TWIK-1/TASK-3 heterodimeric channels contribute to the neurotensin-mediated excitation of hippocampal dentate gyrus granule cells

β-COP Regulates TWIK1/TREK1 Heterodimeric Channel-Mediated Passive Conductance in Astrocytes

Mature astrocytes are characterized by a K⁺ conductance (passive conductance) that changes with a constant slope with voltage, which is involved in K⁺ homeostasis in the brain. Recently, we reported that the tandem of pore domains in a weak inward rectifying K⁺ channel (TWIK1 or KCNK1) and TWIK-related K⁺ channel 1 (TREK1 or KCNK2) form heterodimeric channels that mediate passive conductance in astrocytes. However, little is known about the binding proteins that regulate the function of the TWIK1/TREK1 heterodimeric channels. Here, we found that β-coat protein (COP) regulated the surface expression and activity of the TWIK1/TREK1 heterodimeric channels in astrocytes. β-COP binds directly to TREK1 but not TWIK1 in a heterologous expression system. However, β-COP also interacts with the TWIK1/TREK1 heterodimeric channel in a TREK1 dependent manner and enhances the surface expression of the heterodimeric channel in astrocytes. Consequently, it regulates TWIK1/TREK1 heterodimeric channel-mediated passive conductance in astrocytes in the mouse brain. Taken together, these results suggest that β-COP is a potential regulator of astrocytic passive conductance in the brain.

Transcriptomic plasticity of the hypothalamic osmoregulatory control centre of the Arabian dromedary camel

Water conservation is vital for life in the desert. The dromedary camel (Camelus dromedarius) produces low volumes of highly concentrated urine, more so when water is scarce, to conserve body water. Two hormones, arginine vasopressin and oxytocin, both produced in the supraoptic nucleus, the core hypothalamic osmoregulatory control centre, are vital for this adaptive process, but the mechanisms that enable the camel supraoptic nucleus to cope with osmotic stress are not known. To investigate the central control of water homeostasis in the camel, we first build three dimensional models of the camel supraoptic nucleus based on the expression of the vasopressin and oxytocin mRNAs in order to facilitate sampling. We then compare the transcriptomes of the supraoptic nucleus under control and water deprived conditions and identified genes that change in expression due to hyperosmotic stress. By comparing camel and rat datasets, we have identified common elements of the water deprivation transcriptomic response network, as well as elements, such as extracellular matrix remodelling and upregulation of angiotensinogen expression, that appear to be unique to the dromedary camel and that may be essential adaptations necessary for life in the desert.

Comparative transcriptomic analyses between dromedary camels and rats provide insight into water homeostasis gene responses in animals under water stress conditions.

Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation

Background

Single cell RNA-sequencing (scRNA-seq) has very rapidly become the new workhorse of modern biology providing an unprecedented global view on cellular diversity and heterogeneity. In particular, the structure of gene-gene expression correlation contains information on the underlying gene regulatory networks. However, interpretation of scRNA-seq data is challenging due to specific experimental error and biases that are unique to this kind of data including drop-out (or technical zeros).

Methods

To deal with this problem several methods for imputation of zeros for scRNA-seq have been developed. However, it is not clear how these processing steps affect inference of genetic networks from single cell data. Here, we introduce Biomodelling.jl, a tool for generation of synthetic scRNA-seq data using multiscale modelling of stochastic gene regulatory networks in growing and dividing cells.

Results

Our tool produces realistic transcription data with a known ground truth network topology that can be used to benchmark different approaches for gene regulatory network inference. Using this tool we investigate the impact of different imputation methods on the performance of several network inference algorithms.

Conclusions

Biomodelling.jl provides a versatile and useful tool for future development and benchmarking of network inference approaches using scRNA-seq data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04778-9

From COVID to fibrosis: lessons from single-cell analyses of the human lung

The increased resolution of single-cell RNA-sequencing technologies has led to major breakthroughs and improved our understanding of the normal and pathologic conditions of multiple tissues and organs. In the study of parenchymal lung disease, single-cell RNA-sequencing has better delineated known cell populations and identified novel cells and changes in cellular phenotypes and gene expression patterns associated with disease. In this review, we aim to highlight the advances and insights that have been made possible by applying these technologies to two seemingly very different lung diseases: fibrotic interstitial lung diseases, a group of relentlessly progressive lung diseases leading to pulmonary fibrosis, and COVID-19 pneumonia, an acute viral disease with life-threatening complications, including pulmonary fibrosis. We discuss changes in cell populations and gene expression, highlighting potential common features, such as alveolar cell epithelial injury and aberrant repair and monocyte-derived macrophage populations, as well as relevance and implications to mechanisms of disease and future directions.

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.

High-throughput single-сell sequencing in cancer research

With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed.

Integrated analysis of single-cell and bulk RNA sequencing data reveals a pan-cancer stemness signature predicting immunotherapy response

BACKGROUND

Although immune checkpoint inhibitor (ICI) is regarded as a breakthrough in cancer therapy, only a limited fraction of patients benefit from it. Cancer stemness can be the potential culprit in ICI resistance, but direct clinical evidence is lacking.

METHODS

Publicly available scRNA-Seq datasets derived from ICI-treated patients were collected and analyzed to elucidate the association between cancer stemness and ICI response. A novel stemness signature (Stem.Sig) was developed and validated using large-scale pan-cancer data, including 34 scRNA-Seq datasets, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 10 ICI transcriptomic cohorts. The therapeutic value of Stem.Sig genes was further explored using 17 CRISPR datasets that screened potential immunotherapy targets.

RESULTS

Cancer stemness, as evaluated by CytoTRACE, was found to be significantly associated with ICI resistance in melanoma and basal cell carcinoma (both P < 0.001). Significantly negative association was found between Stem.Sig and anti-tumor immunity, while positive correlations were detected between Stem.Sig and intra-tumoral heterogenicity (ITH) / total mutational burden (TMB). Based on this signature, machine learning model predicted ICI response with an AUC of 0.71 in both validation and testing set. Remarkably, compared with previous well-established signatures, Stem.Sig achieved better predictive performance across multiple cancers. Moreover, we generated a gene list ranked by the average effect of each gene to enhance tumor immune response after genetic knockout across different CRISPR datasets. Then we matched Stem.Sig to this gene list and found Stem.Sig significantly enriched 3% top-ranked genes from the list (P = 0.03), including EMC3, BECN1, VPS35, PCBP2, VPS29, PSMF1, GCLC, KXD1, SPRR1B, PTMA, YBX1, CYP27B1, NACA, PPP1CA, TCEB2, PIGC, NR0B2, PEX13, SERF2, and ZBTB43, which were potential therapeutic targets.

CONCLUSIONS

We revealed a robust link between cancer stemness and immunotherapy resistance and developed a promising signature, Stem.Sig, which showed increased performance in comparison to other signatures regarding ICI response prediction. This signature could serve as a competitive tool for patient selection of immunotherapy. Meanwhile, our study potentially paves the way for overcoming immune resistance by targeting stemness-associated genes.

MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts

BACKGROUND

Total-RNA sequencing (total-RNA-seq) allows the simultaneous study of both the coding and the non-coding transcriptome. Yet, computational pipelines have traditionally focused on particular biotypes, making assumptions that are not fullfilled by total-RNA-seq datasets. Transcripts from distinct RNA biotypes vary in length, biogenesis, and function, can overlap in a genomic region, and may be present in the genome with a high copy number. Consequently, reads from total-RNA-seq libraries may cause ambiguous genomic alignments, demanding for flexible quantification approaches.

RESULTS

Here we present Multi-Graph count (MGcount), a total-RNA-seq quantification tool combining two strategies for handling ambiguous alignments. First, MGcount assigns reads hierarchically to small-RNA and long-RNA features to account for length disparity when transcripts overlap in the same genomic position. Next, MGcount aggregates RNA products with similar sequences where reads systematically multi-map using a graph-based approach. MGcount outputs a transcriptomic count matrix compatible with RNA-sequencing downstream analysis pipelines, with both bulk and single-cell resolution, and the graphs that model repeated transcript structures for different biotypes. The software can be used as a python module or as a single-file executable program.

CONCLUSIONS

MGcount is a flexible total-RNA-seq quantification tool that successfully integrates reads that align to multiple genomic locations or that overlap with multiple gene features. Its approach is suitable for the simultaneous estimation of protein-coding, long non-coding and small non-coding transcript concentration, in both precursor and processed forms. Both source code and compiled software are available at https://github.com/hitaandrea/MGcount .

Sevoflurane Increases Hippocampal Theta Oscillations and Impairs Memory Via TASK-3 Channels

Sevoflurane can induce memory impairment during clinical anesthesia; however, the underlying mechanisms are largely unknown. TASK-3 channels are one of the potential targets of sevoflurane. Accumulating evidence supports a negative role of intracranial theta rhythms (4–12 Hz) in memory formation. Here, we investigated whether TASK-3 channels contribute to sevoflurane-induced memory impairment by regulating hippocampal theta rhythms. In this study, the memory performance of mice was tested by contextual fear conditioning and inhibitory avoidance experiments. The hippocampal local field potentials (LFPs) were recorded from chronically implanted electrodes located in CA3 region. The results showed that sevoflurane concentration-dependently impaired the memory function of mice, as evidenced by the decreased time mice spent on freezing and reduced latencies for mice to enter the shock compartment. Our electrophysiological results revealed that sevoflurane also enhanced the spectral power of hippocampal LFPs (1–30 Hz), particularly in memory-related theta rhythms (4–12 Hz). These effects were mitigated by viral-mediated knockdown of TASK-3 channels in the hippocampal CA3 region. The knockdown of hippocampal TASK-3 channels significantly reduced the enhancing effect of sevoflurane on hippocampal theta rhythms and alleviated sevoflurane-induced memory impairment. Our data indicate that sevoflurane can increase hippocampal theta oscillations and impair memory function via TASK-3 channels.

The potential application of organoids in breast cancer research and treatment

Tumor heterogeneity is a major challenge for breast cancer researchers who have struggled to find effective treatments despite recent advances in oncology. Although the use of 2D cell culture methods in breast cancer research has been effective, it cannot model the heterogeneity of breast cancer as found within the body. The development of 3D culture of tumor cells and breast cancer organoids has provided a new approach in breast cancer research, allowing the identification of biomarkers, study of the interaction of tumor cells with the microenvironment, and for drug screening and discovery. In addition, the possibility of gene editing in organoids, especially using the CRISPR/Cas9 system, is convenient, and has allowed a more detailed study of tumor behavior in models closer to the physiological condition. The present review covers the application of organoids in breast cancer research. The recent use of gene-editing systems to provide insights into therapeutic approaches for breast cancer, is highlighted. The study of organoids and the possibility of gene manipulation may be a step towards the personalized treatment of breast cancer, which has so far remained unattainable due to the high heterogeneity of breast cancer.

Two-Pore-Domain Potassium (K2P-) Channels: Cardiac Expression Patterns and Disease-Specific Remodelling Processes

Two-pore-domain potassium (K_2P-) channels conduct outward K⁺ currents that maintain the resting membrane potential and modulate action potential repolarization. Members of the K_2P channel family are widely expressed among different human cell types and organs where they were shown to regulate important physiological processes. Their functional activity is controlled by a broad variety of different stimuli, like pH level, temperature, and mechanical stress but also by the presence of lipids or pharmacological agents. In patients suffering from cardiovascular diseases, alterations in K_2P-channel expression and function have been observed, suggesting functional significance and a potential therapeutic role of these ion channels. For example, upregulation of atrial specific K_2P3.1 (TASK-1) currents in atrial fibrillation (AF) patients was shown to contribute to atrial action potential duration shortening, a key feature of AF-associated atrial electrical remodelling. Therefore, targeting K_2P3.1 (TASK-1) channels might constitute an intriguing strategy for AF treatment. Further, mechanoactive K_2P2.1 (TREK-1) currents have been implicated in the development of cardiac hypertrophy, cardiac fibrosis and heart failure. Cardiovascular expression of other K_2P channels has been described, functional evidence in cardiac tissue however remains sparse. In the present review, expression, function, and regulation of cardiovascular K_2P channels are summarized and compared among different species. Remodelling patterns, observed in disease models are discussed and compared to findings from clinical patients to assess the therapeutic potential of K_2P channels.

TWIK-1 BAC-GFP Transgenic Mice, an Animal Model for TWIK-1 Expression

TWIK-1 is the first identified member of the two-pore domain potassium (K2P) channels that are involved in neuronal excitability and astrocytic passive conductance in the brain. Despite the physiological roles of TWIK-1, there is still a lack of information on the basic expression patterns of TWIK-1 proteins in the brain. Here, using a modified bacterial artificial chromosome (BAC), we generated a transgenic mouse (Tg mouse) line expressing green fluorescent protein (GFP) under the control of the TWIK-1 promoter (TWIK-1 BAC-GFP Tg mice). We confirmed that nearly all GFP-producing cells co-expressed endogenous TWIK-1 in the brain of TWIK-1 BAC-GFP Tg mice. GFP signals were highly expressed in various brain areas, including the dentate gyrus (DG), lateral entorhinal cortex (LEC), and cerebellum (Cb). In addition, we found that GFP signals were highly expressed in immature granule cells in the DG. Finally, our TWIK-1 BAC-GFP Tg mice mimic the upregulation of TWIK-1 mRNA expression in the hippocampus following the injection of kainic acid (KA). Our data clearly showed that TWIK-1 BAC-GFP Tg mice are a useful animal model for studying the mechanisms regulating TWIK-1 gene expression and the physiological roles of TWIK-1 channels in the brain.

Subretinal fibrosis in neovascular age-related macular degeneration: current concepts, therapeutic avenues, and future perspectives

Age-related macular degeneration (AMD) is a progressive, degenerative disease of the human retina which in its most aggressive form is associated with the formation of macular neovascularization (MNV) and subretinal fibrosis leading to irreversible blindness. MNVs contain blood vessels as well as infiltrating immune cells, myofibroblasts, and excessive amounts of extracellular matrix proteins such as collagens, fibronectin, and laminin which disrupts retinal function and triggers neurodegeneration. In the mammalian retina, damaged neurons cannot be replaced by tissue regeneration, and subretinal MNV and fibrosis persist and thus fuel degeneration and visual loss. This review provides an overview of subretinal fibrosis in neovascular AMD, by summarizing its clinical manifestations, exploring the current understanding of the underlying cellular and molecular mechanisms and discussing potential therapeutic approaches to inhibit subretinal fibrosis in the future.

Contribution of Neuronal and Glial Two-Pore-Domain Potassium Channels in Health and Neurological Disorders

Two-pore-domain potassium (K2P) channels are widespread in the nervous system and play a critical role in maintaining membrane potential in neurons and glia. They have been implicated in many stress-relevant neurological disorders, including pain, sleep disorder, epilepsy, ischemia, and depression. K2P channels give rise to leaky K⁺ currents, which stabilize cellular membrane potential and regulate cellular excitability. A range of natural and chemical effectors, including temperature, pressure, pH, phospholipids, and intracellular signaling molecules, substantially modulate the activity of K2P channels. In this review, we summarize the contribution of K2P channels to neuronal excitability and to potassium homeostasis in glia. We describe recently discovered functions of K2P channels in glia, such as astrocytic passive conductance and glutamate release, microglial surveillance, and myelin generation by oligodendrocytes. We also discuss the potential role of glial K2P channels in neurological disorders. In the end, we discuss current limitations in K2P channel researches and suggest directions for future studies.

Preparation of single-cell suspensions of mouse glomeruli for high-throughput analysis

The kidney glomerulus is essential for proper kidney function. Until recently, technical challenges associated with glomerular isolation and subsequent dissolution into single cells have limited the detailed characterization of cells in the glomerulus. Previous techniques of kidney dissociation result in low glomerular cell yield, which limits high-throughput analysis. The ability to efficiently purify glomeruli and digest the tissue into single cells is especially important for single-cell characterization methods. Here, we present a detailed and comprehensive technique for the extraction and preparation of mouse glomerular cells, with high yield and viability. The method includes direct renal perfusion of Dynabeads via the renal artery followed by kidney dissociation and isolation of glomeruli by magnet; these steps provide a high number and purity of isolated glomeruli, which are further dissociated into single cells. The balanced representation of podocytes, mesangial and endothelial cells in single-cell suspensions of mouse glomeruli, and the high cell viability observed, confirm the efficiency of our method. With some practice, the procedure can be done in <3 h (excluding equipment setup and data analysis). This protocol provides a valuable technique for advancing future single-cell-based studies of the glomerulus in health, injury and disease.

Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods

Single-cell transcriptomics can profile thousands of cells in a single experiment and identify novel cell types, states and dynamics in a wide variety of tissues and organisms. Standard experimental protocols and analysis workflows have been developed to create single-cell transcriptomic maps from tissues. This tutorial focuses on how to interpret these data to identify cell types, states and other biologically relevant patterns with the objective of creating an annotated map of cells. We recommend a three-step workflow including automatic cell annotation (wherever possible), manual cell annotation and verification. Frequently encountered challenges are discussed, as well as strategies to address them. Guiding principles and specific recommendations for software tools and resources that can be used for each step are covered, and an R notebook is included to help run the recommended workflow. Basic familiarity with computer software is assumed, and basic knowledge of programming (e.g., in the R language) is recommended.

AEG-1 Regulates TWIK-1 Expression as an RNA-Binding Protein in Astrocytes

AEG-1, also called MTDH, has oncogenic potential in numerous cancers and is considered a multifunctional modulator because of its involvement in developmental processes and inflammatory and degenerative brain diseases. However, the role of AEG-1 in astrocytes remains unknown. This study aimed to investigate proteins directly regulated by AEG-1 by analyzing their RNA expression patterns in astrocytes transfected with scramble shRNA and AEG-1 shRNA. AEG-1 knockdown down-regulated TWIK-1 mRNA. Real-time quantitative PCR (qPCR) and immunocytochemistry assays confirmed that AEG-1 modulates TWIK-1 mRNA and protein expression. Electrophysiological experiments further revealed that AEG-1 further regulates TWIK-1-mediated potassium currents in normal astrocytes. An RNA immunoprecipitation assay to determine how AEG-1 regulates the expression of TWIK-1 revealed that AEG-1 binds directly to TWIK-1 mRNA. Furthermore, TWIK-1 mRNA stability was significantly increased upon overexpression of AEG-1 in cultured astrocytes (p < 0.01). Our findings show that AEG-1 serves as an RNA-binding protein to regulate TWIK-1 expression in normal astrocytes.

Mapping regulators of cell fate determination: Approaches and challenges

Given the limited regenerative capacities of most organs, strategies are needed to efficiently generate large numbers of parenchymal cells capable of integration into the diseased organ. Although it was initially thought that terminally differentiated cells lacked the ability to transdifferentiate, it has since been shown that cellular reprogramming of stromal cells to parenchymal cells through direct lineage conversion holds great potential for the replacement of post-mitotic parenchymal cells lost to disease. To this end, an assortment of genetic, chemical, and mechanical cues have been identified to reprogram cells to different lineages both in vitro and in vivo. However, some key challenges persist that limit broader applications of reprogramming technologies. These include: (1) low reprogramming efficiencies; (2) incomplete functional maturation of derived cells; and (3) difficulty in determining the typically multi-factor combinatorial recipes required for successful transdifferentiation. To improve efficiency by comprehensively identifying factors that regulate cell fate, large scale genetic and chemical screening methods have thus been utilized. Here, we provide an overview of the underlying concept of cell reprogramming as well as the rationale, considerations, and limitations of high throughput screening methods. We next follow with a summary of unique hits that have been identified by high throughput screens to induce reprogramming to various parenchymal lineages. Finally, we discuss future directions of applying this technology toward human disease biology via disease modeling, drug screening, and regenerative medicine.