acetate and propionate, whereas the sum of acetate and butyrate divided by propionate was decreased. At the bacterial level, the relative abundance of Rikenellaceae RC9 gut group, Christensenellaceae R7 group, Candidatus Saccharimonas, Desulfovibrio, and Lachnospiraceae FE2018 group decreased with RA supplementation. Conversely, the addition of RA significantly increased the relative abundance of DNF00809 (a genus from Eggerthellaceae), Denitrobacterium, an unclassified genus from Eggerthellaceae, an unclassified genus from Bacteroidales, and an unclassified genus from Atopobiaceae. At the archaeal level, the relative abundance of Methanobrevibacter decreased, while that of Methanosphaera increased with the RA supplementation. These findings suggested that RA has the potential to be used as a novel natural additive for inhibiting ruminal methane production.

Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network.

We aimed to improve the detection accuracy of laser methane sensors in expansive temperature application environments. In this paper, a large-scale dataset of the measured concentration of the sensor at different temperatures is established, and a temperature compensation model based on the ISSA-BP neural network is proposed. On the data side, a large-scale dataset of 15,810 sets of laser methane sensors with different temperatures and concentrations was established, and an Improved Isolation Forest algorithm was used to clean the large-scale data and remove the outliers in the dataset. On the modeling framework, a temperature compensation model based on the ISSA-BP neural network is proposed. The quasi-reflective learning, chameleon swarm algorithm, Lévy flight, and artificial rabbits optimization are utilized to improve the initialization of the sparrow population, explorer position, anti-predator position, and position of individual sparrows in each generation, respectively, to improve the global optimization seeking ability of the standard sparrow search algorithm. The ISSA-BP temperature compensation model far outperforms the four models, SVM, RF, BP, and PSO-BP, in model evaluation metrics such as MAE, MAPE, RMSE, and R-square for both the training and test sets. The results show that the algorithm in this paper can significantly improve the detection accuracy of the laser methane sensor under the wide temperature application environment.

Structural Basis of Nucleic Acid Recognition and 6mA Demethylation by Caenorhabditis elegans NMAD-1A.

N6-methyladenine (6mA) of DNA is an emerging epigenetic mark in the genomes of Chlamydomonas, Caenorhabditis elegans, and mammals recently. Levels of 6mA undergo drastic fluctuation and thus affect fertility during meiosis and early embryogenesis. Here, we showed three complex structures of 6mA demethylase C. elegans NMAD-1A, a canonical isoform of NMAD-1 (F09F7.7). Biochemical results revealed that NMAD-1A prefers 6mA Bubble or Bulge DNAs. Structural studies of NMAD-1A revealed an unexpected "stretch-out" conformation of its Flip2 region, a conserved element that is usually bent over the catalytic center to facilitate substrate base flipping in other DNA demethylases. Moreover, the wide channel between the Flip1 and Flip2 of the NMAD-1A explained the observed preference of NMAD-1A for unpairing substrates, of which the flipped 6mA was primed for catalysis. Structural analysis and mutagenesis studies confirmed that key elements such as carboxy-terminal domain (CTD) and hypothetical zinc finger domain (ZFD) critically contributed to structural integrity, catalytic activity, and nucleosome binding. Collectively, our biochemical and structural studies suggest that NMAD-1A prefers to regulate 6mA in the unpairing regions and is thus possibly associated with dynamic chromosome regulation and meiosis regulation.

Structural insights into the interactions and epigenetic functions of human nucleic acid repair protein ALKBH6.

Human AlkB homolog 6, ALKBH6, plays key roles in nucleic acid damage repair and tumor therapy. However, no precise structural and functional information are available for this protein. In this study, we determined atomic resolution crystal structures of human holo-ALKBH6 and its complex with ligands. AlkB members bind nucleic acids by NRLs (nucleotide recognition lids, also called Flips), which can recognize DNA/RNA and flip methylated lesions. We found that ALKBH6 has unusual Flip1 and Flip2 domains, distinct from other AlkB family members both in sequence and conformation. Moreover, we show that its unique Flip3 domain has multiple unreported functions, such as discriminating against double-stranded nucleic acids, blocking the active center, binding other proteins, and in suppressing tumor growth. Structural analyses and substrate screening reveal how ALKBH6 discriminates between different types of nucleic acids and may also function as a nucleic acid demethylase. Structure-based interacting partner screening not only uncovered an unidentified interaction of transcription repressor ZMYND11 and ALKBH6 in tumor suppression but also revealed cross talk between histone modification and nucleic acid modification in epigenetic regulation. Taken together, these results shed light on the molecular mechanism underlying ALKBH6-associated nucleic acid damage repair and tumor therapy.

Structural and genome-wide analyses suggest that transposon-derived protein SETMAR alters transcription and splicing.

Extensive portions of the human genome have unknown function, including those derived from transposable elements. One such element, the DNA transposon Hsmar1, entered the primate lineage approximately 50 million years ago leaving behind terminal inverted repeat (TIR) sequences and a single intact copy of the Hsmar1 transposase, which retains its ancestral TIR-DNA-binding activity, and is fused with a lysine methyltransferase SET domain to constitute the chimeric SETMAR gene. Here, we provide a structural basis for recognition of TIRs by SETMAR and investigate the function of SETMAR through genome-wide approaches. As elucidated in our 2.37 Å crystal structure, SETMAR forms a dimeric complex with each DNA-binding domain bound specifically to TIR-DNA through the formation of 32 hydrogen bonds. We found that SETMAR recognizes primarily TIR sequences (∼5000 sites) within the human genome as assessed by chromatin immunoprecipitation sequencing analysis. In two SETMAR KO cell lines, we identified 163 shared differentially expressed genes and 233 shared alternative splicing events. Among these genes are several pre-mRNA-splicing factors, transcription factors, and genes associated with neuronal function, and one alternatively spliced primate-specific gene, TMEM14B, which has been identified as a marker for neocortex expansion associated with brain evolution. Taken together, our results suggest a model in which SETMAR impacts differential expression and alternative splicing of genes associated with transcription and neuronal function, potentially through both its TIR-specific DNA-binding and lysine methyltransferase activities, consistent with a role for SETMAR in simian primate development.

A novel deep learning method for predictive modeling of microbiome data.

With the development and decreasing cost of next-generation sequencing technologies, the study of the human microbiome has become a rapid expanding research field, which provides an unprecedented opportunity in various clinical applications such as drug response predictions and disease diagnosis. It is thus essential and desirable to build a prediction model for clinical outcomes based on microbiome data that usually consist of taxon abundance and a phylogenetic tree. Importantly, all microbial species are not uniformly distributed in the phylogenetic tree but tend to be clustered at different phylogenetic depths. Therefore, the phylogenetic tree represents a unique correlation structure of microbiome, which can be an important prior to improve the prediction performance. However, prediction methods that consider the phylogenetic tree in an efficient and rigorous way are under-developed. Here, we develop a novel deep learning prediction method MDeep (microbiome-based deep learning method) to predict both continuous and binary outcomes. Conceptually, MDeep designs convolutional layers to mimic taxonomic ranks with multiple convolutional filters on each convolutional layer to capture the phylogenetic correlation among microbial species in a local receptive field and maintain the correlation structure across different convolutional layers via feature mapping. Taken together, the convolutional layers with its built-in convolutional filters capture microbial signals at different taxonomic levels while encouraging local smoothing and preserving local connectivity induced by the phylogenetic tree. We use both simulation studies and real data applications to demonstrate that MDeep outperforms competing methods in both regression and binary classifications. Availability and Implementation: MDeep software is available at https://github.com/lichen-lab/MDeep Contact:chen61@iu.edu.

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants.

Understanding the functional consequence of noncoding variants is of great interest. Though genome-wide association studies or quantitative trait locus analyses have identified variants associated with traits or molecular phenotypes, most of them are located in the noncoding regions, making the identification of causal variants a particular challenge. Existing computational approaches developed for prioritizing noncoding variants produce inconsistent and even conflicting results. To address these challenges, we propose a novel statistical learning framework, which directly integrates the precomputed functional scores from representative scoring methods. It will maximize the usage of integrated methods by automatically learning the relative contribution of each method and produce an ensemble score as the final prediction. The framework consists of two modes. The first 'context-free' mode is trained using curated causal regulatory variants from a wide range of context and is applicable to predict regulatory variants of unknown and diverse context. The second 'context-dependent' mode further improves the prediction when the training and testing variants are from the same context. By evaluating the framework via both simulation and empirical studies, we demonstrate that it outperforms integrated scoring methods and the ensemble score successfully prioritizes experimentally validated regulatory variants in multiple risk loci.

AIscEA: unsupervised integration of single-cell gene expression and chromatin accessibility via their biological consistency.

MOTIVATION: The integrative analysis of single-cell gene expression and chromatin accessibility measurements is essential for revealing gene regulation, but it is one of the key challenges in computational biology. Gene expression and chromatin accessibility are measurements from different modalities, and no common features can be directly used to guide integration. Current state-of-the-art methods lack practical solutions for finding heterogeneous clusters. However, previous methods might not generate reliable results when cluster heterogeneity exists. More importantly, current methods lack an effective way to select hyper-parameters under an unsupervised setting. Therefore, applying computational methods to integrate single-cell gene expression and chromatin accessibility measurements remains difficult. RESULTS: We introduce AIscEA-Alignment-based Integration of single-cell gene Expression and chromatin Accessibility-a computational method that integrates single-cell gene expression and chromatin accessibility measurements using their biological consistency. AIscEA first defines a ranked similarity score to quantify the biological consistency between cell clusters across measurements. AIscEA then uses the ranked similarity score and a novel permutation test to identify cluster alignment across measurements. AIscEA further utilizes graph alignment for the aligned cell clusters to align the cells across measurements. We compared AIscEA with the competing methods on several benchmark datasets and demonstrated that AIscEA is highly robust to the choice of hyper-parameters and can better handle the cluster heterogeneity problem. Furthermore, AIscEA significantly outperforms the state-of-the-art methods when integrating real-world SNARE-seq and scMultiome-seq datasets in terms of integration accuracy. AVAILABILITY AND IMPLEMENTATION: AIscEA is available at https://figshare.com/articles/software/AIscEA_zip/21291135 on FigShare as well as {https://github.com/elhaam/AIscEA} onGitHub. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Alteration of N6-methyladenosine epitranscriptome profiles in bilateral ureteral obstruction-induced obstructive nephropathy in juvenile rats.

BACKGROUND: Urinary tract obstruction is a common cause of renal failure in children and infants, and the pathophysiological mechanisms of obstructive nephropathy are largely unclear. It has been reported that m6A modulation is involved in renal injury. However, whether m6A RNA modulation is associated with obstructive nephropathy has not yet been reported. The aim of this study was to investigate the m6A epitranscriptome profiles in the kidneys of bilateral ureteral obstruction (BUO) in young rats. METHODS: The total level of m6A in the kidneys was measured by liquid chromatography-tandem mass spectrometry. The mRNAs of related genes were detected by real-time PCR. Methylated RNA immunoprecipitation sequencing was performed to map the epitranscriptome-wide m6A profile. RESULTS: Global m6A levels were increased after BUO, and the mRNA expression levels of m6A methyltransferases and demethylases were significantly decreased in BUO group rat kidneys; the expression levels of EGFR and Brcal were significantly upregulated, while the mRNA expression levels of Notch1 were downregulated (P < 0.05). A total of 154 genes associated with 163 m6A peaks were identified. CONCLUSION: The m6A epitranscriptome was significantly altered in BUO rat kidneys, which is potentially implicated in the pathophysiological processes of obstructive nephropathy. IMPACT: The m6A RNA modification was associated with the process of renal injury in ureteral obstructive nephropathy by participating in multiple dimensions. The dysregulation of m6A methyltransferases and demethylases may be related to the pathophysiological changes of BUO-induced obstructive nephropathy. The m6A RNA modulation of the genes EGFR, Brca1, and Notch1 that were related to the regulation of aquaporin2 might be the potential mechanism for the polyuresis after ureteral obstruction.

B3galt5 deficiency attenuates hepatocellular carcinoma by suppressing mTOR/p70s6k-mediated glycolysis.

Hepatocellular carcinoma (HCC) is one of the most common malignancies with high morbidity and mortality. Beta-1,3-galactosyltransferase 5 (b3galt5) plays crucial roles in protein glycosylation, but its function in HCC remains unclear. Here, we investigated the role and underlying mechanism of b3galt5 in HCC. We found that b3galt5 is highly expressed and associated with a poor prognosis in HCC patients. In vitro studies showed that b3galt5 promoted the proliferation and survival of HCC cells. We also demonstrated that b3galt5 deficiency suppressed hepatocarcinogenesis in DEN/TCPOBOP-induced HCC. Further investigation confirmed that b3galt5 promoted aerobic glycolysis in HCC. Mechanistically, b3galt5 promoted glycolysis by activating the mTOR/p70s6k pathway through O-linked glycosylation modification on mTOR. Moreover, p70s6k inhibition reduced the expression of key glycolytic enzymes and the glycolysis rate in b3galt5-overexpressing cells. Our study uncovers a novel mechanism by which b3galt5 mediates glycolysis in HCC and highlights the b3galt5-mTOR/p70s6k axis as a potential target for HCC therapy.