Identification of a copper-responsive small molecule inhibitor of uropathogenic Escherichia coli.

Urinary tract infections (UTIs) are a major global health problem and are caused predominantly by uropathogenic Escherichia coli (UPEC). UTIs are a leading cause of prescription antimicrobial use. Incessant increase in antimicrobial resistance in UPEC and other uropathogens poses a serious threat to the current treatment practices. Copper is an effector of nutritional immunity that impedes the growth of pathogens during infection. We hypothesized that copper would augment the toxicity of select small molecules against bacterial pathogens. We conducted a small molecule screening campaign with a library of 51,098 molecules to detect hits that inhibit a UPEC ΔtolC mutant in a copper-dependent manner. A molecule, denoted as E. coli inhibitor or ECIN, was identified as a copper-responsive inhibitor of wild-type UPEC strains. Our gene expression and metal content analysis results demonstrate that ECIN works in concert with copper to exacerbate Cu toxicity in UPEC. ECIN has a broad spectrum of activity against pathogens of medical and veterinary significance including Acinetobacter baumannii, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus. Subinhibitory levels of ECIN eliminate UPEC biofilm formation. Transcriptome analysis of UPEC treated with ECIN reveals induction of multiple stress response systems. Furthermore, we demonstrate that L-cysteine rescues the growth of UPEC exposed to ECIN. In summary, we report the identification and characterization of a novel copper-responsive small molecule inhibitor of UPEC.IMPORTANCEUrinary tract infection (UTI) is a ubiquitous infectious condition affecting millions of people annually. Uropathogenic Escherichia coli (UPEC) is the predominant etiological agent of UTI. However, UTIs are becoming increasingly difficult to resolve with antimicrobials due to increased antimicrobial resistance in UPEC and other uropathogens. Here, we report the identification and characterization of a novel copper-responsive small molecule inhibitor of UPEC. In addition to E. coli, this small molecule also inhibits pathogens of medical and veterinary significance including Acinetobacter baumannii, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus.

Parallel degradome-seq and DMS-MaPseq substantially revise the miRNA biogenesis atlas in Arabidopsis.

MicroRNAs (miRNAs) are produced from highly structured primary transcripts (pri-miRNAs) and regulate numerous biological processes in eukaryotes. Due to the extreme heterogeneity of these structures, the initial processing sites of plant pri-miRNAs and the structural rules that determine their processing have been predicted for many miRNAs but remain elusive for others. Here we used semi-active DCL1 mutants and advanced degradome-sequencing strategies to accurately identify the initial processing sites for 147 of 326 previously annotated Arabidopsis miRNAs and to illustrate their associated pri-miRNA cleavage patterns. Elucidating the in vivo RNA secondary structures of 73 pri-miRNAs revealed that about 95% of them differ from in silico predictions, and that the revised structures offer clearer interpretation of the processing sites and patterns. Finally, DCL1 partners Serrate and HYL1 could synergistically and independently impact processing patterns and in vivo RNA secondary structures of pri-miRNAs. Together, our work sheds light on the precise processing mechanisms of plant pri-miRNAs.

Transcriptomic signature, bioactivity and safety of a non-hepatotoxic analgesic generating AM404 in the midbrain PAG region.

Safe and effective pain management is a critical healthcare and societal need. The potential for acute liver injury from paracetamol (ApAP) overdose; nephrotoxicity and gastrointestinal damage from chronic non-steroidal anti-inflammatory drug (NSAID) use; and opioids' addiction are unresolved challenges. We developed SRP-001, a non-opioid and non-hepatotoxic small molecule that, unlike ApAP, does not produce the hepatotoxic metabolite N-acetyl-p-benzoquinone-imine (NAPQI) and preserves hepatic tight junction integrity at high doses. CD-1 mice exposed to SRP-001 showed no mortality, unlike a 70% mortality observed with increasing equimolar doses of ApAP within 72 h. SRP-001 and ApAP have comparable antinociceptive effects, including the complete Freund's adjuvant-induced inflammatory von Frey model. Both induce analgesia via N-arachidonoylphenolamine (AM404) formation in the midbrain periaqueductal grey (PAG) nociception region, with SRP-001 generating higher amounts of AM404 than ApAP. Single-cell transcriptomics of PAG uncovered that SRP-001 and ApAP also share modulation of pain-related gene expression and cell signaling pathways/networks, including endocannabinoid signaling, genes pertaining to mechanical nociception, and fatty acid amide hydrolase (FAAH). Both regulate the expression of key genes encoding FAAH, 2-arachidonoylglycerol (2-AG), cannabinoid receptor 1 (CNR1), CNR2, transient receptor potential vanilloid type 4 (TRPV4), and voltage-gated Ca2+ channel. Phase 1 trial (NCT05484414) (02/08/2022) demonstrates SRP-001's safety, tolerability, and favorable pharmacokinetics, including a half-life from 4.9 to 9.8 h. Given its non-hepatotoxicity and clinically validated analgesic mechanisms, SRP-001 offers a promising alternative to ApAP, NSAIDs, and opioids for safer pain treatment.

Single-nucleus transcriptomics of epicardial adipose tissue from female pigs reveals effects of exercise training on resident innate and adaptive immune cells.

BACKGROUND: Coronary artery disease (CAD) is a leading cause of death in women. Epicardial adipose tissue (EAT) secretes cytokines to modulate coronary artery function, and the release of fatty acids from EAT serves as a readily available energy source for cardiomyocytes. However, despite having beneficial functions, excessive amounts of EAT can cause the secretion of proinflammatory molecules that increase the instability of atherosclerotic plaques and contribute to CAD progression. Although exercise mitigates CAD, the mechanisms by which exercise impacts EAT are unknown. The Yucatan pig is an excellent translational model for the effects of exercise on cardiac function. Therefore, we sought to determine if chronic aerobic exercise promotes an anti-inflammatory microenvironment in EAT from female Yucatan pigs. METHODS: Sexually mature, female Yucatan pigs (n = 7 total) were assigned to sedentary (Sed, n = 3) or exercise (Ex, n = 4) treatments, and coronary arteries were occluded (O) with an ameroid to mimic CAD or remained non-occluded (N). EAT was collected for bulk (n = 7 total) and single nucleus transcriptomic sequencing (n = 2 total, 1 per exercise treatment). RESULTS: Based on the bulk transcriptomic analysis, exercise upregulated S100 family, G-protein coupled receptor, and CREB signaling in neurons canonical pathways in EAT. The top networks in EAT affected by exercise as measured by bulk RNA sequencing were SRC kinase family, fibroblast growth factor receptor, Jak-Stat, and vascular endothelial growth factor. Single nucleus transcriptomic analysis revealed that exercise increased the interaction between immune, endothelial, and mesenchymal cells in the insulin-like growth factor pathway and between endothelial and other cell types in the platelet endothelial cell adhesion molecule 1 pathway. Sub-clustering revealed nine cell types in EAT, with fibroblast and macrophage populations predominant in O-Ex EAT and T cell populations predominant in N-Ex EAT. Unlike the findings for exercise alone as a treatment, there were not increased interactions between endothelial and mesenchymal cells in O-Ex EAT. Coronary artery occlusion impacted the most genes in T cells and endothelial cells. Genes related to fatty acid metabolism were the most highly upregulated in non-immune cells from O-Ex EAT. Sub-clustering of endothelial cells revealed that N-Ex EAT separated from other treatments. CONCLUSIONS: According to bulk transcriptomics, exercise upregulated pathways and networks related to growth factors and immune cell communication. Based on single nucleus transcriptomics, aerobic exercise increased cell-to-cell interaction amongst immune, mesenchymal, and endothelial cells in female EAT. Yet, exercise was minimally effective at reversing alterations in gene expression in endothelial and mesenchymal cells in EAT surrounding occluded arteries. These findings lay the foundation for future work focused on the impact of exercise on cell types in EAT.

Novel Nuclear Roles for Testis-Specific ACTL7A and ACTL7B Supported by In Vivo Characterizations and AI Facilitated In Silico Mechanistic Modeling with Implications for Epigenetic Regulation in Spermiogenesis.

A mechanistic role for nuclear function of testis-specific actin related proteins (ARPs) is proposed here through contributions of ARP subunit swapping in canonical chromatin regulatory complexes. This is significant to our understanding of both mechanisms controlling regulation of spermiogenesis, and the expanding functional roles of the ARPs in cell biology. Among these roles, actins and ARPs are pivotal not only in cytoskeletal regulation, but also in intranuclear chromatin organization, influencing gene regulation and nucleosome remodeling. This study focuses on two testis-specific ARPs, ACTL7A and ACTL7B, exploring their intranuclear activities and broader implications utilizing combined in vivo, in vitro, and in silico approaches. ACTL7A and ACTL7B, previously associated with structural roles, are hypothesized here to serve in chromatin regulation during germline development. This study confirms the intranuclear presence of ACTL7B in spermatocytes and round spermatids, revealing a potential role in intranuclear processes, and identifies a putative nuclear localization sequence conserved across mammalian ACTL7B, indicating a potentially unique mode of nuclear transport which differs from conventional actin. Ablation of ACTL7B leads to varied transcriptional changes reported here. Additionally, in the absence of ACTL7A or ACTL7B there is a loss of intranuclear localization of HDAC1 and HDAC3, which are known regulators of epigenetic associated acetylation changes that in turn regulate gene expression. Thus, these HDACs are implicated as contributors to the aberrant gene expression observed in the KO mouse testis transcriptomic analysis. Furthermore, this study employed and confirmed the accuracy of in silico models to predict ARP interactions with Helicase-SANT-associated (HSA) domains, uncovering putative roles for testis-specific ARPs in nucleosome remodeling complexes. In these models, ACTL7A and ACTL7B were found capable of binding to INO80 and SWI/SNF nucleosome remodeler family members in a manner akin to nuclear actin and ACTL6A. These models thus implicate germline-specific ARP subunit swapping within chromatin regulatory complexes as a potential regulatory mechanism for chromatin and associated molecular machinery adaptations in nuclear reorganizations required during spermiogenesis. These results hold implications for male fertility and epigenetic programing in the male-germline that warrant significant future investigation. In summary, this study reveals that ACTL7A and ACTL7B play intranuclear gene regulation roles in male gametogenesis, adding to the multifaceted roles identified also spanning structural, acrosomal, and flagellar stability. ACTL7A and ACTL7B unique nuclear transport, impact on HDAC nuclear associations, impact on transcriptional processes, and proposed mechanism for involvement in nucleosome remodeling complexes supported by AI facilitated in silico modeling contribute to a more comprehensive understanding of the indispensable functions of ARPs broadly in cell biology, and specifically in male fertility.

Experimental and analytical pipeline for sub-genomic RNA landscape of coronavirus by Nanopore sequencer.

Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2, can infect a variety of mammalian and avian hosts with significant medical and economic consequences. During the life cycle of CoV, a coordinated series of subgenomic RNAs, including canonical subgenomic messenger RNA and non-canonical defective viral genomes (DVGs), are generated with different biological implications. Studies that adopted the Nanopore sequencer (ONT) to investigate the landscape and dynamics of viral RNA subgenomic transcriptomes applied arbitrary bioinformatics parameters without justification or experimental validation. The current study used bovine coronavirus (BCoV), which can be performed under biosafety level 2 for library construction and experimental validation using traditional colony polymerase chain reaction and Sanger sequencing. Four different ONT protocols, including RNA direct and cDNA direct sequencing with or without exonuclease treatment, were used to generate RNA transcriptomic libraries from BCoV-infected cell lysates. Through rigorously examining the k-mer, gap size, segment size, and bin size, the optimal cutoffs for the bioinformatic pipeline were determined to remove the sequence noise while keeping the informative DVG reads. The sensitivity and specificity of identifying DVG reads using the proposed pipeline can reach 82.6% and 99.6% under the k-mer size cutoff of 15. Exonuclease treatment reduced the abundance of RNA transcripts; however, it was not necessary for future library preparation. Additional recovery of clipped BCoV nucleotide sequences with experimental validation expands the landscape of the CoV discontinuous RNA transcriptome, whose biological function requires future investigation. The results of this study provide the benchmarks for library construction and bioinformatic parameters for studying the discontinuous CoV RNA transcriptome.IMPORTANCEFunctional defective viral genomic RNA, containing all the cis-acting elements required for translation or replication, may play different roles in triggering cell innate immune signaling, interfering with the canonical subgenomic messenger RNA transcription/translation or assisting in establishing persistence infection. This study does not only provide benchmarks for library construction and bioinformatic parameters for studying the discontinuous coronavirus RNA transcriptome but also reveals the complexity of the bovine coronavirus transcriptome, whose functional assays will be critical in future studies.

Single-nucleus transcriptomics of epicardial adipose tissue from females reveals exercise control of innate and adaptive immune cells.

Coronary artery disease (CAD) is a leading cause of death in women. Although exercise mitigates CAD, the mechanisms by which exercise impacts epicardial adipose tissue (EAT) are unknown. We hypothesized that exercise promotes an anti-inflammatory microenvironment in EAT from female pigs. Yucatan pigs (n=7) were assigned to sedentary (Sed) or exercise (Ex) treatments and coronary arteries were occluded (O) with an ameroid to mimic CAD or remained non-occluded (N). EAT was collected for bulk and single nucleus transcriptomic sequencing (snRNA-seq). Exercise upregulated G-protein coupled receptor, S100 family, and FAK pathways and downregulated the coagulation pathway. Exercise increased the interaction between immune, endothelial, and mesenchymal cells in the insulin-like growth factor pathway and between endothelial and other cell types in the platelet endothelial cell adhesion molecule 1 pathway. Sub-clustering revealed nine cell types in EAT with fibroblast and macrophage populations predominant in O-Ex EAT and T cell population predominant in N-Ex EAT. Coronary occlusion impacted the largest number of genes in T and endothelial cells. Genes related to fatty acid metabolism were the most highly upregulated in non-immune cells from O-Ex EAT. Sub-clustering of endothelial cells revealed that N-Ex EAT separated from other treatments. In conclusion, aerobic exercise increased interaction amongst immune and mesenchymal and endothelial cells in female EAT. Exercise was minimally effective at reversing alterations in gene expression in endothelial and mesenchymal cells in EAT surrounding occluded arteries. These findings lay the foundation for future work focused on the impact of exercise on cell types in EAT.

Interpretable modeling of time-resolved single-cell gene-protein expression with CrossmodalNet.

Cell-surface proteins play a critical role in cell function and are primary targets for therapeutics. CITE-seq is a single-cell technique that enables simultaneous measurement of gene and surface protein expression. It is powerful but costly and technically challenging. Computational methods have been developed to predict surface protein expression using gene expression information such as from single-cell RNA sequencing (scRNA-seq) data. Existing methods however are computationally demanding and lack the interpretability to reveal underlying biological processes. We propose CrossmodalNet, an interpretable machine learning model, to predict surface protein expression from scRNA-seq data. Our model with a customized adaptive loss accurately predicts surface protein abundances. When samples from multiple time points are given, our model encodes temporal information into an easy-to-interpret time embedding to make prediction in a time-point-specific manner, and is able to uncover noise-free causal gene-protein relationships. Using three publicly available time-resolved CITE-seq data sets, we validate the performance of our model by comparing it with benchmarking methods and evaluate its interpretability. Together, we show that our method accurately and interpretably profiles surface protein expression using scRNA-seq data, thereby expanding the capacity of CITE-seq experiments for investigating molecular mechanisms involving surface proteins.

Suppression of FOXO1 attenuates inflamm-aging and improves liver function during aging.

The liver is a key metabolic organ that maintains whole-body nutrient homeostasis. Aging-induced liver function alterations contribute to systemic susceptibility to aging-related diseases. However, the molecular mechanisms of liver aging remain insufficiently understood. In this study, we performed bulk RNA-Seq and single-cell RNA-Seq analyses to investigate the underlying mechanisms of the aging-induced liver function changes. We found that liver inflammation, glucose intolerance, and liver fat deposition were aggravated in old mice. Aging significantly increased pro-inflammation in hepatic macrophages. Furthermore, we found that Kupffer cells (KCs) were the major driver to induce pro-inflammation in hepatic macrophages during aging. In KCs, aging significantly increased pro-inflammatory levels; in monocyte-derived macrophages (MDMs), aging had a limited effect on pro-inflammation but led to a functional quiescence in antigen presentation and phagosome process. In addition, we identified an aging-responsive KC-specific (ARKC) gene set that potentially mediates aging-induced pro-inflammation in KCs. Interestingly, FOXO1 activity was significantly increased in the liver of old mice. FOXO1 inhibition by AS1842856 significantly alleviated glucose intolerance, hepatic steatosis, and systemic inflammation in old mice. FOXO1 inhibition significantly attenuated aging-induced pro-inflammation in KCs partially through downregulation of ARKC genes. However, FOXO1 inhibition had a limited effect on aging-induced functional quiescence in MDMs. These results indicate that aging induces pro-inflammation in liver mainly through targeting KCs and FOXO1 is a key player in aging-induced pro-inflammation in KCs. Thus, FOXO1 could be a potential therapeutic target for the treatment of age-associated chronic diseases.

Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs.

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

Hepatocyte Adenosine Kinase Promotes Excessive Fat Deposition and Liver Inflammation.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease is highly associated with obesity and progresses to nonalcoholic steatohepatitis when the liver develops overt inflammatory damage. While removing adenosine in the purine salvage pathway, adenosine kinase (ADK) regulates methylation reactions. We aimed to study whether hepatocyte ADK functions as an obesogenic gene/enzyme to promote excessive fat deposition and liver inflammation. METHODS: Liver sections of human subjects were examined for ADK expression using immunohistochemistry. Mice with hepatocyte-specific ADK disruption or overexpression were examined for hepatic fat deposition and inflammation. Liver lipidomics, hepatocyte RNA sequencing (RNA-seq), and single-cell RNA-seq for liver nonparenchymal cells were performed to analyze ADK regulation of hepatocyte metabolic responses and hepatocyte-nonparenchymal cells crosstalk. RESULTS: Whereas patients with nonalcoholic fatty liver disease had increased hepatic ADK levels, mice with hepatocyte-specific ADK disruption displayed decreased hepatic fat deposition on a chow diet and were protected from diet-induced excessive hepatic fat deposition and inflammation. In contrast, mice with hepatocyte-specific ADK overexpression displayed increased body weight and adiposity and elevated degrees of hepatic steatosis and inflammation compared with control mice. RNA-seq and epigenetic analyses indicated that ADK increased hepatic DNA methylation and decreased hepatic Ppara expression and fatty acid oxidation. Lipidomic and single-cell RNA-seq analyses indicated that ADK-driven hepatocyte factors, due to mitochondrial dysfunction, enhanced macrophage proinflammatory activation in manners involving increased expression of stimulator of interferon genes. CONCLUSIONS: Hepatocyte ADK functions to promote excessive fat deposition and liver inflammation through suppressing hepatocyte fatty acid oxidation and producing hepatocyte-derived proinflammatory mediators. Therefore, hepatocyte ADK is a therapeutic target for managing obesity and nonalcoholic fatty liver disease.

A Unified Bayesian Framework for Bi-overlapping-Clustering Multi-omics Data via Sparse Matrix Factorization.

The advances of modern sequencing techniques have generated an unprecedented amount of multi-omics data which provide great opportunities to quantitatively explore functional genomes from different but complementary perspectives. However, distinct modalities/sequencing technologies generate diverse types of data which greatly complicate statistical modeling because uniquely optimized methods are required for handling each type of data. In this paper, we propose a unified framework for Bayesian nonparametric matrix factorization that infers overlapping bi-clusters for multi-omics data. The proposed method adaptively discretizes different types of observations into common latent states on which cluster structures are built hierarchically. The proposed Bayesian nonparametric method is able to automatically determine the number of clusters. We demonstrate the utility of the proposed method using simulation studies and applications to a single-cell RNA-sequencing dataset, a combination of single-cell RNA-sequencing and single-cell ATAC-sequencing dataset, a bulk RNA-sequencing dataset, and a DNA methylation dataset which reveal several interesting findings that are consistent with biological literature.

Aryl Hydrocarbon Receptor (AhR) Signaling in Colonic Cells and Tumors.

The aryl hydrocarbon receptor (AhR) is overexpressed in many tumor types and exhibits tumor-specific tumor promoter and tumor suppressor-like activity. In colon cancer, most but not all studies suggest that the AhR exhibits tumor suppressor activity which is enhanced by AhR ligands acting as agonists. Our studies investigated the role of the AhR in colon tumorigenesis using wild-type and AhR-knockout mice, the inflammation model of colon tumorigenesis using mice treated with azoxymethane (AOM)/dextran sodium sulfate (DSS) and APCS580/+; KrasG12D/+ mice all of which form intestinal tumors. The effects of tissue-specific AhR loss in the intestine of the tumor-forming mice on colonic stem cells, organoid-initiating capacity, colon tumor formation and mechanisms of AhR-mediated effects were investigated. Loss of AhR enhanced stem cell and tumor growth and in the AOM/DSS model AhR-dependent suppression of FOXM1 and downstream genes was important for AhR-dependent anticancer activity. Furthermore, the effectiveness of interleukin-22 (IL22) in colonic epithelial cells was also dependent on AhR expression. IL22 induced phosphorylation of STAT3, inhibited colonic organoid growth, promoted colonic cell proliferation in vivo and enhanced DNA repair in AOM/DSS-induced tumors. In this mouse model, the AhR suppressed SOCS3 expression and enhanced IL22-mediated activation of STAT3, whereas the loss of the AhR increased levels of SOCS3 which in turn inhibited IL22-induced STAT3 activation. In the APCS580/+; KrasG12D/+ mouse model, the loss of the AhR enhanced Wnt signaling and colon carcinogenesis. Results in both mouse models of colon carcinogenesis were complemented by single cell transcriptomics on colonic intestinal crypts which also showed that AhR deletion promoted expression of FOXM1-regulated genes in multiple colonic cell subtypes. These results support the role of the AhR as a tumor suppressor-like gene in the colon.

HIV-1 Tat and cocaine impact astrocytic energy reservoirs and epigenetic regulation by influencing the LINC01133-hsa-miR-4726-5p-NDUFA9 axis.

Clinical research has proven that HIV-positive (HIV+) individuals with cocaine abuse show behavioral and neurocognitive disorders. Noncoding RNAs (ncRNAs), such as long ncRNAs (lncRNAs) and microRNAs (miRNAs), are known to regulate gene expression in the contexts of HIV infection and drug abuse. However, there are no specific lncRNA or miRNA biomarkers associated with HIV-1 Transactivator of transcription protein (Tat) and cocaine coexposure. In the central nervous system (CNS), astrocytes are the primary regulators of energy metabolism, and impairment of the astrocytic energy supply can trigger neurodegeneration. The aim of this study was to uncover the roles of lncRNAs and miRNAs in the regulation of messenger RNA (mRNA) targets affected by HIV infection and cocaine abuse. Integrative bioinformatics analysis revealed altered expression of 10 lncRNAs, 10 miRNAs, and 4 mRNA/gene targets in human primary astrocytes treated with cocaine and HIV-1 Tat. We assessed the alterations in the expression of two miRNAs, hsa-miR-2355 and hsa-miR-4726-5p; four lncRNAs, LINC01133, H19, HHIP-AS1, and NOP14-AS1; and four genes, NDUFA9, KYNU, HKDC1, and LIPG. The results revealed interactions in the LINC01133-hsa-miR-4726-5p-NDUFA9 axis that may eventually help us understand cocaine- and HIV-1 Tat-induced astrocyte dysfunction that may ultimately result in neurodegeneration.

Ablation of long noncoding RNA MALAT1 activates antioxidant pathway and alleviates sepsis in mice.

The metastasis-associated lung adenocarcinoma transcript1 (MALAT1) is a long noncoding RNA (lncRNA) and is known for its role in cancer development and prognosis. In this study, we report that MALAT1 plays an important role in regulating acute inflammatory responses in sepsis. In patient samples, MALAT1 expression was positively correlated with severity of sepsis. In cultured macrophages, LPS treatment significantly induced MALAT1 expression, while genetic ablation of MALAT1 greatly reduced proinflammatory cytokine levels. Furthermore, MALAT1-ablated mice had significantly increased survival rates in cecal ligation and puncture (CLP)-induced sepsis and LPS-induced endotoxemia. One novel and salient feature of MALAT1-ablated mice is greatly reduced ROS level in macrophages and other cell types and increased glutathione/oxidized glutathione (GSH/GSSG) ratio in macrophages, suggesting an increased antioxidant capacity. We showed a mechanism for MALAT1 ablation leading to enhanced antioxidant capacity is through activation of methionine cycle by epitranscriptomical regulation of methionine adenosyltransferase 2A (MAT2A). MAT2A 3'UTR can be methylated by METTL16 which was known to directly bind to MALAT1. MALAT1 ablation was found to reduce methylation in MAT2A hairpin1 and increase MAT2A protein levels. Our results suggest a MALAT1-METTL16-MAT2A interactive axis which may be targeted for treatments of sepsis.

Transcriptomic Profiling of Gene Expression Associated with Granulosa Cell Tumor Development in a Mouse Model.

Ovarian granulosa cell tumors (GCTs) are rare sex cord-stromal tumors, accounting for ~5% ovarian tumors. The etiology of GCTs remains poorly defined. Genetically engineered mouse models are potentially valuable for understanding the pathogenesis of GCTs. Mice harboring constitutively active TGFß signaling (TGFBR1-CA) develop ovarian GCTs that phenocopy several hormonal and molecular characteristics of human GCTs. To determine molecular alterations in the ovary upon TGFß signaling activation, we performed transcriptomic profiling of gene expression associated with GCT development using ovaries from 1-month-old TGFBR1-CA mice and age-matched controls. RNA-sequencing and bioinformatics analysis coupled with the validation of select target genes revealed dysregulations of multiple cellular events and signaling molecules/pathways. The differentially expressed genes are enriched not only for known GCT-related pathways and tumorigenic events but also for signaling events potentially mediated by neuroactive ligand-receptor interaction, relaxin signaling, insulin signaling, and complements in TGFBR1-CA ovaries. Additionally, a comparative analysis of our data in mice with genes dysregulated in human GCTs or granulosa cells overexpressing a mutant FOXL2, the genetic hallmark of adult GCTs, identified some common genes altered in both conditions. In summary, this study has revealed the molecular signature of ovarian GCTs in a mouse model that harbors the constitutive activation of TGFBR1. The findings may be further exploited to understand the pathogenesis of a class of poorly defined ovarian tumors.

scTenifoldKnk: An efficient virtual knockout tool for gene function predictions via single-cell gene regulatory network perturbation.

Gene knockout (KO) experiments are a proven, powerful approach for studying gene function. However, systematic KO experiments targeting a large number of genes are usually prohibitive due to the limit of experimental and animal resources. Here, we present scTenifoldKnk, an efficient virtual KO tool that enables systematic KO investigation of gene function using data from single-cell RNA sequencing (scRNA-seq). In scTenifoldKnk analysis, a gene regulatory network (GRN) is first constructed from scRNA-seq data of wild-type samples, and a target gene is then virtually deleted from the constructed GRN. Manifold alignment is used to align the resulting reduced GRN to the original GRN to identify differentially regulated genes, which are used to infer target gene functions in analyzed cells. We demonstrate that the scTenifoldKnk-based virtual KO analysis recapitulates the main findings of real-animal KO experiments and recovers the expected functions of genes in relevant cell types.

Association of pyroptosis and severeness of COVID-19 as revealed by integrated single-cell transcriptome data analysis.

Cytokine storm and inflammatory cytokine release syndrome are often found to be associated with severe instances of the 2019 coronavirus disease (COVID-19). However, factors that contribute to the development of the COVID-19-associated cytokine storm and intensify the hyperinflammatory response are not well known. Here, we integratively analyzed scRNAseq data of 37,607 immune cells of eight different cell types from four studies involving COVID-19 patients in either moderate or severe conditions. Our analysis showed that pyroptosis-a lytic, inflammatory type of programmed cell death-may play a critical role in the SARS-CoV-2-induced cytokine storm. The expression of the key markers of pyroptosis, such as pro-inflammatory cytokine genes IL1B and IL18, is significantly higher in moderate and severe COVID-19 patients than in healthy controls. The pattern is more pronounced in macrophages and neutrophils than in adaptive immune cells such as T cells and B cells. Furthermore, the lack of interferon-gamma (IFN-γ) and overexpression of ninjurin 1 (NINJ1) in macrophages may exacerbate the systemic inflammation, as shown in severe COVID-19 patients. Finally, we developed a scoring metric to quantitatively assess single cell's pyroptotic state and demonstrated the use of this pyroptosis signature score to scRNAseq data. Taken together, our study underscores the importance of the pyroptosis pathway and highlights its clinical relevance, suggesting that pyroptosis is a cellular process that can be a potential target for the treatment of COVID-19 associated diseases.

scInTime: A Computational Method Leveraging Single-Cell Trajectory and Gene Regulatory Networks to Identify Master Regulators of Cellular Differentiation.

Trajectory inference (TI) or pseudotime analysis has dramatically extended the analytical framework of single-cell RNA-seq data, allowing regulatory genes contributing to cell differentiation and those involved in various dynamic cellular processes to be identified. However, most TI analysis procedures deal with individual genes independently while overlooking the regulatory relations between genes. Integrating information from gene regulatory networks (GRNs) at different pseudotime points may lead to more interpretable TI results. To this end, we introduce scInTime-an unsupervised machine learning framework coupling inferred trajectory with single-cell GRNs (scGRNs) to identify master regulatory genes. We validated the performance of our method by analyzing multiple scRNA-seq data sets. In each of the cases, top-ranking genes predicted by scInTime supported their functional relevance with corresponding signaling pathways, in line with the results of available functional studies. Overall results demonstrated that scInTime is a powerful tool to exploit pseudotime-series scGRNs, allowing for a clear interpretation of TI results toward more significant biological insights.